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Effects of Soil Moisture Sensor Based Irrigation on Drip Irrigated Bell Peppers Grown on Sandy Soil

Permanent Link: http://ufdc.ufl.edu/UFE0022365/00001

Material Information

Title: Effects of Soil Moisture Sensor Based Irrigation on Drip Irrigated Bell Peppers Grown on Sandy Soil
Physical Description: 1 online resource (149 p.)
Language: english
Creator: Femminella, Kristen
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: coefficient, crop, drip, irrigation, soil, vegetables
Agricultural and Biological Engineering -- Dissertations, Academic -- UF
Genre: Agricultural and Biological Engineering thesis, M.E.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: As competition for freshwater continues to rise in the state of Florida, there is a growing need for improvements in agricultural irrigation efficiency. Automated irrigation systems using soil moisture sensors can improve efficiencies by applying irrigation water based on the soil moisture content of the plant root zone. Irrigation is initiated or bypassed based on the sensor reading of soil moisture content. This project was intended to investigate the effects of soil moisture sensor based irrigation on bell peppers grown on drip irrigated, plastic mulched raised beds by analyzing cumulative irrigation water, fruit yield, deep drainage, and sensor performance. Crop coefficients, Kc initial, Kc mid, and Kc late were estimated using the soil water balance equation. The study was conducted during four growing seasons in Citra, FL at the University of Florida Plant Science and Research Education Unit. Five irrigation treatments, four SMS based and one time based, were initiated each season. The SMS treatments reduced irrigation water up to 70% compared to the time based treatment and showed increases in irrigation water use efficiency (IWUE) up to 300%. Drainage volumes were also reduced from 36-92% during the four seasons. The SMS treatments with low threshold settings (8-10%) showed higher water savings than treatments with higher threshold settings (12%). Sensor performance was determined by analyzing the number of bypassed/initiated events and the soil moisture content at which each event was initiated. Treatments with the lowest threshold setting, 8%, bypassed up to 87% of the scheduled irrigation events and initiated irrigation at the lowest soil moisture content compared with other treatments. A soil water balance equation was applied to estimate the crop water demand, ETc, which, in turn, was used to estimate local crop coefficients, Kc, for bell pepper. These estimates, Kc mid = 0.93 and Kc late = 0.71, closely approximated University of Florida IFAS recommended values, as well as other values estimated for drip irrigated, plastic mulched vegetables.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Kristen Femminella.
Thesis: Thesis (M.E.)--University of Florida, 2008.
Local: Adviser: Dukes, Michael D.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2010-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022365:00001

Permanent Link: http://ufdc.ufl.edu/UFE0022365/00001

Material Information

Title: Effects of Soil Moisture Sensor Based Irrigation on Drip Irrigated Bell Peppers Grown on Sandy Soil
Physical Description: 1 online resource (149 p.)
Language: english
Creator: Femminella, Kristen
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: coefficient, crop, drip, irrigation, soil, vegetables
Agricultural and Biological Engineering -- Dissertations, Academic -- UF
Genre: Agricultural and Biological Engineering thesis, M.E.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: As competition for freshwater continues to rise in the state of Florida, there is a growing need for improvements in agricultural irrigation efficiency. Automated irrigation systems using soil moisture sensors can improve efficiencies by applying irrigation water based on the soil moisture content of the plant root zone. Irrigation is initiated or bypassed based on the sensor reading of soil moisture content. This project was intended to investigate the effects of soil moisture sensor based irrigation on bell peppers grown on drip irrigated, plastic mulched raised beds by analyzing cumulative irrigation water, fruit yield, deep drainage, and sensor performance. Crop coefficients, Kc initial, Kc mid, and Kc late were estimated using the soil water balance equation. The study was conducted during four growing seasons in Citra, FL at the University of Florida Plant Science and Research Education Unit. Five irrigation treatments, four SMS based and one time based, were initiated each season. The SMS treatments reduced irrigation water up to 70% compared to the time based treatment and showed increases in irrigation water use efficiency (IWUE) up to 300%. Drainage volumes were also reduced from 36-92% during the four seasons. The SMS treatments with low threshold settings (8-10%) showed higher water savings than treatments with higher threshold settings (12%). Sensor performance was determined by analyzing the number of bypassed/initiated events and the soil moisture content at which each event was initiated. Treatments with the lowest threshold setting, 8%, bypassed up to 87% of the scheduled irrigation events and initiated irrigation at the lowest soil moisture content compared with other treatments. A soil water balance equation was applied to estimate the crop water demand, ETc, which, in turn, was used to estimate local crop coefficients, Kc, for bell pepper. These estimates, Kc mid = 0.93 and Kc late = 0.71, closely approximated University of Florida IFAS recommended values, as well as other values estimated for drip irrigated, plastic mulched vegetables.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Kristen Femminella.
Thesis: Thesis (M.E.)--University of Florida, 2008.
Local: Adviser: Dukes, Michael D.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2010-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0022365:00001


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EFFECTS OF SOIL MOISTURE SENSOR BASED IRRIGATION ON DRIP IRRIGATED
BELL PEPPERS GROWN ON SANDY SOIL




















By

KRISTEN FEMMINELLA


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2008

































2008 Kristen Femminella


































To my grandmother, Alice Ferraiuolo.









ACKNOWLEDGMENTS

I would like to thank my parents for all of the unconditional love and support they have

shown me during this incredible journey. I am fortunate to have been handed so many

wonderful opportunities, and will forever be appreciative for all they have given me. I would

also like to thank Dr. Dukes for patiently advising and encouraging me during my time at the

University of Florida. Due to his influence and guidance, I have emerged from grad school as a

stronger, more responsible and proactive person.

For their assistance with my project, I would like to extend a special thanks to Lincoln

Zotarelli, Danny Burch, and Larry Miller. I would also like to thank Eban Bean, Jason Icerman,

and Jono Schroder for so many times volunteering to get up early to suffer alongside me in the

field.

To the older siblings I always wish I had, I thank Melissa Baum Haley, Stuart Muller,

and David Kaplan for their unwavering support and encouragement, both in school and out. To

Stacia Davis, Victoria Rouisse, Mary Shedd, Sam Tripson, and Nikki White a thank you is just

not sufficient. They are the greatest friends a girl could have, and they continue to amaze me

with their limitless compassion and kindness.









TABLE OF CONTENTS



A C K N O W L E D G M E N T S ..............................................................................................................4

L IST O F T A B L E S ......................................................................................................... ........ .. 7

LIST OF FIGURES ............................................. .. ......... ............ ............... 10

A B S T R A C T .......................................................................................................... ..................... 16

CHAPTER

1 INTRODUCTION .................................. .. ........... ............................. 18

R a tio n a le ........................................................................................................ ......... . ....... 1 8
O bjectiv es ............................................................................................................. ....... .. 2 1

2 EFFECTS OF SOIL MOISTURE BASED IRRIGATION ON BELL PEPPER
PRODUCTION............................................. ... ......... ............ ............... 23

In tro du ctio n ............................................................................................................ ........ .. 2 3
M materials and M methods .............. .............................................................................. 25
Soils C characteristics .................................................... ........................ .. .. ..... ........... 2 5
Experimental Design and Field Layout......................................................................25
Irrigation and Fertigation Control and Data Collection .............................................26
Soil Moisture Monitoring and Drainage Collection...................................................28
Harvest ................................................. ............................. 29
A analysis M ethod ....................................................................................................... 29
R results and D discussion .................................................................................................... 29
S p rin g 2 0 0 5 .....................................................................................................................2 9
C lim ate C on edition s ............ ........................................... ....................... .. .......... ... 2 9
Irrigation T reatm ents......................................................................... ... .......... .. 30
D drainage ....... ....... ..................................................... ...................... 31
Y ield and W ater U se Effi ciency.......................................................... .................. 31
S p rin g 2 0 0 6 .....................................................................................................................3 2
C lim ate C onditions..... .................................................................... .... ........... 32
Irrigation T reatm ents ... .. .......................................... ....................... ... ............ 32
D ra in a g e ................................................................................................................ ... 3 3
Yield and Water Use Efficiency..........................................................................34
F all 2 0 0 6 ......................................................................................................... ........ .. 3 4
C lim ate C onditions..... .................................................................... .... ........... 34
Irrigation T reatm ents ... .. .......................................... ....................... ... .......... 34
D ra in a g e ................................................................................................................ ... 3 5
Yield and Water Use Efficiency..........................................................................36
S p rin g 2 0 0 7 .................................................................................................................. ... 3 6
C lim ate C onditions..... .................................................................... .... ........... 36









Irrigation T reatm ents ... ................................................................... ... ............ 36
D drainage .......................................................................... ......................37
Y ield and W ater U se Efficiency.......................................................... ................ 38
C om prison of R results ................ .............. .............................................. 38
Conclusions ...................................................... .................. 38

3 EVAPOTRANSPIRATION AND CROP COEFFICIENTS FOR Green BELL
P E P P E R S IN F L O R ID A .................................................... .............................................. 57

Introduction ...................................................... .................. 57
M methods and M materials .............. .............................................................................. 59
Soils C characteristics .................................................... ........................ .. .. ..... ........... 59
Experim ental D esign and Field Layout...................................................... ................ 60
Irrigation and Fertigation Control and Data Collection ............................. ................ 61
Soil M oisture M monitoring and Drainage Collection .............. .................................... 62
D y e Inje ctio n ...................................................................................................................6 3
W weather D ata C collection ..................... ................................................................. 63
K c v a lu e s .........................................................................................................................6 4
Theoretical E T c .............. ...................................................................... ......66
F ield E stim ated E T c ........................................................................................................6 6
R results and D iscu ssion .................................................... ............................................... 68
C lim ate C conditions and E T o ....................................................................... ................ 68
E stim atin g D rain ag e ........................................................................................................6 8
Estim eating ET ........................ ................. ............. ..................70
Estimating K ............................................ .................................. 71
Conclusions ...................................................... .................. 72

4 ANALYSIS OF SOIL MOISTURE SENSOR PERFORMANCE ON AUTOMATED
DRIP IRRIGATED PEPPERS GROWN IN SANDY SOIL ...........................................87

Introduction ........................................................ .................. 87
M materials and M methods .............. .............................................................................. 90
Soils C characteristics .................................................... ........................ .. .. ..... ........... 90
Experim ental D esign and Field Layout...................................................... ................ 91
Irrigation and Fertigation Control and Data Collection ............................. ................ 92
Soil M oisture M monitoring ....................................................................... ................ 93
R results and D iscu ssion .................................................... ............................................... 94
C lim ate C condition s ................. ............................................................................ 94
Irrigation Treatments and W ater Savings.................................................... 94
Soil moisture content ..... .. ................... ........... .....................................98
Sum m ary of Sensor Perform ance....................................................... ............... 105
Conclusions .............................................................................. 108

L IST O F R E F E R E N C E S ....................................................... ................................................ 146

B IO G R A PH IC A L SK E T C H .................................................... ............................................. 149




6










LIST OF TABLES


Table page

2-1 Irrigation treatments, threshold settings (VWC), and programmed irrigation
w in d ow s ......................................................................................................... . ....... .. 4 0

2-2 Total water application during entire season, total water applied after treatment
initiation, 23 DAT, average application rate, and target soil moisture settings for
sp rin g 2 0 0 5 ...................................................................................................... ....... .. 4 3

2-3 Irrigation treatment effects on marketable yield and irrigation water use efficiency,
along with total applied irrigation for spring 2005. ...................................... ................ 44

2-4 Total water application during entire season, total water applied after treatment
initiation, 23 DAT, average application rate, and target soil moisture settings for
sp rin g 2 0 0 6 ..................................................................................................... . ....... .. 4 6

2-5 Irrigation treatment effects on marketable yield and irrigation water use efficiency,
along with total applied irrigation for spring 2006. ...................................... ................ 47

2-6 Total water application during entire season, total water applied after treatment
initiation, 23 DAT, average application rate, and target soil moisture settings for fall
2 006 .......................................................................................................... 50

2-7 Irrigation treatment effects on marketable yield and irrigation water use efficiency,
along w ith total applied irrigation for fall 2006............................................ ................ 51

2-8 Total water application during entire season, total water applied after treatment
initiation, 23 DAT, average application rate, and target soil moisture settings for
sp rin g 2 0 0 7 ...................................................................................................... ....... .. 54

2-9 Irrigation treatment effects on marketable yield and irrigation water use efficiency
(IWUE), along with total applied irrigation for spring 2007 ........................................55

2-10 Summary of successful SMS treatments over spring 2005, spring 2006, fall 2006,
and spring 2007 growing seasons, with average treatment irrigation water,
marketable yield, irrigation water use efficiency (IWUE), and water
sa v in g s ................................................................................................... 5 6

3-1 Irrigation treatments, threshold settings (VWC), and programmed irrigation run
tim es .......................................................................................................... 74

3-2 Summary of SMS treatments that approximate ET, over spring 2005, spring 2006,
and spring 2007 growing seasons, along with treatment irrigation and ET, (calculated
w ith K initial=0.2, K mid=1.0, K late=0.85). ......................................................... 83









3-3 Estimated Kc values for each treatment along with overall averages..............................85

3-4 Recommended, adjusted and estimated Kc values for bell peppers...............................86

4-1 Irrigation treatments, threshold settings (VWC), and programmed irrigation run
tim es ............................................................................................ .......... 109

4-2 Irrigation treatments, threshold settings, and total irrigation water applied after
treatments were initiated (DAT 24), and overall water savings compared to the 15
control treatm ent during the spring 2005 season. ....................................... ................ 113

4-3 Water savings of SMS based treatments compared to the I5 control treatment for
growth stages 2-4 during the spring 2005 season after treatments were initiated .........114

4-4 Irrigation treatments, threshold settings, and total irrigation water applied after
treatments were initiated (DAT 16), and overall water savings compared to the I5
control treatm ent during the spring 2006 season. ....................................... ................ 115

4-5 Water savings of SMS based treatments compared to the I5 control treatment for
growth stages 2-4 during the spring 2006 season after treatments were initiated .........115

4-6 Irrigation treatments, threshold settings, total irrigation water applied after treatments
were initiated (DAT 17), and overall water savings compared to the I5 control
treatm ent during the fall 2006 season. ...... .......... .......... .....................1... 16

4-7 Water savings of SMS based treatments compared to the I5 control treatment for
growth stages 3 and 4 during the fall 2006 season after treatments were initiated. ........117

4-8 Irrigation treatments, threshold settings, total irrigation water applied after treatments
were initiated (DAT 20), and overall water savings compared to the I5 control
treatment during the spring 2007 season. ...... ... ...... .....................1... 18

4-9 Water savings of SMS based treatments compared to the I5 control treatment for
growth stages 2-4 during the spring 2007 season after treatments were initiated .........118

4-10 Irrigation threshold settings, number of irrigation events, and average volumetric
water content (VWC) at beginning of irrigation events for pepper cultivated in spring
2 00 5 ........................................................................................................ 119

4-11 Irrigation threshold settings, number of irrigation events, and average volumetric
water content (VWC) at beginning of irrigation events for pepper cultivated in spring
2 006 ............................................................................................. ......... 124

4-12 Irrigation threshold settings, number of irrigation events, and average volumetric
water content (VWC) at beginning of irrigation events for pepper cultivated in fall
2 006 ............................................................................................. ......... 12 9









4-13 Irrigation threshold settings, number of irrigation events, and average volumetric
water content (VWC) at beginning of irrigation events for pepper cultivated in spring
2 007 ............................................................................................. ......... 134

4-14 Summary of successful SMS treatments over spring 2005, spring 2006, fall 2006,
and spring 2007 growing seasons, with total and daily average irrigation water and
water savings compared with the time based treatment, 15. ................. ...................142

4-15 Average daily and total irrigation and water savings for each treatment type across
all four grow ing seasons. ............................ ............................................ 142

4-16 Summary of successful SMS treatments over spring 2005, spring 2006, fall 2006,
and spring 2007 growing seasons, detailing initiated and bypassed irrigation event
totals, along with the average soil moisture content (SMC) at the start of the event ......143

4-17 Average bypassed and initiated irrigation event totals, along with average soil
moisture content (SMC) at the start of the events for each treatment type across the
four growing seasons ......................... ........... ............ ............... 144









LIST OF FIGURES


Figure page

2-1 Details and dimensions of drainage lysimeter burial beneath raised bed.......................41

2-2 Minimum, maximum, and average temperatures during spring 2005 along with daily
and cum ulativ e rainfall. ................................................ ............................................. 42

2-3 Cumulative irrigation water after initiation of individual treatments in spring
2 0 0 5 ...... .. .............................. .................................................... ....... .. 4 2

2-4 Cumulative water (drainage) percolated beneath the root zone for treatments 12, 13,
and 15 for spring 2005 ............ .. .................... ................ ............ ........ .... .... ........... 43

2-5 Disproportionate plant growth from reduced water due to a horizontal shift in drip
tape caused by field activities and/or improper installation during week 5 of the
sp rin g 2 0 0 5 sea so n ............................................................................................................. 4 4

2-6 Minimum, maximum, and average temperatures during spring 2006 along with daily
and cum ulativ e rainfall. ................................................ ............................................. 4 5

2-7 Cumulative irrigation water after initiation of individual treatments in spring
2 0 0 6 ......................................................................................................... ........ . ....... 4 5

2-8 Cumulative drainage of water percolated beneath the root zone for treatments 12, 13,
and I5 for spring 2006. There were no significant differences (ns) between
treatm ents........................................................................................................ ....... .. 4 7

2-9 Pepper plot with mature pepper plants and fruit during week 12 of the spring 2006
g ro w in g se a so n ................................................................................................................. .. 4 8

2-10 Minimum, maximum, and average temperatures during fall 2006 along with daily
and cum ulativ e rainfall. ................................................ ............................................. 4 8

2-11 Cumulative irrigation water after initiation of individual treatments in fall 2006.
Treatments II and 12 began functioning independently after 58 days after transplant
(D A T ) .................................... .............................. 49

2-12 Cumulative drainage of water percolated beneath the root zone for treatments 12, 13,
14 an d I5 fo r fa ll 2 0 0 6 ........................................................................................................5 1

2-13 Effects of over irrigation of treatment 14 (left) on plant growth compared to I5 (right)
during week 6 of the fall 2006 growing season ............................................ ................ 52

2-14 Minimum, maximum, and average temperatures during spring 2007 along with daily
and cum ulative rainfall. ............................................................................................. 52









2-15 Cumulative irrigation water after initiation of individual treatments in spring
2 0 0 7 .... ....... ..................................................................................................... 5 3

2-16 Cumulative drainage of water percolated beneath the root zone for treatments 12, 13,
14 and 15 for spring 2007. ........... .. .............................. ........ .... ............... 55

3-1 Details and dimensions of drainage lysimeter burial beneath raised bed ..........................75

3-2 Example of negligible change in soil moisture content during one week in the fall
2 0 0 6 season ...................................................................................................... ........ .. 7 6

3-3 Minimum, maximum, and average temperatures during spring 2005 along with daily
and cumulative rainfall and evapotranspiration, ETo.................................... ................ 76

3-4 Minimum, maximum, and average temperatures during spring 2006 along with daily
and cumulative rainfall and evapotranspiration, ETo.................................... ................ 77

3-5 Minimum, maximum, and average temperatures during fall 2006 along with daily
and cumulative rainfall and evapotranspiration, ETo.................................... ................ 77

3-6 Minimum, maximum, and average temperatures during spring 2007 along with daily
and cumulative rainfall and evapotranspiration, ETo.................................... ................ 78

3-7 The wetted front of the time based irrigation treatment I5 after day 7 of the dye
injection test (82 DAT) ................................... ............................. 79

3-8 Weekly estimated and measured drainage along with cumulative irrigation for all
treatments during the spring 2005 season. Drainage is shown as vertical bars with
dark shaded bars representing calculated drainage and lighter bars depicting
measured drainage. Drainage was not collected from treatments II and 14 ..................80

3-9 Weekly estimated and measured drainage along with cumulative irrigation for all
treatments during the spring 2006 season. Drainage is shown as vertical bars with
dark shaded bars representing calculated drainage and lighter bars depicting
measured drainage. Drainage was not collected from treatments II and 14...................81

3-10 Weekly estimated and measured drainage along with cumulative irrigation for all
treatments during the spring 2007 season. Drainage is shown as vertical bars with
dark shaded bars representing calculated drainage and lighter bars depicting
measured drainage. Drainage was not collected from II.............................. ................ 82

3-11 Volumetric water content measured at 15 cm for April 28 to May 4, 2006 (17 to 23
DAT). The horizontal line indicates the approximated field capacity...........................83

3-12 Weekly rainfall and soil moisture content averages, measured by TDR probes across
the entire field, for II and 14 after treatment initiation in spring 2006. Growth stages
2-4 are shown at the top of the graph. The red line represents the observed field
capacity of the soil (0.082) ... .................................................. ............. 84









3-12 Weekly rainfall and soil moisture content averages, measured by TDR probes across
the entire field, for II after treatment initiation in spring 2007. Growth stages 2-4 are
shown at the top of the graph. The red line represents the observed field capacity of
th e so il (0 .1 3 3 ). ................................................................................................................ .. 8 4

3-13 Estimated Kc values averaged across spring growing seasons along with published
values, KJlFA S and KcFAO for bell peppers................................................ ............... 85

4-1 Additional TDR probe locations surrounding Acclima sensors during spring 2007.
Typical plot layout for treatments II, 12, and 13 is shown in the upper diagram, while
14 (twin drip lines) is shown in the lower diagram. ......................................110

4-2 Minimum, maximum, and average temperatures during spring 2005 along with daily
and cum ulative rainfall (m m ).......................................... ...................................... ..... 111

4-3 Minimum, maximum, and average temperatures during spring 2006 along with daily
and cum ulative rainfall (m m ).......................................... ...................................... ..... 111

4-4 Minimum, maximum, and average temperatures during fall 2006 along with daily
and cum ulative rainfall (m m )....................................... ......................... ............... 112

4-5 Minimum, maximum, and average temperatures during spring 2007 along with daily
and cum ulative rainfall (m m )....................................... ......................... ............... 112

4-7 Cumulative irrigation water for treatments during spring 2006. SMS treatment 14
(12-14%) was not properly programmed until 29 DAT. ...................... ....... ............114

4-8 Cumulative irrigation water for treatments in fall 2006. SMS treatments were wired
to separate irrigation controllers 58 DAT. ...... ...........................1... 16

4-9 Cumulative irrigation water for treatments in spring 2007. Treatments 12 and 14
w ere adjusted 30 D A T ...................... .................. ...................... .. ............ .. 117

4-10 Volumetric water content measured at 15 cm for April 28 to May 4, 2006 (17 to 23
DAT). The horizontal line indicates the approximated field capacity averaged for the
15 time based treatment after a 2 hour irrigation event......................... ................... 119

4-11 Volumetric water content (VWC) measured at 15 cm for May 15 to June 15, 2005
(40 to 71 DAT) along with rainfall events. Horizontal lines indicate the
approximated field capacity (VWC) for each replicate........................ ...................120

4-12 Volumetric water content (VWC) measured at 15 cm for April 28 to May 4, 2005
(23 to 29 DAT) with scheduled irrigation events during vegetative development
stage and rainfall. The double horizontal lines indicate minimum and maximum soil
moisture content at which irrigation was initiated. Approximated field capacity is
represented by a single bold line on the I5 graph. ....................................... ................ 121









4-13 Volumetric water content (VWC) measured at 15 cm for May 26 to June 1, 2005 (51
to 57 DAT) with scheduled irrigation events during flowering period and rainfall.
The double horizontal lines indicate minimum and maximum soil moisture content at
which irrigation was initiated. Approximated field capacity is represented by a
single bold line on the I5 graph................................... ........................ ............... 122

4-14 Volumetric water content (VWC) measured at 15 cm for June 22 to June 26, 2005
(78 to 82 DAT) with scheduled irrigation events during harvest period and rainfall.
The double horizontal lines indicate minimum and maximum soil moisture content at
which irrigation was initiated. Approximated field capacity is represented by a
single bold line on the I5 graph................................... ........................ ............... 123

4-15 Volumetric water content (VWC) measured at 15 cm for May 17 to June 17, 2006
(35 to 66 DAT) along with rainfall events. Horizontal lines indicate the
approximated field capacity (VW C) for each replicate...................... .................... 125

4-16 Volumetric water content (VWC) measured at 15 cm for April 28 to May 4, 2006
(17 to 23 DAT) with scheduled irrigation events and rainfall during initial vegetative
development stage of pepper. The double horizontal lines indicate minimum and
maximum soil moisture content at which irrigation was initiated. Approximated
field capacity is represented by a single bold line on the I5 graph...............................126

4-17 Volumetric water content (VWC) measured at 15 cm for June 8 to June 16, 2006 (58
to 66 DAT) with scheduled irrigation events and rainfall during early fruit
development stage of pepper. The double horizontal lines indicate minimum and
maximum soil moisture content at which irrigation was initiated. Approximated
field capacity is represented by a single bold line on the I5 graph...............................127

4-18 Volumetric water content (VWC) measured at 15 cm for June 29 to July 3, 2006 (79
to 83 DAT) with scheduled irrigation events and rainfall during harvesting period of
pepper. The double horizontal lines indicate minimum and maximum soil moisture
content at which irrigation was initiated. Approximated field capacity is represented
by a single bold line on the I5 graph ........ ......... .......... ...................... 128

4-19 Volumetric water content (VWC) measured at 15 cm for November 7 to December
7, 2006 (57 to 87 DAT) along with rainfall events. Horizontal lines indicate the
approximated field capacity (VW C) for each replicate. ..................... ....... ............. 130

4-20 Volumetric water content (VWC) measured at 15 cm for September 28 to October 2,
2006 (19 to 23 DAT) with scheduled irrigation events and rainfall during vegetative
development of pepper. The double horizontal lines indicate minimum and
maximum soil moisture content at which irrigation was initiated. Approximated
field capacity is represented by a single bold line on the I5 graph............................... 131









4-21 Volumetric water content (VWC) measured at 15 cm for October 18 to October 24,
2006 (39 to 45 DAT) with scheduled irrigation events and rainfall during flowering
of pepper. The double horizontal lines indicate minimum and maximum soil
moisture content at which irrigation was initiated. Approximated field capacity is
represented by a single bold line on the I5 graph. ....................................... ................ 132

4-22 Volumetric water content (VWC) measured at 15 cm for November 23 to November
30, 2006 (75 to 82 DAT) with scheduled irrigation events and rainfall during
harvesting period for pepper. The double horizontal lines indicate minimum and
maximum soil moisture content at which irrigation was initiated. Approximated
field capacity is represented by a single bold line on the I5 graph...............................133

4-23 Volumetric water content (VWC) measured at 15 cm for May 15 to June 15, 2007
(35 to 66 DAT) along with rainfall events. Horizontal lines indicate the
approximated field capacity (VW C) for each replicate...................... .................... 135

4-24 Volumetric water content (VWC) measured at 15 cm for May 9 to May 15, 2007 (29
to 35 DAT) with scheduled irrigation events and rainfall during vegetative
development for pepper. The double horizontal lines indicate minimum and
maximum soil moisture content at which irrigation was initiated. Approximated
field capacity is represented by a single bold line on the I5 graph...............................136

4-25 Volumetric water content (VWC) measured at 15 cm for May 30 to June 5, 2007 (50
to 56 DAT) with scheduled irrigation events and rainfall during flowering period for
pepper. The double horizontal lines indicate minimum and maximum soil moisture
content at which irrigation was initiated. Approximated field capacity is represented
by a single bold line on the I5 graph ........ ......... .......... ...................... 137

4-26 Volumetric water content (VWC) measured at 15 cm for June 20 to June 26, 2007
(71 to 77 DAT) with scheduled irrigation events and rainfall during harvest period
for pepper. The double horizontal lines indicate minimum and maximum soil
moisture content at which irrigation was initiated. Approximated field capacity is
represented by a single bold line on the I5 graph. ....................................... ................ 138

4-27 Volumetric water content (VWC) measured by four TDR probes installed adjacent to
the buried Acclima sensors for May 9 to May 15, 2007 (29 to 35 DAT) along with
se a so n al rain fall. .............................................................................................................. 13 9

4-28 Volumetric water content (VWC) measured by four TDR probes installed adjacent to
the buried Acclima sensors for May 30 to June 5, 2007 (50 to 56 DAT) along with
season n al rain fall. .............................................................................................................. 14 0

4-29 Volumetric water content (VWC) measured by four TDR probes installed adjacent to
the buried Acclima sensors for June 20 to June 26, 2007 (71 to 77 DAT) along with
se a so n al rain fall. .............................................................................................................. 14 1









4-30 Volumetric water content (VWC) for the 15 time based treatment averaged over all
four replicates for a one month period during the growing seasons along with
recorded rainfall events. Horizontal lines indicate the approximate field capacity
(F.C.) VWC, with dashed lines depicting the individual season average and solid
lines showing the average over all four seasons. ...... ... .................. .................... 145










Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Engineering

EFFECTS OF SOIL MOISTURE SENSOR BASED IRRIGATION ON DRIP IRRIGATED
BELL PEPPERS GROWN ON SANDY SOIL

By

Kristen Femminella

August 2008

Chair: Michael Dukes
Cochair: Rafael Munoz-Carpena
Major: Agricultural and Biological Engineering

As competition for freshwater continues to rise in the state of Florida, there is a growing

need for improvements in agricultural irrigation efficiency. Automated irrigation systems using

soil moisture sensors can improve efficiencies by applying irrigation water based on the soil

moisture content of the plant root zone. Irrigation is initiated or bypassed based on the sensor

reading of soil moisture content. This project was intended to investigate the effects of soil

moisture sensor based irrigation on bell peppers grown on drip irrigated, plastic mulched raised

beds by analyzing cumulative irrigation water, fruit yield, deep drainage, and sensor

performance. Crop coefficients, Kc initial, Kc mid, and Kc late were estimated using the soil water

balance equation. The study was conducted during four growing seasons in Citra, FL at the

University of Florida Plant Science and Research Education Unit. Five irrigation treatments,

four SMS based and one time based, were initiated each season. The SMS treatments reduced

irrigation water up to 70% compared to the time based treatment and showed increases in

irrigation water use efficiency (IWUE) up to 300%. Drainage volumes were also reduced from

36-92% during the four seasons. The SMS treatments with low threshold settings (8-10%)

showed higher water savings than treatments with higher threshold settings (12%). Sensor









performance was determined by analyzing the number of bypassed/initiated events and the soil

moisture content at which each event was initiated. Treatments with the lowest threshold setting,

8%, bypassed up to 87% of the scheduled irrigation events and initiated irrigation at the lowest

soil moisture content compared with other treatments. A soil water balance equation was applied

to estimate the crop water demand, ETc, which, in turn, was used to estimate local crop

coefficients, Ko, for bell pepper. These estimates, Kc mid= 0.93 and Kciate= 0.71, closely

approximated University of Florida IFAS recommended values, as well as other values estimated

for drip irrigated, plastic mulched vegetables.









CHAPTER 1
INTRODUCTION

Rationale

The abundance of rivers, lakes, springs, canals, and tributaries throughout the state of

Florida leaves many residents and visitors with the misguided conception that water is an

infinitely renewable. This notion; however, could not be further from the truth. As agricultural

production, urban and suburban development, and resident and tourist populations continue to

increase, water management districts are faced with the challenge of allocating water to support

the state's growing demands and needs. Experts in central Florida are researching alternative

water resources as local withdrawals from the Floridan aquifer approach maximum sustainable

levels (Dedekorkut et al., 2003). Even the relatively underdeveloped panhandle region of the

state cannot escape the impending threat of water scarcity. This region has been battling with

Georgia and Alabama for decades over rights to the Apalachicola-Chattahoochee-Flint River that

would provide sufficient water flows to support the fragile and diverse ecosystem of the area, as

well as a million dollar seafood and oyster industry (Hanson et al., 2002). Many restrictions and

limitations on water use have been imposed across the state in an effort to lessen the strain on

limited and, in some cases, dwindling supplies. As water allocation becomes increasingly

scrutinized, Florida will be forced to reexamine existing perceptions and ideas about water, and

find new technologies and methods to efficiently use and conserve this priceless resource.

Of the total state water withdrawals, 60% is from surface saline water used in power plant

generation. Nearly the entire amount, 99%, is returned to the oceans and rivers in which it

originated from. The remaining 40% of the total withdrawal is ground and surface freshwater.

Agricultural operations account for the largest consumer of freshwater, using 39% of the

groundwater supply and 62% of surface water (Marella, 2005). Most of this water comes from









canals, ditches, ponds, lakes, rivers, and tributaries that are fed by various underlying aquifers.

Nationwide, Florida ranks 11th in agricultural water use and uses the largest amount of water in

the eastern U.S. to irrigate crops (Hutson et al., 2004). With the exclusion of improved pasture,

nearly 80% of the farmed acres are watered with supplemental irrigation. Most of this land is

planted with citrus, but ornamental and vegetable production has increased in the last decade

(Marella, 2005).

The efficiency in which all of these crops are irrigated has also increased as new

advancements in farm management technologies have been made readily available to growers.

All new citrus groves are now established with drip irrigation systems as opposed to flooding

systems that require huge amounts of surface water to be pumped into groves from canals or on-

site reservoirs. Although the water was pumped back after being used, much was lost to

evaporation and infiltration. Many older groves are being converted from flooding to drip

irrigation to increase efficiency. In 1980, 60% of farmed acres used flood irrigation, 24% used

sprinkler irrigation and only 16% had drip systems. By 2000, 45% of farmed acres were still

using flood irrigation, sprinkler irrigated acres decreased to 17%, and drip irrigated acres

increased to 38% (Marella, 2005).

High value ornamentals and vegetable crops have received much attention for their

ability to be produced relatively quickly and efficiently, while greatly contributing to the state's

total agricultural revenue. Of these crops, bell pepper is among the most important. Florida is

ranked 2nd in the nation in production, acreage, and crop value, and also produces nearly 100%

of the nation's winter crop (Mossler, 2004). The state averages about 7,284 harvested hectares a

year that accounted for nearly 200 million dollars in 2004 or 15% of the total fresh vegetable

revenue. The crop is an extremely labor intensive crop that requires large field crews on hand









from the beginning of the season for soil fumigation and polyethylene plastic mulch installation

to the end of the season when fields may experience up to five harvests. This, coupled with

increasing competition from foreign as well as in-state producers, along with impending water

shortages, has motivated growers to seek out more efficient production methods.

The establishment of drip irrigation systems on Florida's farmed lands has contributed

tremendously in the conservation of water and nutrients. Drip irrigation delivers water directly

to the plant's root zone where it is readily available for uptake. However, installation of a drip

irrigation system alone does not guarantee a large water savings. An effective system must be

properly managed and follow an irrigation schedule appropriate to crop, climate, and field

conditions. Many growers use the common scheduling method of irrigating their crops for 1

hour a day when plants are small and 3 hours a day when the plants reach full growth. This

method can often result in under-irrigation in the beginning of the season and over-irrigation in

the end of the season (Simonne et al., 2002). Over-irrigation is a problem in Florida which is

comprised mostly of sandy soils with very low water holding capacities averaging 0.75 in/ft

(Haman and Izuno, 1993). Research has shown that excess water that is not used by the plant is

percolated out of the rooting zone and into the groundwater supply (Paramasivam et al., 2000).

This typical scheduling method of high volume, low frequency events not only wastes water, but

may also contribute to groundwater pollution (Fares and Alva, 2000). As the water leaves the

soil profile, any existing chemicals or nutrients are likely to be carried with it (Hochmuth and

Smajstrla, 1994; Paramasivam et al., 2001; Zotarelli et al., 2007).

A more efficient schedule would initiate irrigation based upon current field conditions

and crop demands. The idea, however, of growers evaluating their fields constantly to determine

whether or not to irrigate is not feasible, as the average size of a Florida farm is around 200









acres. The solution may lie in soil moisture sensor technology. These sensors can accurately

monitor the soil moisture conditions of the soil at various time intervals throughout the day.

When programmed into an existing drip irrigation system, the sensors can control water outputs

based upon the current soil moisture content of the field. Soil moisture sensor (SMS) based

irrigation has shown great potential in reducing irrigation water. Preliminary studies show that a

low volume, high frequency irrigation schedule coupled with soil moisture sensors can result in

significant water savings while maintaining a competitive marketable yield, increasing water use

efficiency, and reducing nitrogen leaching (Dukes et al., 2003).

The following chapters will discuss in greater detail field studies conducted to test the

performance of different soil moisture sensors on four seasons of bell pepper production from

2005-2007. Sensor performance as a function of irrigation water applied, irrigation events

initiated/skipped, volumetric soil moisture content, pepper yield, and nitrogen leaching will be

discussed.

Objectives

Objective 1

To evaluate the effects of soil moisture sensor (SMS) based irrigation on
irrigation water application, fruit yield, drainage, and water use efficiency.

Objective 2

To implement three different fertigation treatment rates based upon IFAS
recommended rates.

Objective 3

To examine the effects of variable irrigation and nitrogen scheduling on bell
pepper yield.









Objective 4


* To quantify field parameters such as irrigation water, deep drainage, and
precipitation.

Objective 5

* To integrate the field parameters to create a soil water balance.


Objective 6

* To develop a crop coefficient, Kc specific to bell pepper grown on plastic
mulched, drip irrigated beds.

Objective 7

* To evaluate the performance of soil moisture sensors based on irrigation water
application, number of seasonal irrigation events, and volumetric soil moisture
content of the beds.

Objective 8

* To demonstrate the ability of soil moisture sensor based irrigation to reduce
irrigation water application and irrigation events while still maintaining a
volumetric soil moisture content at or above field capacity.









CHAPTER 2
EFFECTS OF SOIL MOISTURE BASED IRRIGATION ON BELL PEPPER PRODUCTION

Introduction

The abundance of water located in and around the state of Florida is deceiving to many

who view water as an unlimited natural resource. The truth is that Florida has a dwindling

supply of available clean water. As agricultural production, urban and suburban development,

and population continues to increase, water management districts are faced with the challenge of

allocating water to support the growing demands in the state. As water distribution becomes

increasingly scrutinized, Florida will be forced to reexamine its existing perceptions and ideas

about water, and find new technologies and methods to efficiently use and conserve this priceless

resource.

The Florida agricultural industry has the potential to conserve large amounts of water.

Agricultural operations in the state account for the largest consumer of freshwater, using 39% of

the groundwater supply and 62% of surface water (Marella, 2004). Although crops such as citrus

and cattle have been the focus for many decades, high value ornamentals and vegetable crops

have begun to receive much attention for their ability to be produced quickly, while producing

substantial revenue. Of these crops, bell peppers (capsicum annuum) are among the most

important. Florida is ranked 2nd in the nation in production, acreage, and crop value, and also

produces nearly 100% of the winter crop for the nation (Mossler, 2004). Bell peppers are very

sensitive to water and heat stress, which can lead to reduced fruit yield. In order to reduce plant

stress and maximize yield, an efficient irrigation schedule is required to deliver an adequate

water supply based on local evapotranspiration (ET) demands.

Improvements in irrigation scheduling can be an effective way for growers to maximize

yields, while conserving water, fertilizer and energy (Martin et al., 1990). Irrigating with









frequently scheduled irrigation events is very effective in Florida where much of the soil is

coarse sand with very low water holding capacities (Fares and Alva, 2000) Crops growing in

this type of soil require frequent irrigation events, sometimes several per day, to keep enough

soil water available for plant transpiration. In response to this relatively high irrigation demand,

growers often over irrigate their fields as insurance against water stress that can lead to a

reduction in crop yield (Howell, 1996). This type of blind irrigation scheduling practice can

often be detrimental to the crop and the surrounding environment. The large pore spaces that

exist in sandy soils are conducive to deep drainage by any excessively applied water. Not only

does this water percolate out of the rooting zone, making it unavailable for plant uptake, but it

also carries nutrients along with it (e.g. nitrates and phosphates) which may contribute to

groundwater contamination (Bouchard et al., 1992; Babiker et al., 2004; Spalding et al., 2001).

Improved irrigation scheduling involves knowledge of climate conditions, crop growth

demands, and soil conditions. Making irrigation decisions based upon these contributing factors

is important for good irrigation management. One way to improve irrigation scheduling is by

applying irrigation water based on the soil moisture content of the crop root zone. Soil moisture

sensor (SMS) based irrigation has been shown to be an effective scheduling method in

strawberries (Clark et al., 1996), citrus (Fares and Alva, 2000) and tomatoes (Munoz-Carpena et

al., 2005). Previous research has also shown an increase in irrigation water use efficiency

(IWUE) for crops irrigated with SMS treatments, compared to typical time-based irrigation

treatments (Zotarelli et al. 2007a). Dukes et al. (2003) reported increased marketable yields and

IWUE for drip irrigated bell peppers using a sensor automated schedule compared to a time

based schedule.









The objective of this study was to determine the effects of SMS irrigation controllers on

bell pepper production. The independent research variables were represented by various

irrigation scheduling thresholds and rates. The dependent variables, including 1) total irrigation

water applied, 2) marketable yield and irrigation water use efficiency, and 3) volume of water

percolated from the rooting zone, were analyzed and compared to a time-based irrigation

schedule that represents grower practices.

Materials and Methods

This research investigated SMS irrigated bell peppers grown on plastic mulch during the

growing seasons of spring 2005, spring 2006, fall 2006, and spring 2007. The experiment was

repeated over four different growing seasons to minimize the affects of variable climate and field

conditions. The study took place in Marion County, Florida at the University of Florida Plant

Science Research and Education Unit.

Soils Characteristics

Each of the four trials was located at the same field site. The soil for this site was

classified as Candler sand and Tavares sand containing 97% sand-sized particles (Buster 1979).

Field capacity is estimated to be in the range of 0.10-0.12 v/v in the upper 0-30 cm (Icerman,

2007) of plastic mulched vegetable beds. The soil is very permeable, with a low water holding

capacity, making excessively applied water and nutrients highly susceptible to drainage and

leaching (Simonne and Hochmuth, 2004)

Experimental Design and Field Layout

In preparation for this study, drainage lysimeters were installed under selected treatments

on March 21, 2005, prior to bed formation (Zotarelli et al., 2007). At the start of each

experiment the field was rototilled, beds were formed, and immediately fumigated (80% methyl

bromide, 20% chloropicrin) and covered with black plastic mulch. Drip irrigation tape was









simultaneously installed under the plastic mulch. Two drip lines, one for irrigation and one for

fertigation, were installed in the center of each plot on the soil surface below the plastic mulch.

The fall 2006 and spring 2007 growing seasons implemented an irrigation treatment that used

twin drip lines. In this case, the lines were installed at a distance of 0.15 m from the center

fertigation line. The pepper transplants of the cultivar 'Brigadier' were transplanted on April 5,

2005, April 10, 2006, September 11, 2006, and April 12, 2007 in raised beds, 15 m long and

spaced 1.8 m apart, center to center. The transplants were spaced 0.3 m apart and planted in

staggered dual rows.

The treatments were laid out in a randomized complete block design with four replicates.

Four of the irrigation treatments (11-14) were scheduled based upon soil moisture, while the other

treatment (I5) was a time based treatment intended to simulate grower practices. The five

irrigation treatments were applied across all four blocks via five separate flow meters installed

off of the main irrigation line. Fertigation based upon IFAS recommendations for bell peppers,

with the recommendation rate of 208 kg/ha. Fertigation events took placed weekly after the

drainage lysimeters were pumped. Irrigation and fertigation was applied through drip tape

(Turbulent Twin Wall, 0.20 m emitter spacing, 0.25 mm thickness, and 0.7 L/hr at 69 kPa

(Chapin Watermatics, NY).

Irrigation and Fertigation Control and Data Collection

The SMS irrigation treatments allowed programmed timed irrigation events based on

readings taken by soil moisture sensors. Two different soil moisture sensor controllers were

used during the four field trials. In spring 2005, SMS treatment, II, used a dielectric capacitance

probe (ECH20, Decagon Devices Inc., Pullman, WA) coupled with a quantified irrigation

controller (QIC) developed by the Agricultural and Biological Engineering Department (Dukes

and Munoz-Carpena, 2005). The rest of the SMS treatments used a Digital TDT Moisture









Sensor paired with either an RS500 or CS3500 irrigation timer, all manufactured by Acclima,

Inc. (Meridian, ID). Each season utilized four sensors, one for each SMS treatment, which were

installed in one replicate located in the south end of the field and controlled irrigation for the

entire field. The Acclima sensors were buried in the plot at a 300 angle to measure the top 0.2 m

of the production bed. The ECH20 probe was installed vertically into the plot to measure the top

0.15 m of the raised bed.

The QIC and Acclima RS500 irrigation controllers were wired to an irrigation timer (ESP-

12LX Irrigation Controller, Rainbird Corporation, Azuga, CA). The timer was programmed with

five irrigation windows each day to apply a potential irrigation depth of approximately 5 mm/d.

Each irrigation window was 24 minutes long, the required time to apply approximately 1 mm of

water, and programmed to begin at 8:00am, 10:00am, 12:00pm, 2:00pm, and 4:00pm for spring

2005, spring 2006, and fall 2006, and 10:00am, 12:00pm, 2:00pm, 4:00pm and 6:00pm for

spring 2007. Each irrigation treatment was assigned a threshold setting that determined when the

system would irrigate based on the moisture content of the soil. The threshold settings were

selected based on the estimated range of the field capacity of the soil, 10-12% (Icerman, 2007).

The settings were varied from 8% up to 14%. The 8% threshold setting was established to study

the effects of possible plant stress when irrigating slightly under estimated field capacity. The

higher threshold settings were established to observe the potential effects of over irrigation like

excess drainage and reduced fruit yield. At the onset of a scheduled event, the irrigation

controller queried the sensor to determine the soil moisture content of the soil. If the reading was

lower than the threshold setting of the controller, irrigation would begin and run for 24 minutes.

If the sensor reading was higher than the controller threshold setting, the event was bypassed.

The Acclima C3500 irrigation controller represented an "on demand" irrigation schedule, and









allowed irrigation events to occur at any time the sensor reading fell below the lower bound of

set threshold range. The irrigation event ended when the sensor indicated the soil moisture

content was at or above the upper bound of the setting. Because irrigation events are

unscheduled and may occur simultaneously, it is difficult to ensure sufficient water pressure for

treatments irrigated across several fields with one common well and main water pipe. This

makes this type of irrigation controller impractical for most large scale growers.

The control treatment represented a time based irrigation schedule intended to represent a

grower schedule. This treatment irrigated once a day, regardless of soil water conditions, for 2

hours (5 mm/day) in the morning. Table 2-1 outlines the irrigation treatments and soil moisture

threshold settings implemented for each experiment.

Water applications from irrigation and fertigation events were manually recorded from

positive displacement flowmeters (V100 1.6 cm diameter bore with pulse output, AMCO

WaterMetering Systems Inc., Ocala, FL). In addition to manual readings, the flowmeters

contained transducers that signaled a switch closure every 18.9 L. The switch closures were

recorded by data loggers (HOBO event logger, Onset Computer Corp. Inc., Bourne, MA) and

continually logged water and fertigation event times, which were downloaded once a week. By

knowing the time and duration of each event, the data was used to determine if and when

irrigation events occurred or were skipped.

Soil Moisture Monitoring and Drainage Collection

Volumetric water content (VWC) was monitored in each experiment using time domain

reflectometry (TDR) probes (CS-615, Campbell Scientific, Inc. Logan, Utah) buried at a 450

angle to measure the upper 0.15 m of the rooting zone. The probes were installed in each

treatment across all replicates. The TDR probes were connected to a data logger (Model CR-10,









Campbell Scientific, Logan, Inc., UT) with a relay multiplexer (Model AM416, Campbell

Scientific, Inc., Logan, UT). The data was downloaded weekly.

Details of the lysimeter dimensions and burial depth can be seen in Figure 2-1 (Zotarelli et

al., 2007). They were constructed by cross-sectioning 208 L polyethylene drums, and had a

capture area of 1.52 m2. The lysimeters were buried 0.75 m below the surface of the bed. The

collected leachate was pumped weekly into 20 L bottles using two vacuum pumps. The bottles

were weighed to determine the leachate volume.

Harvest

Harvest occurred 75, 79 and 83 days after transplanting (DAT) for spring 2005, 58, 70, and

74 DAT for spring 2006, 79 and 88 DAT for fall 2006, and 70 and 82 DAT for spring 2007. The

fruits were counted, weighed, and sorted according to USDA (1997) standards. Marketable yield

was calculated as the total yield minus culls.

Analysis Method

Marketable yield and irrigation water use efficiency (IWUE) were analyzed using analysis

of variance with PROC GLM (SAS Inst. Inc., 1996). Variances among treatments were analyzed

using Duncan's Multiple Range Test, assuming a 95% confidence level.

Results and Discussion

Results and discussion are presented below for each individual season, followed by an

overall comparison of the four growing seasons.

Spring 2005

Climate Conditions

For spring 2005, cumulative rainfall totaled nearly 343 mm (Figure 2-2) which was much

higher than the average rainfall of 253 mm for this region during this time period. This

exceptionally high amount of rainfall likely contributed to a high incidence of disease that spread









through the field approximately midway (40 DAT) through the growing season. Bacterial spot

and phytophthora blight, both found throughout the field and across all treatments, are known to

thrive under warm, moist conditions (Mossler, 2006).

Irrigation Treatments

The bell pepper transplants were established with an irrigation schedule of 1 hr/d (2 mm/d)

for nearly three weeks. Irrigation treatments were initiated on April 28, 2005 (23 DAT). The

SMS treatments, which included the QIC and Acclima controlled systems, applied less water

than the time based grower treatment. The two different sensor types, however, did not perform

the same. The SMS treatments controlled by the Acclima sensors, 12 (10%), I13 (12%), and 14

(12-14%), functioned as predicted, bypassing scheduled irrigation events as needed. After

treatments were initiated, 12 applied 53 mm (0.9 mm/d), 13 applied 138 mm (2.3 mm/d), and 14

applied 131 mm (2.2 mm/d). I5 resulted in 253 mm (4.2 mm/d) as seen in Table 2-2. The II

QIC treatment bypassed few irrigation events, resulting in a cumulative application 230 mm (3.8

mm/d) and only a 9% savings compared with I5. The controller was thought to be set too high

and was adjusted during the season (58 DAT) from 550 mV (10% VWC) to 515 mV (8% VWC).

The controller; however, did not respond to this adjustment, and continued to initiate irrigation

for most of the scheduled events (Figure 2-3.). Several factors may have contributed to the

malfunctioning of this treatment since sensor performance is influenced by placement in the bed,

proper installation, soil salinity, proximity to drip emitters, and soil characteristics. In 2006

Schroder evaluated the effects of salinity on the performance of the QIC treatment (Schroder,

2006). Just as Schroder observed, large spikes in soil moisture were also observed after weekly

QIC fertigation events which may indicate effects from salinity in the applied fertilizer. An

analysis of soil moisture content can be found in Chapter 4. 12, set at the lowest threshold,

resulted in the largest water savings, 79%. 13 and 14, set at similar threshold settings, applied









nearly the same amount of water and resulted in similar water reductions of 48 and 49%,

respectively.

Drainage

Drainage lysimeters were installed under treatments 12, 13, and 15 which amounted to

cumulative drainage totals of 14.7 mm, 29.5 mm, and 60.5 mm for 12, 13, and 15, respectively.

These values differed significantly, and increased with the amount of irrigation water applied, as

total seasonal irrigation was 129 mm, 229 mm, and 375 mm across 12, 13, and 15, respectively

(Table 2-2). This increase is a result of the low water holding capacity of the soil which holds

about 25 mm of water in 30 cm of sandy soil. Each treatment experienced similar amounts of

drainage during the establishment phase when water applications were similar. After treatments

were initiated (23 DAT), the weekly collected drainage began to vary. 12 experienced little to no

drainage after the SMS treatment (10% VWC) was established (Figure 2-4). This was the result

of very few irrigation events that resulted in a treatment total of 53 mm (0.9 mm/d) as seen in

Table 2-2. Drainage decreased for 13 as well after the SMS treatment (12% VWC) was initiated

due to a decrease in the number of irrigation events (2.3 mm/d average daily application).

Drainage continued to increase for the time based treatment, I5, after treatments were established

as irrigation applications were consistent and averaged 4.2 mm/d (Table 2-2). It is unknown

why there was no drainage from I5 during week 7 (Figure 2-4), as there were no changes in

irrigation.

Yield and Water Use Efficiency

Three harvests took place during spring 2005 on 75 DAT, 79 DAT, and 83 DAT.

Marketable yields for the season can be seen in Table 2-3 and ranged from 20, 320 kg/ha for II

to 29,080 kg/ha for 13. There were statistical differences between yields related to irrigation and

only one of the treatments produced yields above the average annual yield for Florida bell









peppers, 28,000 kg/ha (Maynard and Santos, 2007). The yields were relatively low this season

due to extensive plant disease. Significant differences were seen in irrigation water use

efficiency (IWUE) across irrigation treatments. II and 15 had the lowest IWUE, 8.4 and 9.2 kg

of fruits/m3, respectively, due to the high amount of irrigation water applied by these treatments.

High amounts of irrigation water can not only drain nutrients from the crop root zone, but also

reduce the efficiency water and nutrient uptake by roots, ultimately affecting the yield potential.

Reduced water can also adversely affect growth and subsequently yield as shown in Figure 2-5.

The figure shows plant growth differences that occurred in a plot during week 5 of the season.

The drip tape was shifted closer to the right side, which led to drier conditions on the left and

obvious differences in plant development. 13 and 14 applied similar amounts of water, likely due

to their threshold settings, produced similar yields, and showed no significant difference in

IWUE. 12 had the highest IWUE of 39.7 kg/m3, which can be attributed to a very low irrigation

total, yet produced a marketable yield of 24,110 kg/ha, well under the state average (Table 2-3).

Spring 2006

Climate Conditions

During spring 2006, cumulative rainfall totaled 149 mm as seen in Figure 2-6. Two events

occurred during the season which resulted in rainfall over 20 mm (61 and 62 DAT). The

relatively drier field conditions reduced the spread of disease, although bacterial spot was present

at the end of the season.

Irrigation Treatments

All irrigation treatments were watered 1 hr/d during the establishment phase (2 mm/d).

Individual irrigation treatments were initiated on April 28, 2006 (16 DAT). A programming

error in the 14 irrigation controller during the beginning of the season caused the treatment to

over-irrigate (Figure 2-7), resulting in the largest irrigation total of all treatments (348 mm). The









problem was successfully adjusted (29 DAT) and 14 functioned properly for the duration of the

season. The treatment irrigated an average of 16.2 mm/d before the error was fixed and averaged

3.4 mm/d after the adjustment was made. Based upon this, it can be assumed that if 14 had

functioned properly from the beginning of the season, it would have applied approximately 169

mm of water and resulted in a 49% water savings. Problems also existed with treatments 12 and

13. Both treatments functioned well, with 12 bypassing more events than 13, until an unpredicted

and unexplainable event caused 12 to irrigate for a 15 hour period (30 DAT). 12 was evaluated

and adjusted on 35 DAT, and from this point on began bypassing the same events as 13. By the

end of the season, 12 applied 301 mm (4.9 mm/d) and 13 applied 287 mm (4.7 mm/d) resulting in

a 9 and 13% water savings, respectively (Table 2-4). This problem may have resulted from the

cross communication between sensor signals since the two SMS irrigation (12 and 13) controllers

shared a common irrigation timer. The miscommunication between the controller and sensor

signals may have caused both controllers to receive signals from one of the buried sensors and

ultimately performing as one treatment. II and I5 were the only treatments to operate properly

throughout the season. II applied 156 mm (2.6 mm/d), 53% less water than I5, which applied

329 mm (5.4 mm/d).

Drainage

For spring 2006, drainage lysimeters captured water that percolated beneath treatments 12,

13, and I5. There were no significant differences with respect to percolation among irrigation

treatments since 12, 13, and I5 all applied similar amounts of irrigation water due to the

malfunctioning of sensors. Cumulative drainage totals were 38.1 mm for 12, 47.7 mm for 13, and

49.3 mm for I5 (Figure 2-8).









Yield and Water Use Efficiency

Three harvests took place in spring 2006 on 58, 70, and 74 DAT. Figure 2-9 shows a

typical pepper plot during the harvest. Marketable yields ranged from 14,200 kg/ha for 14 to

17,100 kg/ha for II (Table 2-5.) There were no significant differences in yield between the

irrigation treatments, and all were well below the state average. The reduced yields were the

result of insect infestation and plant disease. II and 14 produced the lowest and highest yields,

yet had similar IWUE as seen in Table 2-5. Although the irrigation total was adjusted for 14

from 348 mm to 169 mm to account for programming error (DAT 23-29), this was not likely the

cause of the reduced yield. The yield may appear low since it was averaged over only four plots

that were irrigated with the 14 treatment, where II, 12, and 13 had 12 plots and 15 had 20 plots.

One of the 14 irrigated plots had a marketable yield of 8,100 kg/ha, which while the highest had

17,600 kg/ha.

Fall 2006

Climate Conditions

The fall 2006 growing season had a cumulative rainfall of 132 mm (Figure 2-10). The low

incidence of rainfall and cooler fall temperatures contributed to a healthy crop with no visible

signs of disease. Temperatures began to fall at the end of the season, but the crop was not

exposed to frost.

Irrigation Treatments

The bell pepper transplants were established with an irrigation schedule of two 1 hour

events, twice a day. Irrigation treatments were initiated on September 28, 2006 (17 DAT).

During the season, a wiring problem caused all of the SMS treatments to malfunction. It was

discovered that II and 12, both wired to a common irrigation controller, and 13 and 14, also wired

to common irrigation controller, were bypassing and irrigating the same scheduled events and









applying same irrigation amounts (Figure 2-11). The problem was attributed to cross

communication between the Acclima sensors, causing each of the irrigation controllers to receive

signals from only one of the two wired sensors. Several adjustments were made, but the problem

was not solved until each controller was wired to a separate individual irrigation timer.

Eventually, 58 DAT, the SMS treatments began to irrigate independently of each other (Figure

2-11). After this point, 12 began bypassing more events than II. This was unexpected, since 12

was set to a higher setting of 10%, compared to II at 8%. In addition to this wiring problem, a

programming error in the irrigation controller caused 14 to over-irrigate from 49 DAT to 65

DAT. The implementation of twin drip lines on this treatment demanded the adjustment of the

irrigation window from 24 minutes to 12 minutes to compensate for the doubled flow rate. The

timer, however, was mistakenly changed and caused 14 to apply double the amount of irrigation

water. By the end of the season, 13 and 14 applied the most water with 319 mm (4.2 mm/d) and

327 mm (4.3 mm/d), respectively (Table 2-6). Each of these treatments applied more water than

I5 which had 303 mm (4.0 mm/d). The lower water application by I5 was a result of 9 missed

programmed events due to power outages and field maintenance. II applied a total amount of

244 mm (3.2 mm/d) and reduced water application by 19%, while 12 applied 213 mm (2.8 mm/d)

with the highest water savings of 30%.

Drainage

Drainage lysimeters were located on treatments 12, 13, 14 and I5 for the fall 2006 season.

The addition of lysimeters to some of the 14 treatment plots was the result of an altered field

layout to account for the 14 modification of twin drip lines. Cumulative drainage totals for

treatments 13, 14, and I5 showed no significant differences (Figure 2-12) as a result of similar

irrigation totals due to the failed performance to the 13 and 14 SMS treatments as seen in Table









2-6. Both treatments applied more irrigation than 15. 12 was the only significantly different

treatment as a result of having the lowest treatment irrigation total of 213 mm (Table 2-6.).

Yield and Water Use Efficiency

Harvest occurred 79 and 88 DAT for the fall 2006 growing season. Yields were higher

during this season compared to the spring seasons due to favorably cooler temperatures during

fruit set and development. Yields ranged from 43,400 kg/ha for II to 45,500 kg/ha for 12 (Table

2-7), and were well above the state average of 28,000 kg/ha (Maynard and Santos, 2007). There

were no statistical differences in yield between irrigation treatments. The reduced irrigation

totals from the SMS treatments resulted in higher values of IWUE as compared to the time based

treatment, 15. Yields were not reported for 13 and 14 since the treatments completely failed to

bypass irrigation events and reduce water. Yield was greatly reduced on 14 from the

programming errors that caused over irrigation in the beginning of the season. Plant growth was

drastically affected and the plants were noticeably smaller and lighter in color throughout the

season (Figure 2-13). The cumulative irrigation totals for these treatments were higher than I5

(Table 2-7).

Spring 2007

Climate Conditions

The spring 2007 season had a cumulative rainfall total of 124 mm (Figure 2-14) and no

incidence of disease.

Irrigation Treatments

In spring 2007 the bell pepper transplants were established with a daily irrigation

schedule of two 1 hour events per day. Individual irrigation treatments were initiated 18 DAT.

Each of the SMS treatments was wired to an individual irrigation controller at the beginning of

the season to avoid past problems with sensor cross communication. This proved to be an









effective method when testing multiple sensors in one field. Problems did arise, however, with

treatments 12 and 14, when both treatments failed to bypass irrigation events in the beginning of

the season. The locations of both treatment sensors, 12 and 14, were assessed 30 DAT. 14 was

reburied in the original location and 12 was moved to a different location in the plot. After the

probes were reburied, 14 continued to irrigate frequently, while 12 began to bypass events as seen

in Figure 2-15. The location of the sensor in the bed was apparently the cause of problem with

the 12 treatment since it functioned properly after it was moved. The problem with 14, however,

was unknown, since the placement of the sensor was evaluated and carefully reburied. Both of

the treatments were set to the same soil moisture threshold level of 10%, but 14 irrigated with

twin drip lines. The location of the sensor relative to the outside drip line and center fertigation

line, although directly in between both, may have been a drier area as compared to other

treatments with centered drip lines. By the end of the season, 14 applied 377 mm (3.6 mm/d),

nearly as much as I5 which applied 308 (4.1 mm/d), and only had a 10% water savings (Table 2-

8.). II and 12 applied similar amounts of water, with 171 mm (2.3 mm/d) and 190 mm (2.5

mm/d), respectively. 13 applied 261 mm (3.1 mm/d), and 15% in water savings.

Drainage

Like the fall 2006 season, drainage lysimeters were located under treatments 12, 13, 14,

and I5. Cumulative drainage totals reflected irrigation applications, as 13, 14, and I5 applied the

most irrigation and drained the most water. There were no statistical differences between these

three treatments. 12 applied a lower treatment irrigation total and drained significantly less water

compared to the other treatments. The affects of the adjustment made to the 12 treatment on 30

DAT which caused irrigation events to be bypassed more frequently can be seen in the

cumulative drainage in Figure 2-16. Drainage appears to steadily increase after the treatments









were initiated (18 DAT) until the adjustment was made (30 DAT). After this, drainage

drastically decreased, and little was collected (0.79 mm) for the duration of the season.

Yield and Water Use Efficiency

Pepper yields varied from 23,800 kg/ha for 13 to 29,700 kg/ha for II (Table 2-9.). Like

previous seasons, there were no significant differences in yield among the irrigation treatments,

and all yields were close to the state average for bell peppers. There were statistical differences,

however, in IWUE among the irrigation treatments. Overall, IWUE decreased with increased

irrigation water totals, where II, with the lowest irrigation total of 171 mm, had an IWUE of

17.37 kg/m3, and 15, with the highest irrigation total of 308 mm, had an IWUE of 7.99 kg/m3.

There were no significant differences among IWUE for the treatments with high irrigation totals,

13, 14, and 15.

Comparison of Results

Over the course of the four growing seasons 16 SMS treatments were initiated and tested

at threshold settings varying from 8-12%, two of which represented "on demand" schedules with

threshold ranges of 12-14%. Eight of the 16 implemented treatments functioned properly and

reduced irrigation water compared to the time based treatment, 15, by skipping scheduled events

based on soil moisture readings. The other eight treatments malfunctioned due to significant

programming, wiring, and/or installation errors. These treatments were not representative of

typical sensor performance, therefore were not included in overall averages and comparisons.

The eight successful treatments are shown in Table 2-10.

Conclusions

The trials conducted over the four growing seasons demonstrated the ability of SMS

treatments to reduce total irrigation water, up to 79%, and increase IWUE, up to 40 kg/m3,

compared to time based irrigation schedules. The SMS treatment performance is highly









dependent on proper sensor installation and burial in the soil, as soil moisture conditions vary

depending on the location of the sensor relative to the drip tape and plants. SMS treatments with

low range threshold settings (8 and 10%) performed similarly in the sandy soil beds, yet both

treatments applied less water and had higher yields than the high threshold treatment (12%). The

"on demand" irrigation treatment (12-14%), like the 10% treatment, showed the greatest

reduction in irrigation water, and produced similar yields to the time based irrigated treatments.

However, on demand control systems would necessitate large hydraulic capacity in commercial

systems and would need to be implemented with care to minimize this expense. To ensure

proper functioning, each sensor requires an independent irrigation controller in order to avoid

over irrigation caused by sensor signaling errors. Further research should include a continued

investigation of sensor performance as well as the water saving potential of "on demand"

irrigation treatments and how they effect marketable yield and drainage.









Table 2-1. Irrigation treatments, threshold settings (VWC), and programmed irrigation
windows.
Treatment Treatment Description VWC threshold setting Irrigation window
(m3/m3)


Spring Pepper 2005
11
12
13
I4
15
Spring Pepper 2006
11
12
13
I4
15
Fall Pepper 2006
11
12
13
I4

15
Spring Pepper 2007
11
12
13
I4

15


QIC
Acclima RS500
Acclima RS500
Acclima CS3500
Time-based schedule

Acclima RS500
Acclima RS500
Acclima RS500
Acclima CS3500
Time-based schedule

Acclima RS500
Acclima RS500
Acclima RS500
Acclima RS500
twin drip lines
Time-based schedule

Acclima RS500
Acclima RS500
Acclima RS500
Acclima RS500
twin drip lines
Time-based schedule


0.1 (500 mV)
0.1
0.12
0.12-0.14
n/a


0.08
0.1
0.12
0.12-0.14
n/a


0.08
0.1
0.12
0.1


24 min, 5 times/day
24 min, 5 times/day
24 min, 5 times/day
Anytime
2 hours, 1 time/day

24 min, 5 times/day
24 min, 5 times/day
24 min, 5 times/day
Anytime
2 hours, 1 time/day

24 min, 5 times/day
24 min, 5 times/day
24 min, 5 times/day
12 min, 5 times/day


n/a 2 hours, 1 time/day


0.08
0.1
0.12
0.1


24 min, 5 times/day
24 min, 5 times/day
24 min, 5 times/day
12 min, 5 times/day


n/a 2 hours, 1 time/day












SOm


0.95m
I ------


- T
0.75m


0.27m-


Raised Bed Edge


i -


T
0.95m 0.55m


0.85m


Drip Tape


neter


Figure 2-1. Details and dimensions of drainage lysimeter burial beneath raised bed.


T-
0.27m
.L


Drainage Lys


I__- Raised Bed Edge
































0 20 40 60 80
Number of Days after Transplanting


Figure 2-2.


Minimum, maximum, and average temperatures during spring 2005 along with
daily and cumulative rainfall.


400




E 300
E
c
0


' 200

.c

E 100
0)


40 60 80

Number of Days after Transplanting


Figure 2-3.


Cumulative irrigation water after initiation of individual treatments in spring
2005.


- 50
0

EE 40


.- M 30





o 10


0


40




30
a)



20




10









Table 2-2. Total water application during entire season, total water applied after treatment


initiation, 23 DAT, average application rate,
spring 2005.


and target soil moisture settings for


Spring Treatment Threshold Total Total Average Treatment
Pepper Description Setting Water Treatment Daily Water
2005 VWC Application* Application Application Savings
Compared
to 15
(%) (mm) (mm) (mm/d) (%)
II QIC 0.1 323 230 3.8 9
Acclima
I2 Aclima 0.1 129 53 0.9 79
RS500
Acclima
13 Acclm 0.12 229 138 2.3 45
RS500
14 Accima 0.12-0.14 176 131 2.2 48
CS3500
I5 Time-based n/a 375 253 4.2 0
*Includes irrigation from establishment, fertigation, and other applications not related to
scheduled irrigation events.

70
12- 10%, AccRS500 Spring 2005
60 -*- 13 12% AccRS500 P


0 20 40 60 80


Figure 2-4.


Number of Days after Transplanting
Cumulative water (drainage) percolated beneath the root zone for treatments 12,
13, and I5 for spring 2005.









Table 2-3. Irrigation treatment effects on marketable yield and irrigation water use efficiency,
along with total applied irrigation for spring 2005.
Treatment Total Treatment Marketable IWUE*
Water Applied Yield*
(mm) (kg/ha) (kg/m3)
11, QIC 230 20, 320 c 8.4 c
12, Acclima RS500 53 24, 110 bc 39.7 a
13, Acclima RS500 138 29,080 a 21.1 b
14, Acclima CS3500 131 27,480 ab 21.0 b
15, time-based 253 24, 660 abc 9.2 c
*Different letters indicate significant differences for P < 0.05 (Duncan's test)


Figure 2-5.


Disproportionate plant growth from reduced water due to a horizontal shift in drip
tape caused by field activities and/or improper installation during week 5 of the
spring 2005 season.

































20 40 60 80
Number of Days after Transplanting


Figure 2-6.


Minimum, maximum, and average temperatures during spring 2006 along with
daily and cumulative rainfall.


0 20 40 60 80


Number of Days after Transplanting


Figure 2-7.


Cumulative irrigation water after initiation of individual treatments in spring
2006.


0
xE
EE

-4
-.E



E
2W ^
C -<5
E


30


25


20


15 .
I-
10


5


0









Table 2-4. Total water application during entire season, total water applied after treatment
initiation, 23 DAT, average application rate, and target soil moisture settings for
spring 2006.
Spring Treatment Threshold Total Total Average Treatment
Pepper Description Setting Water Treatment Daily Water
2006 VWC Application* Application Application Savings
Compared
to 15
(%) (mm) (mm) (mm/d) (%)
Acclima
11 R550 0.08 273 156 2.6 53
RS500
12 Accima 0.1 417 301 4.9 9
RS500
13 Accima 0.12 365 287 4.7 13
RS500
Acclima
14 c350 0.12-0.14 435 169 2.8 49**
C3500
I5 Time-based n/a 421 329 5.4 0
*Includes irrigation from establishment, fertigation, and other applications not related to
scheduled irrigation events.
**Savings after programming error was fixed (29 DAT).













60 13 12% AccRS500
-.- 15 Time-based
E 50 -


40 -


30 -

20 -





01
0 20 40 60 80

Number of Days after Transplanting

Figure 2-8. Cumulative drainage of water percolated beneath the root zone for treatments 12,
13, and 15 for spring 2006. There were no significant differences (ns) between
treatments.


Table 2-5. Irrigation treatment effects on marketable yield and irrigation water use efficiency,
along with total applied irrigation for spring 2006.
Treatment Total Irrigation Marketable IWUE**
Applied Yield**
(mm) (kg/ha) (kg/m3)
11, Acclima RS500 156 17, 100 a 11.0 a
12, Acclima RS500 301 14, 600 a 4.9 b
13, Acclima RS500 287 14,700 a 5.1 b
14, Acclima CS3500 169* 14,200 a 4.1 b
IS, time-based 329 16,200 a 9.6 a
*Value reflects irrigation after programming error was fixed (29 DAT).
**Different letters indicate significant differences for P < 0.05 (Duncan's test).
































- A


Figure 2-9.


Pepper plot with mature pepper plants and fruit during week 12 of the spring 2006
growing season.



60 50
Cumulative Rainfall
4 ] Daily Rainfall
50 -- A/r_ ann Air Trmnrfti r


E 40
- C
4-.
l' 030


20


o 10


0


4U



30 w



20 E



10



0


Figure 2-10.


0 20 40 60 80
Number of Days after Transplanting

Minimum, maximum, and average temperatures during fall 2006
and cumulative rainfall.


along with daily


9






























20 40 60 80
Number of Days after Transplanting


Figure 2-11.


Cumulative irrigation water after initiation of individual treatments in fall 2006.
Treatments II and 12 began functioning independently after 58 days after
transplant (DAT).









Table 2-6. Total water application during entire season, total water applied after treatment


initiation, 23 DAT, average application rate,
2006.


and target soil moisture settings for fall


Fall Treatment Threshold Total Total Average Treatment
Pepper Description Setting Water Treatment Daily Water
2006 VWC Application* Application Application Savings
Compared
to 15
(%) (mm) (mm) (mm/d) (%)
II Acclima 0.08 370 244 3.2 19
RS500
12 Acclima 0.1 294 213 2.8 30
RS500
13 Accima 0.12 401 319 4.2 -5
RS500
Acclima
14 RS500 0.1 464 327 4.3 -8
Twin drip
lines
15 Time-based n/a 390 303 4.0 0
*Includes irrigation from establishment, fertigation, and other applications not related to
scheduled irrigation events.

































Figure 2-12.


0 20 40 60 80 100
Number of Days after Transplanting

Cumulative drainage of water percolated beneath the root zone for treatments 12,
13, I14 and 15 for fall 2006.


Table 2-7. Irrigation treatment effects on marketable yield and irrigation water use efficiency,
along with total applied irrigation for fall 2006.
Treatment Total Irrigation Marketable IWUE**
Applied Yield**
(mm) (kg/ha) (kg/m3)
11, Acclima RS500 244 43, 400 a 17.8 b
12, Acclima RS500 213 45, 500 a 21.4 a


13, Acclima RS500 319 ---
14, Acclima RS500* 327 ---
IS, time-based 303 44, 900 a
*Treatment yields not reported due failed sensor performance.
**Different letters indicate significant differences for P < 0.05 (Duncan's test)


14.8 c





































Figure 2-13.


Effects of over irrigation of treatment 14 (left) on plant growth compared to 15
(right) during week 6 of the fall 2006 growing season.


-*- Cumulative Rainfall
I Daily Rainfall
0 50 -- Average Air Temperature


E= 40
4-
4-.-
30


co 20


10


50



40



30


0
20 E
I--


10



0


0 20 40 60 80
Number of Days after Transplanting


Figure 2-14.


Minimum, maximum, and average temperatures during spring 2007 along with
daily and cumulative rainfall.

















E 300 15- time based
E
r-

0)





-100





0
0 20 40 60 80 100

Number of Days after Transplanting


Figure 2-15. Cumulative irrigation water after initiation of individual treatments in spring
2007.









Table 2-8. Total water application during entire season, total water applied after treatment


initiation, 23 DAT, average application rate,
spring 2007.


and target soil moisture settings for


Spring Treatment Threshold Total Total Average Treatment
Pepper Description Setting Water Treatment Daily Water
2007 VWC Application* Application Application Savings
Compared
to 15
(%) (mm) (mm) (mm/d) (%)
II Acclima 0.08 240 171 2.3 44
RS500
12 Acclima 0.1 267 190 2.5 38
RS500
13 Accima 0.12 361 261 3.4 15
RS500
Acclima
14 RS500 0.1 433 277 3.6 10
Twin drip
lines
I5 Time-based n/a 426 308 4.1 0
*Includes irrigation from establishment, fertigation, and other applications not related to
scheduled irrigation events.












60 13 12% AccRSb
14 10% AccRS500, twin drip
E 15 Time-based
E 50 -

S40 -

30



E 20 -

10


0
0 20 40 60 80 10C
Number of Days after Transplanting

Figure 2-16. Cumulative drainage of water percolated beneath the root zone for treatments 12,
13, I14 and 15 for spring 2007.

Table 2-9. Irrigation treatment effects on marketable yield and irrigation water use efficiency
(IWUE), along with total applied irrigation for spring 2007.
Treatment Total Treatment Marketable IWUE*
Application Yield*
(mm) (kg/ha) (kg/m3)
11, Acclima RS500 171 29,700 a 17.4 a
12, Acclima RS500 190 27,500 a 14.5 b
13, Acclima RS500 261 23,800 a 9.1 c
14, Acclima RS500 277 27,000 a 9.8 c
15, time-based 308 24,600 a 8.0 c
*Different letters indicate significant differences for P < 0.05 (Duncan's test)









Table 2-10.


Summary of successful SMS treatments over spring 2005, spring 2006, fall 2006, and
spring 2007 growing seasons, with average treatment irrigation water, marketable yield,


irrigation water use efficiency (IWUE), and water savings.
Season Treat. Setting Total Average Average Average Average Treatment
Rainfall Total Daily Market Irrigation Water
Treatment App. Yield Water Savings
App. Use Compared
Efficiency to 15
(mm) (mm) (mm/d) (kg/ha) (kg/m3) (%)
12 10% 343 53 0.88 24,110 40 79

Spring 13 12% 343 138 2.3 29,080 22 45
2005 14 12-14% 343 131 2.2 27,480 22 48
II 8% 149 156 2.6 17,100 11 53
Spring
2006 I4 12-14% 149 169 2.8 14,200 4 49
II 8% 132 244 3.2 43,400 18 44
Fall
2006 I2 10% 132 213 2.8 45,500 21 38


Spring II 8% 124 171 2.3 29,700 17 44
2007 12 10% 124 190 2.5 27,500 15 38









CHAPTER 3
EVAPOTRANSPIRATION AND CROP COEFFICIENTS FOR GREEN BELL PEPPERS IN
FLORIDA

Introduction

As the demand for fresh fruits and vegetables rises, so does the need to conserve the

limited state water supply. Irrigated agriculture is one of the main industries with a high

potential for large water savings. Row crops, particularly tomatoes and peppers, are two of the

mostly widely grown cash crops. Green bell peppers (capsicum annuum L.) grow well

throughout the state and thrive in the sandy soil. They are typically planted on raised beds

covered with plastic mulch to help maintain water and nutrient levels in the rooting zone. The

raised beds are most often drip irrigated to deliver water directly to the root zone; thereby,

reducing losses to evaporation and percolation. Proper irrigation scheduling and management is

important when growing bell peppers, as they are susceptible to water stress. It is important to

maintain a constant supply of available water to prevent stress that can result in yield reduction.

Two of the most critical stages in of bell pepper growth occur in the very beginning, when

transplants are developing stable and efficient root systems to support future growth, and during

flower and fruit set when even small amounts of water stress can significantly reduce yields.

Over irrigation can also damage plants. If the soil in the root zone becomes saturated, the lack of

oxygen can damage the uptake functioning of roots reducing the transport of nutrients and water.

Excessively applied water can also cause the leaching of valuable nutrients from the soil profile

which also can lead to yield reductions.

Effective irrigation scheduling requires knowledge of the crop water demand, ETc during

the primary growth stages. This can be calculated by multiplying the reference

evapotranspiration, ETo, by a specific crop coefficient, K,. Many Kc values have been published

for various crops during the three main growth stages. For bell peppers, Allen et al. (1998)









recommends general values ofKc ini = 0.6, Kc mid = 1.06, and Kc late = 0.9., with Kc int referring to

the initial part of the season, Kc mid for the middle of the season, and Kc late for the end. The Kc

values are adjusted throughout the season based upon the growth stage of the crop. Kc int is low

when plants are small and require less water for transpiration. Kc mid is the highest Kc value to

account for the increased water demands during fruit and vegetation development. Kc late is

slightly lower than Kc mid to account for the decreasing water demands as the plant reaches

maturity. Since many factors influence Kc, including location, length of growth stage, and

management practices, Allen et al. recommends the development and adjustment of Kc based on

local field conditions.

In the past, research has been done on drip irrigated tomatoes grown on plastic mulched

beds (Amayreh and Al-Amed, 2005; Hanson and May, 2006), but few studies exist for bell

peppers. Amayreh and Al-Amed (2005) reported crop coefficients of Kc mid = 0.82 and Kc late =

0.76, much lower than the FAO recommended values for the Jordan Valley, which they

attributed to the plastic mulch and drip irrigation. Fernandez et al (2000) researched Kc values

for peppers grown under greenhouse conditions. The reported Kc mid value of 1.4 was higher

than previously suggested Kc mid values for bell peppers due to the modified indoor growing

conditions of the greenhouse that increased net radiation. Jabar et al. (2007) investigated Kc

values of seepage irrigated, Florida grown bell peppers. They also reported higher Kc values,

with Kc int = 0.71, Kc mid = 1.61, and Kc late = 1.1, which they attributed to the wetter growing

conditions caused by the seepage irrigation system.

In order to estimate Kc, the actual crop water demand, ETc, must be estimated first. This

can be done using a soil water balance approach that reflects the water inputs and outputs of the

system. Drainage is a difficult component to measure in the soil water balance. A common way









to quantify this water loss is by installing lysimeters under the irrigated area of the field. Two

types of lysimeters commonly used in research are weighing and drainage. Weighing lysimeters

can be used to measure ET, with a mass balance approach, and are typically used when small

time steps (hourly or daily) are required. Drainage lysimeters measure ET, with a volumetric

water balance approach, and can accurately quantify drainage on a weekly or monthly basis

(Shukla et al., 2006). Any excessively applied water drains from the profile by gravity and

collects until it is pumped out. The volume of the collected leachate can then be converted to a

depth and used as an output in the soil water balance equation. By knowing the actual crop

water demand, accurate crop coefficients, K,, which account for differences in the local

microclimate and growing practices, can be determined.

The objective of this study was to collect, measure, and analyze the soil water balance

parameters of the raised bed system with the purpose of estimating crop ET and Kc values for

green bell pepper.

Methods and Materials

This research investigated the crop water use of soil moisture sensor (SMS) based, drip

irrigated bell peppers grown on plastic mulch during the growing seasons of spring 2005, spring

2006, fall 2006, and spring 2007. The experiment was repeated over four different growing

seasons to minimize the effects of variable climate and field conditions. The study took place in

Marion County, Florida at the University of Florida Plant Science Research and Education Unit.

Soils Characteristics

Each of the four trials was located at the same field site. The soil for this site was

classified as Candler sand and Tavares sand containing 97% sand-sized particles (Buster 1979).

Field capacity was estimated to be in the range of 0.10-0.12 v/v in the upper 0-30 cm (Icerman,

2007). The soil is very permeable, with a low water holding capacity, making excessively









applied water and nutrients highly susceptible to drainage and leaching (Simonne and Hochmuth,

2004). Paramasivam et al. (2000) estimated the field capacity and permanent wilting point

(PWP) of Candler and Tavares sand as 0.1 and 0.025 cm3/cm3, respectively. This amounts to

0.075 cm3/cm3 of available water (AW) in the soil profile.

Experimental Design and Field Layout

In preparation for this study, drainage lysimeters were installed under selected treatments

on March 21, 2005, prior to bed formation (Zotarelli et al., 2007). At the start of each

experiment the field was rototilled, beds were formed, and immediately fumigated (80% methyl

bromide, 20% chloropicrin) and covered with black plastic mulch. Drip irrigation tape was

simultaneously installed with the plastic mulch. Two drip lines, one for irrigation and one for

fertigation, were installed in the center of each plot on the soil surface below the plastic mulch.

Approximately 45 day old bell pepper plants ('Brigadier') were transplanted on April 5, 2005,

April 10, 2006, September 11, 2006, and April 12, 2007 into raised plastic mulched beds, 15 m

long and spaced 1.8 m apart, center to center. The transplants were spaced 0.3 m apart and

planted in staggered dual rows.

The treatments were laid out in a randomized complete block design with four replicates.

Each experiment had a factorial design of five irrigation treatments (II, 12, 13, 14 and I5) and

three nitrogen treatments (NI, N2 and N3). Four of the irrigation treatments (11-14) were

scheduled based upon soil moisture, while the other treatment (15) was a time based treatment

intended to simulate grower practices. The five irrigation treatments and three fertigation

treatments were applied across all four blocks via eight separate flow meters installed off of the

main irrigation line. The fertigation levels were based on IFAS recommendations for bell

peppers, with N2 being 100% of the recommended rate (208 kg/ha), NI as 80% of N2 166

kg/ha), and N3 as 150% of N2 (312 kg/ha). Irrigation and fertigation was applied via drip tape









(Turbulent Twin Wall, 0.20 m emitter spacing, 0.25 mm thickness, and 0.7 L/hr at 69 kPa

(Chapin Watermatics, NY).

Irrigation and Fertigation Control and Data Collection

The SMS irrigation treatments allowed or bypassed programmed irrigation events based on

readings taken by soil moisture sensors. Two different soil moisture sensors were used during

the four field trials. In spring 2006, SMS treatment, II, used a dielectric capacitance probe

(ECH20, Decagon Devices Inc., Pullman, WA) coupled with a quantified irrigation controller

(QIC) developed by the Agricultural and Biological Engineering Department ( Munoz-Carpena

et al., 2008). The rest of the SMS treatments used a Digital TDT Moisture Sensor paired with

either an RS500 or CS3500 irrigation timer, all manufactured by Acclima, Inc. (Meridian, ID).

Each season utilized four sensors, one for each SMS treatment, which were installed in one

replicate located in the south end of the field and controlled irrigation for the entire field. The

Acclima sensors were buried in the plot at a 30 angle to measure the top 0.15 m of the rooting

zone. The ECH20 probe was installed vertically into the plot to measure the top 0.2 m of the

rooting zone.

The QIC and Acclima RS500 irrigation controllers were wired to an irrigation timer (ESP-

12LX Irrigation Controller, Rainbird Corporation, Azuga, CA). The timer was programmed to

allow five irrigation events throughout the day to apply a potential irrigation depth of

approximately 5 mm/d. Each irrigation window was 24 minutes long, the required time to apply

1 mm of water, and programmed to begin at 8:00am, 10:00am, 12:00pm, 2:00pm, and 4:00pm

for spring 2005, spring 2006, and fall 2006, and 10:00am, 12:00pm, 2:00pm, 4:00pm and

6:00pm for spring 2007. Although the sensors were constantly monitoring the soil water content,

irrigation was initiated only during these scheduled windows. At the onset of a scheduled event,

the SMS controller queried the soil moisture sensor to determine the soil moisture content of the









soil. If the reading was lower than the threshold setting of the controller, irrigation would begin

and run for 24 minutes. If the sensor reading was higher than the controller threshold setting, the

event was bypassed. The QIC treatment functioned slightly different. While it too was only able

to irrigate during the scheduled windows, instead of relying only on the initial soil moisture

reading at the onset of the event to determine whether or not to irrigate, this controller queried

the sensor every minute during the window allowing irrigation to start and stop based on the

sensor readings. The Acclima RS3500 irrigation controller represented an "on demand"

irrigation schedule, and allowed irrigation events to occur at any time the sensor reading fell

below the lower bound of set threshold range. The irrigation event ended when the sensor

indicated the soil moisture content was at or above the upper bound of the setting.

The control treatment represented a time based irrigation schedule intended to represent a

grower schedule. This treatment irrigated once a day, regardless of soil water conditions, for 2

consecutive hours (5 mm/day) in the morning. Table 3-1 outlines the irrigation treatments and

soil moisture threshold settings implemented for each experiment.

Water applications from irrigation and fertigation events were manually recorded weekly

from positive displacement flowmeters (V100 1.6 cm diameter bore with pulse output, AMCO

WaterMetering Systems Inc., Ocala, FL). In addition to manual readings, the flowmeters

contained transducers that signaled a switch closure every 18.9 L. The switch closures were

recorded by data loggers (HOBO event logger, Onset Computer Corp. Inc., Bourne, MA) and

continually logged water and fertigation event times, which were downloaded once a week.

These data were used to determine if and when irrigation events occurred or were skipped.

Soil Moisture Monitoring and Drainage Collection

Soil moisture content was monitored in each experiment by time domain reflectometry

(TDR) probes (CS-615, Campbell Scientific, Inc. Logan, Utah) buried at a 300 angle to measure









the upper 0.15 m of the rooting zone. The probes were installed in each irrigation treatment plot

across all replicates. All of the TDR probes were connected to a data logger (Model CR-10,

Campbell Scientific, Logan, Inc., UT) with a relay multiplexer (Model AM416, Campbell

Scientific, Inc., Logan, UT). The data was downloaded weekly and analyzed to provide hourly

soil moisture readings (VWC).

Drainage lysimeters were installed under the raised beds prior to the start of the trials with

the purpose of capturing and quantifying the amount of water percolated below the effective

rooting zone of the crop. Details of the lysimeter dimensions and burial depth can be seen in

Figure 3-1. The lysimeters were constructed by cross-sectioning 208 L polyethylene drums, and

had a capture area of 1.52 m2 (Zotarelli et al., 2007). They were buried 0.75 m below the surface

of bed. Water drained into the lysimeters by gravity and was pumped out weekly into 20 L

bottles using two vacuum pumps. The bottles were weighed to determine the leachate volume,

mL, which was then used to calculate a drainage depth, mm. For the spring 2005 and spring

2006 seasons, leachate was collected from treatments 12, 13, and I5. In fall 2006 and spring

2007, the 14 treatment was also included.

Dye Injection

To further investigate the movement of irrigation water under the plastic mulched bed,

soluble blue dye was injected into the main irrigation lines. Transverse sections of the bed were

dug to observe the wetting front over 7 days (76-82 DAT). Measurements of the wetting front,

length, width, and depth, were taken after irrigation applications on days 1, 3 and 7.

Weather Data Collection

Weather data was collected during the four growing seasons from a weather station

located approximately 500 m from the experiment site. The downloaded meteorological data

included relative humidity, temperature, wind speed, and solar radiation which were used to









calculate daily and weekly grass reference evapotranspiration (ETo) using the FAO Penman-

Monteith method (Allen et al.,1998):

900
0.408A(R, G) + 90 (e, -e)
ET =-- T+273 (3-1)
A A+ (1+0.34u2)

where ETo reference evapotranspiration (mm/d),
Rn net radiation at the crop surface (MJ/mm/d)
G soil heat flux density (MJ/m2/d)
T air temperature at 2 m height (C),
U2 wind speed at 2 m height (m/s),
es saturation vapour pressure (kPa),
ea actual vapor pressure (kPa),
es-ea saturation vapour pressure deficit (kPa),
A slope vapour pressure curve (kPa/C),
7 psychrometric constant (kPa/C),


Crop ET, is calculated by multiplying grass reference ETo by a theoretical or field

estimated crop coefficient, Kc.

Kc values

According to Allen et al. (1998), crop coefficients can account for specific crop

characteristics, variations in climate, and modified management practices to provide an accurate

representation of crop water demand, ETc. Although recommended Kc values exist for a wide

variety of crops and regions throughout the country, the estimation of Kc values should reflect

the local microclimate and growing practices.

To investigate differences between Kc values, three different published Kc values were

compared to a field estimated K,. The published values used in the analysis are given in Table

3-2. The first Kc value, KCIFAS, was taken from the Vegetable Production Guide for Florida

(Maynard and Olsen, 2001). The second value, KCFAO, was based on recommendations given in

FAO Irrigation and Drainage Paper No. 56 (Allen et. al. 1998) for crops grown on plastic mulch.









KcFAO was calculated by reducing KCIFAS by 30% to account for the large decrease (50-80%) in

evaporation from the soil surface due to the plastic mulch covered beds (Allen et al. 1998).

Although the plastic mulch causes a slight increase in plant transpiration, a 30% reduction in Kc

is suggested by Allen et al. (1998) to compensate for the evaporative deficit on frequently

irrigated plastic mulch covered beds. The third value, KcSHUKLA, was taken from research

conducted on seepage irrigated bell peppers in southwest Florida (Jabar et al., 2007). The values

are high due to the wet growing conditions caused by the seepage irrigation.

The Kc values vary during the major growth stages of the crop. Kcint is used during growth

stages 1 and all or part of growth stage 2. The pepper transplants are small during this stage and

do not have large water demands yet. The main function of the transplant during this phase is to

establish an extensive and efficient root system to support plant growth. Kcint is low during this

phase to reflect the low water demand of the crop. Kcmid is used for part of growth stage 2, and

all of growth stage 3. This is the highest Kc value during the life of a pepper plant, and reflects

the increased crop water demand to support optimal reproductive and vegetative growth. Flower

and fruit set are the most important functions during this growth stage, and even small levels of

water stress can greatly reduce the future yield of the plant. Values for Kciate are slightly lower

than Kcmid, indicating a small reduction in water demand, which corresponds to fruit maturation

and harvest during growth stage 4.

Crop coefficients can be estimated using field measured parameters to measure the actual crop

water demand, ETc. This study used drainage lysimeters to capture drainage under the raised

beds. This, along with known irrigation applications, can be used to estimate the actual water

demand of the crop. Field estimated Kc can be calculated from the ratio of estimated crop ETc

and reference crop ETo.









Theoretical ETc

The crop water demand, ET, was estimated two different ways. The first method

calculated the theoretical ETc based on the relationship between grass reference ETo, and a crop

coefficient, K,:

ET, = ETo x Kc (3-2)

where ETo is the reference ET in mm as calculated in Equation 3-1, and Kc is the bell

pepper crop coefficient.

Field Estimated ETc

ET, was also estimated using field measured parameters in a soil water balance equation

which accounts for all water inputs and outputs that pass through the system:

ET= I+P -AS-D R (3-3)

where ET, is the actual crop water demand in mm, I is the irrigation depth applied to the entire

field in mm, P is precipitation contribution to the root zone in mm, AS is the change in soil water

storage from the last time step in mm, D is the collected drainage depth in mm, and R is runoff in

mm. For this project several assumptions were made based on the soil water interactions specific

to the field site. Precipitation, P, is assumed to zero due to the plastic mulched beds that keeps

most rainfall events from greatly impacting the soil water balance. This can be seen in Figure 3-

-12 and Figure 3-13. There were only nine events over the four growing seasons, four in spring

2005, that were large enough (over 15 mm) to increase VWC by an average of 4.7%. However,

water from these events was considered negligible to the weekly soil water balance. More on

this topic can be found in Chapter 4. The change in soil moisture content, AS, although known

to undergo frequent fluctuations throughout the day in relation to irrigation events, is also

assumed to be zero, since the water is easily drained from the sandy soil profile resulting in









negligible changes over weekly time steps (Figure 3-2). During weeks when there is a change in

weekly water storage, the change is very small, for example 0.1 VWC in the beginning of the

week and 0.12 VWC at the end of the week. With field capacity and permanent wilting point

estimated as 0.1 and 0.025 v/v, respectively, the available water in the soil profile is

approximately 0.075 VWC (Paramasivam et al., 2000). This small amount of water is the result

of the low water holding capacity of sandy soils, and any changes in water storage can be

considered negligible in the overall weekly soil water balance calculation.

And lastly, runoff, R, is negligible due to flat field conditions and application of water by

drip irrigation. Equation 3-3 can then be simplified as follows:

ETc = I D (3-4)

where the only significant factors are irrigation depth, I, in mm and drainage, D, in mm.

Drainage depth, D, used to estimate ET, in Equation 3-4, was calculated on a weekly

basis from the volume collected from the drainage lysimeters. However, for sufficiently watered

SMS treatments, drainage, D, should be negligible which would simply Equation 3-4 even

further by assuming that for properly functioning, well watered SMS treatments:

ET, = I (3-5)

As previously mentioned, this estimated ET, can then be used to obtain the actual field

estimated crop coefficient, Kc as:

ET
K,=- (3-6)
ET,

where ET, is the estimated crop water demand in mm from Equation 3-4, and ETo is grass

reference ET calculated with weather parameters using Equation 3-1.









Results and Discussion


Climate Conditions and ETo

For spring 2005, cumulative rainfall totaled nearly 343 mm (Figure 3-3) which was much

higher than the average rainfall of 253 mm for this region during this time period (FAWN,

2007). This rainfall amount was exceptionally high and exceeded the season total ETo of 248

mm. The high rainfall may have contributed to a high incidence of disease that spread through

the field approximately midway (40 DAT) through the growing season. The spring 2006 season

experienced much less rainfall than the previous with a total of 149 mm, while ETo totaled 245

mm (Figure 3-4). The relatively drier field conditions reduced the spread of disease, although

bacterial spot was present at the end of the season. The fall 2006 growing season had a

cumulative rainfall and ETo of 132 and 160 mm, respectively (Figure 3-5) The low incidence of

rainfall and cooler fall temperatures contributed to a very low occurrence of plant disease. ETo

was much lower, nearly 50%, compared to the spring seasons due to the decrease in day length,

solar radiation, and temperature. Cumulative rainfall for spring 2007 totaled 124 mm, while ETo

totaled 273 mm as seen in Figure 3-6.

Estimating Drainage

Since drainage lysimeters were not installed under all irrigation treatments, drainage was

calculated using Equation 3-4 and the Kc values published in the Vegetable Production Guide

for Florida (Maynard and Olsen, 2001), KcIFAs, to estimate ETc.

Figures 3-8 through 3-10 show calculated drainage depths compared to measured

drainage depths along with cumulative irrigation. Overall, the estimated drainage depths were

much higher than measured depths when large amounts of irrigation were applied. This

difference may be attributed to lyismeter collection or inaccurate KcIFAS values. The drainage

lysimeters seem incapable of capturing high volumes of leachate, as all weekly drainage depths









collected from the four seasons were less than 10.3 mm. This may be due to the small lysimeter

capture area, 1.27 m2, relative to the irrigated area under the raised bed, 10.41 m2. This area may

not be large enough to thoroughly collect drainage if water traveled laterally out of the capture

zone. A dye experiment was conducted after the last harvest during the spring 2006 season to

identify movement of irrigation water through the soil profile. Figure 3-7 illustrates the wetted

front of treatment 15 after day 7 (82 DAT) of the dye experiment. The figure shows irrigation

water percolating laterally through the profile to a maximum width of 56 cm (Figure 3-7), a

large enough range to be captured by the 55 cm wide lysimeter. The problem may be attributed

to the actual burial placement of the lysimeter in relation to the planted bed. Since the drainage

lysimeters were installed prior to the formation of the beds, there is a possibility that the rows

were not centered exactly over the lysimeters, which would decrease the capture area.

The difference between calculated and measured drainage may also be attributed to the reported

KcIFAS values used to calculate drainage for this comparison. The values may be too low,

especially during growth stages 1 and 2 when the transplants were established with a time based

irrigation schedule. The low KcIFAS value, 0.2, during this time drastically reduced ETc, which

caused calculated drainage to be much higher than the measured drainage across all treatments

and seasons. The measured drainage values were similar to the calculated values only at very

low depths. Most of these low drainage volumes were collected from SMS treatments with low

irrigation applications during growth stage 3 when ETc values increased due to an increase in

KcIFAS. Although the exact volume totals collected by the lysimeters did not match the calculated

drainage, the lysimeter drainage data that show increased drainage with increased irrigation.

More information on these trends can be found in Chapter 2.









Estimating ETc

Estimated field ET, can be approximated by analyzing the irrigation applications of the

functioning SMS treatments. These treatments applied limited amounts of water that greatly

reduced or eliminated drainage to supply just enough water to support the demands of the crop,

or ETc. So for a properly functioning SMS treatment, ET, can be approximated by the amount of

irrigation applied to the crop after treatment initiation. The functioning treatments are

summarized in Table 3-2 along with treatment irrigation and ET, totals. Figures 3-12 through

3-14 illustrate the average daily soil moisture content, as measured by TDR probes, for the seven

treatments. The field capacity shown on the graphs was approximated based on the average soil

moisture content of the time based irrigation treatment, 15, 24 hours after an irrigation event.

Although measured to be 10-12% in previous field studies (Icerman, 2007), field capacity can

vary depending on soil and field conditions. Due to this variation, field capacity was

approximated based on the treatment average of the entire field. On average, the TDR probes

recorded a 0.042 VWC increase in soil moisture during the 2 hour irrigation events, reaching

maximum VWC at the end of the event, followed immediately by a rapid decrease until the soil

reached a relatively steady moisture state. This steady state was usually reached within 24 hours

of the onset of the irrigation event, and is assumed to approximate the field capacity of the raised

bed. Treatment 15 in Figure 3-11 illustrates this assumption and shows the majority of available

soil water was drained during the 24 hour period following the scheduled irrigation event. The

graph shows a missed irrigation event, resulting in a 48 hour period between events, during the

beginning of the growing season (19 DAT) when plant roots were still underdeveloped and

therefore not able to uptake a significant amount of water from the soil. The change in soil

moisture between the missed event (May 1-May 2) is very small, only 0.008 VWC, which

indicates that the soil had reached approximate field capacity within 24 hours after the irrigation









event on April 30. All of the functioning treatments in Figures 3-12 and 3-13 maintained soil

moisture content near the approximated field capacity. Over irrigation did not appear to occur

since there were no significant spikes in SMC during irrigation events, unlike those observed in

the time based 15 treatment as shown in Chapter 4 in Figure 4-11. This indicates sufficient water

was supplied to support plant demands, ETc, without excess losses to drainage.

Estimating Kc

Once ET, was estimated by using SMS treatment irrigation totals, field estimated Kc

values were obtained by rearranging Equation 3-2 to get:


K, = E_ or K = (7)
SETo ET,

where ET, is the field estimated crop demand in mm, and ETo is grass reference ET calculated

from Equation 3-1, and I is the irrigation total after treatment initiation. Table 3-3 shows Kc

values developed for each of the successful SMS treatments. The 14 (12-14%) SMS treatment in

the spring 2005 season produced the lowest values which were likely the result of lowered crop

water demand caused by high precipitation (342 mm). Kc values were calculated by averaging

treatment values across each growth stage. It should be noted that Kc int was not calculated based

on the full four weeks of the initial growth stage due to the transplant establishment phase prior

to SMS treatment initiation. Kc int is was not calculated for treatments 14 (12-14%) in spring

2006 and II (8%) in spring 2007 because they were not fully initiated until growth stage 2.

The averaged field estimated Kc values are shown in Table 3-4 and Figure 3-14 along

with two reference crop coefficients given for bell peppers, Kc IFAS and KCFAO and values

published by Jabar et al (2007). Each give three values depending on the growth stage of the

crop. As mentioned earlier, Kc IFAS is recommended by the Vegetable Production Guide for

Florida and KCFAO is based on the KCIFAS values that have been adjusted according to guidelines









set out by Allen et al (1998) in FAO Paper No. 56. This adjustment reduced KCIFAS by 30% to

account for the lower evaporative demands of the plastic mulch covered beds. Figure 3-14

shows the Kc estimates based on treatment irrigation totals along with KclIFAS, KcFAO, and

KcSHUKLA for each season as well as an overall three season average. The low irrigation volumes

applied during spring 2005 resulted in lower estimated Kc values. The spring 2006 and spring

2007 seasons were very close to KclFAS for growth stage 3. Overall, the average Kc values over

the three seasons were close to those of KcIFAS (Figure 3-14) as well as values reported for drip

irrigated tomatoes. Kc mid, 0.93, was 12% higher than Kc mid, 0.82, reported by Amayreh and Al-

Abed (2005) for drip irrigated tomatoes in the Jordan Valley, while the estimation of Kc late was

slightly lower, 0.71, than Kc late reported for tomatoes, 0.76. KcSHUKLA (Jabar et al., 2007) were

estimated based on bell peppers grown under seepage irrigation in southwest Florida, and were

the highest values in this comparison (Figure 3-14). This was likely the result of the wet field

conditions caused by seepage irrigation (Jabar et al., 2007). The values of KcFAO, which factored

in a 30% reduction for plastic mulched beds under high frequency irrigation schedules, are most

likely too low. Further research should be conducted to investigate the effects of Florida

vegetable crops grown in raised plastic mulched beds on ETc. Also, Kc int values could not be

accurately estimated since the transplants were established during most of this phase with a time

based schedule. The recommended Kc values, KclIFAS and KcFAO for this stage, however, are very

low ranging from 0.1-0.3. Further research should investigate row crop growth on raised beds

using these recommended values in growth stages 1 and 2.

Conclusions

This project studied the effects of SMS based irrigation scheduling on drip irrigated bell

peppers for four seasons. Various ways to estimate crop water demand were investigated

including the calculation of theoretical values and a soil water balance approach. A soil water









balance was created using measured and estimated field parameters. Since the SMS treatments

were initiated to maintain moisture content around field capacity, keeping just enough water

available for plant uptake, it was assumed that the average irrigation depth applied by the SMS

treatments was equal to actual ET, for functioning treatments. Soil moisture data was analyzed

for each treatment and compared to the average seasonal field capacity to confirm that the

treatments maintained soil moisture content within an acceptable range. Drainage, both

calculated and measured, was also very low after these SMS treatments were initiated. Crop

coefficients were calculated for bell peppers grown on plastic mulch covered beds and compared

to existing Kc values recommended for the location and management practices of the project.

The field estimated Kc values fell in between the range of recommended values, KclFAS and

KcFAO, for the major growth and development stage, but are much lower than Kc values published

by Jabar et al, 2007 for seepage irrigated bell peppers. Future research should investigate the

lower limits of crop water demand to establish an accurate estimation of ETc for drip irrigated

bell peppers. Also, because Kc int could not be accurately estimated since the plants were

uniformly irrigated for establishment during the majority of this growth phase, further research

should include the effects of various Kc values on plant growth and development during the first

and second growth stages. Research should also be conducted to investigate the accuracy of

drainage lysimeters buried beneath drip irrigated, plastic mulched, raised beds.









Table 3-1. Irrigation treatments, threshold
times.


settings (VWC), and programmed irrigation run


Treatment Description VWC threshold Irrigation window
setting
(m3/m3)


Spring Pepper 2005
11
12
13
I4
15

Spring Pepper 2006
11
12
13
I4
15

Fall Pepper 2006
11
12
13
I4

15

Spring Pepper 2007
11
12
13
I4

15


QIC
Acclima RS500
Acclima RS500
Acclima CS3500
Time-based
schedule

Acclima RS500
Acclima RS500
Acclima RS500
Acclima CS3500
Time-based
schedule

Acclima RS500
Acclima RS500
Acclima RS500
Acclima RS500
twin drip lines
Time-based
schedule

Acclima RS500
Acclima RS500
Acclima RS500
Acclima RS500
twin drip lines
Time-based
schedule


0.1 (500 mV)
0.1
0.12
0.12-0.14
n/a


0.08
0.1
0.12
0.12-0.14
n/a


0.08
0.1
0.12
0.1


24 min, 5 times/day
24 min, 5 times/day
24 min, 5 times/day
Anytime
2 hours, 1 time/day


24 min, 5 times/day
24 min, 5 times/day
24 min, 5 times/day
Anytime
2 hours, 1 time/day


24 min, 5 times/day
24 min, 5 times/day
24 min, 5 times/day
12 min, 5 times/day


n/a 2 hours, 1 time/day


0.08
0.1
0.12
0.1


24 min, 5 times/day
24 min, 5 times/day
24 min, 5 times/day
12 min, 5 times/day


n/a 2 hours, 1 time/day


















DUFH


0.95m


- T
0.75m



0.27m -


i -


Raised Bed Edge
0.85m


Details and dimensions of drainage lysimeter burial beneath raised bed


"T
0.27m
-L


0.95m


- Drip Tape


Drainage Lys


_ I Raised Bed Edge


Figure 3-1.











0.25 -

-,0.20 -

0 0.15 -

S0.10 -

0.05 -


10


10/7 10/8 10/9 10/10


Date


Figure 3-2.


Example of negligible change in soil moisture content during one week in the fall
2006 season.


50


E 40
4-
30


c
Co


50



40



30


I--

20



10


0 20 40 60 80
Number of Days after Transplanting


Figure 3-3.


Minimum, maximum, and average temperatures during spring 2005 along with
daily and cumulative rainfall and evapotranspiration, ETo.


10/5 10/6


Fall 2006 15, time based








Average SMC= .075
111111 i


/3 10/4













Cumulative Rainfall
r I Daily Rainfall
--Average Air Temperature
Cumulative Eto


Number of Days after Transplanting


Figure 3-4.


Minimum, maximum, and average temperatures during spring 2006 along with
daily and cumulative rainfall and evapotranspiration, ETo.


50


40

S
30

a
- 20


10


50



40


o
30



20 E
1-


10



0


20 40 60 80
Number of Days after Transplanting


Figure 3-5.


Minimum, maximum, and average temperatures during fall 2006 along with daily
and cumulative rainfall and evapotranspiration, ETo.


30


25


20


15 C.
E
I-
10


5


0


- G~n~


- A


- *


* **
















50 -

E
=- 40 -
r4-

30 -
-


20 -


10 -


Cumulative Rainfall
r -I Daily Rainfall
-- Average Air Temperature
-- Cumulative ETo


n n


Spring 2007


















--n
" mm


40



30



20 E
I-


* 10



0


Number of Days after Transplanting




Figure 3-6. Minimum, maximum, and average temperatures during spring 2007 along with
daily and cumulative rainfall and evapotranspiration, ETo.














































Figure 3-7.


The wetted front of the time based irrigation treatment 15 after day 7 of the dye
injection test (82 DAT).


J


M4














11, QIC 10%
Growth Stage 4
1 2 3 ..


14, 12-14% Acclima
Growth Stage
1 2 3 4









15, time based
Growth Stage

1 2 _3






I n 1 In In I In n n In I n


80 9


10 20 30 40 50 60 70
Number of Days after Transplanting


E

E 0

C C

# Q


Figure 3-8.


Weekly estimated and measured drainage along with cumulative irrigation for all
treatments during the spring 2005 season. Drainage is shown as vertical bars with
dark shaded bars representing calculated drainage and lighter bars depicting
measured drainage. Drainage was not collected from treatments II and 14.


- 400 E

- 300 a

-200 E

- 100 *^

0
500

-400

-300 E
'5 .2
-200 E

100

0
500

-400

-300 = -
*5 .2
-200 E



0
500

-400 -

-300

-200 E

-100

0
500

400

300 ~
M c
*5 .2
200 E

100

0
0


-U 1UU

C-; 80

S 60
E

Lu 40

20

2 0
100

- 80

S 60
E

S40

S 20

2 0


E



0)




02
LU C




E
i
E



LU-o
.E
>.E )


100


500
















E E






E -

E '










"0





E %






>,.E
M EC
LU'



ES


E'75^


0 10 20 30 40 50 60 70
Number of Days after Transplanting


Figure 3-9.


Weekly estimated and measured drainage along with cumulative irrigation for all
treatments during the spring 2006 season. Drainage is shown as vertical bars with
dark shaded bars representing calculated drainage and lighter bars depicting
measured drainage. Drainage was not collected from treatments II and 14.


11,8% Acclima
Growth Stage
- 1 : 2 -3 4


14,12-14% Acclima











15, time based
Growth Stage 2
- 1 = 2 3







n n n n In In I In


-400
E
-300 ,

200 ES

-100

0
500

-400 E

-300 E
-3.2
-200 E-S
-500
-100 -

0
500

-400 -
E
-300

-200 ES
-3.2
-100

0
500

-400 E

-300
nM C
200 E S

100

0
500

400

-300 |
*oo .
-200 ES

100

0


80 90












100 500
11,8% Acclima
4 80 Growth Stage 400 -
E E 1 2 3 > E
S 60 300

> 40- 200 E 1-

|i 20 100 :

o8 R. 00oo
o E 12, 10% Acclima
80 Growth Stage 400
) u4 E
CS 60 300 '
E 'i5
U 40- 200 E
L -
S 20 1 0 "0

0 0 "
-E 100 500
0 0 13,12% Acclima
80 Growth Stage 400
1 -..- 2 .3
60 300
E
40o 200 E2

21 20 100

2 0o .n n n In 1. *r 0
100500
1oE 14, 10% twin drip, Acclima
SE- E 80 Growth Stage 2 4 -400



40 200 E

S 20 |- 100


100 500
1 E 15, time based
E 80- Growth Stage -400
=n < 1 2 -- __ 3 4>~ 40 E
.S 60 300 -

l 40 200 E

(n 20 100
2 0 n .n n, n n In In 0

0 10 20 30 40 50 60 70 80 90
Number of Days after Transplanting


Figure 3-10. Weekly estimated and measured drainage along with cumulative irrigation for all
treatments during the spring 2007 season. Drainage is shown as vertical bars with
dark shaded bars representing calculated drainage and lighter bars depicting
measured drainage. Drainage was not collected from II.









Table 3-2. Summary of SMS treatments that approximate ET, over spring 2005, spring 2006,
and spring 2007 growing seasons, along with treatment irrigation and ET, (calculated
with Kinitial=0.2, Kmid= 1.0, Klate=0.85).
Treatment Treatment Threshold Total Treatment Total
Description Description Setting Application Treatment
ET,
(mm) (mm)
II, 8% spring 2006 Acclima-based 0.08 156 150

14, 12-14% spring 2006 Acclima-based 0.12-0.14 169 150

II, 8% spring 2007 Acclima-based 0.08 171 139


0.25

- 0.20
"- 0.15
0
0.10

0.05


25

20 E

15 E
,-
10 -

5

0


4/28 4/29 4/30 5/1 5/2


5/3 5/4 5/5


Date


Figure 3-11.


Volumetric water content measured at 15 cm for April 28 to May 4, 2006 (17 to
23 DAT). The horizontal line indicates the approximated field capacity.

















0.20


,> 0.15
-

S0.10
-)

> 0.05
-




0.25 -


0.20

0.15


0.10-
S0.05


Growth Stage
2


F.C.= 0.082


I II.


24
Figure 3-12.


0.25 -


0 0.20 -


>, 0.15-


) 0.10-
0)

> 0.05 -


Figure 3-12.


I I I


* 50

40 E
E
30 =
.4-
20 '

* 10

0
60

- 50


40 2
E

30 -=
cc
.4-
C
20 '

10


28 32 36 o 44 48 52 56 o 64 68 72 76 o
Weekly rainfall and soil moisture content averages, measured by TDR probes
across the entire field, for II and 14 after treatment initiation in spring 2006.
Growth stages 2-4 are shown at the top of the graph. The red line represents the
observed field capacity of the soil (0.082).



60
11, 8% Acclima
Stage 50
3 4
E
30 =

20 '5
133





Weekly rainfall and soil moisture content averages, measured by TDR probes
across the entire field, for II after treatment initiation in spring 2007. Growth
stages 2-4 are shown at the top of the graph. The red line represents the observed
field capacity of the soil (0.133).


14,12-14% Acclima


Growth
2





F.C.= .


4


-












Table 3-3. Estimated Kc values for each treatment along with overall averages.

Season Treatment Threshold Kc initial* K, mid Kc late
Setting
Spring 2006 II 8% 0.70 0.96 0.59
Spring 2006 14 12-4% -** 0.95 0.84
Spring 2007 II 8% -** 0.88 0.69
Average -- -- 0.7 0.93 0.71
* Data represents final week of initial growth stage when SMS treatments were initiated.
**Insufficient data.


1 2 -

1 0 -
1-2
S08 -0

06
0
0
04 -
C
0
02

00
00

00


S- KclFAS
KcFAO
_-- Kc- field estimated
KcSHUKLA

0 10 20 30 40 50 60 70 80


Days after Transplanting


1.4

1.2

, 1.0

-,,
.20.8

0

0.4
0


0.2

0.0


Spring 2007


1.2 -

* 1.0-

. 0.8-

0
0.

S0.4-


-- KclFAS
- KcFAO
- -- Kc- field estimated
KcSHUKLA


0.2 -


0 10 20 30 40 50 60 70


0 10 20 30 40 50 60 70 80 90


Days after Transplanting


Figure 3-13.


Estimated Kc values averaged across spring growing seasons along with published
values, KclFAS and KcFAO for bell peppers.


Spring 2006


Days after Transplanting


80 90


Season Average Kc






--J /


- KclFAS
- KcFAO
- -- Kc- field estimated
KcSHUKLA









Table 3-4. Recommended, adjusted and estimated Kc values for bell peppers.
Kc Kc initial Kc mid Kc mid

Growth stage 1-2 3 4-5
Kc IFAS 0.2 1.0 0.85
Kc FAO 0.14 0.7 0.6
KcSHUKLA 0.71 1.16 1.1
Kc, estimate 0.7* 0.93 0.71
* Data represents final week of initial growth stage when SMS treatments were initiated.









CHAPTER 4
ANALYSIS OF SOIL MOISTURE SENSOR PERFORMANCE ON AUTOMATED DRIP
IRRIGATED PEPPERS GROWN IN SANDY SOIL

Introduction

Of the many crops that thrive in Florida, bell peppers (capsicum annuum) are among the

most important. Florida is ranked 2nd in the nation in production, acreage, and crop value, and

also produces nearly 100% of the winter crop for the nation (Mossler, 2004). To produce

maximum fruit yields, bell peppers, along with most other Florida crops, must be supplemented

with irrigation throughout the year. Agricultural operations in the state account for the largest

consumer of freshwater, using 39% of the groundwater supply and 62% of surface water

(Marella, 2004). The Florida agriculture industry has great potential to conserve large amounts of

water. Competition from foreign industry and an increasing demand for limited water has

motivated growers to seek out ways of improving the efficiency of their farming operations.

Improvements in irrigation scheduling can be an effective way for growers to maximize

yields, while conserving water, fertilizer and energy costs (Martin et al., 1990). Irrigating with

frequently scheduled irrigation events is very effective in Florida where much of the soil is

coarse sand with very low water holding capacities (Fares and Alva, 2000) Crops growing in

this type of soil require frequent irrigation events, sometimes several per day, to keep enough

available water in the soil for plant needs. In response to limited soil water holding capacity,

growers often over irrigate their fields as insurance against water stress that can lead to a

reduction in crop yield (Howell, 1996). This type of blind irrigation scheduling practice can

often be detrimental to the crop and the surrounding environment. The large pore spaces that

exist in sandy soils are conducive to deep drainage by any excessively applied water. Not only

does this water percolate out of the root zone, making it unavailable for plant uptake, but it also









carries nutrients along with it which may contribute to groundwater contamination (Bouchard et

al., 1992; Babiker et al., 2004; Spalding et al., 2001).

Improved irrigation scheduling involves an overall knowledge of climate conditions, crop

growth demands, and soil conditions. Making irrigation decisions based upon these contributing

factors is important to proper irrigation management. There are several methods for determining

soil water status ranging from the "feel" method and gravimetric sampling to neutron scattering

and various types of soil moisture sensors (Ley et al., 1994). Soil moisture sensors offer growers

a relatively inexpensive and "hands off" way monitor the soil water status of their fields. The

soil moisture readings from the field can help growers decide when to manually turn on

irrigation or sensors can be integrated into an irrigation control system to automatically make

irrigation decisions based upon this information. Soil moisture sensor (SMS) based irrigation

has been shown to be an effective scheduling technique in strawberries (Clark et al., 1996), citrus

(Fares and Alva, 2000), tomatoes (Munoz-Carpena et al., 2005). Previous studies have shown an

increase in irrigation water use efficiency (IWUE) for SMS based irrigation treatments, as

compared to typical time based treatments, while still producing acceptable marketable yields

(Dukes et al., 2003, Zotarelli et al., 2007a).

Research has been conducted on SMS based irrigation using soil water potential

measurements from tensiometers to control irrigation events. Smajstrla and Locascio (1996)

investigated the effects of SMS based irrigation using tensiometers to grow tomatoes in sandy

soil on plastic mulched beds. They found significant yield increases in sensor based treatments

with mid range threshold values (10 and 15 cb). Problems can exist; however, when

tensiometers are installed in sandy soils since the performance of the device is highly dependent

on establishing close contact with the surrounding soil, which can be challenging in coarse









textured, sandy soils (Munoz-Carpena, 2004). Tensiometers can also have a delayed response

time that could potentially be lethal to plants grown in sandy soils, where water can move

rapidly. Tensiometers also require frequent attention, especially in hot weather, to maintain an

unbroken water column (Munoz-Carpena, 2004).

Time domain reflectometry (TDR) probes are another kind of soil moisture sensor that has

been extensively researched. Topp and Davis (1985) field-tested the performance of

uncalibrated TDR sensors and compared the readings to gravimetric soil sample measurements.

The study found TDR probes to be an accurate method to assess soil moisture content; however,

the probes are expensive, making them an impractical option for most growers. New soil

moisture technology uses time domain transmission (TDT), similar to TDR in that it relies on a

reflection travel time to determine the permissivity of the soil. TDT probes are less expensive

than TDR probes, making them more accessible to growers (Blonquist et al., 2005).

Despite differences among the types of sensors, when integrated into an irrigation control

system, the sensors all operate one of two ways: 1) bypass control and 2) on-demand control

(Munoz-Carpena et al., 2008). A bypass control system allows irrigation events to occur only

during certain programmed times during the day. At the onset of a programmed event the

controller queries the sensor for a soil moisture reading. Depending on the result of this reading

and its relation to the threshold soil moisture setting, the system will either allow or bypass the

irrigation event. The system irrigates for a programmed amount of time and does not allow

irrigation until the next scheduled event. Bypass control differs from an on-demand controlled

system which queries the probe continually throughout the day and allows irrigation any time the

probe reads the soil moisture content to be below the programmed threshold range. The

irrigation event lasts only until the probe recognizes the soil moisture content to be at or above









the upper threshold range. The threshold soil moisture is predetermined by the operator during

the set up of the system. This setting should represent the minimum allowable soil moisture

content before an irrigation event is initiated. For example, if just before an irrigation event a

sensor measures a soil moisture content of 9% by volume, and the system threshold setting is

8%, the controller will bypass the event. If the sensor had read volumetric water content less

than 8%, the controller would have initiated the event.

The objective of this research was to evaluate the performance of two different soil

moisture sensor irrigation controllers set at various threshold settings by analyzing the number of

bypassed irrigation events, measured soil moisture content at event initiation, and the average

soil moisture content of the treatment throughout the season on drip irrigated green bell pepper.

Materials and Methods

This research investigated the performance of soil moisture sensors on drip irrigated bell

peppers grown on plastic mulch during the growing seasons of spring 2005, spring 2006, fall

2006, and spring 2007. The experiment was repeated over four different growing seasons to

minimize the affects of variable climate and field conditions. The study took place in Marion

County, Florida at the University of Florida Plant Science Research and Education Unit.

Soils Characteristics

Each of the four trials was located at the same field site. The soil for this site was

classified as Candler sand and Tavares sand containing 97% sand-sized particles (Buster 1979).

Field capacity was estimated to be in the range of 0.10-0.12 v/v in the upper 0-30 cm (Icerman,

2007). The soil was very permeable, with a low water holding capacity, making excessively

applied water and nutrients highly susceptible to drainage and leaching (Simonne and Hochmuth,

2004). Paramasivam et al. (2000) estimated the field capacity and permanent wilting point









(PWP) of Candler and Tavares sand as 0.1 and 0.025 cm3/cm3, respectively. This amounts to

0.075 cm3/cm3 of available water (AW) in the soil profile.

Experimental Design and Field Layout

At the start of each experiment the field was rototilled, beds were formed, and immediately

fumigated (80% methyl bromide, 20% chloropicrin) and covered with black plastic mulch. Drip

irrigation tape was simultaneously installed with the plastic mulch. Two drip lines, one for

irrigation and one for fertigation, were installed in the center of each plot on the soil surface

below the plastic mulch. The fall 2006 and spring 2007 growing seasons implemented an

irrigation treatment that used twin drip lines. In this case, the lines were installed at a distance of

0.15 m from the center fertigation line. The pepper transplants of the cultivar 'Brigadier' were

transplanted on April 5, 2005, April 10, 2006, September 11, 2006, and April 12, 2007 in raised

beds, 15 m long and spaced 1.8 m apart, center to center. The transplants were spaced 0.3 m

apart and planted in staggered dual rows.

The treatments were laid out in a randomized complete block design with four replicates.

Each experiment had a factorial design of five irrigation treatments (II, 12, 13, 14 and I5) and

three nitrogen treatments (NI, N2 and N3). Four of the irrigation treatments (11-14) were

scheduled based upon soil moisture, while the other treatment (15) was a time based treatment

intended to simulate grower practices. The five irrigation treatments and three fertigation

treatments were applied across all four blocks via eight separate flow meters installed off of the

main irrigation line. The fertigation levels were based upon IFAS recommendations for bell

peppers, with N2 being 100% of the recommended rate (208 kg/ha), NI as 80% of N2 166

kg/ha), and N3 as 150% of N2 (312 kg/ha). Irrigation and fertigation was applied via drip tape

(Turbulent Twin Wall, 0.20 m emitter spacing, 0.25 mm thickness, 0.7 L/hr at 69 kPa (Chapin

Watermatics, NY).









Irrigation and Fertigation Control and Data Collection

The SMS irrigation treatments allowed programmed timed irrigation events based on

readings taken by soil moisture sensors. Two different soil moisture sensor controllers were

used during the four field trials. In spring 2006, SMS treatment, II (See Table 4-1), used a

dielectric capacitance probe (ECH20, Decagon Devices Inc., Pullman, WA) coupled with a

quantified irrigation controller (QIC) developed by the Agricultural and Biological Engineering

Department (Dukes and Munoz-Carpena, 2005). The rest of the SMS treatments used a Digital

TDT Moisture Sensor paired with either an RS500 or CS3500 irrigation timer, all manufactured

by Acclima, Inc. (Meridian, ID). Each season had four sensors, one for each SMS treatment,

which were installed in one replication located in the south end of the field and controlled

irrigation for the entire field. The Acclima sensors were buried in the plot at a 300 angle to

measure the top 0.2 m of the production bed. The ECH20 probe was installed vertically into the

plot to measure the top 0.15 m of the raised bed.

The QIC and Acclima RS500 irrigation controllers were connected to an irrigation timer

(ESP-12LX Irrigation Controller, Rainbird Corporation, Azuga, CA). The timer was

programmed with five irrigation windows each day to apply a potential irrigation depth of

approximately 5 mm/d. Each irrigation window was 24 minutes long, the required time to apply

approximately 1 mm of water, and programmed to begin at 8:00am, 10:00am, 12:00pm, 2:00pm,

and 4:00pm for spring 2005, spring 2006, and fall 2006, and 10:00am, 12:00pm, 2:00pm,

4:00pm and 6:00pm for spring 2007. At the onset of a scheduled event, the irrigation controller

queried the sensor to determine the soil moisture content of the soil. If the reading was lower

than the threshold setting of the controller, irrigation would begin and run for 24 minutes. If the

sensor reading was higher than the controller threshold setting, the event was bypassed. The

Acclima CS3500 irrigation controller represented an "on demand" irrigation schedule, and









allowed irrigation events to occur at any time the sensor reading fell below the lower bound of

set threshold range. The irrigation event ended when the sensor indicated the soil moisture

content was at or above the upper bound of the setting.

The comparison treatment represented a time based irrigation schedule intended to

represent grower practices. This treatment irrigated once a day, regardless of soil water

conditions, for 2 hours (5 mm/day) in the morning. Table 4-1 outlines the irrigation treatments

and soil moisture threshold settings implemented for each experiment.

Water applications from irrigation and fertigation events were manually recorded from

positive displacement flowmeters (V100 1.6 cm diameter bore with pulse output, AMCO

WaterMetering Systems Inc., Ocala, FL). In addition to manual readings, the flowmeters

contained transducers that signaled a switch closure every 18.9 L. The switch closures were

recorded by data loggers (HOBO event logger, Onset Computer Corp. Inc., Bourne, MA) and

continually logged water and fertigation event times, which were downloaded once a week. By

knowing the time and duration of each event, the data was used to determine if and when

irrigation events occurred or were skipped.

Soil Moisture Monitoring

Soil moisture content was monitored in each experiment by time domain reflectometry

(TDR) probes (CS-615, Campbell Scientific, Inc. Logan, Utah) buried at a 300 angle to measure

the upper 0.15 m of the rooting zone. The probes were installed in each irrigation treatment plot

across all replicates. For the spring 2007 season, four additional TDR probes were buried in

each of the SMS treatment plots in an effort to further investigate the soil moisture content at

which irrigation events were bypassed and initiated around individual SMS control probes

(Figure 4-1). These TDR probes were installed in a close proximity to the soil moisture sensor,

with one probe buried opposite the Acclima sensor on the other side of the center drip tape and









the other three in similar locations to the Acclima relative to the plants and drip tape. All of the

TDR probes were connected to a data logger (Model CR-10, Campbell Scientific, Logan, Inc.,

UT) with a relay multiplexer (Model AM416, Campbell Scientific, Inc., Logan, UT). The data

was downloaded weekly.

Results and Discussion

The performance of the SMS treatments was evaluated by comparing the cumulative

amount of irrigation water, the number of bypassed irrigation events, and the average soil

moisture content at which events were initiated.

Climate Conditions

For spring 2005, cumulative rainfall totaled nearly 343 mm (Figure 4-2) which is much

higher than the average rainfall of 253 mm for this region during this time period. This

exceptionally high amount of rainfall may have contributed to a noticeable high incidence of

disease that spread through the field approximately midway (40 DAT) through the growing

season. During spring 2006, cumulative rainfall totaled 149 mm (Figure 4-3). The relatively

drier field conditions reduced the spread of disease, although bacterial spot was present at the

end of the season. The fall 2006 growing season had a cumulative rainfall of 132 mm as seen in

Figure 4-4. The low incidence of rainfall and cooler fall temperatures contributed to a very low

occurrence of disease. Temperatures began to fall at the end of the season, but the crop was not

exposed to frost. The spring 2007 season had a cumulative rainfall total of 124 mm (Figure 4-5)

and no reported incidence of disease.

Irrigation Treatments and Water Savings

Figures 4-6 through 4-9 and Tables 4-2 through 4-5 below illustrate cumulative

irrigation water applied by each treatment and a water savings comparison between the SMS and

time based treatments during the four growing seasons.









In spring 2005, the irrigation treatment schedules were initiated on April 28 (23 DAT).

By the end of the season, the SMS treatments applied less water than the time- based grower

treatment; however, the two different sensor types did not perform the same. The SMS

treatments controlled by the Acclima sensors, 12 (10%), I13 (12%), and 14 (12-14%) performed

well. After treatments were initiated, 12 applied 53 mm (0.9 mm/d), 13 applied 138 mm (2.3

mm/d), and 14 applied 131 mm (2.2 mm/d). The time based treatment, 15, resulted in 253 mm

(4.2 mm/d) as seen in Table 4-2. The II (10%) QIC treatment did not bypass many irrigation

events, resulting in a cumulative application 230 mm (3.8 mm/d) and only a 9% savings

compared with I5. The controller was thought to be set too high and was adjusted during the

season (58 DAT) from 550 mV (10% VWC) to 515 mV (8% VWC). The treatment, however,

did not respond to this adjustment, and continued to initiate irrigation for most of the scheduled

events (Figure 4-6). Several factors may have contributed to the malfunctioning of this

treatment since sensor performance is influenced by placement in the bed, proper installation,

soil salinity, proximity to drip emitters, and soil characteristics. Treatment 11 resulted in a 13%

water savings compared to I5 during the second growth stage (Table 4-3), which can be

attributed to the temporary decrease in II irrigation events caused by a sensor adjustment. 12, set

at the lowest threshold (10% VWC), resulted in the largest water savings, 79% (Table 4-2). 13

(12%VWC) and 14 (12-14% VWC), set at similar threshold settings, applied nearly the same

amount of water and resulted in similar water reductions of 48 and 49%, respectively (Table 4-

2), although they functioned differently. 13 was a bypass controlled treatment, while 14 was "on

demand". 12 showed relatively large savings (79%) relative to I5 throughout the three analyzed

growth stages (Table 4-3), while 13 and 14 resulted in larger savings during growth stages 2 and









3. The reason for lower savings of treatments 13 and 14 during growth stage 4, 27% and 14%,

respectively, is unknown.

In spring 2006, a programming error in the 14 irrigation controller during the beginning of

the season caused the treatment to over-irrigate (Figure 4-7), resulting in the largest irrigation

total of all treatments (348 mm). The problem was successfully adjusted (29 DAT) and 14

functioned properly for the duration of the season. The treatment irrigated an average of 16.2

mm/d before the error was fixed and averaged 3.4 mm/d after the adjustment was made. After

this point, 14 resulted in a 45% water savings in the second growth stage and a 60% savings in

the third growth stage (Table 4-5). II showed similar water savings to 14 during this period,

while 12 and 13 resulted in much less savings, with the largest occurring in the third growth stage

(Table 4-5). Treatments 12 and 13 malfunctioned for the majority of the season. Both treatments

functioned well, with 12 bypassing more events than 13, until an unpredicted and unexplainable

event caused 12 to irrigate for a 15 hour period (30 DAT). 12 was evaluated and adjusted on 35

DAT, and from this point on began bypassing similar to 13. By the end of the season, 12 applied

301 mm (4.9 mm/d) and 13 applied 287 mm (4.7 mm/d) resulting in a 9 and 13% water savings,

respectively (Table 4-3). This problem may have resulted from the cross communication

between sensor signals since the two treatment controllers shared a common irrigation timer.

The miscommunication between the controller and sensor signals may have caused both

controllers to receive signals from one of the buried sensors. II and 14 were the only treatments

to operate properly throughout the season. II applied 156 mm (2.6 mm/d), 53% less water than

I5, which applied 329 mm (5.4 mm/d). Treatments II and 14 showed the highest water savings,

47% and 45%, respectively, during the third growth stage which is the longest and most water

demanding stage of the season.









In the fall 2006 season, a wiring problem caused all of the SMS treatments to malfunction.

Both II and 12, were wired to a single irrigation time clock, and 13 and 14, also wired to a shared

irrigation time clock, were bypassing and irrigating the same scheduled events and applying

same irrigation amounts (Figure 4-8). The problem was attributed to cross communication

between the Acclima sensors, causing each of the irrigation controllers to receive signals from

only one of the two wired sensors. Several adjustments were made, but the problem was not

solved until each controller was wired to a separate individual irrigation timer. Eventually, 58

DAT, the SMS treatments began to irrigate independently of each other (Figure 4-8). After this

point, 12 began bypassing more events than II. This was unexpected, since 12 was set to a higher

setting of 10%, compared to II at 8%. This may be attributed more to the sensor placement and

location in the plot rather than the actual sensor settings. In addition to this wiring problem, a

programming error in the irrigation controller caused 14 to over-irrigate from 49 DAT to 65

DAT. The implementation of twin drip lines on this treatment required the adjustment of the

irrigation window from 24 minutes to 12 minutes to compensate for the doubled flow rate. The

timer, however, was mistakenly programmed to allow 24 minute irrigation windows which

caused 14 to apply double the amount of intended irrigation water. By the end of the season, 13

and 14 applied the most water with 319 mm (4.2 mm/d) and 327 mm (4.3 mm/d), respectively.

Each of these treatments applied more water than I5 which had 303 mm (4.0 mm/d). The lower

water application by 15 was a result of 9 missed programmed events due to power outages and

field maintenance. II applied a total amount of 244 mm (3.2 mm/d), while 12 applied 213 mm

(2.8 mm/d) as seen in Table 4-6. II and 12 showed water savings of 12 and 46%, respectively,

during the third growth stage (Table 4-7).









In spring 2007, each of the SMS treatments were wired to an individual irrigation

controller at the beginning of the season to avoid past problems with sensor cross

communication. This proved to be an effective method when testing multiple sensors in one

field. Problems did arise, however, with treatments 12 and 14, when both treatments failed to

bypass irrigation events in the beginning of the season. The locations of both treatment sensors,

12 and 14, were assessed 30 DAT. 14 was reburied in the original location and 12 was moved to a

different location in the plot. After the probes were reburied, 14 continued to irrigate frequently,

while 12 began to bypass events as seen in Figure 4-8. The location of the sensor in the bed was

apparently the cause of problem with the 12 treatment since it functioned properly after it was

moved. The problem with 14, however, was unknown, since the placement of the sensor was

evaluated and carefully reburied. Both of the treatments were set to the same soil moisture

threshold level of 10%, but 14 irrigated with twin drip lines. The location of the sensor relative

to the outside drip line and center fertigation line, although directly in between both, may have

been a drier area as compared to other treatments with centered drip lines. By the end of the

season, 14 applied 277 mm (3.6 mm/d), nearly as much as 15 which applied 308 (4.1 mm/d), and

only had a 10% water savings (Table 4-8). II and 12 applied similar amounts of water, with 171

mm (2.3 mm/d) and 190 mm (2.5 mm/d), respectively, and resulted in the highest water savings

during the third growth stage. 13 applied 261 mm (3.1 mm/d) during the season, and reduced

irrigation water by 20% in the second growth stage, yet applied 5 more mm of water compared to

15 during the third growth stage which resulted in a 20% increase (Table 4-9).

Soil moisture content

Figures 4-12 through 4-22 illustrate soil moisture content as measured by the TDR probes

and the occurrence of scheduled irrigation events and rainfall during several periods throughout

the growing season. Three weeks of data were selected for each season to illustrate soil moisture









conditions at the beginning (growth stage 2), middle (growth stage 3), and end (growth stage 4)

of season. Although TDR probes were buried across all replicates, data was analyzed based on

readings taken from the same replicate in which the soil moisture sensors were buried unless

otherwise indicated. Tables 4-10 through 4-14 detail the seasonal totals of irrigation events, as

well as the soil moisture content at which treatments initiated the events. It should be noted that

the values of soil moisture content used for comparison, readings from TDR probes and

threshold settings for Acclima soil moisture sensors, originate from two different sensor types

each with its own level of accuracy. The uncalibrated Acclima soil moisture sensors were

manufactured to measure soil moisture content within a level of 1% VWC accuracy (Acclima

TDT Data Sheet, Acclima, Inc., Meridian, ID), while the TDR probes measure within a level of

2.5 VWC (Campbell Scientific CS616 and CS625 Water Content Reflectometers Manual.

Revised 8/06, Campbell Scientific, Inc., Logan, UT).

Increases in soil moisture content can be seen in the graphs below following each irrigation

event. The SMS treatments had a much different effect on the soil moisture content of the soil

compared with the time-based treatment. For example, the SMS based treatments irrigated for

short periods of time, only when the soil reached a programmed VWC threshold value; allowing

the applied water to be held in the soil profile, making it available for plant uptake. The SMS

treatments resulted in relatively small increases in soil moisture, and consequently decreased the

volume of drainage. Drainage is further analyzed and discussed in Chapter 2. The time based

treatment; however, irrigated for a longer time period, regardless of soil moisture conditions, and

resulted in large increases in soil moisture. This spike in moisture content caused by irrigation

was temporary and most of the excessively applied water was quickly drained from the soil

profile as seen in Figure 4-10. On average, the TDR probes recorded a 0.042 VWC increase in









soil moisture during the 2 hour time based irrigation events, reaching a maximum at the end of

the event, followed immediately by a rapid decrease until the soil reached a relatively steady

moisture state. This steady state was usually reached within 24 hours of the onset of the

irrigation event, and is assumed to approximate the field capacity of the raised bed. Treatment 15

in Figure 4-10 illustrates this assumption and shows that the majority of available soil water was

drained during the 24 hour period following the scheduled irrigation event. The graph shows a

missed irrigation event, resulting in a 48 hour period between events, during the beginning of the

growing season (19 DAT) when plant roots were still underdeveloped and therefore not able to

uptake a significant amount of water from the soil. The change in soil moisture between the

missed event on May 1 and the next event on May 2 is very small, only 0.008 VWC, which

indicates that the soil had reached approximate field capacity within 24 hours after the irrigation

event on April 30. Although measured to be 10-12% in previous field studies (Icerman, 2007),

field capacity can widely vary depending on soil and field conditions. Due to this variation, field

capacity was approximated based on the average of the entire field. Figures 4-11, 4-15, 4-19,

and 4-23 illustrate the approximated field capacity for each replicate during the specified

growing season. .

It is often assumed that rainfall events have little or no effect on the soil moisture content

of plastic mulch covered beds. During this study, however, there were five recorded rainfall

events (two in spring 2006, two in fall 2006, and one in spring 2007) that lead to noticeable

increases in soil moisture content (Figure 4-17). The spring 2005 season was not included in the

rainfall analysis due to the deterioration of plastic mulch midway through the season that caused

the plant bed to be exposed. The effective rainfall events all measured over 15 mm and resulted

in an average VWC increase of 0.054. This increase in soil moisture was temporary, and









immediately decreased at the end of the event. So although large rainfall events seem to

temporarily influence VWC beneath the plastic mulched beds, the overall contribution to the

crop water demand is negligible during the course of the season. The soil moisture based

treatments performed well during the seasonal rainfall events by skipping scheduled irrigation

events and not allowing irrigation again until soil moisture content decreased.

In the spring 2005 season, the improper threshold setting on II caused this treatment to

bypass only 53 irrigation events (18%), while 12, set to a similar threshold setting of 10%,

bypassed the most events with 261 (87%). 12 irrigated very little compared to the other

treatments. Substantial increases in soil moisture after the weekly fertigation, with an average

weekly increase of 0.111 VWC, and frequent rainfall events can be seen in treatment 12 (Figure

4-12), which may have reduced the need for irrigation. Although 12 bypassed far more irrigation

events than II, both treatments, set at 10%, initiated irrigation at a similar average VWC, 13.1%

for II and 12.9% for 12. The difference in irrigation frequency may be attributed to the probe

burial location in the plot. The 12 Acclima probe may have been buried close to a drip emitter

which would maintain wetter soil conditions surrounding the probe and cause frequently

bypassed events. The II QIC probe may have been buried in a drier location, further from a drip

emitter, which would have resulted in frequent irrigation events caused by the drier soil

surrounding the probe. Differences between the soil moisture threshold setting and the measured

VWC point at which irrigation is initiated can be attributed to variations in sensor readings. The

uncalibrated Acclima soil moisture sensors used in this project were manufactured to measure

soil moisture content to a level of 1% VWC accuracy (Acclima TDT Sensor Data Sheet,

Acclima, Inc., Meirdian, ID.), while the TDR probes measure within accuracy of 2.5% VWC









(Campbell Scientific CS616 and CS625 Water Content Reflectometers Manual. Revised 8/06,

Campbell Scientific, Inc., Logan, UT.).

13 initiated irrigation at a higher VWC range of 14.5-20.6% and bypassed 162 events

(54%), consistent with the high threshold setting of 12% (Table 4-10). The 14 treatment was

programmed to initiate irrigation any time the VWC reached 12%, and terminate the event at

14%. This treatment only irrigated for 57 events, about 1 event per day, and initiated irrigation

at an average soil moisture content of 18.8% and ended when the soil reached 20.2% (Table 4-

10). These values are higher than the threshold settings of 12-14%, and are likely caused by

differences between the actual soil moisture of the raised bed and TDR readings. Field capacity

was estimated to be 14.7% across all plots (Figure 4-11), higher than the measured 10-12%

range (Icerman, 2007), indicating wetter field conditions. As seen in Figure 4-11, estimated

field capacity ranged from 0.127 0.167. SMS treatments with lower threshold settings, II and

12, initiated irrigation at average moisture contents below the estimated average field capacity,

while the treatments with higher settings, 13 and 14, initiated irrigation at averages above this

value.

In spring 2006, II functioned as expected for the low threshold setting, by bypassing the

most irrigation events (58%) and initiating irrigation at the lowest average VWC (10.5%) as seen

in Table 4-11. An unexplainable and unpredicted irrigation event caused II to irrigate for over

15 hours and apply 49 mm of water. This resulted in an increase in soil moisture of 0.059 VWC

(Figure 4-16). Treatments 12 and 13 performed similarly during the season due to wiring

problems, resulting in a similar total of irrigation events and irrigation initiation range (Table 4-

11). Both of the treatments bypassed approximately 30 irrigation events, and initiated the events

at an average of 11.9%, which may indicate 13, set at 12%, as the controlling sensor signal









during the signal. 14, set to irrigate with in 12-14% range, initiated irrigation at an average VWC

of 9.9% and terminated the events when the soil reached 10.3%. Field capacity was estimated as

8.2% across all replicates (Figure 4-15), and all treatments, including II set at 8%, initiated

irrigation at average soil moisture contents above this value of 8.2%. Approximated field

capacity ranged from 0.069 to 0.088 VWC over the four replicates as seen in Figure 4-15.

During the fall 2006 growing season, problems with the sensor wiring caused cross

communication between sensor signals resulting in uniform irrigation applications among II and

12 treatments and 13 and 14 in the beginning of the season. The problem was solved when the

sensors were wired to separate irrigation timers. II and 12 were rewired on 30 DAT and began

irrigating independently for the duration of the season. II went on to bypass 27% of the

irrigation events at an average VWC of 9.1%, while 12 bypassed 40% at an average VWC of

11.6% (Table 4-12). 13 and 14 were rewired 38 DAT, and irrigated separately for a few weeks

(DAT 34 to DAT 66), but eventually reestablished a similar schedule. The late establishment of

the four treatments likely caused little differences among the treatment pairs as differences

among irrigation applications can be harder to detect later in the season when the crop water

demand increases. Water savings are most often seen in the early growth stages before water

demands increase with the onset of flower set and fruit development. By the end of the season,

14, set at 10%, bypassed more events than 13, 66 for 14 as compared to 36 for 13 (Table 4-12).

14, however, applied the most amount of water, due to the programming error (49 DAT to 65

DAT) that caused 14 to apply double the amount of intended water for 15 days in the middle of

the season. Average field capacity was estimated to be 7.5% across the field, and all SMS

treatments initiated irrigation at average moisture contents above this value (Figures 4-20









through 4-22). Approximated field capacity ranged from 0.074 to 0.077 across the four

replicates (Figure 4-19).

In spring 2007, additional TDR probes were installed in the SMS treatment plots to more

accurately monitor the soil moisture content of the area directly surrounding the soil moisture

sensor. For this season, the average soil moisture content for each SMS treatment was calculated

by averaging the readings of these four additional probes. Figures 4-27 through 4-29 illustrate

soil moisture content of the four TDR probes for each SMS treatment. Most of the probes

performed similarly with the exception of the I1B4A probe shown in Figure 4-27 and the I4B4D

probe shown in Figures 4-27 through 4-29. The I1B4A was excluded from the II TDR average

until the probe was reburied (42 DAT). Readings taken from the I4B4D probe were included in

the 14 TDR average since the higher values were likely attributed to the probe position in the plot

(Figure 4-1).

From the beginning of the growing season, each irrigation controller was connected to a

separate timer to avoid previously discussed problems with sensor signaling. This,

unfortunately, did not eliminate sensor performance problems. 12 and 14 failed to bypass

irrigation events in the beginning of the season, causing the treatments to irrigate at nearly every

scheduled event. Each sensor was reburied on 30 DAT. After this adjustment, 12 began

bypassing so many events that it ended the season with the same number of bypassed events as

II, which was set at the lower threshold of 8%. 12 did, however, initiate irrigation at a higher

VWC of 12.8% compared to 11.2% for II (Table 4-13). 14 continued to bypass very few events,

25 in all, after the adjustment. As discussed earlier, this may have been caused by the location of

the Acclima sensor in the plot in relation to the twin drip lines. The Acclima is buried near the

center of the raised bed, approximately 15 cm away from TDR D. Figures 4-27 through 4-29









illustrate average VWC measured by the four individual probes in the 14 plots. The highest

measurements are read from TDR D (avg. 17.9% VWC), followed by TDR B (avg. 11.8%

VWC), both of which were located closest to the twin drip lines. TDR A and TDR C, located

closer to the center line, near the Acclima sensor, recorded lower readings of VWC, averaging

10.2 and 10.6%, respectively. The VWC, as measured by the TDR probes, indicate drier

conditions near the Acclima sensor, causing the frequent irrigation events. 12 and 14, both set at

10%, initiated irrigation at similar average moisture contents of 12.8% and 12.2%, respectively.

One of the TDR probes (I1A) surrounding the II treatment malfunctioned in the beginning of the

season, causing the probe to measure very high soil moisture contents (Figure 4-27). The

location of the probe was evaluated and the probe was successfully reburied on May 23, 2007

(43 DAT). The readings from the I1A TDR probes were not included in the calculated average

soil moisture content prior to 43 DAT. 13 had the highest threshold setting, bypassed 67% of

events, and initiated events at the highest VWC (13.4%). Field capacity was estimated as 13.3%

across the field (Figure 4-23). All treatments initiated irrigation near or under this soil moisture

average as seen in Table 4-13. Approximated field capacity ranged from 0.106 to 0.162 VWC

across the four replicates (Figure 4-23).

Summary of Sensor Performance

Over the course of the four growing seasons 16 SMS treatments were initiated and tested

at threshold settings varying from 8-12%, two of which represented "on demand" schedules with

threshold ranges of 12-14%. Eight of the 16 implemented treatments functioned properly and

reduced irrigation water compared to the time based treatment, 15, by skipping scheduled events

based on soil moisture readings. The other eight treatments malfunctioned due to significant

programming, wiring, and/or installation problems. These treatments were not representative of

typical sensor performance, therefore were not included in overall averages and comparisons.









The eight successful treatments are detailed in Tables 4-14 and 4-15. Overall treatment

performance for each threshold setting is shown in Tables 4-16 and 4-17.

Overall, the functioning SMS treatments reduced irrigation application totals from 23-

50% compared with the time based treatment, 15 (Table 4-15). Treatments with a 12% threshold

setting resulted in the lowest water savings, 23%. This was the highest threshold setting among

the timer controlled treatments, and demanded wetter soil conditions to bypass irrigation events.

Since very little water is stored in the beds due to the low water holding capacity of the sandy

soil, the sensor rarely read a SMC at or above 12% which caused only 28% of the irrigation

events to be bypassed (Table 4-16). Although the treatment was programmed to irrigate at a soil

moisture content of 12%, the average measured by TDR probes at the onset of each event was

14.1%. This was likely attributed to differences in the TDR probe readings (2% accuracy) and

the Acclima sensor readings (1% accuracy).

SMS treatments with an 8% threshold setting applied an average irrigation water total of

190 mm with an average water savings of 36%, whereas treatments with a 10% threshold setting

averaged an application of 152 mm with a 49% water savings. This was unexpected since an 8%

threshold setting should require drier soil moisture conditions to initiate irrigation compared to a

10% threshold setting. The two treatments, however, applied similar irrigation applications

throughout the trials, with differences totaling less than 30 mm (Table 4-14). The lower

averages of the 10% setting can be attributed to the very low water application of the 12

treatment during the spring 2005 growing season as seen in (Table 4-14). The soil moisture

content at which the two treatments initiated irrigation was, however, consistent with their

threshold settings. The II treatment initiated events at an average of 10.3%, while 12 initiated

events at 12.4% (Table 4-16). All of the timer controlled SMS treatments initiated irrigation









events at all consistent with programmed threshold settings. The TDR measured soil moisture

content, with 2% accuracy, at the onset of irrigation was very close to the programmed threshold

settings of the SMS treatments (Table 4-17)

The 12-14% "on demand" treatment and the 10% SMS treatment performed similarly,

resulting in the lowest irrigation applications, 150 and 152 mm, and water savings, 50 and 49%,

respectively, of all SMS treatments (Table 4-15). The "on demand" schedule allowed irrigation

to occur at any time throughout the day, and maintained a relatively stable soil moisture content,

as seen in Figures 4-10 through 4-12 and 4-13 through 4-16. Irrigation water was reduced by

this treatment due to the lack of a programmed irrigation time window. This enabled the

treatment to irrigate only until the sensor read the soil moisture content to be 14%. The average

moisture content, measured by TDR probes, maintained by this treatment was between 14.4-

15.3%. This is very close to the 12-14% programmed range when probe and sensor error are

considered.

Of all the irrigation treatments, the time based treatment, I5, applied the highest total and

daily rate of irrigation water with an average of 298 mm or 4.4 mm/d during the four seasons. I5

had the fewest irrigation events because it was programmed to irrigate once a day. Since I5

irrigated once a day for 2 hours, allowing nearly 24 hours for all excess water to drain from the

profile before the next event, the soil moisture content measured just before irrigation occurred

was estimated to be the actual field capacity of the raised bed system. Each 2 hour irrigation

event, increased the soil moisture content by an average of 4.2%, which resulted in the rapid

drainage as seen in the I5 graphs in Figures 4-11 through 4-21. Estimated field capacities for

each season and a four season average are shown in Figure 4-30. Values ranged from 0.075 -









0.147 over the four seasons. The overall field capacity was averaged to be 0.109, which was

consistent with the measured field capacity of 10-12% (Icerman, 2007).

Conclusions

When properly installed and programmed, soil moisture sensors can successfully be

integrated into an automated irrigation system to reduce irrigation water compared to a time-

based schedule, while maintaining adequate soil moisture in the plant rooting zone. After four

growing seasons, the Acclima SMS treatment with a 10% threshold setting, proved the most

successful. The treatment reduced the most amount of water, nearly 50%, produced the highest

fruit yield, as well as the highest water use efficiency. Future research should further investigate

the "on demand" irrigation schedule using the Acclima CS3500 at various threshold settings.

Acclima RS500 soil moisture controllers perform best when they are programmed to separate

irrigation timers to avoid cross communication between sensor signals. The placement of the

soil moisture sensor in the raised bed, in relation to the plant and drip tape, can greatly affect

sensor performance. Sensor burial is also important, as the accuracy of the probe depends on

close contact with soil particles. Air pockets and other soil disturbances may result in inaccurate

readings, ultimately reducing the efficiency of the irrigation system.









Table 4-1. Irrigation treatments, threshold settings
times.


(VWC), and programmed irrigation run


Treatment Treatment VWC threshold Irrigation window
Description setting
(m3/m3)


Spring Pepper 2005
11
12
13
I4
15

Spring Pepper 2006
11
12
13
I4
15

Fall Pepper 2006
11
12
13
I4

15

Spring Pepper 2007
11
12
13
I4

15


QIC
Acclima RS500
Acclima RS500
Acclima CS3500
Time-based
schedule

Acclima RS500
Acclima RS500
Acclima RS500
Acclima CS3500
Time-based
schedule

Acclima RS500
Acclima RS500
Acclima RS500
Acclima RS500
twin drip lines
Time-based
schedule

Acclima RS500
Acclima RS500
Acclima RS500
Acclima RS500
twin drip lines
Time-based
schedule


0.1 (500 mV)
0.1
0.12
0.12-0.14
n/a


0.08
0.1
0.12
0.12-0.14
n/a


0.08
0.1
0.12
0.1


24 min, 5 times/day
24 min, 5 times/day
24 min, 5 times/day
Anytime
2 hours, 1 time/day


24 min, 5 times/day
24 min, 5 times/day
24 min, 5 times/day
Anytime
2 hours, 1 time/day


24 min, 5 times/day
24 min, 5 times/day
24 min, 5 times/day
12 min, 5 times/day


n/a 2 hours, 1 time/day


0.08
0.1
0.12
0.1


24 min, 5 times/day
24 min, 5 times/day
24 min, 5 times/day
12 min, 5 times/day


n/a 2 hours, 1 time/day












I Raised Bed Edge


S Acclima sensor W
0.95m

1I- -


- '-D'p ape


Raised Bed Edge



SRaised Bed Edge


Acclima sensor i

0.95m -


Drip Line


- Raised Bed Edge


Figure 4-1. Additional TDR probe locations surrounding Acclima sensors during spring 2007.
Typical plot layout for treatments II, 12, and 13 is shown in the upper diagram,
while 14 (twin drip lines) is shown in the lower diagram.

















110



































0 20 40 60 80

Number of Days after Transplanting


Figure 4-2.


Minimum, maximum, and average temperatures during spring 2005 along with
daily and cumulative rainfall (mm).


0



x E
22
E-
E =o
ar<



E
0
2W


20


15 0.
E
I-
10


5


0


0 20 40 60 80
Number of Days after Transplanting


Figure 4-3.


Minimum, maximum, and average temperatures during spring 2006 along with
daily and cumulative rainfall (mm).


- 50
0
XE
EE 40

E
4-
4-.-
.- M 30



7I0 20

E cu

U 10


0


40




30




20




10










60


- 50
50

EE
E 40
4-
30
O,
_ 0 20


S10


0


20 40 60 80
Number of Days after Transplanting


Figure 4-4.


Minimum, maximum, and average temperatures during fall 2006
and cumulative rainfall (mm).


50


-40









0
a20 w
10I-





0o 0





along with daily


Cumulative Rainfall
I I Daily Rainfall
-- Average Air Temperature


LJM


Number of Days after Transplanting


Figure 4-5.


Minimum, maximum, and average temperatures during spring 2007 along with
daily and cumulative rainfall (mm).


o 50

EE
E= 40
4-
Cr


2 2
E

10


50


- 40


-30 w



1-

- 10


-0


. 1n


Ar-AA


--Fr














E 300
E
0
100
^ 200



1 100
C-


0 20 40 60 80
Number of Days after Transplanting

Figure 4-6. Cumulative irrigation water for treatments in spring 2005.


Table 4-2. Irrigation treatments, threshold settings, and total irrigation water applied after
treatments were initiated (DAT 24), and overall water savings compared to the 15
control treatment during the spring 2005 season.
Spring Treatment Threshold Total Treatment Average Daily Water Savings
Pepper Description Setting Application Application Compared
2005 To 15
(mm) (mm/d) (%)
11 QIC 0.1 230 3.8 9
Acclima
12 0.1 53 0.9 79
RS500

13 Accima 0.12 138 2.3 45
RS500

14 Accma 0.12-0.14 131 2.2 48
CS3500
I5 Time-based n/a 253 4.2 0









Table 4-3. Water savings of SMS based treatments compared to the 15 control treatment for
growth stages 2-4 during the spring 2005 season after treatments were initiated.
Spring Pepper 2005
Crop Growth SMS Treatment Water Savings
Stage* Compared to 15
(%)
II, 10% 12, 10% 13, 12% 14, 12-14%
QIC Acclima Acclima Acclima
2 -2 91 57 43
3 13 77 50 48
4 -18 86 5 41
*All treatments were irrigated similarly during the establishment phase in growth stage 1.


20 40 60 80


Number of Days after Transplanting

Figure 4-7. Cumulative irrigation water for treatments during spring 2006. SMS treatment 14
(12-14%) was not properly programmed until 29 DAT.









Table 4-4. Irrigation treatments, threshold settings, and total irrigation water applied after
treatments were initiated (DAT 16), and overall water savings compared to the 15
control treatment during the spring 2006 season.
Spring Treatment Threshold Total Treatment Average Daily Water Savings
Pepper Description Setting Application Application Compared
2006 to 15
(mm) (mm/d) (%)
Acclima
II A a 0.1 156 2.6 53
RS500
Acclima
12 Accla 0.1 301 4.9 9
RS500
13 Accima 0.12 287 4.7 13
RS500
14 Accima 0.12-0.14 348 (169)* 16.2 (2.8)* -6 (49)*
CS3500
I5 Time-based n/a 329 5.4 0
*Values reflect irrigation after programming error was fixed (DAT 29).

Table 4-5. Water savings of SMS based treatments compared to the I5 control treatment for
growth stages 2-4 during the spring 2006 season after treatments were initiated.
Spring Pepper 2006 Water Savings
Crop Growth SMS Treatment Water Savings
Stage* Compared to I5
(%)
II, 8% 12, 10% 13, 12% 14, 12-14%
Acclima Acclima Acclima Acclima
2 61 13 5 n/a**
3 47 6 12 45
4 72 23 33 60
*All treatments were irrigated similarly during the establishment phase in growth stage 1.
** Treatment 14 was not properly initiated until growth stage 3.




























20 40 60 80
Number of Days after Transplanting


Figure 4-8.


Cumulative irrigation water for treatments in fall 2006. SMS treatments were
wired to separate irrigation controllers 58 DAT.


Table 4-6. Irrigation treatments, threshold settings, total irrigation water applied after treatments
were initiated (DAT 17), and overall water savings compared to the 15 control
treatment during the fall 2006 season.
Fall Treatment Threshold Total Treatment Average Daily Water
Pepper Description Setting Application Application Savings
2006 (mm) (mm/d) (%)

I1 SAcma 0.08 244 (106)* 3.2 19 (6)*

12 Accima 0.1 213 (77)* 2.8 30 (32)*
RS500
13 Acclima 0.12 319 (138)* 4.2 -5 (-22)*
RS500
Acclima
RS500
14 R5 0. 0.10 327 (115)* 4.3 -8 (-2)*
Twin drip
lines
15 Time-based n/a 303 (113)* 4.0 0
*Values reflect irrigation after sensors were wired to separate controllers (DAT 58).










Table 4-7. Water savings of SMS based treatments compared to the 15 control treatment for
growth stages 3 and 4 during the fall 2006 season after treatments were initiated.
Fall Pepper 2006 Water Savings
Crop Growth SMS Treatment
Stage II, 8% I2, 10% 13, 12% i4, 10%

Acclima Acclima Acclima Acclima,
twin drip lines
2 n/a** n/a** n/a** n/a**
3 12 46 -8 -8
4 0 -3 -71 47
*All treatments were irrigated similarly during the establishment phase in growth stage 1.
** The SMS treatments did not function independently until 58 DAT during growth stage 3.


400




E
| 300


to

' 200



E
100
0-


20 40 60 80

Number of Days after Transplanting


Figure 4-9. Cumulative irrigation water for treatments in spring 2007. Treatments 12 and 14
were adjusted 30 DAT.









Table 4-8. Irrigation treatments, threshold settings, total irrigation water applied after treatments
were initiated (DAT 20), and overall water savings compared to the 15 control
treatment during the spring 2007 season.
Spring Treatment Threshold Total Treatment Average Daily Water
Pepper 2007 Description Setting Application Application Savings
(mm) (mm/d) (%)
II Acclima 0.08 171 2.3 44
RS500
12 Accima 0.1 190 (161)* 2.5 43 (60)*
RS500
Acclima
13 Accima 0.12 261 3.4 15
RS500
Acclima
RS500
14 Twindrip 0.10 277 (272)* 3.6 17 (33)*
Twin drip
lines
I5 Time-based n/a 308 4.1 0
*Values reflect irrigation after sensors were adjusted (DAT 30).

Table 4-9. Water savings of SMS based treatments compared to the I5 control treatment for
growth stages 2-4 during the spring 2007 season after treatments were initiated.
Spring Pepper 2007 Water Savings
Crop Growth SMS Treatment
Stage I1, 8% I2, 10% 13, 12% 14, 10%
Acclima Acclima Acclima Acclima,
twin drip lines
2 72 n/a** 3 n/a**
3 44 49 20 7
4 8 24 -20 72
* All treatments were irrigated similarly during the establishment phase in growth stage 1.
** Treatments 12 and 14 did not function properly until 30 DAT during growth stage 3.










0.25 -
15,time-based soil moisture
0.20 -* irrigation ever
VWC = .087 VWC = .086 skipped event



0.15- 0
0405 4F.C. = .081 VWC = .078

4/28 4/29 4/30 5/1 5/2 5/3 5/4


Date


Figure 4-10.


Volumetric water content measured at 15 cm for April 28 to May 4, 2006 (17 to
23 DAT). The horizontal line indicates the approximated field capacity averaged
for the I5 time based treatment after a 2 hour irrigation event.


Table 4-10. Irrigation threshold settings, number of irrigation events, and average volumetric
water content (VWC) at beginning of irrigation events for pepper cultivated in spring
2005.
Irrig. Total Treatment Total Number Irrig. Average Average C.V. of
Treat. irrig. Water irrig. and set VWC irrigation VWC
water Savings events Percentage point at start initiation measured
applied Compared of total of irrig. range by TDR
to 15 skipped Event
events
(mm) (%) (#) (#) (%) (%) (%) (%)
11 230 9 247 53 (18%) 10 13.1 10.5-17.3 12.3
12 53 79 39 261 (87%) 10 12.9 11.3-14.4 20.6
13 138 45 138 162 (54%) 12 16.7 14.5-20.6 11.4
18.8 17.5-21.0 7.4
14 131 48 57 n/a 12-14 18.8 17.521.0 7.4
20.2* 16.4-19.6* 7.3*
15 253 0 58 n/a n/a 14.7 n/a n/a
*Values represent soil moisture content at upper set point range when irrigation event was terminated.


20 E

15

10 II
5

0














0.25


0.20


0.15


0.10


0.05



0.25


0.20


0.15


0.10


0.05



0.25


0.20


0.15


0.10


0.05


0.25


0.20


0.15


0.10


0.05


0.25


0.20


0.15


0.10


0.05


-


-


-



-







-


-



-







-


-


25


20


15 |


10


5
S


5/17 5/21 5/25 5/29 6/2 6/6 6/10 6/14
Date

Figure 4-11. Volumetric water content (VWC) measured at 15 cm for May 15 to June 15, 2005

(40 to 71 DAT) along with rainfall events. Horizontal lines indicate the

approximated field capacity (VWC) for each replicate.


F.C. = .142



5 Field Avera







F.C. = .147


15B1








F.C. =.167






15B2










F.C.= .127 /



15B3










F.C. = .144



15B4











0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05


0.25

0.20


0.15

0.10

0.05


4/28 4/29 4/30


5/1 5/2 5/3 5/4 5/5


Date
Figure 4-12. Volumetric water content (VWC) measured at 15 cm for April 28 to May 4, 2005
(23 to 29 DAT) with scheduled irrigation events during vegetative development
stage and rainfall. The double horizontal lines indicate minimum and maximum
soil moisture content at which irrigation was initiated. Approximated field
capacity is represented by a single bold line on the 15 graph.


I1, 8% VWC
maximum VWC %

---------------------------A


13, 12% VWC


14, 10 % VWC


15, time based





F.C. = .147
-i


-

-

-


-- soil moisture content minimum VWC %
* irrigation event
* skipped event



-N





12, 10% VWC
I











0.25 -


II, 8% VWC maximum vwc %


11, 8% VWC maximum VWC %

0.15 -

0.10 soil moisture content minimum VWC %

0.05 irrigation event
skipped event

0.25 -

0.20 -

0.15 -

0.10 -

0.05- 12, 10% VWC


0.25 -




0.10 -

0.05 13, 12% VWC


0.25 -

0.20

0.15

0.10

0.05 14, 10 % VWC


0.25 25
15, time based 20 "


0.10 F.C.= .147 -
-5

0.05 -

5/26 5/27 5/28 5/29 5/30 5/31 6/1 6/2
Date
Figure 4-13. Volumetric water content (VWC) measured at 15 cm for May 26 to June 1, 2005
(51 to 57 DAT) with scheduled irrigation events during flowering period and
rainfall. The double horizontal lines indicate minimum and maximum soil
moisture content at which irrigation was initiated. Approximated field capacity is
represented by a single bold line on the I5 graph.











0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05


0.25

0.20

S0.15

0.10

0.05


-


-V













14, 10 % VWC


15, time based






- F.C.= .147/


6/24


Figure 4-14.


6/26


Date
Volumetric water content (VWC) measured at 15 cm for June 22 to June 26, 2005
(78 to 82 DAT) with scheduled irrigation events during harvest period and
rainfall. The double horizontal lines indicate minimum and maximum soil
moisture content at which irrigation was initiated. Approximated field capacity is
represented by a single bold line on the 15 graph.


11, 8% VWC
maximum VWC %


- soil moisture content minimum VWC %
* irrigation event
* skipped event


12, 10% VWC









13, 12% VWC
1 -*


20 E

15 E

10

5


-

-

-


N VI-j









Table 4-11. Irrigation threshold settings, number of irrigation events, and average volumetric
water content (VWC) at beginning of irrigation events for pepper cultivated in spring
2006.
Irrig. Total Treatment Total Total of Irrig. Average Average C.V. of
Treat. irrigation Water irrig. skipped set VWC at irrigation VWC
water Savings events events point start of initiation measured
applied Compared irrigation range by TDR
to 15 Event
(mm) (%) (#) (#) (%) (%) (%) (%)
11 156 53 137 195 8 10.5 9.3-12.5 15.4
(58%)
12 301 9 298 32 10 11.6 9.9-13.9 7.9
(10%)
28
13 287 13 302 28 12 12.1 10.8-13.4 8.5
(8%)
348 338 9.9 8.8-10.9 12.7
(169)** (240)** 10.3* 7.9-11.1* 12.1
15 329 0 55 n/a n/a 8.2 n/a n/a
*Values represent soil moisture content at upper set point range when irrigation event was terminated.
**Value represents total irrigation after the 14 programming error was fixed.












0.25 -


15B1


0.20
-
0.15
-







0.25

0.20


Date


Figure 4-15.


Volumetric water content (VWC) measured at 15 cm for May 17 to June 17, 2006
(35 to 66 DAT) along with rainfall events. Horizontal lines indicate the
approximated field capacity (VWC) for each replicate.


15B2








F.C. =.086


15B3









F.C. = .064

15B4










25
15 Field Average
20
2
-\15
F.C. = .081 -


0.05


0.25

0.20

S> 0.15

> 0.10

0.05


0.25

0.20






0.15


0.25 -

0.20 -

S> 0.15 -

0.10

0.05 -











0.25 -

S0.20-

0.15 -

0.10 -

0.05 -


0.25 -

0.20 -

- 0.15 -

0.10 -

0.05 -


0.25 -

0.20 -

S0.15 -

0.10

0.05 -


0.25

0.20

S0.15

0.10

0.05


0.25

0.20

- 0.15

0.10

0.05


- soil moisture content 11, 8%
* irrigation event
* skipped event maximum VWC%




minimum VWC%



12,10%










13,12%


15,time-based






F.C. = .082


4/28 4/29 4/30


Figure 4-16.


5/1 5/2 5/3 5/4 5/5

Date


Volumetric water content (VWC) measured at 15 cm for April 28 to May 4, 2006
(17 to 23 DAT) with scheduled irrigation events and rainfall during initial
vegetative development stage of pepper. The double horizontal lines indicate
minimum and maximum soil moisture content at which irrigation was initiated.
Approximated field capacity is represented by a single bold line on the 15 graph.


14,12-14%


-

-

-











0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05


0.25

0.20

- 0.15

0.10

0.05


0.25

0.20

S0.15

0.10

0.05


0.25

0.20

S0.15

0.10

0.05


6/8 6/9 6/10


Figure 4-17.


6/11 6/12 6/13 6/14 6/15 6/16


Date
Volumetric water content (VWC) measured at 15 cm for June 8 to June 16, 2006
(58 to 66 DAT) with scheduled irrigation events and rainfall during early fruit
development stage of pepper. The double horizontal lines indicate minimum and
maximum soil moisture content at which irrigation was initiated. Approximated
field capacity is represented by a single bold line on the 15 graph.


- soil moisture content 11, 8%
* irrigation event
* skipped event
Maximum VWC%

minimum VWC%
minimum vwc%


13,12%


14,12-14%

~A
- :--M-

--^ ^ M ^ ^ ^^ ^ j














0.25

0.20
0.15

0.10

0.05


0.25

0.20
0.15

0.10

0.05


0.25

0.20

- 0.15

0.10

0.05


0.25

0.20

S0.15

0.10


Figure 4-18.


Date
Volumetric water content (VWC) measured at 15 cm for June 29 to July 3, 2006
(79 to 83 DAT) with scheduled irrigation events and rainfall during harvesting
period of pepper. The double horizontal lines indicate minimum and maximum
soil moisture content at which irrigation was initiated. Approximated field
capacity is represented by a single bold line on the 15 graph.


soil moisture content 1i, 8%
irrigation event
skipped event
maximum VWC%


minimum VWC%




12,10%



-i





13,12%










14,12-14%


~ N


0.05 -


15,time-based






F.C. = .082


-


IV Id -0 ---G -


0.25 -

0.20 -

0.15 -

0.10 -

0.05 -









Table 4-12. Irrigation threshold settings, number of irrigation events, and average volumetric
water content (VWC) at beginning of irrigation events for pepper cultivated in fall
2006.
Irrig. Total Treatment Total Total of Irrig. Average Average C.V. of
Treat. irrig. Water irrig. skipped set VWC irrigation VWC
water Savings events events point at start of initiation measured
applied Compared irrigation range by tdr
to 15 event
(mm) (%) (#) (#) (%) (%) (%) (%)
11 244 19 (6)* 264 96 8 9.1 7.9-9.6 11.4
(27%)
12 213 30 (32)* 217 143 10 11.6 9.9-13.2 7.9
(40%)
13 319 -5 (-22)* 324 36 12 10.0 9.5-10.9 7.8
(10%)
14 327 -8 (-2)* 294 66 10 10.3 9.5-12.1 8.7
(18%)
15 303 0 64 n/a n/a 7.5 n/a n/a














15B1









F.C. = .075


0.15


0.10


0.05


0.00
0.20


0.15


0.10


0.05


0.00
0.20


0.15


0.10


0.05


0.00
0.20


0.15


0.10


0.05


0.00
0.20


0.15


0.10


0.05


0.00


11/9 11/13 11/17 11/21
Date


25

-20




- 15

- 5


11/25 11/29 12/3 12/7


Figure 4-19. Volumetric water content (VWC) measured at 15 cm for November 7 to
December 7, 2006 (57 to 87 DAT) along with rainfall events. Horizontal lines
indicate the approximated field capacity (VWC) for each replicate.


-^

F.C. = .076


15B4


-, -





< F.C. = .074


15 Field Average








F.C. .075


15B3





&. & K K & N kNN rKNJ^ J

-


-


-


-


-


-


15B2






JF.C. = .077


F.C. = .077











0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05

0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10


0.05 -


soil moisture content 11, 8% VWC
irrigation event
skipped event
maximum VWC %

minimum VWC %



12, 10% VWC









13, 12% VWC









14, 10 % VWC


1


Date


Figure 4-20.


Volumetric water content (VWC) measured at 15 cm for September 28 to October
2, 2006 (19 to 23 DAT) with scheduled irrigation events and rainfall during
vegetative development of pepper. The double horizontal lines indicate minimum
and maximum soil moisture content at which irrigation was initiated.
Approximated field capacity is represented by a single bold line on the 15 graph.


15, time based





F.C.= .082 .P- -
F.C.= .82^ ^______________________i


0.25

S0.20

0.15

S0.10

0.05











0.25 -- soil moisture content

0.20 irrigation event I1,8%VWC
> skipped event
,0.15 maximum VWC %

0.10 -

0.05 minimum VWC %


0.25 -
12, 10% VWC
S0.20 -

0.15 -

0.10 ----- .

0.05 -


0.25 -
13, 12% VWC
S0.20 -

0.15 -
0.10
0.10 -- j .-_ __ -- -

0.05 -


0.25 -
14, 10% VWC
0.20 -

0.15 -

0.10 -""-,* -~ "- -~*^^---->~-- _--' --- --,

0.05 -


0.25 25
15, time based 20
0.20 E

a 0.15 15
10
0.10 -

0.05 ,

10/18 10/19 10/20 10/21 10/22 10/23 10/24 10/25 10/26
Date
Figure 4-21. Volumetric water content (VWC) measured at 15 cm for October 18 to October
24, 2006 (39 to 45 DAT) with scheduled irrigation events and rainfall during
flowering of pepper. The double horizontal lines indicate minimum and
maximum soil moisture content at which irrigation was initiated. Approximated
field capacity is represented by a single bold line on the I5 graph.












0.25

-0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05


Figure 4-22.


11/23 11/24 11/25 11/26 11/27 11/28 11/29 11/30 12/1
Date
Volumetric water content (VWC) measured at 15 cm for November 23 to
November 30, 2006 (75 to 82 DAT) with scheduled irrigation events and rainfall
during harvesting period for pepper. The double horizontal lines indicate
minimum and maximum soil moisture content at which irrigation was initiated.
Approximated field capacity is represented by a single bold line on the I5 graph.


- soil moisture content I1, 8%o VWC
* irrigation event
* skipped event

maximum VWC %

minimum VWC %



12, 10% VWC










13, 12% VWC










14, 10% VWC


15, time based






F.C.= .082-__ ,.,_.__,


-


-

-

-

-

-









Table 4-13. Irrigation threshold settings, number of irrigation events, and average volumetric
water content (VWC) at beginning of irrigation events for pepper cultivated in spring
2007.
Irrig. Total Treatment Total Total Irrigation Average Average C.V. of
Treat. irrig. Water irrig. of set VWC at irrigation VWC
water Savings events skipped point start of initiation measured
applied Compared events irrigation range by TDR
to 15 event
(mm) (%) (#) (#) (%) (%) (%) (%)
11 171 44 175 145 8 11.2 9.8-13.3 10.4
(45%)
12 190 43 (60)* 175 145 10 12.8 10.6 18.4
(45%) 15.0
13 261 15 253 67 12 13.4 11.3 11.7
(21%) 16.5

14 277 17 (33)* 296 25 10 12.2 10.7 13.3
IS 308 0 64 n/a n/a 13.3 n/a n/a




























0.2


0.1 -

F.C. = .152
0.0
0 .4 i--------, ------------------ 2 5
0.4 15 Field Average 25

0.3 20
F.C. = .133 E1
0.2 10

0.1 5

0.0 0


5/17 5/21 5/25 5/29
Date


Figure 4-23.


6/2 6/6 6/10 6/14


Volumetric water content (VWC) measured at 15 cm for May 15 to June 15, 2007
(35 to 66 DAT) along with rainfall events. Horizontal lines indicate the
approximated field capacity (VWC) for each replicate.


15B2



h n k Ku h I m I I I K L m


F.C. = .162


15B3







F.C. = .106


15B4


15B1


F.C. = .113


.m 'iJl. \ \,j i\j \JjQQQ 1











0.25 -

- 0.20-

0.15 -

0.10 -

0.05 -


0.25 -

0.20 -

0.15 -

0.10 -

0.05 -


0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05

0.25

0.20

0.15

0.10

0.05


5/9 5/10 5/11 5/12 5/13
Date


5/14 5/15 5/16


Figure 4-24. Volumetric water content (VWC) measured at 15 cm for May 9 to May 15, 2007
(29 to 35 DAT) with scheduled irrigation events and rainfall during vegetative
development for pepper. The double horizontal lines indicate minimum and
maximum soil moisture content at which irrigation was initiated. Approximated
field capacity is represented by a single bold line on the 15 graph.


- soil moisture content 11, 8% VWC
* irrigation event
* skipped event maximum VWC %


minimum VWC %




12, 10% VWC

M IN ------------------s


13, 12% VWC
---------A


14, 10 % VWC












0.25

0.20

S0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05


0.25

0.20

0.15

" 0.10


0.05 -


0.25

0.20

0.15

0.10

0.05


Figure 4-25.


5/30 5/31 6/1 6/2 6/3 6/4 6/5 6/6
Date
Volumetric water content (VWC) measured at 15 cm for May 30 to June 5, 2007
(50 to 56 DAT) with scheduled irrigation events and rainfall during flowering
period for pepper. The double horizontal lines indicate minimum and maximum
soil moisture content at which irrigation was initiated. Approximated field
capacity is represented by a single bold line on the 15 graph.


-- soil moisture content 11, 8% VWC
* irrigation event
* skipped event maximum VWC %



minimum VWC %


-

-





_


-

-

-


13, 12% VWC










14, 10 % VWC
:- ,_J ^ ^


12, 10% VWC











0.25

, 0.20

0.15

0.10

0.05


0.25

0.20

0.15

0.10

0.05


0.25 -

0.20 -

0.15 -

0.10 -

0.05 -


0.25 -

0.20 -

0.15 -

0.10 -

0.05 -


0.25 -

0.20 -

0.15 -

0.10 -

0.05 -


-- soil moisture content
- irrigation event 11,8% VWC
* skipped event
maximum VWC %


minimum VWC %



12, 10% VWC










13, 12% VWC
,,,1___________________________


6/20 6/21


6/22 6/23 6/24 6/25 6/26 6/27


Date
Figure 4-26. Volumetric water content (VWC) measured at 15 cm for June 20 to June 26, 2007
(71 to 77 DAT) with scheduled irrigation events and rainfall during harvest period
for pepper. The double horizontal lines indicate minimum and maximum soil
moisture content at which irrigation was initiated. Approximated field capacity is
represented by a single bold line on the 15 graph.


14, 10 % VWC










0.25


0.20 TDR C J '

0.15 -

0.10

0.05

0.25




0.25 -13, 12% VWC
0.20 -
> 0.15 -

0.10 -

0.05 -







0.25 -




14, 10% VWC
>0.20

0.15 -






0.10 -
0.05 -

0.25 -






%- 20 VWC
-- 0.15

0.10 -- 10

0.05


0.25 15, time based

0.20 20E

0.15 1



0.05 F.C. =.133 -5

5/9 5/10 5/11 5/12 5/13 5/14 5/15 5/16
Date
Figure 4-27. Volumetric water content (VWC) measured by four TDR probes installed
adjacent to the buried Acclima sensors for May 9 to May 15, 2007 (29 to 35
DAT) along with seasonal rainfall.











0.25 -


0.20 TDR C




0.05

0.25
12, 10% VWC
0.20 -

0.10


0.05


2 13, 12% VWC
0.20 -

0.15 -

0.10

0.05

0.25 -\
14, 10% VWC ~I
-0.20 -


-^
0.15



0.05


0.25 15, time based 25

-0.20- A 20


S F.C. = .1331 5
45
0.05 -
> 0 05 -- -- -' .133 -- 5
5/30 5/31 6/1 6/2 6/3 6/4 6/5 6/6
Date
Figure 4-28. Volumetric water content (VWC) measured by four TDR probes installed
adjacent to the buried Acclima sensors for May 30 to June 5, 2007 (50 to 56
DAT) along with seasonal rainfall.


TDR B I1,8% VWC










0.25


Figure 4-29.


0.20 TDR C
-- TDR D


0.05 -

0.05

0.25
12, 10% VWC
0.20 -

0.15 -

0.10 -

0.05 -


0.25

0.20 -

0.15 -

0.10 '- 0 -

0.05 -

0.25 -
14, 10% VWC
0.20

0.15



0.05 -


0.25 15, time based 25
S20
0.20 -

0.15 -15

F.C. =.133 5'
0.05 r I

6/20 6/21 6/22 6/23 6/24 6/25 6/26 6/27
Date
Volumetric water content (VWC) measured by four TDR probes installed
adjacent to the buried Acclima sensors for June 20 to June 26, 2007 (71 to 77
DAT) along with seasonal rainfall.









Table 4-14. Summary of successful SMS treatments over spring 2005, spring 2006, fall 2006,
and spring 2007 growing seasons, with total and daily average irrigation water and
water savings compared with the time based treatment, 15.
Treatment and Treatment Threshold Total Treatment Average Daily Water
Season Description Setting Application Application Savings
(VWC) (mm) (mm/d) (%)
12, spring Acclima
0.1 53 0.88 79
2005 RS500
13, spring Acclima 0.12 138 2. 45
2005 RS500
I4, spring Acclima
14, spring Acclima 0.12-0.14 131 2.2 48
2005 C3500
I1, spring Acclima
spring Acclima 0.08 156 2.6 53
2006 RS500
13, spring Acclima 0.12 287 4.7 13
2006 RS500
14, spring Acclima 0.12-0.14 169* 2.8* 49*
2006 C3500
11, fall 2006 Acclima 0.08 244 3.2 19
RS500
12, fall 2006 Acclima 0.1 213 2.8 30
RS500
II, spring Acclima
2007 RS500
12, spring Acclima
2007 RS500
13, spring Acclima
2007 RS500
* Values adjusted for programming error fixed DAT 29.

Table 4-15. Average daily and total irrigation and water savings for each treatment type across
all four growing seasons.
Threshold Average Treatment Average Daily Average Water
Setting Application Application Savings
(mm) (mm/d) (%)
8% 190 2.5 36
10% 152 2.1 49
12% 229 3.5 23
12-14% 150 2.5 50
Time-based 298 4.4 0









Table 4-16. Summary of successful SMS treatments over spring 2005, spring 2006, fall 2006,
and spring 2007 growing seasons, detailing initiated and bypassed irrigation event
totals, along with the average soil moisture content (SMC) at the start of the event.
Treatment Treatment Threshold Total Total Avg. VWC at Avg. VWC
Description Setting Initiated Bypassed Start of of Initiation
Events Events Initiated Start
Event Range
(%) (#) (#) (%) (%)
12, spring Accima 10 39 261 (87%) 12.9 11.3-14.4
2005 RS500
13, spring Accima 12 138 162 (54%) 16.7 14.5-20.6
2005 RS500
14, spring Acclima 12-14 57 n/a 18.8 17.5-21
2005 CS3500 20.2* 16.4-19.6
II, spring Acclima
, spring Accima 8 137 195 (58%) 10.5 9.3-12.5
2006 RS500
13, spring Accima 12 302 28 (8%) 12.1 10.8-13.4
2006 RS500
14, spring Acclima 9.9 8.8-10.9
2006 CS3500 10.3** 7.9-11.1**
, fall Acclima 8 264 96 (27%) 9.1 7.9-9.6
2006 RS500
12, fall Acclima 10 217 143 (40%) 11.6 9.9-13.2
2006 RS500
, spring Accima 8 175 145 (45%) 11.2 9.8-13.3
2007 RS500
12, spring Accima 10 175 145 (45%) 12.8 10.6-15.0
2007 RS500
I3, spring Acclima
13, spring Acclima 12 253 67 (21%) 13.4 11.3-16.5
2007 RS500
*Value adjusted for programming error fixed DAT 29.
** Values reflect SMC at the end of irrigation event.









Table 4-17. Average bypassed and initiated irrigation event totals, along with average soil
moisture content (SMC) at the start of the events for each treatment type across the
four growing seasons.
SMS Average Total Average Total Average VWC Average VWC of
Threshold Initiated Bypassed at Start of Initiation Start
Setting Events Events Initiated Event Range
0(#) %(#) (%) (%)
8% 192 145 (43%) 10.3 9.0-11.8
10% 144 183 (57%) 12.4 10.6-14.2
12% 231 86(28%) 14.1 12.2-16.8
14.4 13.2-16.0
12-14% 149 n/a 14.4 13.2-16.0
15.3* 12.2-15.4*
10.1
Time-based 59 n/a 1. n/a
13.5
*Values reflect SMC at the end of irrigation event
















0.20

0.15
F.C. = .147 Y
0.10-
F.C. = .109
0.05 -

5/17 5/21 5/25 5/29 6/2 6/6 6/10 6/14


0.25 -
Estimated Field Capacity Spring 2006

0.20 -

0.15 F.C. =.109

0.10

0.05
F.C. = .082

5/17 5/21 5/25 5/29 6/2 6/6 6/10 6/14 6/18


0.25 Estimated Field Capacity Fall 2006

0.20 -

0.15 F.C.= .109

0.10

0 -F.C.=.07-

11/9 11/13 11/17 11/21 11/25 11/29 12/3 12/7

0.25 Estimated Field Capacity Spring 2007

0.20 F.C. = .133

0.15 -

0.10 -
F.C. = .111g -
0.05 -

5/17 5/21 5/25 5/29 6/2 6/6 6/10 6/14
Date


Figure 4-30.


Volumetric water content (VWC) for the 15 time based treatment averaged over
all four replicates for a one month period during the growing seasons along with
recorded rainfall events. Horizontal lines indicate the approximate field capacity
(F.C.) VWC, with dashed lines depicting the individual season average and solid
lines showing the average over all four seasons.


20

15

10

5

0


15

10

5

0


25

20

15

10

5

0


25

20

15

10

5









LIST OF REFERENCES


Allen, R.G., L.S. Pereira, D. Raes, and M. Smith, 1998. Crop evapotranspiration: Guidelines
for computing crop water requirements. Irr. Drain. Paper 56. UN-FAO, Rome.

Amayreh, J., and N. Al-Abed. 2005. Developing crop coefficients for field grown tomato under
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Babiker, I.S., A.A. Mohamed, H. Terao, K. Kato, and K. Ohta. 2004. Assessment of groundwater
contamination by nitrate leaching from intensive vegetable cultivation using geographical
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Blonquist, J.M., Jr., S.B. Jones, and D.A. Robinson. A time domain transmission sensor with
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Bouchard, D.C., M.K. Williams and R.Y. Surampalli, Nitrate contamination of groundwater:
sources and potential health effects. J. Am. Water Works Assoc., September 1992 84 9
(1992), pp. 85-90.

Buster, T.P. 1979. Soil survey of Marion County, Florida. Soil Conservation Service,
Washington, D.C.

Clark, G.A., E.E. Albregts, C.D. Stanley, A.G. Smajstrla and F.S. Zazueta. 1996. Water
requirements and crop coefficients of drip-irrigated strawberry plants. Trans. ASAE 39 3
(1996), pp. 905-912.

Dedekorkut, Aysin, J. Scholz, B. Stiftel (eds.). 2003. Adaptive Governance andFlorida's Water
Conflicts: The Case Studies. Tallahassee, FL: Florida State University DeVoe L. Moore
Center.

Dukes, M.D., E.H. Simonne, W.E. Davis, D.W. Studstill, and R. Hochmuth. 2003. Effect of
sensor-based high frequency irrigation on bell pepper yield and water use, P. 665-674. In:
Proc. 2nd Int. Conf. Irr. And Drainage, 12-15 May, Phoenix, Ariz.

Fares, A., and A.K. Alva. 2000. Soil water components based on capacitance probes in a sandy
soil. Soil Sci. Soc. Am. J. 64:311-318.

Fernandandez, M.D., M. Gallardo, S. Bonachela, F. Orgaz, and E. Federes. 2000. Crop
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BIOGRAPHICAL SKETCH

Born in Morristown, New Jersey, in January 1982, Kristen Femminella was raised and

educated in Vero Beach, Florida. It was here she spent most of her days outdoors developing a

deep love and respect for the natural resources that make Florida so uniquely beautiful. After

graduation she decided to pursue a degree in land and water resources engineering, and

graduated from the University of Florida in 2005 with her bachelor's degree. She decided to

continue her studies in this field and went on to receive her Master of Engineering degree.





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1 EFFECTS OF SOIL MOISTURE SENSOR BASED IRRIGATION ON DRIP IRRIGATED BELL PEPPERS GROWN ON SANDY SOIL By KRISTEN FEMMINELLA A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2008

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2 2008 Kristen Femminella

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3 To my grandmother, Alice Ferraiuolo.

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4 ACKNOWLEDGMENTS I would lik e to thank my parents for all of the unconditional love and support they have shown me during this in credible journey. I am fortunate to have been handed so many wonderful opportunities, and will forever be appreci ative for all they have given me. I would also like to thank Dr. Dukes for patiently advi sing and encouraging me during my time at the University of Florida. Due to his influence a nd guidance, I have emerged from grad school as a stronger, more responsible and proactive person. For their assistance with my project, I woul d like to extend a special thanks to Lincoln Zotarelli, Danny Burch, and Larry Miller. I would also like to thank Eban Bean, Jason Icerman, and Jono Schroder for so many times volunteering to get up early to suffer alongside me in the field. To the older siblings I always wish I ha d, I thank Melissa Baum Haley, Stuart Muller, and David Kaplan for their unwavering support an d encouragement, both in school and out. To Stacia Davis, Victoria Rouisse, Mary Shedd, Sa m Tripson, and Nikki White a thank you is just not sufficient. They are the greatest friends a girl could have, and they continue to amaze me with their limitless compassion and kindness.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........7 LIST OF FIGURES.......................................................................................................................10 ABSTRACT...................................................................................................................................16 CHAP TER 1 INTRODUCTION..................................................................................................................18 Rationale.................................................................................................................................18 Objectives...............................................................................................................................21 2 EFFECTS OF SOIL MOISTURE BASED IRRIGATION ON BELL PEPPER PRODUCTI ON..................................................................................................................... ..23 Introduction................................................................................................................... ..........23 Materials and Methods...........................................................................................................25 Soils Characteristics........................................................................................................25 Experimental Design and Field Layout...........................................................................25 Irrigation and Fertig ation Control and Data Collection .................................................. 26 Soil Moisture Monitoring and Drainage Collection........................................................28 Harvest.............................................................................................................................29 Analysis Method..............................................................................................................29 Results and Discussion......................................................................................................... ..29 Spring 2005.....................................................................................................................29 Climate Conditions................................................................................................... 29 Irrigation Treatments................................................................................................ 30 Drainage...................................................................................................................31 Yield and Water Use Efficiency............................................................................... 31 Spring 2006.....................................................................................................................32 Climate Conditions................................................................................................... 32 Irrigation Treatments................................................................................................ 32 Drainage...................................................................................................................33 Yield and Water Use Efficiency............................................................................... 34 Fall 2006...................................................................................................................... ....34 Climate Conditions................................................................................................... 34 Irrigation Treatments................................................................................................ 34 Drainage...................................................................................................................35 Yield and Water Use Efficiency............................................................................... 36 Spring 2007.....................................................................................................................36 Climate Conditions................................................................................................... 36

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6 Irrigation Treatments................................................................................................ 36 Drainage...................................................................................................................37 Yield and Water Use Efficiency............................................................................... 38 Comparison of Results............................................................................................. 38 Conclusions.............................................................................................................................38 3 EVAPOTRANSPIRATION AND CROP COEFFICIENTS FOR Green BELL PEPPERS IN FLORIDA ........................................................................................................57 Introduction................................................................................................................... ..........57 Methods and Materials...........................................................................................................59 Soils Characteristics........................................................................................................59 Experimental Design and Field Layout...........................................................................60 Irrigation and Fertig ation Control and Data Collection .................................................. 61 Soil Moisture Monitoring and Drainage Collection........................................................62 Dye Injection...................................................................................................................63 Weather Data Collection................................................................................................. 63 Kc values.........................................................................................................................64 Theoretical ETc............................................................................................................... 66 Field Estimated ETc........................................................................................................66 Results and Discussion......................................................................................................... ..68 Climate Conditions and ETo............................................................................................68 Estimating Drainage........................................................................................................68 Estimating ETc.................................................................................................................70 Estimating Kc...................................................................................................................71 Conclusions.............................................................................................................................72 4 ANALYSIS OF SOIL MOISTURE SENS OR P ERFORMANCE ON AUTOMATED DRIP IRRIGATED PEPPERS GROWN IN SANDY SOIL................................................. 87 Introduction................................................................................................................... ..........87 Materials and Methods...........................................................................................................90 Soils Characteristics........................................................................................................90 Experimental Design and Field Layout...........................................................................91 Irrigation and Fertig ation Control and Data Collection .................................................. 92 Soil Moisture Monitoring................................................................................................93 Results and Discussion......................................................................................................... ..94 Climate Co nditions .......................................................................................................... 94 Irrigation Treatments and Water Savings........................................................................ 94 Soil moisture content....................................................................................................... 98 Summary of Sensor Performance.................................................................................. 105 Conclusions...........................................................................................................................108 LIST OF REFERENCES.............................................................................................................146 BIOGRAPHICAL SKETCH.......................................................................................................149

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7 LIST OF TABLES Table page 2-1 Irrigation treatments, threshold sett ings (VW C), and programmed irrigation windows.............................................................................................................................40 2-2 Total water application during entire season, total wate r applied after treatm ent initiation, 23 DAT, average application rate and target soil moisture settings for spring 2005.........................................................................................................................43 2-3 Irrigation treatment effects on marketable yield and irrigation water use efficiency, along with total applied ir rigation for spring 2005. ...........................................................44 2-4 Total water application during entire season, total wate r applied after treatm ent initiation, 23 DAT, average application rate and target soil moisture settings for spring 2006.........................................................................................................................46 2-5 Irrigation treatment effects on marketable yield and irrigation water use efficiency, along with total applied ir rigation for spring 2006. ...........................................................47 2-6 Total water application during entire season, total wate r applied after treatm ent initiation, 23 DAT, average application rate, and target soil moisture settings for fall 2006....................................................................................................................................50 2-7 Irrigation treatment effects on marketable yield and irrigation water use efficiency, along with total applied irrigation for fall 2006. ................................................................ 51 2-8 Total water application during entire season, total wate r applied after treatm ent initiation, 23 DAT, average application rate and target soil moisture settings for spring 2007.........................................................................................................................54 2-9 Irrigation treatment effects on marketable yield and irrigation water use efficiency (IW UE), along with total app lied irrigation for spring 2007............................................. 55 2-10 Summary of successful SMS treat m ents over spring 2005, spring 2006, fall 2006, and spring 2007 growing seasons, with average treatment irrigation water, marketable yield, irrigation water use efficiency (IWUE), and water savings............56 3-1 Irrigation treatments, threshold settin gs (VW C), and programmed irrigation run times.......................................................................................................................... .........74 3-2 Summary of SMS treatme nts that approxim ate ETc over spring 2005, spring 2006, and spring 2007 growing seasons, alo ng with treatment irrigation and ETc (calculated with Kinitial=0.2, Kmid=1.0, Klate=0.85)............................................................................... 83

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8 3-3 Estimated Kc values for each treatment along with overall averages................................ 85 3-4 Recommended, adjusted and estimated Kc values for bell peppers................................... 86 4-1 Irrigation treatments, threshold settin gs (VW C), and programmed irrigation run times.......................................................................................................................... .......109 4-2 Irrigation treatments, threshold settings and total irrigation water applied after trea tments were initiated (DAT 24), and overall water savings compared to the I5 control treatment during the spring 2005 season............................................................. 113 4-3 Water savings of SMS based treatments co m pared to the I5 control treatment for growth stages 2-4 during th e spring 2005 season after tr eatments were initiated........... 114 4-4 Irrigation treatments, threshold settings and total irrigation water applied after trea tments were initiated (DAT 16), and overall water savings compared to the I5 control treatment during the spring 2006 season............................................................. 115 4-5 Water savings of SMS based treatments co m pared to the I5 control treatment for growth stages 2-4 during th e spring 2006 season after tr eatments were initiated........... 115 4-6 Irrigation treatments, threshold settings, tota l irrigation water applied after treatments were initiated (DAT 17), a nd overall water savings compared to the I5 control treatment during the fall 2006 season.............................................................................. 116 4-7 Water savings of SMS based treatments co m pared to the I5 control treatment for growth stages 3 and 4 during the fall 2006 season after treatments were initiated......... 117 4-8 Irrigation treatments, threshold settings, to ta l irrigation water applied after treatments were initiated (DAT 20), a nd overall water savings compared to the I5 control treatment during the spring 2007 season......................................................................... 118 4-9 Water savings of SMS based treatments co m pared to the I5 control treatment for growth stages 2-4 during th e spring 2007 season after tr eatments were initiated........... 118 4-10 Irrigation threshold settings, number of irrigation events, and average volumetric water content (VWC) at beginning of irrigati on events for pepper cultivated in spring 2005..................................................................................................................................119 4-11 Irrigation threshold settings, number of irrigation events, and average volumetric water content (VWC) at beginning of irrigati on events for pepper cultivated in spring 2006..................................................................................................................................124 4-12 Irrigation threshold settings, number of irrigation events, and average volumetric water content (VWC) at beginning of irriga tion events for pepper cultivated in fall 2006..................................................................................................................................129

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9 4-13 Irrigation threshold settings, number of irrigation events, and average volumetric water content (VWC) at beginning of irrigati on events for pepper cultivated in spring 2007..................................................................................................................................134 4-14 Summary of successful SMS treat m ents over spring 2005, spring 2006, fall 2006, and spring 2007 growing seasons, with tota l and daily average irrigation water and water savings compared with th e time based treatment, I5............................................. 142 4-15 Average daily and total irrigation and wa ter sav ings for each treatment type across all four growing seasons..................................................................................................142 4-16 Summary of successful SMS treat m ents over spring 2005, spring 2006, fall 2006, and spring 2007 growing seasons, detailing initiated and bypassed irrigation event totals, along with the averag e soil moisture content (SMC) at the start of the event...... 143 4-17 Average bypassed and initiated irriga tion event totals, al ong with average soil moisture co ntent (SMC) at th e start of the events for each treatment type across the four growing seasons.......................................................................................................144

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10 LIST OF FIGURES Figure page 2-1 Details and dimensions of drainage lysim eter burial beneath raised bed.......................... 41 2-2 Minimum, maximum, and average temper atures during spring 2005 along with daily and cum ulative rainfall...................................................................................................... 42 2-3 Cumulative irrigation water after initiation of individual treatments in spring 2005............................................................................................................42 2-4 Cumulative water (drainage) percolated beneath the root zone for treatm ents I2, I3, and I5 for spring 2005........................................................................................................43 2-5 Disproportionate plant growth from reduced water due to a horizontal shift in drip tape caused by field activities and/or im proper installation during week 5 of the spring 2005 season. ............................................................................................................ 44 2-6 Minimum, maximum, and average temper atures during spring 2006 along with daily and cum ulative rainfall...................................................................................................... 45 2-7 Cumulative irrigation water after initiation of individual treatments in spring 2006................................................................................................................................45 2-8 Cumulative drainage of water percolated be neath the root zone for treatm ents I2, I3, and I5 for spring 2006. There were no significant differences (ns) between treatments..................................................................................................................... ......47 2-9 Pepper plot with mature pepper plants and fruit during week 12 of the spring 2006 growing season...................................................................................................................48 2-10 Minimum, maximum, and average temp eratures during fall 2006 along with daily and cum ulative rainfall...................................................................................................... 48 2-11 Cumulative irrigation water after initia tion of individual trea tm ents in fall 2006. Treatments I1 and I2 began functioning independently after 58 days after transplant (DAT).........................................................................................................................49 2-12 Cumulative drainage of water percolated be neath the root zone for treatm ents I2, I3, I4 and I5 for fall 2006........................................................................................................51 2-13 Effects of over irrigation of treatment I4 (l eft) o n plant growth compared to I5 (right) during week 6 of the fall 2006 growing season.................................................................52 2-14 Minimum, maximum, and average temper atures during spring 2007 along with daily and cum ulative rainfall...................................................................................................... 52

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11 2-15 Cumulative irrigation water after initia tion of individual tr ea tments in spring 2007............................................................................................................................53 2-16 Cumulative drainage of water percolated be neath the root zone for treatm ents I2, I3, I4 and I5 for spring 2007...................................................................................................55 3-1 Details and dimensions of drainage lysim eter burial beneath raised bed.......................... 75 3-2 Example of negligible cha nge in so il moisture conten t during one week in the fall 2006 season........................................................................................................................76 3-3 Minimum, maximum, and average temper atures during spring 2005 along with daily and cum ulative rainfall and evapotranspiration, ETo.........................................................76 3-4 Minimum, maximum, and average temper atures during spring 2006 along with daily and cum ulative rainfall and evapotranspiration, ETo.........................................................77 3-5 Minimum, maximum, and average temp eratures during fall 2006 along with daily and cum ulative rainfall and evapotranspiration, ETo.........................................................77 3-6 Minimum, maximum, and average temper atures during spring 2007 along with daily and cum ulative rainfall and evapotranspiration, ETo.........................................................78 3-7 The wetted front of the time based irrigation treatment I5 after day 7 of the dye injection test (82 DAT). ..................................................................................................... 79 3-8 Weekly estimated and measured drainage a long with cumulative irrigation for all treatments during the spring 2005 season. Drai nage is shown as vertical bars with dark shaded bars representing calculated drainage and lighter bars depicting measured drainage. Drainage was not collected from treatments I1 and I4..................... 80 3-9 Weekly estimated and measured drainage a long with cumulative irrigation for all treatments during the spring 2006 season. Drai nage is shown as vertical bars with dark shaded bars representing calculated drainage and lighter bars depicting measured drainage. Drainage was not co llected from treatments I1 and I4...................... 81 3-10 Weekly estimated and measured drainage a long with cumulative irrigation for all treatments during the spring 2007 season. Drai nage is shown as vertical bars with dark shaded bars representing calculated drainage and lighter bars depicting measured drainage. Drainage was not collected from I1................................................... 82 3-11 Volumetric water content measured at 15 cm for April 28 to May 4, 2006 (17 to 23 DAT). The horizontal line indicate s the approximated field capacity.............................. 83 3-12 Weekly rainfall and soil moisture cont ent av erages, measured by TDR probes across the entire field, for I1 and I4 after treatm ent initiation in spring 2006. Growth stages 2-4 are shown at the top of the graph. Th e red line represents the observed field capacity of the soil (0.082)................................................................................................. 84

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12 3-12 Weekly rainfall and soil moisture cont ent av erages, measured by TDR probes across the entire field, for I1 after treatment init iation in spring 2007. Growth stages 2-4 are shown at the top of the graph. The red line represents the observe d field capacity of the soil (0.133)...................................................................................................................84 3-13 Estimated Kc values averaged across spring growing seasons along with published values, KcIFAS and KcFAO for bell peppers.....................................................................85 4-1 Additional TDR probe locations su rrounding Acclim a sensors during spring 2007. Typical plot layout for treatme nts I1, I2, and I3 is shown in the upper diagram, while I4 (twin drip lines) is shown in the lower diagram.......................................................... 110 4-2 Minimum, maximum, and average temper atures during spring 2005 along with daily and cum ulative rainfall (mm)........................................................................................... 111 4-3 Minimum, maximum, and average temper atures during spring 2006 along with daily and cum ulative rainfall (mm)........................................................................................... 111 4-4 Minimum, maximum, and average temp eratures during fall 2006 along with daily and cum ulative rainfall (mm)........................................................................................... 112 4-5 Minimum, maximum, and average temper atures during spring 2007 along with daily and cum ulative rainfall (mm)........................................................................................... 112 4-7 Cumulative irrigation water for treatmen ts during spring 2006. SMS treatm ent I4 (12-14%) was not properly programmed until 29 DAT.................................................. 114 4-8 Cumulative irrigation water for treatments in fall 2006. SMS treatm ents were wired to separate irrigati on controllers 58 DAT........................................................................ 116 4-9 Cumulative irrigation water for treatmen ts in spring 2007. Treatm ents I2 and I4 were adjusted 30 DAT.....................................................................................................117 4-10 Volumetric water content measured at 15 cm for April 28 to May 4, 2006 (17 to 23 DAT). The horizontal line i ndicates the approximated field capacity averaged for the I5 time based treatment afte r a 2 hour irrigation event.................................................... 119 4-11 Volumetric water content (VWC) measur ed at 15 cm for May 15 to June 15, 2005 (40 to 71 DAT) along with rainfall even ts. Horizontal lines indicate the approximated field capacity (VWC) for each replicate................................................... 120 4-12 Volumetric water content (VWC) measur ed at 15 cm for April 28 to May 4, 2005 (23 to 29 DAT) with scheduled irrigation events during vegetative development stage and rainfall. The double horizonta l lines indicate minimum and maximum soil moisture content at which irrigation was initiated. Approximated field capacity is represented by a single bold line on the I5 graph............................................................ 121

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13 4-13 Volumetric water content (VWC) measured at 15 cm for May 26 to June 1, 2005 (51 to 57 DAT) with scheduled irrigation events during flowering period and rainfall. The double horizontal lines indicate minimum and maximum soil moisture content at which irrigation was initiated. Approxima ted field capacity is represented by a single bold line on the I5 graph........................................................................................ 122 4-14 Volumetric water content (VWC) measur ed at 15 cm for June 22 to June 26, 2005 (78 to 82 DAT) with scheduled irrigation ev ents during harvest period and rainfall. The double horizontal lines indicate minimum and maximum soil moisture content at which irrigation was initiated. Approxima ted field capacity is represented by a single bold line on the I5 graph........................................................................................ 123 4-15 Volumetric water content (VWC) measur ed at 15 cm for May 17 to June 17, 2006 (35 to 66 DAT) along with rainfall even ts. Horizontal lines indicate the approximated field capacity (VWC) for each replicate................................................... 125 4-16 Volumetric water content (VWC) measur ed at 15 cm for April 28 to May 4, 2006 (17 to 23 DAT) with scheduled irrigation events and rainfall duri ng initial vegetative development stage of pepper. The doubl e horizontal lines indicate minimum and maximum soil moisture content at which irrigation was initia ted. Approximated field capacity is represented by a single bold line on the I5 graph.................................. 126 4-17 Volumetric water content (VWC) measured at 15 cm for June 8 to June 16, 2006 (58 to 66 DAT) with scheduled irrigation events and rainfall during early fruit development stage of pepper. The doubl e horizontal lines indicate minimum and maximum soil moisture content at which irrigation was initia ted. Approximated field capacity is represented by a single bold line on the I5 graph.................................. 127 4-18 Volumetric water content (VWC) measured at 15 cm for June 29 to July 3, 2006 (79 to 83 DAT) with scheduled irrigation events and rainfall during harvesting period of pepper. The double horizontal lines indi cate minimum and maximum soil moisture content at which irrigation was initiated. Approximated field capacity is represented by a single bold line on the I5 graph................................................................................ 128 4-19 Volumetric water content (VWC) measured at 15 cm for November 7 to December 7, 2006 (57 to 87 DAT) along with rainfall even ts. Horizontal lin es indicate the approximated field capacity (VWC) for each replicate................................................... 130 4-20 Volumetric water content (VWC) measured at 15 cm for September 28 to October 2, 2006 (19 to 23 DAT) with scheduled irrigati on events and rainfall during vegetative development of pepper. The double hor izontal lines indicate minimum and maximum soil moisture content at which irrigation was initia ted. Approximated field capacity is represented by a single bold line on the I5 graph.................................. 131

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14 4-21 Volumetric water content (VWC) measured at 15 cm for October 18 to October 24, 2006 (39 to 45 DAT) with scheduled irrigati on events and rainfall during flowering of pepper. The double horizontal line s indicate minimum and maximum soil moisture content at which irrigation was initiated. Approximated field capacity is represented by a single bold line on the I5 graph............................................................ 132 4-22 Volumetric water content (VWC) measured at 15 cm for November 23 to November 30, 2006 (75 to 82 DAT) with scheduled irrigation events and rainfall during harvesting period for pepper. The doubl e horizontal lines indicate minimum and maximum soil moisture content at which irrigation was initia ted. Approximated field capacity is represented by a single bold line on the I5 graph.................................. 133 4-23 Volumetric water content (VWC) measur ed at 15 cm for May 15 to June 15, 2007 (35 to 66 DAT) along with rainfall even ts. Horizontal lines indicate the approximated field capacity (VWC) for each replicate................................................... 135 4-24 Volumetric water content (VWC) measured at 15 cm for May 9 to May 15, 2007 (29 to 35 DAT) with scheduled irrigation ev ents and rainfall during vegetative development for pepper. The double hor izontal lines indicate minimum and maximum soil moisture content at which irrigation was initia ted. Approximated field capacity is represented by a single bold line on the I5 graph.................................. 136 4-25 Volumetric water content (VWC) measured at 15 cm for May 30 to June 5, 2007 (50 to 56 DAT) with scheduled irrigation events and rainfall during flowering period for pepper. The double horizontal lines indi cate minimum and maximum soil moisture content at which irrigation was initiated. Approximated field capacity is represented by a single bold line on the I5 graph................................................................................ 137 4-26 Volumetric water content (VWC) measur ed at 15 cm for June 20 to June 26, 2007 (71 to 77 DAT) with scheduled irrigation ev ents and rainfall during harvest period for pepper. The double horizontal line s indicate minimum and maximum soil moisture content at which irrigation was initiated. Approximated field capacity is represented by a single bold line on the I5 graph............................................................ 138 4-27 Volumetric water content (VWC) measured by f our TDR probes installed adjacent to the buried Acclima sensors for May 9 to May 15, 2007 (29 to 35 DAT) along with seasonal rainfall.............................................................................................................. .139 4-28 Volumetric water content (VWC) measured by f our TDR probes installed adjacent to the buried Acclima sensors for May 30 to June 5, 2007 (50 to 56 DAT) along with seasonal rainfall.............................................................................................................. .140 4-29 Volumetric water content (VWC) measured by f our TDR probes installed adjacent to the buried Acclima sensors for June 20 to June 26, 2007 (71 to 77 DAT) along with seasonal rainfall.............................................................................................................. .141

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15 4-30 Volumetric water content (VWC) for the I5 tim e based treatment averaged over all four replicates for a one month period during the growing seasons along with recorded rainfall events. Horizontal lines indicate the approx imate field capacity (F.C.) VWC, with dashed lines depicti ng the individual season average and solid lines showing the average over all four seasons.............................................................. 145

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16 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Engineering EFFECTS OF SOIL MOISTURE SENSOR BASED IRRIGATION ON DRIP IRRIGATED BELL PEPPERS GROWN ON SANDY SOIL By Kristen Femminella August 2008 Chair: Michael Dukes Cochair: Rafael Munoz-Carpena Major: Agricultural and Biological Engineering As competition for freshwater continues to rise in the state of Florid a, there is a growing need for improvements in agricultural irrigation efficiency. Automated irrigation systems using soil moisture sensors can improve efficiencies by applying irrigation water based on the soil moisture content of the plant r oot zone. Irrigation is initiate d or bypassed based on the sensor reading of soil moisture content. This project was intended to investigate the effects of soil moisture sensor based irrigati on on bell peppers grown on drip ir rigated, plastic mulched raised beds by analyzing cumulative irrigation wate r, fruit yield, deep drainage, and sensor performance. Crop coefficients, Kc initial, Kc mid, and Kc late were estimated using the soil water balance equation. The study was conducted during f our growing seasons in Citra, FL at the University of Florida Plant Science and Research Education Unit. Five irrigation treatments, four SMS based and one time based, were initia ted each season. The SMS treatments reduced irrigation water up to 70% compared to the tim e based treatment and showed increases in irrigation water use efficiency (IWUE) up to 300%. Drainage volumes were also reduced from 36-92% during the four seasons. The SMS treat ments with low thres hold settings (8-10%) showed higher water savings than treatments w ith higher threshold settings (12%). Sensor

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17 performance was determined by analyzing the numb er of bypassed/initiate d events and the soil moisture content at which each event was initiated. Treatments with the lowest threshold setting, 8%, bypassed up to 87% of the scheduled irrigation events and initiated irrigation at the lowest soil moisture content compared with other treatm ents. A soil water balance equation was applied to estimate the crop water demand, ETc, which, in turn, was used to estimate local crop coefficients, Kc, for bell pepper. These estimates, Kc mid = 0.93 and Kc late = 0.71, closely approximated University of Florida IFAS recomme nded values, as well as other values estimated for drip irrigated, plastic mulched vegetables.

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18 CHAPTER 1 INTRODUCTION Rationale The abundance of rivers, lakes, springs, can als, and tributaries throughout the state of Florida leaves m any residents and visitors with the misguided conception that water is an infinitely renewable. This notion; however, coul d not be further from the truth. As agricultural production, urban and suburban development, and re sident and tourist popul ations continue to increase, water management districts are faced w ith the challenge of a llocating water to support the states growing demands and needs. Experts in central Florida are researching alternative water resources as local withdrawals from the Floridan aquifer approach maximum sustainable levels (Dedekorkut et al., 2003). Even the re latively underdeveloped panhandle region of the state cannot escape the impending th reat of water scarcity. This region has been battling with Georgia and Alabama for decades over rights to the Apalachicola-Chattahoochee-Flint River that would provide sufficient water flows to support the fragile and diverse ecos ystem of the area, as well as a million dollar seafood a nd oyster industry (Hanson et al., 2002). Many restrictions and limitations on water use have been imposed across the state in an effort to lessen the strain on limited and, in some cases, dwindling supplies. As water allocati on becomes increasingly scrutinized, Florida will be forced to reexamine existing perceptions and ideas about water, and find new technologies and methods to efficiently use and conserve this priceless resource. Of the total state water withdr awals, 60% is from surface salin e water used in power plant generation. Nearly the entire amount, 99%, is retu rned to the oceans and rivers in which it originated from. The remaining 40% of the to tal withdrawal is ground and surface freshwater. Agricultural operations account for the larges t consumer of freshwat er, using 39% of the groundwater supply and 62% of surf ace water (Marella, 2005). Most of this water comes from

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19 canals, ditches, ponds, lakes, rivers, and tributar ies that are fed by vari ous underlying aquifers. Nationwide, Florida ranks 11th in agricultural water use and uses the largest amount of water in the eastern U.S. to irrigate crops (Hutson et al ., 2004). With the exclusion of improved pasture, nearly 80% of the farmed acres are watered with supplemental irri gation. Most of this land is planted with citrus, but ornamental and vegeta ble production has increase d in the last decade (Marella, 2005). The efficiency in which all of these crops are irrigated has also increased as new advancements in farm management technologies ha ve been made readily available to growers. All new citrus groves are now established with drip irrigation systems as opposed to flooding systems that require huge amounts of surface water to be pumped into groves from canals or onsite reservoirs. Although the water was pumped back after being used, much was lost to evaporation and infiltration. Many older groves are being conv erted from flooding to drip irrigation to increase efficienc y. In 1980, 60% of farmed acres used flood irrigation, 24% used sprinkler irrigation and only 16% had drip systems. By 2000, 45% of farmed acres were still using flood irrigation, sprinkler ir rigated acres decreased to 17%, and drip irrigated acres increased to 38% (Marella, 2005). High value ornamentals and vegetable crops have received much attention for their ability to be produced relatively quickly and effi ciently, while greatly cont ributing to the states total agricultural revenue. Of these crops, bell pepper is among the most important. Florida is ranked 2nd in the nation in production, acreage, and crop value, and also produces nearly 100% of the nations winter crop (Mossler, 2004). The state averages about 7,284 harvested hectares a year that accounted for nearly 200 million dollars in 2004 or 15% of the total fresh vegetable revenue. The crop is an extremely labor intens ive crop that requires la rge field crews on hand

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20 from the beginning of the season for soil fumigation and polyethylene plastic mulch installation to the end of the season when fields may experi ence up to five harvests. This, coupled with increasing competition from foreign as well as in-state producers, along with impending water shortages, has motivated growers to seek out more efficient production methods. The establishment of drip irrigation system s on Floridas farmed lands has contributed tremendously in the conservation of water and nutr ients. Drip irrigation delivers water directly to the plants root zone where it is readily available for uptake. However, installation of a drip irrigation system alone does not gua rantee a large water savings. An effective system must be properly managed and follow an irrigation schedu le appropriate to crop, climate, and field conditions. Many growers use the common schedu ling method of irrigatin g their crops for 1 hour a day when plants are small and 3 hours a day when the plants reach full growth. This method can often result in under-i rrigation in the beginning of th e season and over-i rrigation in the end of the season (Simonne et al., 2002). Ove r-irrigation is a proble m in Florida which is comprised mostly of sandy soils with very low water holding capacities averaging 0.75 in/ft (Haman and Izuno, 1993). Research has shown that excess water that is not used by the plant is percolated out of the rooting zone and into the groundwater s upply (Paramasivam et al., 2000). This typical scheduling method of high volume, lo w frequency events not only wastes water, but may also contribute to groundwater pollution (Far es and Alva, 2000). As the water leaves the soil profile, any existing chemical s or nutrients are likely to be carried with it (Hochmuth and Smajstrla, 1994; Paramasivam et al ., 2001; Zotarelli et al., 2007). A more efficient schedule would initiate ir rigation based upon cu rrent field conditions and crop demands. The idea, however, of growers ev aluating their fields constantly to determine whether or not to irrigate is not feasible, as the average size of a Florida farm is around 200

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21 acres. The solution may lie in soil moisture se nsor technology. Thes e sensors can accurately monitor the soil moisture conditions of the so il at various time intervals throughout the day. When programmed into an existing drip irrigati on system, the sensors can control water outputs based upon the current soil moisture content of th e field. Soil moisture sensor (SMS) based irrigation has shown great potential in reducing irrigation water. Pr eliminary studies show that a low volume, high frequency irriga tion schedule coupled with soil moisture sensors can result in significant water savings while maintaining a competitive marketable yield, increasing water use efficiency, and reducing nitrogen leaching (Dukes et al., 2003). The following chapters will disc uss in greater detail field studies conducted to test the performance of different soil moisture sensors on four seasons of be ll pepper production from 2005-2007. Sensor performance as a function of irrigation water applie d, irrigation events initiated/skipped, volumetric soil moisture cont ent, pepper yield, and nitrogen leaching will be discussed. Objectives Objective 1 To evaluate the effects of soil mois ture sensor (SMS) based irrigation on irrigation water applicati on, fruit yield, drainage, a nd water use efficiency. Objective 2 To implement three different fertig ation treatment rates based upon IFAS recommended rates. Objective 3 To examine the effects of variable i rrigation and nitrogen scheduling on bell pepper yield.

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22 Objective 4 To quantify field parameters such as irrigation water, deep drainage, and precipitation. Objective 5 To integrate the field parameters to create a soil water balance. Objective 6 To develop a crop coefficient, Kc specific to bell pepper grown on plastic mulched, drip irrigated beds. Objective 7 To evaluate the performance of soil mois ture sensors based on irrigation water application, number of seasonal irrigati on events, and volumetric soil moisture content of the beds. Objective 8 To demonstrate the ability of soil mois ture sensor based irrigation to reduce irrigation water applicati on and irrigation events while still maintaining a volumetric soil moisture conten t at or above field capacity.

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23 CHAPTER 2 EFFECTS OF SOIL MOISTURE BASED IR RIGATION ON BELL PEPPER PRODUCTION Introduction The abundance of water located in and around th e state of Florida is deceiving to m any who view water as an unlimited natural resource. The truth is that Florida has a dwindling supply of available clean water. As agricultu ral production, urban and suburban development, and population continues to increase, water manageme nt districts are faced with the challenge of allocating water to support the growing demands in the state. As water distribution becomes increasingly scrutinized, Florid a will be forced to reexamine its existing perceptions and ideas about water, and find new technologies and methods to efficiently use and conserve this priceless resource. The Florida agricultural industr y has the potential to conserve large amounts of water. Agricultural operations in the state account for th e largest consumer of fr eshwater, using 39% of the groundwater supply and 62% of surface water (M arella, 2004). Although crops such as citrus and cattle have been the focus for many decades high value ornamentals and vegetable crops have begun to receive much attention for their ability to be produced quickly, while producing substantial revenue. Of these crops, bell peppers ( capsicum annuum ) are among the most important. Florida is ranked 2nd in the nation in production, acreag e, and crop value, and also produces nearly 100% of the winter crop for the nation (Mossler, 2004). Bell peppers are very sensitive to water and heat stress, which can lead to reduced fruit yield. In order to reduce plant stress and maximize yield, an efficient irrigati on schedule is required to deliver an adequate water supply based on local evapotranspiration (ET) demands. Improvements in irrigation scheduling can be an effective way for growers to maximize yields, while conserving water, fertilizer and energy (Martin et al., 1990). Irrigating with

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24 frequently scheduled irrigation events is very effective in Florida where much of the soil is coarse sand with very low wate r holding capacities (Fares and Alva, 2000) Crops growing in this type of soil require frequent irrigation events, sometimes several per day, to keep enough soil water available for plant transpiration. In response to this relativel y high irrigation demand, growers often over irrigate their fields as insu rance against water stress that can lead to a reduction in crop yield (Howell, 1996). This ty pe of blind irrigation scheduling practice can often be detrimental to the crop and the surround ing environment. The large pore spaces that exist in sandy soils are conducive to deep draina ge by any excessively applied water. Not only does this water percolate out of the rooting zone making it unavailable for plant uptake, but it also carries nutrients along w ith it (e.g. nitrates and phospha tes) which may contribute to groundwater contamination (Bouchard et al., 1992; Babiker et al., 2004; Sp alding et al., 2001). Improved irrigation scheduling involves know ledge of climate conditions, crop growth demands, and soil conditions. Making irrigati on decisions based upon these contributing factors is important for good irrigation management. On e way to improve irrigation scheduling is by applying irrigation water based on the soil moisture content of the crop root zone. Soil moisture sensor (SMS) based irrigation has been show n to be an effective scheduling method in strawberries (Clark et al., 1996) citrus (Fares and Alva, 2000) and tomatoes (Munoz-Carpena et al., 2005). Previous research has also shown an increase in irrigation water use efficiency (IWUE) for crops irrigated with SMS treatments compared to typical time-based irrigation treatments (Zotarelli et al. 2007a). Dukes et al (2003) reported increased marketable yields and IWUE for drip irrigated bell pe ppers using a sensor automate d schedule compared to a time based schedule.

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25 The objective of this study was to determine the effects of SMS irrigation controllers on bell pepper production. The independent resear ch variables were represented by various irrigation scheduling thresholds a nd rates. The dependent variable s, including 1) total irrigation water applied, 2) marketable yield and irrigati on water use efficiency, and 3) volume of water percolated from the rooting zone, were analy zed and compared to a time-based irrigation schedule that represents grower practices. Materials and Methods This rese arch investigated SMS irrigated bell peppers grown on plastic mulch during the growing seasons of spring 2005, spring 2006, fa ll 2006, and spring 2007. The experiment was repeated over four different grow ing seasons to minimize the affect s of variable climate and field conditions. The study took place in Marion County, Florida at the University of Florida Plant Science Research and Education Unit. Soils Characteristics Each of the four trials was located at the same field site. The soil for this site was classified as Candler sand a nd Tavares sand containing 97% sand-sized particles (Buster 1979). Field capacity is estimated to be in the ra nge of 0.10-0.12 v/v in the upper 0-30 cm (Icerman, 2007) of plastic mulched vegetable beds. The soil is very permeable, with a low water holding capacity, making excessively applied water and nu trients highly susceptible to drainage and leaching (Simonne and Hochmuth, 2004) Experimental Design and Field Layout In preparation for this study, drainage lysim ete rs were installed under selected treatments on March 21, 2005, prior to bed formation (Zotar elli et al., 2007). At the start of each experiment the field was rototill ed, beds were formed, and immediately fumigated (80% methyl bromide, 20% chloropicrin) and covered with bl ack plastic mulch. Drip irrigation tape was

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26 simultaneously installed under the plastic mulch. Two drip lines, one for irrigation and one for fertigation, were installed in the center of each plot on the soil surface below the plastic mulch. The fall 2006 and spring 2007 growing seasons imple mented an irrigation treatment that used twin drip lines. In this case the lines were installed at a distance of 0.15 m from the center fertigation line. The pepper transplants of the cultivar Brigadier were transplanted on April 5, 2005, April 10, 2006, September 11, 2006, and April 12, 2007 in raised beds, 15 m long and spaced 1.8 m apart, center to center. The transplants were spaced 0.3 m apart and planted in staggered dual rows. The treatments were laid out in a randomized complete block design with four replicates. Four of the irrigation treatments (I1-I4) were scheduled based upon soil moisture, while the other treatment (I5) was a time based treatment intende d to simulate grower practices. The five irrigation treatments were applied across all four blocks via five separate flow meters installed off of the main irrigation line. Fertigation based upon IFAS recommendations for bell peppers, with the recommendation rate of 208 kg/ha. Fe rtigation events took placed weekly after the drainage lysimeters were pumped. Irrigation and fertigation was applied through drip tape (Turbulent Twin Wall, 0.20 m em itter spacing, 0.25 mm thickness, and 0.7 L/hr at 69 kPa (Chapin Watermatics, NY). Irrigation and Fertigation Control and Data Collection The SMS irrigation treatm ents allowed programmed timed irrigation events based on readings taken by soil moisture sensors. Two di fferent soil moisture sensor controllers were used during the four field trials In spring 2005, SMS treatment, I 1, used a dielectric capacitance probe (ECH2O, Decagon Devices Inc., Pullman, WA) coupled with a quantified irrigation controller (QIC) developed by th e Agricultural and Biological Engineering Department (Dukes and Munoz-Carpena, 2005). The rest of the SMS treatments used a Digital TDT Moisture

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27 Sensor paired with either an RS500 or CS3500 irrigation timer, all manufactured by Acclima, Inc. (Meridian, ID). Each season utilized four sensors, one for each SMS treatment, which were installed in one replicate located in the south en d of the field and controlled irrigation for the entire field. The Acclima sensors were buried in the plot at a 30 angle to measure the top 0.2 m of the production bed. The ECH2O probe was installed vertically in to the plot to measure the top 0.15 m of the raised bed. The QIC and Acclima RS500 irrigation controllers were wired to an irrigation timer (ESP12LX Irrigation Controller, Rainbird Corporation, Azuga, CA). The timer was programmed with five irrigation windows each day to apply a poten tial irrigation depth of approximately 5 mm/d. Each irrigation window was 24 minut es long, the required time to apply approximately 1 mm of water, and programmed to begin at 8:00am, 10:00am, 12:00pm, 2:00pm, and 4:00pm for spring 2005, spring 2006, and fall 2006, and 10:00am, 12:00pm, 2:00pm, 4:00pm and 6:00pm for spring 2007. Each irrigation treatment was assigned a threshold setting that determined when the system would irrigate based on the moisture cont ent of the soil. The th reshold settings were selected based on the estimated range of the fi eld capacity of the soil, 10-12% (Icerman, 2007). The settings were varied from 8% up to 14%. The 8% threshold setting was established to study the effects of possible plant stress when irrigatin g slightly under estimated field capacity. The higher threshold settings were established to obs erve the potential effects of over irrigation like excess drainage and reduced fruit yield. At the onset of a scheduled event, the irrigation controller queried the sensor to determine the soil mo isture content of the soil. If the reading was lower than the threshold setting of the controlle r, irrigation would begin and run for 24 minutes. If the sensor reading was higher than the contro ller threshold setting, the event was bypassed. The Acclima C3500 irrigation controller represen ted an on demand irrigation schedule, and

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28 allowed irrigation events to occur at any time the sensor reading fell below the lower bound of set threshold range. The irrigation event ended when the sensor indicated the soil moisture content was at or above the upper bound of th e setting. Because ir rigation events are unscheduled and may occur simultaneously, it is di fficult to ensure sufficient water pressure for treatments irrigated across several fields with one common well and main water pipe. This makes this type of irrigation controller im practical for most large scale growers. The control treatment represented a time base d irrigation schedule intended to represent a grower schedule. This treatment irrigated once a day, regardless of soil water conditions, for 2 hours (5 mm/day) in the morning. Table 2 outlines the irrigation treatments and soil moisture threshold settings implemented for each experiment. Water applications from irrigation and fertigation events were manually recorded from positive displacement flowmeters (V100 1.6 cm diameter bore with pulse output, AMCO WaterMetering Systems Inc., Ocala, FL). In addition to manual readings, the flowmeters contained transducers that signaled a switch cl osure every 18.9 L. The switch closures were recorded by data loggers (HOB O event logger, Onset Computer Corp. Inc., Bourne, MA) and continually logged water and fertigation event ti mes, which were downloaded once a week. By knowing the time and duration of each event, the data was used to determine if and when irrigation events occurred or were skipped. Soil Moisture Monitoring and Drainage Collection Volum etric water content (VWC) was monito red in each experiment using time domain reflectometry (TDR) probes (CS-615, Campbell Scientific, Inc. Logan, Utah) buried at a 45 angle to measure the upper 0.15 m of the rooti ng zone. The probes were installed in each treatment across all replicates. The TDR probe s were connected to a data logger (Model CR-10,

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29 Campbell Scientific, Logan, Inc., UT) with a relay multiplexer (Model AM416, Campbell Scientific, Inc., Logan, UT). The data was downloaded weekly. Details of the lysimeter dimensions and burial depth can be seen in Figure 2 (Zotarelli et al., 2007). They were constructed by cross-sectioning 208 L polyethylene drums, and had a capture area of 1.52 m2. The lysimeters were buried 0.75 m below the surface of the bed. The collected leachate was pumped weekly into 20 L bottles using two vacuum pumps. The bottles were weighed to determine the leachate volume. Harvest Harvest occurred 75, 79 and 83 days after tr ansplanting (DAT) for spring 2005, 58, 70, and 74 DAT for spring 2006, 79 and 88 DAT for fall 2006, and 70 and 82 DAT for spring 2007. The fruits were counted, weighed, and sorted according to USDA (1997) standards. Marketable yield was calculated as the total yield m inus culls. Analysis Method Marketable yield and irrigation water use efficiency (IW UE) were analyzed using analysis of variance with PROC GLM (SAS Inst. Inc., 1996). Variances among treatments were analyzed using Duncans Multiple Range Test, assuming a 95% confidence level. Results and Discussion Results and discussion are presented below for each individual season, followed by an overall comparison of the four growing seasons. Spring 2005 Climate Conditions For spring 2005, cum ulative rainfall totaled nearly 343 mm (Figure 2) which was much higher than the average rainfall of 253 mm for this region du ring this time period. This exceptionally high amount of rainfall likely contribut ed to a high incidence of disease that spread

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30 through the field approximately midway (40 DAT) through the growing season. Bacterial spot and phytophthora blight, both found throughout the field and across all treatments, are known to thrive under warm, moist condi tions (Mossler, 2006). Irrigation Treatments The bell pepper transplants were established with an irrigation schedul e of 1 hr/d (2 mm/d) for nearly three weeks. Irriga tion treatm ents were initiated on April 28, 2005 (23 DAT). The SMS treatments, which included the QIC and Acclima controlled systems, applied less water than the time based grower treatment. The two di fferent sensor types, however, did not perform the same. The SMS treatments controlled by the A cclima sensors, I2 (10%), I3 (12%), and I4 (12-14%), functioned as predic ted, bypassing scheduled irrigation events as needed. After treatments were initiated, I2 applied 53 mm (0.9 mm/d), I3 applied 138 mm (2.3 mm/d), and I4 applied 131 mm (2.2 mm/d). I5 resulted in 253 mm (4.2 mm/d) as seen in Table 2. The I1 QIC treatment bypassed few irrigation events, resu lting in a cumulative application 230 mm (3.8 mm/d) and only a 9% savings compared with I5. The controller was thou ght to be set too high and was adjusted during the season (58 DAT) fr om 550 mV (10% VWC) to 515 mV (8% VWC). The controller; however, did not respond to this adjustment, and continued to initiate irrigation for most of the scheduled events (Figure 2.). Several factors may have contributed to the malfunctioning of this treatment since sensor perf ormance is influenced by placement in the bed, proper installation, soil salinity, proximity to dr ip emitters, and soil characteristics. In 2006 Schroder evaluated the effects of salinity on th e performance of the QIC treatment (Schroder, 2006). Just as Schroder observed, large spikes in soil moisture were also observed after weekly QIC fertigation events which may indicate effects from salinity in the applied fertilizer. An analysis of soil moisture conten t can be found in Chapter 4. I2, set at the lowest threshold, resulted in the largest water savings, 79%. I3 an d I4, set at similar threshold settings, applied

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31 nearly the same amount of water and resulted in similar water reductions of 48 and 49%, respectively. Drainage Drainage lysim eters were installed under treatments I2, I3, and I5 which amounted to cumulative drainage totals of 14.7 mm, 29.5 mm, and 60.5 mm for I2, I3, and I5, respectively. These values differed significantly, and increased with the amount of irrigation water applied, as total seasonal irrigation was 129 mm, 229 mm, and 375 mm across I2, I3, and I5, respectively (Table 2). This increase is a result of the low water holding capacity of the soil which holds about 25 mm of water in 30 cm of sandy soil. Each treatment experienced similar amounts of drainage during the establishment phase when water applications were similar. After treatments were initiated (23 DAT), the weekly collected drai nage began to vary. I2 experienced little to no drainage after the SMS treatment (10% VWC) wa s established (Figure 2). This was the result of very few irrigation events th at resulted in a treatment total of 53 mm (0.9 mm/d) as seen in Table 2. Drainage decreased for I3 as well af ter the SMS treatment (12% VWC) was initiated due to a decrease in the number of irrigation events (2.3 mm/d average daily application). Drainage continued to increase fo r the time based treatment, I5, after treatments were established as irrigation applications were consistent and averaged 4.2 mm/d (Table 2). It is unknown why there was no drainage from I5 during week 7 (Figure 2), as there were no changes in irrigation. Yield and Water Use Efficiency Three harvests took place during sp ring 2005 on 75 DAT, 79 DAT, and 83 DAT. Marketable yields for the season can be seen in T able 2 and ranged from 20, 320 kg/ha for I1 to 29,080 kg/ha for I3. There were statistical diffe rences between yields re lated to irrigation and only one of the treatments produced yields above the average annual yield for Florida bell

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32 peppers, 28,000 kg/ha (Maynard and Santos, 2007). The yields were relatively low this season due to extensive plant disease. Significant differences were seen in irrigation water use efficiency (IWUE) across irrigation treatments. I1 and I5 had the lowest IWUE, 8.4 and 9.2 kg of fruits/m3, respectively, due to the high amount of i rrigation water applied by these treatments. High amounts of irrigation water can not only drai n nutrients from the crop root zone, but also reduce the efficiency water and nutrient uptake by roots, ultimately affecting the yield potential. Reduced water can also adversely affect growth and subsequently yield as shown in Figure 2. The figure shows plant growth differences that o ccurred in a plot duri ng week 5 of the season. The drip tape was shifted closer to the right si de, which led to drier conditions on the left and obvious differences in plant development. I3 and I4 applied similar amounts of water, likely due to their threshold settings, produced similar yi elds, and showed no significant difference in IWUE. I2 had the hi ghest IWUE of 39.7 kg/m3, which can be attributed to a very low irrigation total, yet produced a marketable yield of 24,110 kg/ha, well under the state average (Table 2). Spring 2006 Climate Conditions During spring 2006, cumulative rainfall totaled 149 mm as seen in Figure 2. Two events occurred during the season wh ich resulted in rainfall over 20 mm (61 and 62 DAT). The relatively drier field conditions re duced the spread of disease, although bacterial spot was present at the end of the season. Irrigation Treatments All ir rigation treatments were watered 1 hr/d during the establishment phase (2 mm/d). Individual irrigation treatments were init iated on April 28, 2006 ( 16 DAT). A programming error in the I4 irrigation controller during the beginni ng of the season caused the treatment to over-irrigate (Figure 2), resulting in the largest irrigation to tal of all treatments (348 mm). The

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33 problem was successfully adjusted (29 DAT) and I4 functioned properly for the duration of the season. The treatment irrigated an average of 16.2 mm/d before the error was fixed and averaged 3.4 mm/d after the adjustment was made. Base d upon this, it can be assu med that if I4 had functioned properly from the beginning of the season, it would have applied approximately 169 mm of water and resulted in a 49% water savings. Problems also existed with treatments I2 and I3. Both treatments functioned well, with I2 byp assing more events than I3, until an unpredicted and unexplainable event caused I2 to irrigate for a 15 hour period (30 DAT). I2 was evaluated and adjusted on 35 DAT, and from this point on be gan bypassing the same events as I3. By the end of the season, I2 applied 301 mm (4.9 mm/d) and I3 applied 287 mm (4.7 mm/d) resulting in a 9 and 13% water savings, respectively (Table 2 ). This problem may have resulted from the cross communication between sensor signals since the two SMS irri gation (I2 and I3) controllers shared a common irrigation timer. The misco mmunication between the controller and sensor signals may have caused both controllers to recei ve signals from one of the buried sensors and ultimately performing as one treatment. I1 and I5 were the only treatments to operate properly throughout the season. I1 applied 156 mm (2.6 mm/d), 53% less water than I5, which applied 329 mm (5.4 mm/d). Drainage For spring 2006, drainage lysim eters captured wa ter that percolated beneath treatments I2, I3, and I5. There were no signi ficant differences with respec t to percolation among irrigation treatments since I2, I3, and I5 all applied similar amounts of irrigation water due to the malfunctioning of sensors. Cumulative drainage totals were 38.1 mm fo r I2, 47.7 mm for I3, and 49.3 mm for I5 (Figure 2).

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34 Yield and Water Use Efficiency Three harvests took place in spring 2006 on 58, 70, and 74 DAT. Figure 2 shows a typical pepper plot during the harvest. Marketable yields ranged from 14,200 kg/ha for I4 to 17,100 kg/ha for I1 (Table 2.) There were no significant differences in yield between the irrigation treatments, and all were well below the state average. The reduced yields were the result of insect infestation and plant disease. I1 and I4 produced the lo west and highest yields, yet had similar IWUE as seen in Table 2. Although the irrigati on total was adjusted for I4 from 348 mm to 169 mm to account for programming error (DAT 23-29), this was not likely the cause of the reduced yield. The yield may appear low since it was averag ed over only four plots that were irrigated with the I4 treatment, where I1, I2, and I3 had 12 plot s and I5 had 20 plots. One of the I4 irrigated plots had a marketable yield of 8,100 kg/ha, which while the highest had 17,600 kg/ha. Fall 2006 Climate Conditions The fall 2006 growing season had a cum ulative rainfall of 132 mm (Figure 2). The low incidence of rainfall and cooler fall temperatures c ontributed to a healt hy crop with no visible signs of disease. Temperatures began to fa ll at the end of the s eason, but the crop was not exposed to frost. Irrigation Treatments The bell pepper transplants were establishe d with an irrigation schedule of two 1 hour events, twice a day. Irrigati on treatm ents were initiated on September 28, 2006 (17 DAT). During the season, a wiring problem caused all of the SMS treatments to malfunction. It was discovered that I1 and I2, both wired to a common irrigation controller, and I3 and I4, also wired to common irrigation controller were bypassing and irrigating th e same scheduled events and

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35 applying same irrigation amounts (Figure 2). The problem was attributed to cross communication between the Acclima sensors, causi ng each of the irrigation controllers to receive signals from only one of the two wired sensors. Several adjustments were made, but the problem was not solved until each controller was wired to a separate indivi dual irrigation timer. Eventually, 58 DAT, the SMS treatments began to irrigate independently of each other (Figure 2). After this point, I2 began bypassing more events than I1. This was unexpected, since I2 was set to a higher settin g of 10%, compared to I1 at 8%. In addition to this wiring problem, a programming error in the irriga tion controller caused I4 to ov er-irrigate from 49 DAT to 65 DAT. The implementation of twin drip lines on this treatment demanded the adjustment of the irrigation window from 24 minutes to 12 minutes to compensate for the doubled flow rate. The timer, however, was mistakenly changed and cause d I4 to apply double the amount of irrigation water. By the end of the season, I3 and I4 a pplied the most water with 319 mm (4.2 mm/d) and 327 mm (4.3 mm/d), respectively (Table 2). Each of these treatments a pplied more water than I5 which had 303 mm (4.0 mm/d). The lower wa ter application by I5 wa s a result of 9 missed programmed events due to power outages and fiel d maintenance. I1 applied a total amount of 244 mm (3.2 mm/d) and reduced water applica tion by 19%, while I2 applied 213 mm (2.8 mm/d) with the highest water savings of 30%. Drainage Drainage lysimeters were located on treatments I2, I3, I4 and I5 for the fall 2006 season. The addition of lysimeters to some of the 14 tr eatment plots was the result of an altered field layout to account for the I4 modification of twin drip lines. Cumulativ e drainage totals for treatments I3, I4, and I5 showed no significant differences (Figure 2) as a result of similar irrigation totals due to the faile d performance to the I3 and I4 SMS treatments as seen in Table

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36 2. Both treatments applied more irrigation than I5. I2 was the only significantly different treatment as a result of having the lowest tr eatment irrigation total of 213 mm (Table 2.). Yield and Water Use Efficiency Harvest occurred 79 and 88 DAT for the fall 200 6 growing season. Yields were higher during this season com pared to the spring season s due to favorably cooler temperatures during fruit set and development. Yields ranged from 43,400 kg/ha for I1 to 45,500 kg/ha for I2 (Table 2), and were well above the state average of 28,000 kg/ha (Maynard and Santos, 2007). There were no statistical differences in yield between irrigation treatments. The reduced irrigation totals from the SMS treatments resulted in highe r values of IWUE as compared to the time based treatment, I5. Yields were not reported for I3 and I4 since the treatments completely failed to bypass irrigation events and reduce water. Yi eld was greatly reduced on I4 from the programming errors that caused ove r irrigation in the beginning of the season. Plant growth was drastically affected and the plants were noticeab ly smaller and lighter in color throughout the season (Figure 2). The cumulative irrigation tota ls for these treatments were higher than I5 (Table 2). Spring 2007 Climate Conditions The spring 2007 season had a cum ulative rain fall total of 124 mm (Figure 2) and no incidence of disease. Irrigation Treatments In spring 2007 the bell pepper transplants were established w ith a daily irrigation schedule of two 1 hour events per day. Individual irrigation treatments we re initiated 18 DAT. Each of the SMS treatments was wired to an in dividual irrigation contro ller at the beginning of the season to avoid past problems with sensor cross communication. Th is proved to be an

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37 effective method when testing multiple sensors in one field. Problems did arise, however, with treatments I2 and I4, when both treatments faile d to bypass irrigation events in the beginning of the season. The locations of both treatment sens ors, I2 and I4, were assessed 30 DAT. I4 was reburied in the original location and I2 was moved to a different location in the plot. After the probes were reburied, I4 continued to irrigate frequently, while I2 began to bypass events as seen in Figure 2. The location of the sensor in th e bed was apparently the cause of problem with the I2 treatment since it func tioned properly after it was moved. The problem with I4, however, was unknown, since the placement of the sensor was evaluated and carefully reburied. Both of the treatments were set to the same soil moisture threshold level of 10%, but I4 irrigated with twin drip lines. The location of the sensor relativ e to the outside drip line and center fertigation line, although directly in betw een both, may have been a drier area as compared to other treatments with centered drip lines. By the e nd of the season, I4 applied 377 mm (3.6 mm/d), nearly as much as I5 which applied 308 (4.1 mm /d), and only had a 10% water savings (Table 2 8.). I1 and I2 applied similar amounts of water, with 171 mm (2.3 mm/d) and 190 mm (2.5 mm/d), respectively. I3 a pplied 261 mm (3.1 mm/d), and 15% in water savings. Drainage Like the fall 2006 season, drainage lysim eters were located under treatments I2, I3, I4, and I5. Cumulative drainage totals reflected irri gation applications, as I3, I4, and I5 applied the most irrigation and drained the most water. Th ere were no statistical differences between these three treatments. I2 applied a lower treatment irrigation total and draine d significantly less water compared to the other treatments. The affects of the adjustment made to the I2 treatment on 30 DAT which caused irrigation events to be bypass ed more frequently can be seen in the cumulative drainage in Figure 2. Drainage appears to steadily increase after the treatments

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38 were initiated (18 DAT) until the adjustment was made (30 DAT). After this, drainage drastically decreased, an d little was collected (0.79 mm) for the duration of the season. Yield and Water Use Efficiency Pepper yields varied from 23,800 kg/ha for I3 to 29,700 kg/ha for I1 (Table 2.). Like previous seasons, there were no significant differences in yiel d am ong the irrigation treatments, and all yields were close to the state average for bell peppers. There were statistical differences, however, in IWUE among the irri gation treatments. Overall, IW UE decreased with increased irrigation water totals, where I1, with the lowe st irrigation total of 171 mm, had an IWUE of 17.37 kg/m3, and I5, with the highest irrigation total of 308 mm, had an IWUE of 7.99 kg/m3. There were no significant differe nces among IWUE for the treatments with high irrigation totals, I3, I4, and I5. Comparison of Results Over the course of the four growing seasons 16 SMS treatm ents were initiated and tested at threshold settings va rying from 8-12%, two of which represented on demand schedules with threshold ranges of 12-14%. Eight of the 16 im plemented treatments functioned properly and reduced irrigation water compared to the time based treatment, I5, by skipping scheduled events based on soil moisture readings. The other ei ght treatments malfunctione d due to significant programming, wiring, and/or insta llation errors. These treatments were not representative of typical sensor performance, therefore were not included in overall averages and comparisons. The eight successful treatments are shown in Table 2. Conclusions The trials conducted over the four growing seasons demonstrated the ability of SMS treatments to reduce total irrigation water, up to 79%, and increase IWUE, up to 40 kg/m3, compared to time based irrigation schedules. The SMS treatment performance is highly

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39 dependent on proper sensor installation and burial in the soil, as soil mo isture conditions vary depending on the location of the sensor relative to the drip tape and plants. SMS treatments with low range threshold settings (8 and 10%) perfor med similarly in the sandy soil beds, yet both treatments applied less water and had higher yields than the high th reshold treatment (12%). The on demand irrigation treatment (12-14%), like the 10% treatment, showed the greatest reduction in irrigation water, and produced similar yields to the time based irrigated treatments. However, on demand control systems would necessitate large hydraulic cap acity in commercial systems and would need to be implemented with care to minimize this expense. To ensure proper functioning, each sensor requires an indepe ndent irrigation controlle r in order to avoid over irrigation caused by sensor signaling errors. Further research shou ld include a continued investigation of sensor performance as well as the water saving potential of on demand irrigation treatments and how they eff ect marketable yield and drainage.

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40 Table 2. Irrigation treatments, threshold settings (VWC), and programmed irrigation windows. Treatment Treatment Description VWC threshold setting (m3/m3) Irrigation window Spring Pepper 2005 I1 I2 I3 I4 I5 Spring Pepper 2006 I1 I2 I3 I4 I5 Fall Pepper 2006 I1 I2 I3 I4 I5 Spring Pepper 2007 I1 I2 I3 I4 I5 QIC Acclima RS500 Acclima RS500 Acclima CS3500 Timebased schedule Acclima RS500 Acclima RS500 Acclima RS500 Acclima CS3500 Timebased schedule Acclima RS500 Acclima RS500 Acclima RS500 Acclima RS500 twin drip lines Timebased schedule Acclima RS500 Acclima RS500 Acclima RS500 Acclima RS500 twin drip lines Timebased schedule 0.1 (500 mV) 0.1 0.12 0.12.14 n/a 0.08 0.1 0.12 0.12.14 n/a 0.08 0.1 0.12 0.1 n/a 0.08 0.1 0.12 0.1 n/a 24 min, 5 times/day 24 min, 5 times/day 24 min, 5 times/day Anytime 2 hours, 1 time/day 24 min, 5 times/day 24 min, 5 times/day 24 min, 5 times/day Anytime 2 hours, 1 time/day 24 min, 5 times/day 24 min, 5 times/day 24 min, 5 times/day 12 min, 5 times/day 2 hours, 1 time/day 24 min, 5 times/day 24 min, 5 times/day 24 min, 5 times/day 12 min, 5 times/day 2 hours, 1 time/day

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41 Figure 2. Details and dimensions of drai nage lysimeter burial beneath raised bed.

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42 02 04 06 08 0 Cumulative Rainfall (mm x 10) and Daily Rainfall (mm) 0 10 20 30 40 50 60 Temperature (C) 10 20 30 40 50 Cumulative Rainfall Daily Rainfall Average Air Temperature Number of Days after Transplanting Figure 2. Minimum, maximum, and average temperatures during spring 2005 along with daily and cumulative rainfall. Spring 2005 Number of Days after Transplanting 02 04 06 08 01 0 0 Cumulative Irrigation (mm) 0 100 200 300 400 I1 10% QIC I2 10% AccRS500 I3 13% AccRS500 I4 12-14% AccCS3500 I5time based Figure 2. Cumulative irrigation water after in itiation of individual treatments in spring 2005.

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43 Table 2. Total water applicati on during entire season, total wa ter applied after treatment initiation, 23 DAT, average application rate and target soil moisture settings for spring 2005. Spring Pepper 2005 Treatment Description Threshold Setting VWC (%) Total Water Application* (mm) Total Treatment Application (mm) Average Daily Application (mm/d) Treatment Water Savings Compared to I5 (%) I1 QIC 0.13232303.8 9 I2 Acclima RS500 0.1129530.9 79 I3 Acclima RS500 0.122291382.3 45 I4 Acclima CS3500 0.12.141761312.2 48 I5 Timebased n/a3752534.2 0 *Includes irrigation from establishment, fertigation, and other applications not related to scheduled irrigation events. Spring 2005 02 04 06 08 01 0 0 Cumulative Drainage (mm) 0 10 20 30 40 50 60 70 I2 10%, AccRS500 I3 12% AccRS500 I5 Time-based Number of Days after Transplanting Figure 2. Cumulative water (drain age) percolated beneath the root zone for treatments I2, I3, and I5 for spring 2005.

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44 Table 2. Irrigation treatment effects on marketab le yield and irrigation water use efficiency, along with total applied irrigation for spring 2005. Treatment Total Treatment Water Applied (mm) Marketable Yield* (kg/ha) IWUE* (kg/m3) I1, QIC 230 20, 320 c 8.4 c I2, Acclima RS500 53 24, 110 bc 39.7 a I3, Acclima RS500 138 29,080 a 21.1 b I4, Acclima CS3500 131 27,480 ab 21.0 b I5, timebased 25324, 660 abc 9.2 c *Different letters indicate significant differences for P 0.05 (Duncans test) Figure 2. Disproportionate plant growth from redu ced water due to a horizontal shift in drip tape caused by field activities and/or im proper installation during week 5 of the spring 2005 season.

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45 02 04 06 08 0 0 10 20 30 40 50 60 Temperature (C) 0 5 10 15 20 25 30 35 Cumulative Rainfall Daily Rainfall Average Air Temperature Cumulative Rainfall (mm x 10) and Daily Rainfall (mm)Number of Days after Transplanting Figure 2. Minimum, maximum, and average temperatures during spring 2006 along with daily and cumulative rainfall. 02 04 06 08 01 0 0 Cumulative Irrigation (mm) 0 100 200 300 400 Spring 2006 Number of Days after TransplantingI1 8% AccRS500 I2 10% AccRS500 I3 13% AccRS500 I4 12-14% AccCS3500 I5time based Figure 2. Cumulative irrigation water after initiati on of individual trea tments in spring 2006.

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46 Table 2. Total water applicati on during entire season, total wa ter applied after treatment initiation, 23 DAT, average application rate and target soil moisture settings for spring 2006. Spring Pepper 2006 Treatment Description Threshold Setting VWC (%) Total Water Application* (mm) Total Treatment Application (mm) Average Daily Application (mm/d) Treatment Water Savings Compared to I5 (%) I1 Acclima RS500 0.082731562.6 53 I2 Acclima RS500 0.14173014.9 9 I3 Acclima RS500 0.123652874.7 13 I4 Acclima C3500 0.120.144351692.8 49** I5 Timebased n/a4213295.4 0 *Includes irrigation from establishment, fertigation, and other applications not related to scheduled irrigation events. **Savings after programming error was fixed (29 DAT).

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47 02 04 06 08 0 Cumulative Drainage (mm) 0 10 20 30 40 50 60 70 Spring 2006I2 10%, AccRS500 I3 12% AccRS500 I5 Time-based Number of Days after Transplanting Figure 2. Cumulative drainage of water percolated beneath the root zone for treatments I2, I3, and I5 for spring 2006. There were no significant differences (ns) between treatments. Table 2. Irrigation treatment effects on marketab le yield and irrigation water use efficiency, along with total applied irrigation for spring 2006. Treatment Total Irrigation Applied (mm) Marketable Yield** (kg/ha) IWUE** (kg/m3) I1, Acclima RS500 156 17, 100 a 11.0 a I2, Acclima RS500 301 14, 600 a 4.9 b I3, Acclima RS500 287 14,700 a 5.1 b I4, Acclima CS3500 169* 14,200 a 4.1 b I5, timebased 329 16,200 a 9.6 a *Value reflects irrigation after programming error was fixed (29 DAT). **Different letters indicate significant differences for P 0.05 (Duncans test).

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48 Figure 2. Pepper plot with mature pepper plan ts and fruit during week 12 of the spring 2006 growing season. 02 04 06 08 0 0 10 20 30 40 50 60 Temperature (C) 0 10 20 30 40 50 Cumulative Rainfall Daily Rainfall Average Air Temperature Cumulative Rainfall (mm x 10) and Daily Rainfall (mm)Number of Days after Transplanting Figure 2. Minimum, maximum, and average temperatures during fa ll 2006 along with daily and cumulative rainfall.

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49 02 04 06 08 01 0 0 Cumulative Irrigation (mm) 0 100 200 300 400 Fall 2006 Number of Days after TransplantingI1 8% AccRS500 I2 10% AccRS500 I3 13% AccRS500 I4 12-14% AccRS500, twin drip I5time based Figure 2. Cumulative irrigation water after initiation of individual treatments in fall 2006. Treatments I1 and I2 began functioning independently after 58 days after transplant (DAT).

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50 Table 2. Total water applicati on during entire season, total wa ter applied after treatment initiation, 23 DAT, average application rate, and target soil moisture settings for fall 2006. Fall Pepper 2006 Treatment Description Threshold Setting VWC (%) Total Water Application* (mm) Total Treatment Application (mm) Average Daily Application (mm/d) Treatment Water Savings Compared to I5 (%) I1 Acclima RS500 0.083702443.2 19 I2 Acclima RS500 0.12942132.8 30 I3 Acclima RS500 0.124013194.2 -5 I4 Acclima RS500 Twin drip lines 0.14643274.3 -8 I5 Timebased n/a3903034.0 0 *Includes irrigation from establishment, fertigation, and other applications not related to scheduled irrigation events.

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51 02 04 06 08 01 0 0 Cumulative Drainage (mm) 0 10 20 30 40 50 60 70 I2 10% AccRS500 I3 12% AccRS500 I4 10% AccRS500, twin drip I5 Time-based Fall 2006Number of Days after Transplanting Figure 2. Cumulative drainage of water percolated beneath the root zone for treatments I2, I3, I4 and I5 for fall 2006. Table 2. Irrigation treatment effects on marketab le yield and irrigation water use efficiency, along with total applied irrigation for fall 2006. Treatment Total Irrigation Applied (mm) Marketable Yield** (kg/ha) IWUE** (kg/m3) I1, Acclima RS500 244 43, 400 a 17.8 b I2, Acclima RS500 213 45, 500 a 21.4 a I3, Acclima RS500 319 ----I4, Acclima RS500* 327 ----I5, timebased 303 44, 900 a 14.8 c *Treatment yields not reported due failed sensor performance. **Different letters indicate significant differences for P 0.05 (Duncans test)

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52 Figure 2. Effects of over irriga tion of treatment I4 (left) on plant growth compared to I5 (right) during week 6 of the fall 2006 growing season. 02 04 06 08 0 0 10 20 30 40 50 60 Temperature (C) 0 10 20 30 40 50 Cumulative Rainfall Daily Rainfall Average Air Temperature Cumulative Rainfall (mm x 10) and Daily Rainfall (mm)Number of Days after Transplanting Figure 2. Minimum, maximum, and average temperatures during spring 2007 along with daily and cumulative rainfall.

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53 02 04 06 08 01 0 0 Cumulative Irrigation (mm) 0 100 200 300 400 Spring 2007 Number of Days after TransplantingI1 8% AccRS500 I2 10% AccRS500 I3 13% AccRS500 I4 12-14% AccRS500, twin drip I5time based Figure 2. Cumulative irrigation water after in itiation of individual treatments in spring 2007.

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54 Table 2. Total water applica tion during entire season, total water applied after treatment initiation, 23 DAT, average application rate and target soil moisture settings for spring 2007. Spring Pepper 2007 Treatment Description Threshold Setting VWC (%) Total Water Application* (mm) Total Treatment Application (mm) Average Daily Application (mm/d) Treatment Water Savings Compared to I5 (%) I1 Acclima RS500 0.082401712.3 44 I2 Acclima RS500 0.12671902.5 38 I3 Acclima RS500 0.123612613.4 15 I4 Acclima RS500 Twin drip lines 0.14332773.6 10 I5 Timebased n/a4263084.1 0 *Includes irrigation from establishment, fertigation, and other applications not related to scheduled irrigation events.

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55 02 04 06 08 01 0 0 Cumulative Drainage (mm) 0 10 20 30 40 50 60 70 Spring 2007I2 10% AccRS500 I3 12% AccRS500 I4 10% AccRS500, twin drip I5 Time-based Number of Days after Transplanting Figure 2. Cumulative drainage of water percolated beneath the root zone for treatments I2, I3, I4 and I5 for spring 2007. Table 2. Irrigation treatment effects on marketable yield and irrigation water use efficiency (IWUE), along with total a pplied irrigation for spring 2007. Treatment Total Treatment Application (mm) Marketable Yield* (kg/ha) IWUE* (kg/m3) I1, Acclima RS500 171 29,700 a 17.4 a I2, Acclima RS500 190 27,500 a 14.5 b I3, Acclima RS500 261 23,800 a 9.1 c I4, Acclima RS500 277 27,000 a 9.8 c I5, timebased 308 24,600 a 8.0 c *Different letters indicate significant differences for P 0.05 (Duncans test)

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56 Table 2. Summary of successf ul SMS treatments over spring 2005, spring 2006, fall 2006, and spring 2007 growing seasons, with average trea tment irrigation water, marketable yield, irrigation water use efficien cy (IWUE), and water savings. Season Treat. Setting Total Rainfall (mm) Average Total Treatment App. (mm) Average Daily App. (mm/d) Average Market Yield (kg/ha) Average Irrigation Water Use Efficiency (kg/m3) Treatment Water Savings Compared to I5 (%) I2 10% 343530.8824,110 4079 I3 12% 3431382.329,080 2245 Spring 2005 I4 12% 3431312.227,480 2248 I1 8% 1491562.617,100 1153 Spring 2006 I4 12% 1491692.814,200 449 I1 8% 1322443.243,400 1844 Fall 2006 I2 10% 1322132.845,500 2138 I1 8% 1241712.329,700 1744 Spring 2007 I2 10% 1241902.527,500 1538

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57 CHAPTER 3 EVAPOTRANSPIRATION AND CROP COEFFI CIENTS FOR GREEN BELL PEPPERS IN FLORIDA Introduction As the dem and for fresh fruits and vegetables rises, so does the need to conserve the limited state water supply. Irrigat ed agriculture is one of th e main industries with a high potential for large water savings. Row crops, particularly tomato es and peppers, are two of the mostly widely grown cash crops. Green bell peppers ( capsicum annuum L.) grow well throughout the state and thrive in the sandy soil. They are typi cally planted on raised beds covered with plastic mulch to help maintain wate r and nutrient levels in the rooting zone. The raised beds are most often drip irrigated to deliver water dire ctly to the root zone; thereby, reducing losses to evaporation and percolation. Proper irrigation scheduling and management is important when growing bell peppers, as they are su sceptible to water stress. It is important to maintain a constant supply of available water to prevent stress that can re sult in yield reduction. Two of the most critical stages in of bell pe pper growth occur in the very beginning, when transplants are developing stable and efficient root systems to support future growth, and during flower and fruit set when even small amounts of water stress can signif icantly reduce yields. Over irrigation can also damage plants. If the soil in the root zone become s saturated, the lack of oxygen can damage the uptake functioning of roots re ducing the transport of nutrients and water. Excessively applied water can also cause the leaching of valuable nutrients from the soil profile which also can lead to yield reductions. Effective irrigation scheduling requires knowledge of the crop water demand, ETc during the primary growth stages. This can be calculated by multiplying the reference evapotranspiration, ETo, by a specific crop coefficient, Kc. Many Kc values have been published for various crops during the three main growth stages. For bell peppers, Allen et al. (1998)

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58 recommends general values of Kc ini = 0.6, Kc mid = 1.06, and Kc late = 0.9., with Kc int referring to the initial part of the season, Kc mid for the middle of the season, and Kc late for the end. The Kc values are adjusted throughout the season ba sed upon the growth stage of the crop. Kc int is low when plants are small and require less water for transpiration. Kc mid is the highest Kc value to account for the increased water demands duri ng fruit and vegetation development. Kc late is slightly lower than Kc mid to account for the decreasing wate r demands as the plant reaches maturity. Since many factors influence Kc, including location, length of growth stage, and management practices, Allen et al. recommends the development and adjustment of Kc based on local field conditions. In the past, research has been done on drip irrigated tomatoes grown on plastic mulched beds (Amayreh and Al-Amed, 2005; Hanson and May, 2006), but few studies exist for bell peppers. Amayreh and Al-Amed (2005) reported crop coefficients of Kc mid = 0.82 and Kc late = 0.76, much lower than the FAO recommended valu es for the Jordan Valley, which they attributed to the plastic mulch and drip irri gation. Fernandez et al (2000) researched Kc values for peppers grown under greenhous e conditions. The reported Kc mid value of 1.4 was higher than previously suggested Kc mid values for bell peppers due to the modified indoor growing conditions of the greenhouse that increased net ra diation. Jabar et al. (2007) investigated Kc values of seepage irrigated, Florida grown bell peppers. They also reported higher Kc values, with Kc int = 0.71, Kc mid = 1.61, and Kc late = 1.1, which they attribut ed to the wetter growing conditions caused by the seepage irrigation system. In order to estimate Kc, the actual crop water demand, ETc, must be estimated first. This can be done using a soil water bala nce approach that reflects the water inputs and outputs of the system. Drainage is a difficult component to m easure in the soil water balance. A common way

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59 to quantify this water loss is by installing lysi meters under the irrigated area of the field. Two types of lysimeters commonly used in research are weighing and drainage. Weighing lysimeters can be used to measure ETc with a mass balance approach, and are typically used when small time steps (hourly or daily) are requi red. Drainage lysimeters measure ETc with a volumetric water balance approach, and can accurately quan tify drainage on a weekly or monthly basis (Shukla et al., 2006). Any excessively applied water drains from the profile by gravity and collects until it is pumped out. Th e volume of the colle cted leachate can then be converted to a depth and used as an output in the soil water balance equation. By knowing the actual crop water demand, accurate crop coefficients, Kc, which account for differences in the local microclimate and growing practices, can be determined. The objective of this study was to collect, measure, and analyze the soil water balance parameters of the raised bed system w ith the purpose of estimating crop ET and Kc values for green bell pepper. Methods and Materials This research investigated the crop w ater us e of soil moisture sensor (SMS) based, drip irrigated bell peppers grown on plastic mulch during the growing seasons of spring 2005, spring 2006, fall 2006, and spring 2007. The experiment was repeated over four different growing seasons to minimize the effects of variable climate and field cond itions. The study took place in Marion County, Florida at the Univ ersity of Florida Plant Science Research and Education Unit. Soils Characteristics Each of the four trials was located at the same field site. The soil for this site was classified as Candler sand a nd Tavares sand containing 97% sand-sized particles (Buster 1979). Field capacity was estimated to be in the ra nge of 0.10-0.12 v/v in the upper 0-30 cm (Icerman, 2007). The soil is very permeable, with a lo w water holding capacity, making excessively

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60 applied water and nutrients highly susceptible to drainage and leaching (Simonne and Hochmuth, 2004). Paramasivam et al. (2000) estimated the field capacity and permanent wilting point (PWP) of Candler and Tava res sand as 0.1 and 0.025 cm3/cm3, respectively. This amounts to 0.075 cm3/cm3 of available water (AW) in the soil profile. Experimental Design and Field Layout In preparation for this study, drainage lysim ete rs were installed under selected treatments on March 21, 2005, prior to bed formation (Zotar elli et al., 2007). At the start of each experiment the field was rototill ed, beds were formed, and immediately fumigated (80% methyl bromide, 20% chloropicrin) and covered with bl ack plastic mulch. Drip irrigation tape was simultaneously installed with the plastic mulch. Two drip lines, one for irrigation and one for fertigation, were installed in the center of each plot on the soil surface below the plastic mulch. Approximately 45 day old bell pepper plants (Brigadier) were tran splanted on April 5, 2005, April 10, 2006, September 11, 2006, and April 12, 2007 into raised plastic mulched beds, 15 m long and spaced 1.8 m apart, center to center. The transplants were spaced 0.3 m apart and planted in staggered dual rows. The treatments were laid out in a randomized complete block design with four replicates. Each experiment had a factorial design of five irrigation treatments (I1, I2, I3, I4 and I5) and three nitrogen treatments (N1, N2 and N3). F our of the irrigation tr eatments (I1-I4) were scheduled based upon soil moisture, while the other treatment (I5) was a time based treatment intended to simulate grower practices. The fi ve irrigation treatments and three fertigation treatments were applied across all four blocks via eight separate flow mete rs installed off of the main irrigation line. The fertigation levels were based on IFAS recommendations for bell peppers, with N2 being 100% of the recommended rate (208 kg/ha), N1 as 80% of N2 166 kg/ha), and N3 as 150% of N2 (312 kg/ha). Irrigation and fertigation was applied via drip tape

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61 (Turbulent Twin Wall, 0.20 m em itter spacing, 0.25 mm thickness, and 0.7 L/hr at 69 kPa (Chapin Watermatics, NY). Irrigation and Fertigation Control and Data Collection The SMS irrigation treatm ents allowed or bypassed programmed irrigation events based on readings taken by soil moisture sensors. Two di fferent soil moisture sensors were used during the four field trials. In spring 2006, SMS treat ment, I1, used a diel ectric capacitance probe (ECH2O, Decagon Devices Inc., Pullman, WA) coupled with a quantified irrigation controller (QIC) developed by the Agricultural and Biologi cal Engineering Department ( Munoz-Carpena et al., 2008). The rest of the SMS treatments us ed a Digital TDT Moisture Sensor paired with either an RS500 or CS3500 irrigation timer, all manufactured by Acclima, Inc. (Meridian, ID). Each season utilized four sensors, one for each SMS treatment, which were installed in one replicate located in the south end of the field a nd controlled irrigation for the entire field. The Acclima sensors were buried in the plot at a 30 angle to measure the t op 0.15 m of the rooting zone. The ECH2O probe was installed vertically into th e plot to measure the top 0.2 m of the rooting zone. The QIC and Acclima RS500 irrigation controllers were wired to an irrigation timer (ESP12LX Irrigation Controller, Rainbi rd Corporation, Azuga, CA). The timer was programmed to allow five irrigation events throughout the day to apply a potentia l irrigation depth of approximately 5 mm/d. Each irrigation window was 24 minutes long, the required time to apply 1 mm of water, and programmed to begin at 8:00am, 10:00am, 12: 00pm, 2:00pm, and 4:00pm for spring 2005, spring 2006, and fall 2006, and 10:00am, 12:00pm, 2:00pm, 4:00pm and 6:00pm for spring 2007. Although the sensors were cons tantly monitoring the soil water content, irrigation was initiated only duri ng these scheduled windows. At th e onset of a scheduled event, the SMS controller queried the soil moisture sensor to determine the soil moisture content of the

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62 soil. If the reading was lower than the threshol d setting of the controlle r, irrigation would begin and run for 24 minutes. If the sensor reading was higher than the controller threshold setting, the event was bypassed. The QIC treatment functioned slightly different. Wh ile it too was only able to irrigate during the scheduled windows, instead of relying only on the initial soil moisture reading at the onset of the event to determine whether or not to ir rigate, this controller queried the sensor every minute during the window allo wing irrigation to start and stop based on the sensor readings. The Acclima RS3500 irriga tion controller represented an on demand irrigation schedule, and allowed irrigation events to occur at any time the sensor reading fell below the lower bound of set threshold range. The irrigation event ended when the sensor indicated the soil moisture content was at or above th e upper bound of the setting. The control treatment represented a time base d irrigation schedule intended to represent a grower schedule. This treatment irrigated once a day, regardless of soil water conditions, for 2 consecutive hours (5 mm/day) in the morning. Table 3 outlines the irrigation treatments and soil moisture threshold settings implemented for each experiment. Water applications from irrigation and fertig ation events were manually recorded weekly from positive displacement flowmeters (V100 1.6 cm diameter bore with pulse output, AMCO WaterMetering Systems Inc., Ocala, FL). In addition to manual readings, the flowmeters contained transducers that signaled a switch cl osure every 18.9 L. The switch closures were recorded by data loggers (HOB O event logger, Onset Computer Corp. Inc., Bourne, MA) and continually logged water and fertigation event times, which were downloaded once a week. These data were used to determine if and when irrigation events occurred or were skipped. Soil Moisture Monitoring and Drainage Collection Soil m oisture content was monitored in each experiment by time domain reflectometry (TDR) probes (CS-615, Campbell Scientific, Inc. L ogan, Utah) buried at a 30 angle to measure

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63 the upper 0.15 m of the rooting zone The probes were installed in each irrigation treatment plot across all replicates. All of the TDR probes were connected to a data logger (Model CR-10, Campbell Scientific, Logan, Inc., UT) with a relay multiplexer (Model AM416, Campbell Scientific, Inc., Logan, UT). The data was dow nloaded weekly and analyzed to provide hourly soil moisture readings (VWC). Drainage lysimeters were installe d under the raised beds prior to the start of the trials with the purpose of capturing and quantifying the amount of water percolated below the effective rooting zone of the crop. Detail s of the lysimeter dimensions and burial depth can be seen in Figure 3. The lysimeters were constructed by cross-sectioning 208 L polyethylene drums, and had a capture area of 1.52 m2 (Zotarelli et al., 2007). They were buried 0.75 m below the surface of bed. Water drained into the lysimeters by gravity and was pumped out weekly into 20 L bottles using two vacuum pumps. The bottles we re weighed to determine the leachate volume, mL, which was then used to calculate a drainage depth, mm. For the spring 2005 and spring 2006 seasons, leachate was collected from treat ments I2, I3, and I5. In fall 2006 and spring 2007, the I4 treatment was also included. Dye Injection To further investigate the m ovement of i rrigation water under the plastic mulched bed, soluble blue dye was injected into the main irriga tion lines. Transverse se ctions of the bed were dug to observe the wetting front over 7 days (7682 DAT). Measurements of the wetting front, length, width, and depth, were taken after irrigati on applications on days 1, 3 and 7. Weather Data Collection Weather data was collected during the four growing seasons from a weather station located approximately 500 m from the experiment site. The downloaded meteorological data included relative humidity, temperature, wind spee d, and solar radiation which were used to

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64 calculate daily and weekly grass reference evapotranspiration (ETo) using the FAO PenmanMonteith method (Allen et al.,1998): )34.01( )( 273 900 )(408.02 2u eeu T GR ETas n o (3) where ETo reference evapotranspiration (mm/d), Rn net radiation at the crop surface (MJ/mm/d) G soil heat flux density (MJ/m2/d) T air temperature at 2 m height (C), u2 wind speed at 2 m height (m/s), es saturation vapour pressure (kPa), ea actual vapor pressure (kPa), es-ea saturation vapour pres sure deficit (kPa), slope vapour pressure curve (kPa/C), psychrometric constant (kPa/C), Crop ETc is calculated by multiplying grass reference ETo by a theoretical or field estimated crop coefficient, Kc. Kc values According to Allen et al. (1998), crop coefficients can account for specific crop characteristics, variations in climate, and modi fied management practices to provide an accurate representation of crop water demand, ETc. Although recommended Kc values exist for a wide variety of crops and regions throughout the country, the estimation of Kc values should reflect the local microclimate and growing practices. To investigate differences between Kc values, three different published Kc values were compared to a field estimated Kc. The published values used in the analysis are given in Table 3. The first Kc value, KcIFAS, was taken from the Vegetabl e Production Guide for Florida (Maynard and Olsen, 2001). The second value, KcFAO, was based on recommendations given in FAO Irrigation and Drainage Paper No. 56 (Allen et. al. 1998) for crops grown on plastic mulch.

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65 KcFAO was calculated by reducing KcIFAS by 30% to account for the la rge decrease (50-80%) in evaporation from the soil surface due to the plastic mulch covered beds (Allen et al. 1998). Although the plastic mulch cau ses a slight increase in plant tr anspiration, a 30% reduction in Kc is suggested by Allen et al. ( 1998) to compensate for the evap orative deficit on frequently irrigated plastic mulch covered beds. The third value, KcSHUKLA, was taken from research conducted on seepage irrigated bell peppers in southwest Florida (Jabar et al., 2007). The values are high due to the wet growing conditi ons caused by the seepage irrigation. The Kc values vary during the major growth stages of the crop. Kcint is used during growth stages 1 and all or part of growth stage 2. Th e pepper transplants are sm all during this stage and do not have large water demands yet. The main function of the transplant during this phase is to establish an extensive and efficient root system to support plant growth. Kcint is low during this phase to reflect the low water demand of the crop. Kcmid is used for part of growth stage 2, and all of growth stage 3. This is the highest Kc value during the life of a pepper plant, and reflects the increased crop water demand to support optimal reproductive and vegetative growth. Flower and fruit set are the most important functions during this growth stage, and even small levels of water stress can greatly reduce the future yield of the plant. Values for Kclate are slightly lower than Kcmid, indicating a small reduction in water dema nd, which corresponds to fruit maturation and harvest during growth stage 4. Crop coefficients can be estimated using field m easured parameters to measure the actual crop water demand, ETc. This study used drainage lysimeters to capture drainage under the raised beds. This, along with known irrigation applications, can be used to estimate the actual water demand of the crop. Field estimated Kc can be calculated from the ratio of estimated crop ETc and reference crop ETo.

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66 Theoretical ETc The crop water demand, ETc was estimated two different ways. The first method calculated the theoretical ETc based on the relationship between grass reference ETo, and a crop coefficient, Kc: ETc = ETo x Kc (3) where ETo is the reference ET in mm as cal culated in Equation 3, and Kc is the bell pepper crop coefficient. Field Estimated ETc ETc was also estimated using field measured parameters in a soil water balance equation which accounts for all water inputs a nd outputs that pass through the system: ETc = I + P S D R (3) where ETc is the actual crop water demand in mm, I is the irrigation depth a pplied to the entire field in mm, P is precipitation cont ribution to the root zone in mm, S is the change in soil water storage from the last time step in mm, D is the collected drainage depth in mm, and R is runoff in mm. For this project several assumptions were made based on the soil water interactions specific to the field site. Precipitation, P, is assumed to zero due to the plastic mulched beds that keeps most rainfall events from greatly impacting the soil water balance. This can be seen in Figure 3and Figure 3. There were only nine events over the four growing s easons, four in spring 2005, that were large enough (over 15 mm) to in crease VWC by an average of 4.7%. However, water from these events was considered negligib le to the weekly soil water balance. More on this topic can be found in Chapter 4. The change in soil moisture content, S, although known to undergo frequent fluctuations throughout the day in relation to irrigation events, is also assumed to be zero, since the water is easily drained from the sandy soil profile resulting in

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67 negligible changes over weekly tim e steps (Figure 3). During week s when there is a change in weekly water storage, the change is very sma ll, for example 0.1 VWC in the beginning of the week and 0.12 VWC at the end of the week. With field capacity and permanent wilting point estimated as 0.1 and 0.025 v/v, respectively, the available water in the soil profile is approximately 0.075 VWC (Paramasivam et al., 2000) This small amount of water is the result of the low water holding capaci ty of sandy soils, and any chan ges in water storage can be considered negligible in the overall w eekly soil water balance calculation. And lastly, runoff, R, is negligible due to fl at field conditions and application of water by drip irrigation. Equation 3 can then be simplified as follows: ETc = I D (3) where the only significant factor s are irrigation depth, I, in mm and drainage, D, in mm. Drainage depth, D, used to estimate ETc in Equation 3, was calculated on a weekly basis from the volume collected from the drainage lysimeters. However, for sufficiently watered SMS treatments, drainage, D, should be negligible which would simply Equation 3 even further by assuming that for properly f unctioning, well watered SMS treatments: ETc = I (3) As previously mentioned, this estimated ETc can then be used to obtain the actual field estimated crop coefficient, Kc as: o c cET ET K (3) where ETc is the estimated crop water demand in mm from Equation 3, and ETo is grass reference ET calculated with weather parameters using Equation 3.

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68 Results and Discussion Climate Conditions and ETo For spring 2005, cumulative rainfall totaled nearly 343 mm (Figure 3) which was much higher than the average rainfall of 253 mm fo r this region during this time period (FAWN, 2007). This rainfall amount was excepti onally high and exceeded the season total ETo of 248 mm. The high rainfall may have contributed to a high incidence of disease that spread through the field approximately midway (40 DAT) thr ough the growing season. The spring 2006 season experienced much less rainfa ll than the previous with a total of 149 mm, while ETo totaled 245 mm (Figure 3). The relatively drier field cond itions reduced the spread of disease, although bacterial spot was present at the end of the season. Th e fall 2006 growing season had a cumulative rainfall and ETo of 132 and 160 mm, respectively (F igure 3) The low incidence of rainfall and cooler fall temperat ures contributed to a very low occurrence of plant disease. ETo was much lower, nearly 50%, compared to the sp ring seasons due to the decrease in day length, solar radiation, and temperature. Cumulativ e rainfall for spring 2007 totaled 124 mm, while ETo totaled 273 mm as seen in Figure 3. Estimating Drainage Since drainage lysimeters were not installe d under all irrigation tr eatments, drainage was calculated using Equation 3 and the Kc values published in the Vegetable Production Guide for Florida (Maynard and Olsen, 2001), KcIFAS, to estimate ETc. Figures 3 through 3 show calculated dr ainage depths comp ared to measured drainage depths along with cumulative irrigation. Overall, the estimated drainage depths were much higher than measured depths when larg e amounts of irrigation were applied. This difference may be attributed to ly ismeter collection or inaccurate KcIFAS values. The drainage lysimeters seem incapable of capturing high volumes of leachate, as all weekly drainage depths

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69 collected from the four seasons were less than 10. 3 mm. This may be due to the small lysimeter capture area, 1.27 m2, relative to the irrigated area under the raised bed, 10.41 m2. This area may not be large enough to thoroughly coll ect drainage if water traveled laterally out of the capture zone. A dye experiment was conducted after th e last harvest during the spring 2006 season to identify movement of irrigation water through the soil profile. Figure 37 illustrates the wetted front of treatment I5 after day 7 (82 DAT) of the dye experiment. The figure shows irrigation water percolating latera lly through the profile to a maximu m width of 56 cm (Figure 3), a large enough range to be captured by the 55 cm wi de lysimeter. The problem may be attributed to the actual burial placement of the lysimeter in relation to the planted bed. Since the drainage lysimeters were installed prior to the formation of the beds, there is a possibility that the rows were not centered exactly over the lysimeters, which would decrease the capture area. The difference between calculated and measured drai nage may also be attr ibuted to the reported KcIFAS values used to calculate drainage for th is comparison. The values may be too low, especially during growth stages 1 and 2 when th e transplants were established with a time based irrigation schedule. The low KcIFAS value, 0.2, during this time drastically reduced ETc, which caused calculated drainage to be much higher th an the measured drainage across all treatments and seasons. The measured drainage values were similar to the calculated values only at very low depths. Most of these low drainage volumes were collected from SMS treatments with low irrigation applications during growth stage 3 when ETc values increased due to an increase in KcIFAS. Although the exact volume totals collected by the lysimeters did not match the calculated drainage, the lysimeter drainage data that show increased draina ge with increased irrigation. More information on these trends can be found in Chapter 2.

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70 Estimating ETc Estimated field ETc can be approximated by analyzing th e irrigation applications of the functioning SMS treatments. These treatments applied limited amounts of water that greatly reduced or eliminated drainage to supply just enough water to support the demands of the crop, or ETc. So for a properly functioning SMS treatment, ETc can be approximated by the amount of irrigation applied to the crop after treatment initiation. The functioning treatments are summarized in Table 3 along w ith treatment ir rigation and ETc totals. Figures 3 through 3 illustrate the average daily soil moisture cont ent, as measured by TDR probes, for the seven treatments. The field capacity shown on the gr aphs was approximated based on the average soil moisture content of the time ba sed irrigation treatment, I5, 24 hour s after an irrigation event. Although measured to be 10-12% in previous fi eld studies (Icerman, 2007), field capacity can vary depending on soil and field conditions. Due to this variation, field capacity was approximated based on the treatment average of the entire field. On average, the TDR probes recorded a 0.042 VWC increase in soil moisture during the 2 hour irri gation events, reaching maximum VWC at the end of the event, followed immediately by a rapid decrease until the soil reached a relatively steady moisture state. This steady state was usually reached within 24 hours of the onset of the irrigation event, and is assume d to approximate the field capacity of the raised bed. Treatment I5 in Figure 3 illustrates this assumption and shows the majority of available soil water was drained during th e 24 hour period following the sche duled irrigation event. The graph shows a missed irrigation event, resulti ng in a 48 hour period between events, during the beginning of the growing season (19 DAT) when plant roots were sti ll underdeveloped and therefore not able to uptake a significant amount of water from the soil. The change in soil moisture between the missed event (May 1-Ma y 2) is very small, only 0.008 VWC, which indicates that the soil had reached approximate field capacity within 24 hours after the irrigation

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71 event on April 30. All of the functioning tr eatments in Figures 3 and 3 maintained soil moisture content near the approximated field cap acity. Over irrigation did not appear to occur since there were no significant spikes in SMC duri ng irrigation events, unlike those observed in the time based I5 treatment as shown in Chapter 4 in Figure 4. This indicates sufficient water was supplied to support plant demands, ETc, without excess losses to drainage. Estimating Kc Once ETc was estimated by using SMS treatment irrigation totals, field estimated Kc values were obtained by rearranging Equation 3 to get: o c cET ET K or o cET I K (7) where ETc is the field estimated crop demand in mm, and ETo is grass reference ET calculated from Equation 3, and I is the irrigation total after treatment initiation Table 3 shows Kc values developed for each of the successful SMS treatments. The I4 (12%) SMS treatment in the spring 2005 season produced the lowest values which were likely the result of lowered crop water demand caused by high precipitation (342 mm). Kc values were calculated by averaging treatment values across each growth stage. It should be noted that Kc int was not calculated based on the full four weeks of the initial growth stage due to the transplant establishment phase prior to SMS treatment initiation. Kc int is was not calculated for tr eatments I4 (12-14%) in spring 2006 and I1 (8%) in spring 2007 because they were not fully initiated until growth stage 2. The averaged field estimated Kc values are shown in Table 3 and Figure 3 along with two reference crop coeffici ents given for bell peppers, Kc IFAS and KcFAO and values published by Jabar et al (2007). Each give th ree values depending on the growth stage of the crop. As mentioned earlier, Kc IFAS is recommended by the Vegetable Production Guide for Florida and KcFAO is based on the KcIFAS values that have been adju sted according to guidelines

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72 set out by Allen et al (1998) in FAO Pa per No. 56. This adjustment reduced KcIFAS by 30% to account for the lower evaporative demands of the plastic mulch covered beds. Figure 3 shows the Kc estimates based on treatment i rrigation totals along with KcIFAS, KcFAO, and KcSHUKLA for each season as well as an overall three season average. The low irrigation volumes applied during spring 2005 resulted in lower estimated Kc values. The spring 2006 and spring 2007 seasons were very close to KcIFAS for growth stage 3. Overall, the average Kc values over the three seasons were close to those of KcIFAS (Figure 3) as well as values reported for drip irrigated tomatoes. Kc mid, 0.93, was 12% higher than Kc mid, 0.82, reported by Amayreh and AlAbed (2005) for drip irrigated tomatoes in the Jordan Valley, while the estimation of Kc late was slightly lower, 0.71, than Kc late reported for tomatoes, 0.76. KcSHUKLA (Jabar et al., 2007) were estimated based on bell peppers grown under seepag e irrigation in southwes t Florida, and were the highest values in this comparison (Figure 3 4). This was likely the result of the wet field conditions caused by seepage irrigation (J abar et al., 2007). The values of KcFAO, which factored in a 30% reduction for plastic mulched beds unde r high frequency irrigatio n schedules, are most likely too low. Further research should be c onducted to investigate the effects of Florida vegetable crops grown in raised plastic mulched beds on ETc. Also, Kc int values could not be accurately estimated since the transplants were esta blished during most of this phase with a time based schedule. The recommended Kc values, KcIFAS and KcFAO for this stage, however, are very low ranging from 0.1-0.3. Further research shou ld investigate row crop growth on raised beds using these recommended values in growth stages 1 and 2. Conclusions This project studied the effect s of SMS based irrigation sche duling on drip irrigated bell peppers for four seasons. Various ways to estimate crop water dema nd were investigated including the calculation of theoretical values and a soil water balance approach. A soil water

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73 balance was created using measured and estimate d field parameters. Since the SMS treatments were initiated to maintain mo isture content around field cap acity, keeping just enough water available for plant uptake, it was assumed that the average irrigation depth applied by the SMS treatments was equal to actual ETc for functioning treatments. Soil moisture data was analyzed for each treatment and compared to the averag e seasonal field capacity to confirm that the treatments maintained soil moisture content within an acceptable range. Drainage, both calculated and measured, was also very low afte r these SMS treatments were initiated. Crop coefficients were calculated for bell peppers gr own on plastic mulch covered beds and compared to existing Kc values recommended for the location and ma nagement practices of the project. The field estimated Kc values fell in between the range of recommended values, KcIFAS and KcFAO, for the major growth and development stage, but are much lower than Kc values published by Jabar et al, 2007 for seepage irrigated bell pepp ers. Future research should investigate the lower limits of crop water demand to establish an accurate estimation of ETc for drip irrigated bell peppers. Also, because Kc int could not be accurately estimated since the plants were uniformly irrigated for establishment during the majority of this growth phase, further research should include the effects of various Kc values on plant growth and development during the first and second growth stages. Research should also be conducted to investigate the accuracy of drainage lysimeters buried beneath drip irrigated, plastic mulched, raised beds.

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74 Table 3. Irrigation treatments, threshold se ttings (VWC), and programmed irrigation run times. Treatment Description VWC threshold setting (m3/m3) Irrigation window Spring Pepper 2005 I1 I2 I3 I4 I5 Spring Pepper 2006 I1 I2 I3 I4 I5 Fall Pepper 2006 I1 I2 I3 I4 I5 Spring Pepper 2007 I1 I2 I3 I4 I5 QIC Acclima RS500 Acclima RS500 Acclima CS3500 Timebased schedule Acclima RS500 Acclima RS500 Acclima RS500 Acclima CS3500 Timebased schedule Acclima RS500 Acclima RS500 Acclima RS500 Acclima RS500 twin drip lines Timebased schedule Acclima RS500 Acclima RS500 Acclima RS500 Acclima RS500 twin drip lines Timebased schedule 0.1 (500 mV) 0.1 0.12 0.12.14 n/a 0.08 0.1 0.12 0.12.14 n/a 0.08 0.1 0.12 0.1 n/a 0.08 0.1 0.12 0.1 n/a 24 min, 5 times/day 24 min, 5 times/day 24 min, 5 times/day Anytime 2 hours, 1 time/day 24 min, 5 times/day 24 min, 5 times/day 24 min, 5 times/day Anytime 2 hours, 1 time/day 24 min, 5 times/day 24 min, 5 times/day 24 min, 5 times/day 12 min, 5 times/day 2 hours, 1 time/day 24 min, 5 times/day 24 min, 5 times/day 24 min, 5 times/day 12 min, 5 times/day 2 hours, 1 time/day

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75 Figure 3. Details and dimensions of drai nage lysimeter burial beneath raised bed

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76 I5, time based 10/3 10/4 10/5 10/6 10/7 10/8 10/9 10/10 Date VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 Average SMC = .075 Fall 2006 Figure 3. Example of negligible change in soil moisture content during one week in the fall 2006 season. 02 04 06 08 0 Cumulative ETo and Rainfall (mm x 10) and Daily Rainfall (mm) 0 10 20 30 40 50 60 Temperature (C) 10 20 30 40 50 Cumulative Rainfall Daily Rainfall Average Air Temperature Cumulative ETo Spring 2005 Number of Days after Transplanting Figure 3. Minimum, maximum, and average temperatures during spring 2005 along with daily and cumulative rainfall and evapotranspiration, ETo.

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77 02 04 06 08 0 0 10 20 30 40 50 60 Temperature (C) 0 5 10 15 20 25 30 35 Cumulative Rainfall Daily Rainfall Average Air Temperature Cumulative Eto Cumulative ETo and Rainfall (mm x 10) and Daily Rainfall (mm)Spring 2006 Number of Days after Transplanting Figure 3. Minimum, maximum, and average temperatures during spring 2006 along with daily and cumulative rainfall and evapotranspiration, ETo. 02 04 06 08 0 0 10 20 30 40 50 60 Temperature (C) 0 10 20 30 40 50 Cumulative Rainfall Daily Rainfall Average Air Temperature Cumulative ETo Cumulative ETo and Rainfall (mm x 10) and Daily Rainfall (mm)Fall 2006 Number of Days after Transplanting Figure 3. Minimum, maximum, and average temperatures during fa ll 2006 along with daily and cumulative rainfall and evapotranspiration, ETo.

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78 02 04 06 08 0 0 10 20 30 40 50 60 Temperature (C) 0 10 20 30 40 50 Cumulative Rainfall Daily Rainfall Average Air Temperature Cumulative ETo Cumulative ETo and Rainfall (mm x 10) and Daily Rainfall (mm)Spring 2007 Number of Days after Transplanting Figure 3. Minimum, maximum, and average temperatures during spring 2007 along with daily and cumulative rainfall and evapotranspiration, ETo.

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79 Figure 3. The wetted front of the time based irrigation treatment I5 after day 7 of the dye injection test (82 DAT).

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80 Weekly Estimated Drainage (mm) 0 20 40 60 80 100 Cumulative Irrigation (mm) 0 100 200 300 400 500 Growth Stage23 4 1 I1, QIC 10% Weekly Estimated and Measured Drainage (mm) 0 20 40 60 80 100 Cumulative Irrigation (mm) 0 100 200 300 400 500 Growth Stage2 3 4 1 I2, 10% Acclima Weekly Estimated and Measured Drainage (mm) 0 20 40 60 80 100 Cumulative Irrigation (mm) 0 100 200 300 400 500 I3, 12% Acclima 23 4 1Growth Stage Weekly Estimated Drainage (mm) 0 20 40 60 80 100 Cumulative Irrigation (mm) 0 100 200 300 400 500 Growth Stage2 34 1 I4, 12-14% Acclima Number of Days after Transplanting 0102030405060708090 Weekly Estimated and Measured Drainage (mm) 0 20 40 60 80 100 Cumulative Irrigation (mm) 0 100 200 300 400 500 Growth Stage2 3 4 1 I5, time based Figure 3. Weekly estimated and measured drai nage along with cumula tive irrigation for all treatments during the spring 2005 season. Drai nage is shown as vertical bars with dark shaded bars representing calculated drainage and lighter bars depicting measured drainage. Drainage was not collected from treatments I1 and I4.

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81 Weekly Estimated Drainage (mm) 0 20 40 60 80 100 Cumulative Irrigation (mm) 0 100 200 300 400 500 Growth Stage23 4 1 I1, 8% Acclima Weekly Estimated and Measured Drainage (mm) 0 20 40 60 80 100 Cumulative Irrigation (mm) 0 100 200 300 400 500 Growth Stage23 4 1 I2, 10% Acclima Weekly Estimated and Measured Drainage (mm) 0 20 40 60 80 100 Cumulative Irrigation (mm) 0 100 200 300 400 500 Growth Stage23 4 1 I3, 12% Acclima Weekly Estimated Drainage, mm 0 20 40 60 80 100 120 Cumulative Irrigation (mm) 0 100 200 300 400 500 Growth Stage2 3 4 1 I4, 12-14% Acclima 0102030405060708090 Weekly Estimated and Measured Drainage (mm) 0 20 40 60 80 100 Cumulative Irrigation (mm) 0 100 200 300 400 500 Growth Stage23 4 1 I5, time basedNumber of Days after Transplanting Figure 3. Weekly estimated and measured drai nage along with cumula tive irrigation for all treatments during the spring 2006 season. Drai nage is shown as vertical bars with dark shaded bars representing calculated drainage and lighter bars depicting measured drainage. Drainage was not collected from treatments I1 and I4.

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82 Weekly Estimated Drainage (mm) 0 20 40 60 80 100 Cumulative Irrigation (mm) 0 100 200 300 400 500 Growth Stage23 4 1 I1, 8% Acclima Weekly Estimated and Measured Drainage (mm) 0 20 40 60 80 100 Cumulative Irrigation (mm) 0 100 200 300 400 500 Growth Stage23 4 1 I2, 10% Acclima Weekly Estimated and Measured Drainage (mm) 0 20 40 60 80 100 Cumulative Irrigation (mm) 0 100 200 300 400 500 Growth Stage23 4 1 I3, 12% Acclima Weekly Estimated and Measured Drainage (mm) 0 20 40 60 80 100 Cumulative Irrigation (mm) 0 100 200 300 400 500 Growth Stage23 4 1 I4, 10% twin drip, Acclima 0102030405060708090 Weekly Estimated and Measured Drainage (mm) 0 20 40 60 80 100 Cumulative Irrigation (mm) 0 100 200 300 400 500 Growth Stage2 3 4 1 I5, time basedNumber of Days after Transplanting Figure 3. Weekly estimated and measured drainage along with cumula tive irrigation for all treatments during the spring 2007 season. Drai nage is shown as vertical bars with dark shaded bars representing calculated drainage and lighter bars depicting measured drainage. Drainage was not collected from I1.

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83 Table 3. Summary of SMS tr eatments that approximate ETc over spring 2005, spring 2006, and spring 2007 growing seasons, alo ng with treatment irrigation and ETc (calculated with Kinitial=0.2, Kmid=1.0, Klate=0.85). Treatment Description Treatment Description Threshold Setting Total Treatment Application (mm) Total Treatment ETc (mm) I1, 8% spring 2006 Acclimabased 0.08 156 150 I4, 12-14% spring 2006 Acclimabased 0.12.14 169 150 I1, 8% spring 2007 Acclimabased 0.08 171 139 I5,time-basedDate 4/28 4/29 4/30 5/ 2 5/3 5/4 5/5 5/1 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 F.C. = .081 VWC = .086 VWC = .078 VWC = .087 soil moisture content irrigation event skipped event Figure 3. Volumetric water content measured at 15 cm for April 28 to May 4, 2006 (17 to 23 DAT). The horizontal line indicates the approximated field capacity.

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84 I1, 8% Acclima Average Daily VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 10 20 30 40 50 60 2 34Growth Stage F.C.= 0.082 I4, 12-14% Acclima 24283236 44485256 6468727640 60 80 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 10 20 30 40 50 60 Average Daily VWC (v/v) 2 34Growth Stage F.C.= 0.082 Figure 3. Weekly rainfall and soil moisture content averages, measured by TDR probes across the entire field, for I1 and I4 af ter treatment initiation in spring 2006. Growth stages 2-4 are shown at the top of the graph. The red line represents the observed field capacity of the soil (0.082). I1, 8% Acclima Average Daily VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 10 20 30 40 50 60 2 34F.C. = .133 Growth Stage 60 Figure 3. Weekly rainfall and soil moisture content averages, measured by TDR probes across the entire field, for I1 after treatment initiati on in spring 2007. Growth stages 2-4 are shown at the top of the graph. The red line represents the observed field capacity of the soil (0.133).

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85 Table 3. Estimated Kc values for each treatment along with overall averages. Season Treatment Threshold Setting Kc intial* Kc mid Kc late Spring 2006 I1 8%0.70 0.96 0.59 Spring 2006 I4 12% --** 0.95 0.84 Spring 2007 I1 8% --** 0.88 0.69 Average --0.7 0.93 0.71 Data represents final week of initial growth stage when SMS treatments were initiated. **Insufficient data. Season Average KcDays after Transplanting 0102030405060708090 Crop Coefficient 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Spring 2006 0102030405060708090 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Spring 2007Days after Transplanting 0102030405060708090 Crop Coefficient 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Crop CoefficientDays after TransplantingKcIFAS KcFAO Kcfield estimated KcSHUKLA KcIFAS KcFAO Kcfield estimated KcSHUKLA KcIFAS KcFAO Kcfield estimated KcSHUKLA Figure 3. Estimated Kc values averaged across spring gr owing seasons along with published values, KcIFAS and KcFAO for bell peppers.

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86 Table 3. Recommended, adjusted and estimated Kc values for bell peppers. Kc Kc initial Kc mid Kc mid Growth stage 1 3 4 Kc IFAS 0.2 1.0 0.85 Kc FAO 0.14 0.7 0.6 KcSHUKLA 0.71 1.16 1.1 Kc estimate 0.7* 0.93 0.71 Data represents final week of initial growth stage when SMS treatments were initiated.

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87 CHAPTER 4 ANALYSIS OF SOIL MOISTURE SENSOR P ERFORMANCE ON AUTOMATED DRIP IRRIGATED PEPPERS GROWN IN SANDY SOIL Introduction Of the many crops that thrive in Florida, bell peppers (capsicum annuum) are among the most important. Florida is ranked 2nd in the nation in production, acreage, and crop value, and also produces nearly 100% of the winter crop for the nation (Mossler, 2004). To produce maximum fruit yields, bell pepper s, along with most other Florid a crops, must be supplemented with irrigation throughout the year. Agricultural operations in the state account for the largest consumer of freshwater, using 39% of th e groundwater supply and 62% of surface water (Marella, 2004). The Florida agri culture industry has gr eat potential to conser ve large amounts of water. Competition from foreign industry a nd an increasing demand for limited water has motivated growers to seek out ways of improving the efficiency of their farming operations. Improvements in irrigation scheduling can be an effective way for growers to maximize yields, while conserving water, fe rtilizer and energy costs (Martin et al., 1990). Irrigating with frequently scheduled irrigation ev ents is very effective in Florida where much of the soil is coarse sand with very low wate r holding capacities (Fares and Alva, 2000) Crops growing in this type of soil require frequent irrigation ev ents, sometimes several per day, to keep enough available water in the soil for plant needs. In response to li mited soil water holding capacity, growers often over irrigate their fields as insurance against water stress that can lead to a reduction in crop yield (Howell, 1996). This ty pe of blind irrigation scheduling practice can often be detrimental to the crop and the surround ing environment. The large pore spaces that exist in sandy soils are conducive to deep draina ge by any excessively applied water. Not only does this water percolate out of the root zone, making it unavailable for pl ant uptake, but it also

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88 carries nutrients along with it which may contri bute to groundwater contamination (Bouchard et al., 1992; Babiker et al., 2004; Sp alding et al., 2001). Improved irrigation scheduling involves an overall knowledge of climate conditions, crop growth demands, and soil conditions. Making irri gation decisions based upon these contributing factors is important to proper ir rigation management. There are several methods for determining soil water status ranging from the feel method and gravimetric sampling to neutron scattering and various types of soil moisture sensors (Ley et al., 1994). Soil moisture sensors offer growers a relatively inexpensive and hands off way monitor the soil wate r status of their fields. The soil moisture readings from the field can help growers decide when to manually turn on irrigation or sensors can be inte grated into an irrigation control system to automatically make irrigation decisions based upon this information. Soil moisture sensor (SMS) based irrigation has been shown to be an effective scheduling techni que in strawberries (Cla rk et al., 1996), citrus (Fares and Alva, 2000), tomatoes (Munoz-Carpena et al., 2005). Previous studies have shown an increase in irrigation water us e efficiency (IWUE) for SMS ba sed irrigation treatments, as compared to typical time based treatments, wh ile still producing acceptable marketable yields (Dukes et al., 2003, Zotarelli et al., 2007a). Research has been conducted on SMS ba sed irrigation using soil water potential measurements from tensiometers to control ir rigation events. Smajst rla and Locascio (1996) investigated the effects of SMS based irrigation using tensiomete rs to grow tomatoes in sandy soil on plastic mulched beds. They found significan t yield increases in se nsor based treatments with mid range threshold values (10 and 15 cb). Problems can exist; however, when tensiometers are installed in sandy soils since the performance of the device is highly dependent on establishing close contact with the surrounding soil, which can be challenging in coarse

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89 textured, sandy soils (Munoz-Car pena, 2004). Tensiometers can also have a delayed response time that could potentially be le thal to plants grown in sandy soils, where water can move rapidly. Tensiometers also requir e frequent attention, especially in hot weather, to maintain an unbroken water column (Munoz-Carpena, 2004). Time domain reflectometry (TDR) probes are an other kind of soil moisture sensor that has been extensively researched. Topp and Davi s (1985) field-tested the performance of uncalibrated TDR sensors and compared the readi ngs to gravimetric soil sample measurements. The study found TDR probes to be an accurate method to assess soil moisture content; however, the probes are expensive, making them an impr actical option for most growers. New soil moisture technology uses time domain transmission (TDT), similar to TDR in that it relies on a reflection travel time to determine the permissi vity of the soil. TDT probes are less expensive than TDR probes, making them more accessible to growers (Blonquist et al., 2005). Despite differences among the types of sensors, when integrated into an irrigation control system, the sensors all operate one of two wa ys: 1) bypass control and 2) on-demand control (Munoz-Carpena et al., 2008). A bypass control sy stem allows irrigation events to occur only during certain programmed times during the day. At the onset of a programmed event the controller queries the sensor for a soil moisture r eading. Depending on the result of this reading and its relation to the threshold soil moisture setting, the system will ei ther allow or bypass the irrigation event. The system irrigates for a programmed amount of time and does not allow irrigation until the next scheduled event. Bypass control differs from an on-demand controlled system which queries the probe continually thro ughout the day and allows irrigation any time the probe reads the soil moisture content to be below the programmed threshold range. The irrigation event lasts only until the probe recognizes the soil moisture content to be at or above

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90 the upper threshold range. The threshold soil mo isture is predetermined by the operator during the set up of the system. This setting should represent the minimum allowable soil moisture content before an irrigation event is initiated. Fo r example, if just before an irrigation event a sensor measures a soil moisture content of 9% by volume, and the system threshold setting is 8%, the controller will bypass the event. If the sensor had read volumetric water content less than 8%, the controller would have initiated the event. The objective of this research was to eval uate the performance of two different soil moisture sensor irrigation controllers set at vari ous threshold settings by analyzing the number of bypassed irrigation events, measured soil moisture content at event initia tion, and the average soil moisture content of the treatment throughout the season on drip irrigated green bell pepper. Materials and Methods This research investigated the performance of soil moisture sensors on drip irrigated bell peppers grown on plastic mulch during the grow ing seasons of spring 2005, spring 2006, fall 2006, and spring 2007. The experiment was repeat ed over four different growing seasons to minimize the affects of variable climate and field conditions. The study took place in Marion County, Florida at the Univers ity of Florida Plant Science Re search and Education Unit. Soils Characteristics Each of the four trials was located at the same field site. The soil for this site was classified as Candler sand a nd Tavares sand containing 97% sand-sized particles (Buster 1979). Field capacity was estimated to be in the range of 0.10-0.12 v/v in the upper 0-30 cm (Icerman, 2007). The soil was very permeable, with a lo w water holding capacity, making excessively applied water and nutrients highly susceptible to drainage and leaching (Simonne and Hochmuth, 2004). Paramasivam et al. (2000) estimated the field capacity and permanent wilting point

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91 (PWP) of Candler and Tava res sand as 0.1 and 0.025 cm3/cm3, respectively. This amounts to 0.075 cm3/cm3 of available water (AW) in the soil profile. Experimental Design and Field Layout At the start of each experiment the field was rototilled, beds were formed, and immediately fumigated (80% methyl bromide, 20% chloropicrin ) and covered with black plastic mulch. Drip irrigation tape was simultaneously installed with the plastic mulch. Two drip lines, one for irrigation and one for fertigation, were installed in the center of each plot on the soil surface below the plastic mulch. The fall 2006 and spring 2007 growing seasons implemented an irrigation treatment that used twin drip lines. In this case, the lines were installed at a distance of 0.15 m from the center fertigation line. The pepp er transplants of the cultivar Brigadier were transplanted on April 5, 2005, Ap ril 10, 2006, September 11, 2006, and April 12, 2007 in raised beds, 15 m long and spaced 1.8 m apart, center to center. The transplants were spaced 0.3 m apart and planted in staggered dual rows. The treatments were laid out in a randomized complete block design with four replicates. Each experiment had a factorial design of five irrigation treatments (I1, I2, I3, I4 and I5) and three nitrogen treatments (N1, N2 and N3). Four of the irrigation treatments (I1-I4) were scheduled based upon soil moisture, while the other treatment (I5) was a time based treatment intended to simulate grower practices. The five irrigation treatments and three fertigation treatments were applied across all four blocks via eight separate flow meters installed off of the main irrigation line. The fertigation levels were based upon IFAS recommendations for bell peppers, with N2 being 100% of the recommended rate (208 kg/ha), N1 as 80% of N2 166 kg/ha), and N3 as 150% of N2 (312 kg/ha). Irrigation and fertigation was applied via drip tape (Turbulent Twin Wall, 0.20 m emitter spacing, 0. 25 mm thickness, 0.7 L/hr at 69 kPa (Chapin Watermatics, NY).

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92 Irrigation and Fertigation Control and Data Collection The SMS irrigation treatments allowed progr ammed timed irrigation events based on readings taken by soil moisture sensors. Two di fferent soil moisture sensor controllers were used during the four field tria ls. In spring 2006, SMS treatment I1 (See Table 4), used a dielectric capacitance probe (ECH2O, Decagon Devices Inc., Pullman, WA) coupled with a quantified irrigation controller (QIC) developed by the Agricultu ral and Biological Engineering Department (Dukes and Munoz-Carpe na, 2005). The rest of the SMS treatments used a Digital TDT Moisture Sensor paired with either an RS500 or CS3500 irrigation timer, all manufactured by Acclima, Inc. (Meridian, ID). Each season had four sensors, one for each SMS treatment, which were installed in one replication located in the south end of the field and controlled irrigation for the entire field. The Acclima sens ors were buried in the plot at a 30 angle to measure the top 0.2 m of the production bed. The ECH2O probe was installed vertically into the plot to measure the top 0.15 m of the raised bed. The QIC and Acclima RS500 irrigation controllers were connected to an irrigation timer (ESP-12LX Irrigation Controller, Rainbird Co rporation, Azuga, CA). The timer was programmed with five irrigation windows each da y to apply a potential irrigation depth of approximately 5 mm/d. Each irrigation window wa s 24 minutes long, the re quired time to apply approximately 1 mm of water, and programmed to begin at 8:00am, 10: 00am, 12:00pm, 2:00pm, and 4:00pm for spring 2005, spring 2006, a nd fall 2006, and 10:00am, 12:00pm, 2:00pm, 4:00pm and 6:00pm for spring 2007. At the onset of a scheduled event, the irrigation controller queried the sensor to determine the soil moisture content of the soil. If the reading was lower than the threshold setting of the controller, irri gation would begin and run for 24 minutes. If the sensor reading was higher than the controller threshold setting, the event was bypassed. The Acclima CS3500 irrigation contro ller represented an on dema nd irrigation schedule, and

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93 allowed irrigation events to occur at any time the sensor reading fell below the lower bound of set threshold range. The irrigation event ended when the sensor indicated the soil moisture content was at or above the upper bound of the setting. The comparison treatment represented a tim e based irrigation schedule intended to represent grower practices. This treatment i rrigated once a day, rega rdless of soil water conditions, for 2 hours (5 mm/day) in the morning. Table 41 outlines the irrigation treatments and soil moisture threshold settings implemented for each experiment. Water applications from irrigation and fertigation events were manually recorded from positive displacement flowmeters (V100 1.6 cm diameter bore with pulse output, AMCO WaterMetering Systems Inc., Ocala, FL). In addition to manual readings, the flowmeters contained transducers that signaled a switch cl osure every 18.9 L. The switch closures were recorded by data loggers (HOB O event logger, Onset Computer Corp. Inc., Bourne, MA) and continually logged water and fertigation event ti mes, which were downloaded once a week. By knowing the time and duration of each event, the data was used to determine if and when irrigation events occurre d or were skipped. Soil Moisture Monitoring Soil moisture content was monitored in each experiment by time domain reflectometry (TDR) probes (CS-615, Campbell Scientific, Inc. L ogan, Utah) buried at a 30 angle to measure the upper 0.15 m of the rooting zone The probes were installed in each irrigation treatment plot across all replicates. For the spring 2007 season, four additional TDR probes were buried in each of the SMS treatment plots in an effort to further investigate the soil moisture content at which irrigation events were bypassed and initiated around individua l SMS control probes (Figure 4). These TDR probes were installed in a close proximity to the soil moisture sensor, with one probe buried opposite the Acclima sensor on the other side of th e center drip tape and

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94 the other three in similar locations to the Acclima relative to the plants and drip tape. All of the TDR probes were connected to a data logger (M odel CR-10, Campbell Scientific, Logan, Inc., UT) with a relay multiplexer (Model AM416, Campbe ll Scientific, Inc., Logan, UT). The data was downloaded weekly. Results and Discussion The performance of the SMS treatments wa s evaluated by comparing the cumulative amount of irrigation water, the number of bypa ssed irrigation events, and the average soil moisture content at which events were initiated. Climate Conditions For spring 2005, cumulative rainfall totaled nearly 343 mm (Figure 4) which is much higher than the average rainfall of 253 mm for this region during this time period. This exceptionally high amount of rainfall may have contributed to a noticeable high incidence of disease that spread through the field appr oximately midway (40 DAT) through the growing season. During spring 2006, cumulative rainfall totaled 149 mm (Figure 4). The relatively drier field conditions reduced the spread of disease, although bact erial spot was present at the end of the season. The fall 2006 growing season ha d a cumulative rainfall of 132 mm as seen in Figure 4. The low incidence of rainfall and cooler fall temperat ures contributed to a very low occurrence of disease. Temperatures began to fall at the end of the season, but the crop was not exposed to frost. The spring 2007 season had a cumulative rainfall total of 124 mm (Figure 4) and no reported incidence of disease. Irrigation Treatments and Water Savings Figures 4 through 4 and Tables 4 th rough 4 below illustrate cumulative irrigation water applied by each treatment and a water savings comparison between the SMS and time based treatments during the four growing seasons.

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95 In spring 2005, the irrigation treatment schedules were in itiated on April 28 (23 DAT). By the end of the season, the SMS treatments applied less water than the timebased grower treatment; however, the two different sensor types did not perform the same. The SMS treatments controlled by the Accl ima sensors, I2 (10%), I3 (1 2%), and I4 (12-14%) performed well. After treatments were initiated, I2 a pplied 53 mm (0.9 mm/d), I3 applied 138 mm (2.3 mm/d), and I4 applied 131 mm (2 .2 mm/d). The time based treat ment, I5, resulted in 253 mm (4.2 mm/d) as seen in Table 4. The I1 ( 10%) QIC treatment did not bypass many irrigation events, resulting in a cumulative applicati on 230 mm (3.8 mm/d) and only a 9% savings compared with I5. The controller was thought to be set too high and was adjusted during the season (58 DAT) from 550 mV (10% VWC) to 515 mV (8% VWC). The treatment, however, did not respond to this adjustment, and continued to initiate irrigation for most of the scheduled events (Figure 4). Several factors may have contributed to the malfunctioning of this treatment since sensor performance is influen ced by placement in the bed, proper installation, soil salinity, proximity to drip emitters, and soil characteristics. Treatment I1 resulted in a 13% water savings compared to I5 during the s econd growth stage (Table 4), which can be attributed to the temporary decrea se in I1 irrigation events caused by a sensor adjustment. I2, set at the lowest threshold (10% VWC), resulted in the largest water savings, 79% (Table 4). I3 (12%VWC) and I4 (12-14% VWC), set at simila r threshold settings, applied nearly the same amount of water and resulted in similar water reductions of 48 and 49%, respectively (Table 4 2), although they functioned differently. I3 was a bypass controlled treatment, while I4 was on demand". I2 showed relatively large savings (79% ) relative to I5 through out the three analyzed growth stages (Table 4), while I3 and I4 resulted in larger savings during growth stages 2 and

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96 3. The reason for lower savings of treatments I3 and I4 during growth stage 4, 27% and 14%, respectively, is unknown. In spring 2006, a programming error in the I4 irrigation controller dur ing the beginning of the season caused the treatment to over-irrigate (Figure 4), resu lting in the la rgest irrigation total of all treatments (348 mm). The problem was successfully adjusted (29 DAT) and I4 functioned properly for the durati on of the season. The treatmen t irrigated an average of 16.2 mm/d before the error was fixed and averaged 3. 4 mm/d after the adjustment was made. After this point, I4 resulted in a 45% water savings in the second growth stage and a 60% savings in the third growth stage (Table 4). I1 showed similar water savings to I4 during this period, while I2 and I3 resulted in much less savings, with the largest occurring in the third growth stage (Table 4). Treatments I2 and I3 malfunctioned for the majority of the season. Both treatments functioned well, with I2 bypassing more events than I3, until an unpredicted and unexplainable event caused I2 to irrigate for a 15 hour period (30 DAT). I2 was evaluated and adjusted on 35 DAT, and from this point on began bypassing similar to I3. By the end of the season, I2 applied 301 mm (4.9 mm/d) and I3 applied 287 mm (4.7 mm/d) resulting in a 9 and 13% water savings, respectively (Table 4). Th is problem may have resulted from the cross communication between sensor signals since the two treatment controllers shared a common irrigation timer. The miscommunication between the controller and sensor si gnals may have caused both controllers to receive signals from one of the burie d sensors. I1 and I4 were the only treatments to operate properly throughout th e season. I1 applied 156 mm (2.6 mm/d), 53% less water than I5, which applied 329 mm (5.4 mm/d). Treatments I1 and I4 showed th e highest water savings, 47% and 45%, respectively, during the third grow th stage which is the longest and most water demanding stage of the season.

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97 In the fall 2006 season, a wiring problem caused all of the SMS treatments to malfunction. Both I1 and I2, were wired to a single irrigation time clock, and I3 and I4, also wired to a shared irrigation time clock, were bypassing and irriga ting the same scheduled events and applying same irrigation amounts (Figure 4). The probl em was attributed to cross communication between the Acclima sensors, causing each of the irrigation controllers to receive signals from only one of the two wired sensors. Several ad justments were made, but the problem was not solved until each controller was wired to a sepa rate individual irrigation timer. Eventually, 58 DAT, the SMS treatments began to irrigate indepe ndently of each other (Figure 4). After this point, I2 began bypassing more events than I1. This was unexpected, since I2 was set to a higher setting of 10%, compared to I1 at 8%. This may be attributed more to the sensor placement and location in the plot rather than the actual sensor settings. In addition to this wiring problem, a programming error in the irriga tion controller caused I4 to over-irrigate from 49 DAT to 65 DAT. The implementation of twin drip lines on th is treatment required the adjustment of the irrigation window from 24 minutes to 12 minutes to compensate for the doubled flow rate. The timer, however, was mistakenly programmed to allow 24 minute irrigation windows which caused I4 to apply double the amount of intended irri gation water. By the end of the season, I3 and I4 applied the most water with 319 mm (4 .2 mm/d) and 327 mm (4.3 mm/d), respectively. Each of these treatments applied more water th an I5 which had 303 mm (4.0 mm/d). The lower water application by I5 was a re sult of 9 missed programmed events due to power outages and field maintenance. I1 applie d a total amount of 244 mm (3.2 mm/d), while I2 applied 213 mm (2.8 mm/d) as seen in Table 4. I1 and I2 showed water savings of 12 and 46%, respectively, during the third growth stage (Table 4).

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98 In spring 2007, each of the SMS treatmen ts were wired to an individual irrigation controller at the begi nning of the season to avoid past problems with sensor cross communication. This proved to be an effectiv e method when testing multiple sensors in one field. Problems did arise, however, with treatme nts I2 and I4, when bot h treatments failed to bypass irrigation events in the beginning of the s eason. The locations of both treatment sensors, I2 and I4, were assessed 30 DAT. I4 was reburied in the original location and I2 was moved to a different location in the plot. Af ter the probes were reburied, I4 c ontinued to irrigate frequently, while I2 began to bypass events as seen in Figure 4. The location of th e sensor in the bed was apparently the cause of problem with the I2 treatment since it functioned properly after it was moved. The problem with I4, however, was unkn own, since the placement of the sensor was evaluated and carefully reburied. Both of the treatments were set to the same soil moisture threshold level of 10%, but I4 irrigated with twin drip lines. The location of the sensor relative to the outside drip line and center fertigation line, although di rectly in between both, may have been a drier area as compared to other treatment s with centered drip lines. By the end of the season, I4 applied 277 mm (3.6 mm/d), nearly as much as I5 which applied 308 (4.1 mm/d), and only had a 10% water savings (Table 4). I1 and I2 applied similar amounts of water, with 171 mm (2.3 mm/d) and 190 mm (2.5 mm/ d), respectively, and resulted in the highest water savings during the third growth stage. I3 applied 261 mm (3.1 mm/d) during the season, and reduced irrigation water by 20% in the second growth stag e, yet applied 5 more mm of water compared to I5 during the third growth stage which re sulted in a 20% increase (Table 4). Soil moisture content Figures 42 through 422 illustrate soil moistu re content as measured by the TDR probes and the occurrence of scheduled irrigation events and rainfall during several periods throughout the growing season. Three weeks of data were se lected for each season to illustrate soil moisture

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99 conditions at the beginning (growth stage 2), middle (growth stage 3), and end (growth stage 4) of season. Although TDR probes were buried acro ss all replicates, data was analyzed based on readings taken from the same replicate in wh ich the soil moisture sensors were buried unless otherwise indicated. Tables 4 through 4 detail the seasonal tota ls of irrigation events, as well as the soil moisture content at which treatment s initiated the events. It should be noted that the values of soil moisture content used fo r comparison, readings from TDR probes and threshold settings for Acclima soil moisture sens ors, originate from two different sensor types each with its own level of accuracy. The unca librated Acclima soil moisture sensors were manufactured to measure soil moisture conten t within a level of 1% VWC accuracy (Acclima TDT Data Sheet, Acclima, Inc., Meridian, ID), while the TDR probes measure within a level of 2.5 VWC (Campbell Scientific CS616 and CS 625 Water Content Reflectometers Manual. Revised 8/06, Campbell Scientific, Inc., Logan, UT). Increases in soil moisture content can be seen in the graphs below following each irrigation event. The SMS treatments had a much different effect on the soil moisture content of the soil compared with the time-based treatment. For example, the SMS based treatments irrigated for short periods of time, only when the soil reached a programmed VWC threshold value; allowing the applied water to be held in the soil profile, making it available for plant uptake. The SMS treatments resulted in relatively small increases in soil moisture, and consequently decreased the volume of drainage. Drainage is further analyzed and discussed in Chapter 2. The time based treatment; however, irrigated for a longer time period, regardless of soil moisture conditions, and resulted in large increases in soil moisture. This spike in moisture content caused by irrigation was temporary and most of the excessively a pplied water was quickly drained from the soil profile as seen in Figure 4. On average, the TDR probes recorded a 0.042 VWC increase in

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100 soil moisture during the 2 hour time based irriga tion events, reaching a maximum at the end of the event, followed immediately by a rapid decrease until the soil reached a relatively steady moisture state. This steady state was usually reached within 24 hour s of the onset of the irrigation event, and is assumed to approximate the field capacity of the raised bed. Treatment I5 in Figure 410 illustrates this assumption and shows that the majority of available soil water was drained during the 24 hour period following the sc heduled irrigation event. The graph shows a missed irrigation event, resulti ng in a 48 hour period be tween events, during the beginning of the growing season (19 DAT) when plant roots were still underdeveloped and th erefore not able to uptake a significant amount of water from the so il. The change in soil moisture between the missed event on May 1 and the next event on May 2 is very small, only 0.008 VWC, which indicates that the soil had reached approximate field capacity within 24 hours after the irrigation event on April 30. Although measured to be 1012% in previous field studies (Icerman, 2007), field capacity can widely vary depending on soil and field conditions. Due to this variation, field capacity was approximated based on the average of the entire field. Figures 4, 4, 4, and 4 illustrate the approximated field capac ity for each replicate during the specified growing season. It is often assumed that rainfall events have l ittle or no effect on the soil moisture content of plastic mulch covered beds. During this study, however, there were five recorded rainfall events (two in spring 2006, two in fall 2006, a nd one in spring 2007) that lead to noticeable increases in soil moisture content (Figure 4). The spring 2005 season was not included in the rainfall analysis due to the de terioration of plastic mulch midw ay through the season that caused the plant bed to be exposed. The effective rainfall events all measured over 15 mm and resulted in an average VWC increase of 0.054. This increase in soil moisture was temporary, and

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101 immediately decreased at the end of the event. So although large rainfall events seem to temporarily influence VWC beneath the plastic mulched beds, the overall contribution to the crop water demand is negligible during the course of the season. The soil moisture based treatments performed well during the seasonal ra infall events by skippi ng scheduled irrigation events and not allowing irrigation again unt il soil moisture content decreased. In the spring 2005 season, the improper thres hold setting on I1 caused this treatment to bypass only 53 irrigation events (18%), while I2 set to a similar threshold setting of 10%, bypassed the most events with 261 (87%). I2 ir rigated very little compared to the other treatments. Substantial increases in soil moisture after the weekly fertig ation, with an average weekly increase of 0.111 VWC, and frequent rainfa ll events can be seen in treatment I2 (Figure 4), which may have reduced the need for irri gation. Although I2 bypassed far more irrigation events than I1, both treatments, set at 10%, ini tiated irrigation at a similar average VWC, 13.1% for I1 and 12.9% for I2. The difference in irri gation frequency may be attributed to the probe burial location in the plot. The I2 Acclima probe may have been buried close to a drip emitter which would maintain wetter soil conditions surr ounding the probe and cause frequently bypassed events. The I1 QIC probe may have been buried in a drier location, further from a drip emitter, which would have resulted in frequent irrigation events caused by the drier soil surrounding the probe. Differences between the soil moisture threshold setting and the measured VWC point at which irrigation is in itiated can be attributed to vari ations in sensor readings. The uncalibrated Acclima soil moisture sensors used in this project were manufactured to measure soil moisture content to a level of 1% VW C accuracy (Acclima TDT Sensor Data Sheet, Acclima, Inc., Meirdian, ID.), while the TDR probes measure within accuracy of 2.5% VWC

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102 (Campbell Scientific CS616 and CS625 Water Cont ent Reflectometers Manual. Revised 8/06, Campbell Scientific, Inc., Logan, UT.). I3 initiated irrigation at a higher VWC range of 14.5-20.6% and bypassed 162 events (54%), consistent with the high threshold set ting of 12% (Table 4). The I4 treatment was programmed to initiate irrigation any time the VWC reached 12%, and terminate the event at 14%. This treatment only irrigated for 57 events, about 1 event per day, and initiated irrigation at an average soil moisture content of 18.8% a nd ended when the soil reached 20.2% (Table 4 10). These values are higher than the threshol d settings of 12-14%, and are likely caused by differences between the actual soil moisture of the raised bed and TDR readings. Field capacity was estimated to be 14.7% across all plots (Figure 4), higher than the measured 10-12% range (Icerman, 2007), indicating wetter field cond itions. As seen in Figure 4, estimated field capacity ranged from 0.127 0.167. SMS treat ments with lower threshold settings, I1 and I2, initiated irrigation at average moisture cont ents below the estimated average field capacity, while the treatments with higher settings, I3 and I4, initiated irrigation at averages above this value. In spring 2006, I1 functioned as expected for the low threshold setting, by bypassing the most irrigation events (58%) and initiating irrigation at the lowest average VWC (10.5%) as seen in Table 4. An unexplainable and unpredicted irrigation event caused I1 to irrigate for over 15 hours and apply 49 mm of water. This resulted in an increas e in soil moisture of 0.059 VWC (Figure 4). Treatments I2 and I3 performed similarly dur ing the season due to wiring problems, resulting in a similar total of irrigati on events and irrigation in itiation range (Table 4 11). Both of the treatments bypassed approximately 30 irrigation events, a nd initiated the events at an average of 11.9%, which may indicate I3, set at 12%, as the controlling sensor signal

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103 during the signal. I4, set to irrigate with in 12-14% range, initiated irri gation at an average VWC of 9.9% and terminated the events when the soil reached 10.3%. Field capacity was estimated as 8.2% across all replicates (Fi gure 4), and all treatments, in cluding I1 set at 8%, initiated irrigation at average soil moisture contents a bove this value of 8.2%. Approximated field capacity ranged from 0.069 to 0.088 VWC over the four replicates as seen in Figure 4. During the fall 2006 growing season, problem s with the sensor wiring caused cross communication between sensor signa ls resulting in uniform irrigation applications among I1 and I2 treatments and I3 and I4 in the beginning of the season. The problem was solved when the sensors were wired to separate irrigation timers I1 and I2 were rewired on 30 DAT and began irrigating independently for the duration of the season. I1 went on to bypass 27% of the irrigation events at an average VWC of 9.1%, while I2 bypassed 40% at an average VWC of 11.6% (Table 4). I3 and I4 were rewired 38 DAT, and irrigated separately for a few weeks (DAT 34 to DAT 66), but eventually reestablished a similar schedule. The late establishment of the four treatments likely caused little differe nces among the treatment pairs as differences among irrigation applications can be harder to detect later in the s eason when the crop water demand increases. Water savings are most often s een in the early growth stages before water demands increase with the onset of flower set and fruit development. By the end of the season, I4, set at 10%, bypassed more events than I3, 66 fo r I4 as compared to 36 for I3 (Table 4). I4, however, applied the most amount of water, due to the programming error (49 DAT to 65 DAT) that caused I4 to apply double the amount of intended water for 15 days in the middle of the season. Average field capacity was estimate d to be 7.5% across the field, and all SMS treatments initiated irrigation at average mois ture contents above this value (Figures 4

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104 through 4). Approximated field capacity ra nged from 0.074 to 0.077 across the four replicates (Figure 4). In spring 2007, additional TDR probes were installed in the SMS treatment plots to more accurately monitor the so il moisture content of the area dire ctly surrounding the soil moisture sensor. For this season, the average soil moisture content for each SMS treatment was calculated by averaging the readings of these four addi tional probes. Figures 4 through 49 illustrate soil moisture content of the four TDR probes for each SMS treatment. Most of the probes performed similarly with the exception of the I1B4A probe s hown in Figure 4 and the I4B4D probe shown in Figures 4 through 4. The I1B4A was excluded from the I1 TDR average until the probe was reburied (42 DAT). Readings taken from the I4B4D probe were included in the I4 TDR average since the higher values were likely attributed to the probe position in the plot (Figure 4). From the beginning of the growing season, each irrigation controller was connected to a separate timer to avoid previously discusse d problems with sensor signaling. This, unfortunately, did not eliminate sensor perfor mance problems. I2 and I4 failed to bypass irrigation events in the beginning of the season, causing the treatments to irrigate at nearly every scheduled event. Each sensor was reburied on 30 DAT. After this adjustment, I2 began bypassing so many events that it ended the season with the same number of bypassed events as I1, which was set at the lower threshold of 8%. I2 did, however, initiat e irrigation at a higher VWC of 12.8% compared to 11.2% for I1 (Table 4). I4 continued to bypass very few events, 25 in all, after the adjustment. As discussed ear lier, this may have been caused by the location of the Acclima sensor in the plot in relation to the twin drip lines. The Acclima is buried near the center of the raised bed, approximately15 cm away from TDR D. Figures 4 through 4

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105 illustrate average VWC measured by the four individual probes in the I4 plots. The highest measurements are read from TDR D (avg. 17.9% VWC), followed by TDR B (avg. 11.8% VWC), both of which were located closest to the twin drip lin es. TDR A and TDR C, located closer to the center line, near the Acclima sens or, recorded lower readings of VWC, averaging 10.2 and 10.6%, respectively. The VWC, as measured by the TDR probes, indicate drier conditions near the Acclima sensor, causing the freque nt irrigation events. I2 and I4, both set at 10%, initiated irrigation at similar average moistu re contents of 12.8% and 12.2%, respectively. One of the TDR probes (I1A) surro unding the I1 treatment malfuncti oned in the beginning of the season, causing the probe to measure very high soil moisture contents (Figure 4). The location of the probe was evaluated and the probe was successfully reburied on May 23, 2007 (43 DAT). The readings from the I1A TDR probes were not included in the calculated average soil moisture content prior to 43 DAT. I3 had the highest threshold se tting, bypassed 67% of events, and initiated events at the highest VWC (13.4%). Field capacity was estimated as 13.3% across the field (Figure 4). All treatments initiated irrigation ne ar or under this soil moisture average as seen in Table 4. Approximated field capacity ranged from 0.106 to 0.162 VWC across the four replicates (Figure 4). Summary of Sensor Performance Over the course of the four growing seasons 16 SMS treatments were initiated and tested at threshold settings va rying from 8-12%, two of which represented on demand schedules with threshold ranges of 12-14%. Eight of the 16 im plemented treatments functioned properly and reduced irrigation water compared to the time based treatment, I5, by skipping scheduled events based on soil moisture readings. The other ei ght treatments malfunctione d due to significant programming, wiring, and/or insta llation problems. These treatments were not representative of typical sensor performance, therefore were not included in overall averages and comparisons.

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106 The eight successful treatments are detailed in Tables 4 and 4. Overall treatment performance for each threshold setting is shown in Tables 416 and 4. Overall, the functioning SMS treatments reduced irrigation applica tion totals from 2350% compared with the time based treatment, I5 (Table 4). Treatments with a 12% threshold setting resulted in the lowest water savings, 23% This was the highest threshold setting among the timer controlled treatments, and demanded wette r soil conditions to b ypass irrigation events. Since very little water is stored in the beds due to the low wa ter holding capacity of the sandy soil, the sensor rarely read a SMC at or above 12% which ca used only 28% of the irrigation events to be bypassed (Table 4). Although the tr eatment was programmed to irrigate at a soil moisture content of 12%, the average measured by TDR probes at the onset of each event was 14.1%. This was likely attributed to differences in the TDR probe readings (2% accuracy) and the Acclima sensor readings (1% accuracy). SMS treatments with an 8% threshold setting applied an average irrigation water total of 190 mm with an average water savings of 36%, whereas treatments with a 10% threshold setting averaged an application of 152 mm with a 49% wate r savings. This was unexpected since an 8% threshold setting should require drier soil moisture conditions to initiate ir rigation compared to a 10% threshold setting. The two treatments, how ever, applied similar irrigation applications throughout the trials, with differences totali ng less than 30 mm (Table 4). The lower averages of the 10% setting can be attributed to the very low water application of the I2 treatment during the spring 2005 gr owing season as seen in (Table 4). The soil moisture content at which the two treatmen ts initiated irrigation was, however, consistent with their threshold settings. The I1 treatment initiated ev ents at an average of 10.3%, while I2 initiated events at 12.4% (Table 4). All of the time r controlled SMS treatments initiated irrigation

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107 events at all consistent with programmed thre shold settings. The TDR measured soil moisture content, with 2% accuracy, at the onset of irri gation was very close to the programmed threshold settings of the SMS treatments (Table 4) The 12-14% on demand treatment and the 10% SMS treatment performed similarly, resulting in the lowest irrigation applicatio ns, 150 and 152 mm, and water savings, 50 and 49%, respectively, of all SMS treatments (Table 4) The on demand schedule allowed irrigation to occur at any time throughout the day, and mainta ined a relatively stable soil moisture content, as seen in Figures 4 through 4 and 4 through 4. Irrigation water was reduced by this treatment due to the lack of a program med irrigation time window. This enabled the treatment to irrigate only until the sensor read th e soil moisture content to be 14%. The average moisture content, measured by TDR probes, ma intained by this treatment was between 14.415.3%. This is very close to the 12-14% pr ogrammed range when probe and sensor error are considered. Of all the irrigation treatments, the time ba sed treatment, I5, applie d the highest total and daily rate of irrigation water with an average of 298 mm or 4.4 mm/d during the four seasons. I5 had the fewest irrigation events because it was programmed to irrigate once a day. Since I5 irrigated once a day for 2 hours, allowing nearly 24 hours for all excess water to drain from the profile before the next event, the soil moisture content measured just before irrigation occurred was estimated to be the actual field capacity of the raised bed system. Each 2 hour irrigation event, increased the soil moisture content by an average of 4.2%, which resulted in the rapid drainage as seen in the I5 gr aphs in Figures 4 through 4. Estimated field capacities for each season and a four season average are show n in Figure 4. Values ranged from 0.075

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108 0.147 over the four seasons. The overall field capacity was averaged to be 0.109, which was consistent with the measured field capacity of 10-12% (Icerman, 2007). Conclusions When properly installed and programmed, so il moisture sensors can successfully be integrated into an automated irrigation system to reduce irrigation water compared to a timebased schedule, while maintaining adequate soil mo isture in the plant rooting zone. After four growing seasons, the Acclima SMS treatment with a 10% threshold setting, proved the most successful. The treatment reduced the most amount of water, n early 50%, produced the highest fruit yield, as well as the highest water use efficiency. Future re search should further investigate the on demand irrigation schedule using the Ac clima CS3500 at various threshold settings. Acclima RS500 soil moisture controllers perform be st when they are programmed to separate irrigation timers to avoid cross communication between sensor signals. The placement of the soil moisture sensor in the raised bed, in relation to the plant and drip tape, can greatly affect sensor performance. Sensor burial is also im portant, as the accuracy of the probe depends on close contact with soil particles. Air pockets and other soil disturbances may result in inaccurate readings, ultimately reducing the effici ency of the irrigation system.

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109 Table 4. Irrigation treatments, threshold se ttings (VWC), and programmed irrigation run times. Treatment Treatment Description VWC threshold setting (m3/m3) Irrigation window Spring Pepper 2005 I1 I2 I3 I4 I5 Spring Pepper 2006 I1 I2 I3 I4 I5 Fall Pepper 2006 I1 I2 I3 I4 I5 Spring Pepper 2007 I1 I2 I3 I4 I5 QIC Acclima RS500 Acclima RS500 Acclima CS3500 Timebased schedule Acclima RS500 Acclima RS500 Acclima RS500 Acclima CS3500 Timebased schedule Acclima RS500 Acclima RS500 Acclima RS500 Acclima RS500 twin drip lines Timebased schedule Acclima RS500 Acclima RS500 Acclima RS500 Acclima RS500 twin drip lines Timebased schedule 0.1 (500 mV) 0.1 0.12 0.12.14 n/a 0.08 0.1 0.12 0.12.14 n/a 0.08 0.1 0.12 0.1 n/a 0.08 0.1 0.12 0.1 n/a 24 min, 5 times/day 24 min, 5 times/day 24 min, 5 times/day Anytime 2 hours, 1 time/day 24 min, 5 times/day 24 min, 5 times/day 24 min, 5 times/day Anytime 2 hours, 1 time/day 24 min, 5 times/day 24 min, 5 times/day 24 min, 5 times/day 12 min, 5 times/day 2 hours, 1 time/day 24 min, 5 times/day 24 min, 5 times/day 24 min, 5 times/day 12 min, 5 times/day 2 hours, 1 time/day

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110 Figure 4. Additional TDR probe locations surrounding Acclima sensors during spring 2007. Typical plot layout for treat ments I1, I2, and I3 is shown in the upper diagram, while I4 (twin drip lines) is shown in the lower diagram.

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111 02 04 06 08 0 Cumulative Rainfall (mm x 10) and Daily Rainfall (mm) 0 10 20 30 40 50 60 Temperature (C) 10 20 30 40 50 Cumulative Rainfall Daily Rainfall Average Air Temperature Number of Days after Transplanting Figure 4. Minimum, maximum, and average temperatures during spring 2005 along with daily and cumulative rainfall (mm). 02 04 06 08 0 0 10 20 30 40 50 60 Temperature (C) 0 5 10 15 20 25 30 35 Cumulative Rainfall Daily Rainfall Average Air Temperature Cumulative Rainfall (mm x 10) and Daily Rainfall (mm)Number of Days after Transplanting Figure 4. Minimum, maximum, and average temperatures during spring 2006 along with daily and cumulative rainfall (mm).

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112 02 04 06 08 0 0 10 20 30 40 50 60 Temperature (C) 0 10 20 30 40 50 Cumulative Rainfall Daily Rainfall Average Air Temperature Cumulative Rainfall (mm x 10) and Daily Rainfall (mm)Number of Days after Transplanting Figure 4. Minimum, maximum, and average temperatures during fa ll 2006 along with daily and cumulative rainfall (mm). 02 04 06 08 0 0 10 20 30 40 50 60 Temperature (C) 0 10 20 30 40 50 Cumulative Rainfall Daily Rainfall Average Air Temperature Cumulative Rainfall (mm x 10) and Daily Rainfall (mm)Number of Days after Transplanting Figure 4. Minimum, maximum, and average temperatures during spring 2007 along with daily and cumulative rainfall (mm).

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113 Spring 2005 Number of Days after Transplanting 02 04 06 08 01 0 0 Cumulative Irrigation (mm) 0 100 200 300 400 I1 10% QIC I2 10% AccRS500 I3 13% AccRS500 I4 12-14% AccCS3500 I5time based Figure 4. Cumulative irrigation wate r for treatments in spring 2005. Table 4. Irrigation treatments, threshold sett ings, and total irrigati on water applied after treatments were initiated (DAT 24), and overall water savings compared to the I5 control treatment during the spring 2005 season. Spring Pepper 2005 Treatment Description Threshold Setting Total Treatment Application (mm) Average Daily Application (mm/d) Water Savings Compared To I5 (%) I1 QIC 0.1 230 3.8 9 I2 Acclima RS500 0.1 53 0.9 79 I3 Acclima RS500 0.12 138 2.3 45 I4 Acclima CS3500 0.12.14 131 2.2 48 I5 Timebased n/a 253 4.2 0

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114 Table 4. Water savings of SMS based treatment s compared to the I5 control treatment for growth stages 2-4 during th e spring 2005 season after treat ments were initiated. Spring Pepper 2005 SMS Treatment Water Savings Compared to I5 (%) Crop Growth Stage* I1, 10% QIC I2, 10% Acclima I3, 12% Acclima I4, 12% Acclima 2 -2 91 57 43 3 13 77 50 48 4 -18 86 5 41 *All treatments were irrigated similarly during the establishment phase in growth stage 1. 02 04 06 08 01 0 0 Cumulative Irrigation (mm) 0 100 200 300 400 Spring 2006 Number of Days after TransplantingI1 8% AccRS500 I2 10% AccRS500 I3 13% AccRS500 I4 12-14% AccCS3500 I5time based Figure 4. Cumulative irrigation water for treatments during sp ring 2006. SMS treatment I4 (12-14%) was not properly programmed until 29 DAT.

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115 Table 4. Irrigation treatments, threshold sett ings, and total irrigati on water applied after treatments were initiated (DAT 16), and overall water savings compared to the I5 control treatment during the spring 2006 season. Spring Pepper 2006 Treatment Description Threshold Setting Total Treatment Application (mm) Average Daily Application (mm/d) Water Savings Compared to I5 (%) I1 Acclima RS500 0.1 156 2.6 53 I2 Acclima RS500 0.1 301 4.9 9 I3 Acclima RS500 0.12 287 4.7 13 I4 Acclima CS3500 0.12.14348 (169)*16.2 (2.8)* -6 (49)* I5 Timebased n/a 329 5.4 0 *Values reflect irrigation after pr ogramming error was fixed (DAT 29). Table 4. Water savings of SMS based treatment s compared to the I5 control treatment for growth stages 2-4 during th e spring 2006 season after treat ments were initiated. Spring Pepper 2006 Water Savings SMS Treatment Water Savings Compared to I5 (%) Crop Growth Stage* I1, 8% Acclima I2, 10% Acclima I3, 12% Acclima I4, 12% Acclima 2 61 13 5 n/a** 3 47 6 12 45 4 72 23 33 60 *All treatments were irrigated similarly during th e establishment phase in growth stage 1. ** Treatment I4 was not properly in itiated until growth stage 3.

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116 02 04 06 08 01 0 0 Cumulative Irrigation (mm) 0 100 200 300 400 Fall 2006 Number of Days after TransplantingI1 8% AccRS500 I2 10% AccRS500 I3 13% AccRS500 I4 12-14% AccR S500, twin drip I5time based Figure 4. Cumulative irrigation water for treatments in fall 2006. SMS treatments were wired to separate irriga tion controllers 58 DAT. Table 4. Irrigation treatments, th reshold settings, tota l irrigation water applied after treatments were initiated (DAT 17), and overall water savings compared to the I5 control treatment during the fall 2006 season. Fall Pepper 2006 Treatment Description Threshold Setting Total Treatment Application (mm) Average Daily Application (mm/d) Water Savings (%) I1 Acclima RS500 0.08244 (106)* 3.2 19 (6)* I2 Acclima RS500 0.1 213 (77)* 2.8 30 (32)* I3 Acclima RS500 0.12319 (138)* 4.2 -5 (-22)* I4 Acclima RS500 Twin drip lines 0.10327 (115)* 4.3 -8 (-2)* I5 Timebased n/a303 (113)* 4.0 0 *Values reflect irrigation after sensors were wired to separate controllers (DAT 58).

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117 Table 4. Water savings of SMS based treatment s compared to the I5 control treatment for growth stages 3 and 4 during the fall 2006 season after treatments were initiated. Fall Pepper 2006 Water Savings SMS Treatment Crop Growth Stage I1, 8% Acclima I2, 10% Acclima I3, 12% Acclima I4, 10% Acclima, twin drip lines 2 n/a** n/a** n/a** n/a** 3 12 46 -8 -8 4 0 -3 -71 47 *All treatments were irrigated similarly during the establishment phase in growth stage 1. ** The SMS treatments did not function independ ently until 58 DAT during growth stage 3. 02 04 06 08 01 0 0 Cumulative Irrigation (mm) 0 100 200 300 400 Spring 2007 Number of Days after TransplantingI1 8% AccRS500 I2 10% AccRS500 I3 13% AccRS500 I4 12-14% AccRS500, twin drip I5time based Figure 4. Cumulative irrigation water for treatments in spring 2007. Treatments I2 and I4 were adjusted 30 DAT.

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118 Table 4. Irrigation treatments, th reshold settings, tota l irrigation water applied after treatments were initiated (DAT 20), and overall water savings compared to the I5 control treatment during the spring 2007 season. Spring Pepper 2007 Treatment Description Threshold Setting Total Treatment Application (mm) Average Daily Application (mm/d) Water Savings (%) I1 Acclima RS500 0.08 171 2.3 44 I2 Acclima RS500 0.1190 (161)* 2.5 43 (60)* I3 Acclima RS500 0.12 261 3.4 15 I4 Acclima RS500 Twin drip lines 0.10277 (272)* 3.6 17 (33)* I5 Timebased n/a 308 4.1 0 *Values reflect irrigation after sensors were adjusted (DAT 30). Table 4. Water savings of SMS based treatment s compared to the I5 control treatment for growth stages 2-4 during th e spring 2007 season after treat ments were initiated. Spring Pepper 2007 Water Savings SMS Treatment Crop Growth Stage I1, 8% Acclima I2, 10% Acclima I3, 12% Acclima I4, 10% Acclima, twin drip lines 2 72n/a**3 n/a** 3 44 49 20 7 4 8 24 -20 72 All treatments were irrigated si milarly during the establishment phase in growth stage 1. ** Treatments I2 and I4 did not function prope rly until 30 DAT during growth stage 3.

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119 I5,time-basedDate 4/28 4/29 4/30 5/ 2 5/3 5/4 5/5 5/1 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 F.C. = .081 VWC = .086 VWC = .078 VWC = .087 soil moisture content irrigation event skipped event Figure 4. Volumetric water content measured at 15 cm for April 28 to May 4, 2006 (17 to 23 DAT). The horizontal line indicates th e approximated field capacity averaged for the I5 time based treatment after a 2 hour irrigation event. Table 4. Irrigation threshold settings, number of irrigation events, and average volumetric water content (VWC) at beginning of irrigati on events for pepper cultivated in spring 2005. Irrig. Treat. Total irrig. water applied (mm) Treatment Water Savings Compared to I5 (%) Total irrig. events (#) Number and Percentage of total skipped events (#) Irrig. set point (%) Average VWC at start of irrig. Event (%) Average irrigation initiation range (%) C.V. of VWC measured by TDR (%) I1 230 9 24753 (18%)1013.1 10.5.312.3 I2 53 79 39261 (87%)1012.9 11.3.420.6 I3 138 45 138162 (54%)1216.7 14.5.611.4 I4 131 48 57n/a12 18.8 20.2* 17.5.0 16.4.6* 7.4 7.3* I5 253 0 58n/an/a14.7 n/an/a *Values represent soil moisture content at upper se t point range when irrigation event was terminated.

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120 I5B1 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 F.C. = .167 I5B2 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 F.C. = .127 I5B3 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 F.C. = .144 I5B4 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 F.C. = .142 I5 Field Average 5/17 5/21 5/25 5/29 6/2 6/6 6/10 6/14 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall ( mm ) 0 5 10 15 20 25 F.C. = .147Date Figure 4. Volumetric water content (VWC) meas ured at 15 cm for May 15 to June 15, 2005 (40 to 71 DAT) along with rainfall even ts. Horizontal lines indicate the approximated field capacity (VWC) for each replicate.

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121 I1, 8% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I2, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I3, 12% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I4, 10 % VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I5, time based 4/28 4/29 4/30 5/2 5/3 5/4 5/5 5/1 Date VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 maximum VWC % minimum VWC % soil moisture content irrigation event skipped event F.C. = .147 Figure 4. Volumetric water content (VWC) meas ured at 15 cm for April 28 to May 4, 2005 (23 to 29 DAT) with scheduled irrigation events during vegetative development stage and rainfall. The double horizon tal lines indicate minimum and maximum soil moisture content at which irrigation was initiated. Approximated field capacity is represented by a single bold line on the I5 graph.

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122 I1, 8% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I2, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I3, 12% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I4, 10 % VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I5, time based 5/26 5/27 5/28 5/29 5/30 5/31 6/2 6/1 Date VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 maximum VWC % minimum VWC % soil moisture content irrigation event skipped event F.C. = .147 Figure 4. Volumetric water content (VWC) meas ured at 15 cm for May 26 to June 1, 2005 (51 to 57 DAT) with scheduled irrigation events during flowering period and rainfall. The double horizontal lines indicate minimum and maximum soil moisture content at which irrigation was initiated. Approximated field capacity is represented by a single bold line on the I5 graph.

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123 I1, 8% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I2, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I3, 12% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I4, 10 % VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I5, time based 6/22 6/23 6/24 6/25 6/26 6/27 Date VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall ( mm ) 0 5 10 15 20 25 maximum VWC % minimum VWC % soil moisture content irrigation event skipped event F.C. = .147 Figure 4. Volumetric water content (VWC) meas ured at 15 cm for June 22 to June 26, 2005 (78 to 82 DAT) with scheduled irrigation events during harvest period and rainfall. The double horizontal lines indicate minimum and maximum soil moisture content at which irrigation was initiated. Approximated field capacity is represented by a single bold line on the I5 graph.

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124 Table 4. Irrigation threshold settings, number of irrigation events, and average volumetric water content (VWC) at beginning of irrigati on events for pepper cultivated in spring 2006. Irrig. Treat. Total irrigation water applied (mm) Treatment Water Savings Compared to I5 (%) Total irrig. events (#) Total of skipped events (#) Irrig. set point (%) Average VWC at start of irrigation Event (%) Average irrigation initiation range (%) C.V. of VWC measured by TDR (%) I1 156 53 137 195 (58%) 810.5 9.3.515.4 I2 301 9 298 32 (10%) 1011.6 9.9.9 7.9 I3 287 13 302 28 (8%) 1212.1 10.8.4 8.5 I4 348 (169)** -6 (49)* 338 (240)** n/a12 9.9 10.3* 8.8.9 7.9.1* 12.7 12.1 I5 329 0 55n/an/a8.2 n/a n/a *Values represent soil moisture content at upper se t point range when irrigation event was terminated. **Value represents total irrigation afte r the I4 programming error was fixed.

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125 I5B1 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 F.C. = .089 I5B2 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 F.C. = .086 I5B3 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 F.C. = .064 I5B4 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 F.C. = .085 I5 Field Average 5/17 5/21 5/25 5/29 6/2 6/6 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall ( mm ) 0 5 10 15 20 25 F.C. = .081Date Figure 4. Volumetric water content (VWC) meas ured at 15 cm for May 17 to June 17, 2006 (35 to 66 DAT) along with rainfall even ts. Horizontal lines indicate the approximated field capacity (VWC) for each replicate.

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126 I1, 8% VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I2,10% VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I3,12% VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I4,12-14% VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I5,time-based Date 4/28 4/29 4/30 5/2 5/3 5/4 5/5 5/1 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall ( mm ) 0 5 10 15 20 25 maximum VWC% minimum VWC%soil moisture content irrigation event skipped event F.C. = .082 Figure 4. Volumetric water content (VWC) meas ured at 15 cm for April 28 to May 4, 2006 (17 to 23 DAT) with scheduled irrigation events and rainfall during initial vegetative development stage of pepper The double horizon tal lines indicate minimum and maximum soil moisture conten t at which irrigation was initiated. Approximated field capacity is represente d by a single bold line on the I5 graph.

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127 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 6/8 6/9 6/10 6/11 6/12 6/13 6/14 6/15 6/16 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall ( mm ) 0 5 10 15 20 25 maximum VWC% minimum VWC%soil moisture content irrigation event skipped event I1, 8% I2,10% I3,12% I4,12-14% I5,time-basedF.C. = .082Date Figure 4. Volumetric water content (VWC) meas ured at 15 cm for June 8 to June 16, 2006 (58 to 66 DAT) with scheduled irrigation events and rainfall during early fruit development stage of pepper. The doubl e horizontal lines indicate minimum and maximum soil moisture content at which i rrigation was initiated. Approximated field capacity is represented by a single bold line on th e I5 graph.

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128 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 6/29 6/30 7/2 7/3 7/1 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall ( mm ) 0 5 10 15 20 25 maximum VWC% minimum VWC%soil moisture content irrigation event skipped event I1, 8% I2,10% I3,12% I4,12-14% I5,time-basedF.C. = .082Date Figure 4. Volumetric water content (VWC) meas ured at 15 cm for June 29 to July 3, 2006 (79 to 83 DAT) with scheduled irrigation events and rainfall during harvesting period of pepper. The double horizonta l lines indicate minimum and maximum soil moisture content at which irrigation was initiated. Approximated field capacity is represented by a single bold line on the I5 graph.

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129 Table 4. Irrigation threshold settings, number of irrigation events, and average volumetric water content (VWC) at beginning of irriga tion events for pepper cultivated in fall 2006. Irrig. Treat. Total irrig. water applied (mm) Treatment Water Savings Compared to I5 (%) Total irrig. events (#) Total of skipped events (#) Irrig. set point (%) Average VWC at start of irrigation event (%) Average irrigation initiation range (%) C.V. of VWC measured by tdr (%) I1 244 19 (6)* 26496 (27%) 89.1 7.9.611.4 I2 213 30 (32)* 217143 (40%) 1011.6 9.9.27.9 I3 319 -5 (-22)* 32436 (10%) 1210.0 9.5.97.8 I4 327 -8 (-2)* 29466 (18%) 1010.3 9.5.18.7 I5 303 0 64n/an/a7.5 n/an/a

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130 I5B1 VWC (v/v) 0.00 0.05 0.10 0.15 0.20 F.C. = .075 I5B2 VWC (v/v) 0.00 0.05 0.10 0.15 0.20 F.C. = .077 I5B3 VWC (v/v) 0.00 0.05 0.10 0.15 0.20 F.C. = .076 I5B4 VWC (v/v) 0.00 0.05 0.10 0.15 0.20 F.C. = .074 I5 Field Average 11/9 11/13 11/17 11/21 11/25 11/29 12/3 12/7 VWC (v/v) 0.00 0.05 0.10 0.15 0.20 Rainfall (mm) 0 5 10 15 20 25 F.C. = .075Date Figure 4. Volumetric water content (VWC) measured at 15 cm for November 7 to December 7, 2006 (57 to 87 DAT) along with rainfall events. Horizontal lines indicate the approximated field cap acity (VWC) for each replicate.

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131 I1, 8% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I2, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I3, 12% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I4, 10 % VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I5, time based 9/28 9/29 9/30 10/2 10/3 10/1 Date VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall(mm) 0 5 10 15 20 25 maximum VWC % minimum VWC %F.C. = .082 soil moisture content irrigation event skipped event Figure 4. Volumetric water content (VWC) meas ured at 15 cm for September 28 to October 2, 2006 (19 to 23 DAT) with scheduled ir rigation events and rainfall during vegetative development of pepper. Th e double horizontal lines indicate minimum and maximum soil moisture content at which irrigation was initiated. Approximated field capacity is represente d by a single bold line on the I5 graph.

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132 I1, 8% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I2, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I3, 12% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I4, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I5, time based Date 10/18 10/19 10/20 10/21 10/22 10/23 10/24 10/25 10/26 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 soil moisture content irrigation event skipped event maximum VWC % minimum VWC %F.C. = .082 Figure 4. Volumetric water content (VWC) meas ured at 15 cm for October 18 to October 24, 2006 (39 to 45 DAT) with scheduled irrigation events and rainfall during flowering of pepper. The double horiz ontal lines indicate minimum and maximum soil moisture content at which i rrigation was initiated. Approximated field capacity is represented by a single bold line on th e I5 graph.

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133 I1, 8% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I2, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I3, 12% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I4, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I5, time based Date 11/23 11/24 11/25 11/26 11/27 11/28 11/29 11/30 12/1 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 soil moisture content irrigation event skipped event maximum VWC % minimum VWC %F.C. = .082 Figure 4. Volumetric water content (VWC) measured at 15 cm for November 23 to November 30, 2006 (75 to 82 DAT) with sc heduled irrigation events and rainfall during harvesting period for pepper. The double horizontal lines indicate minimum and maximum soil moisture conten t at which irrigation was initiated. Approximated field capacity is represente d by a single bold line on the I5 graph.

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134 Table 4. Irrigation threshold settings, number of irrigation events, and average volumetric water content (VWC) at beginning of irrigati on events for pepper cultivated in spring 2007. Irrig. Treat. Total irrig. water applied (mm) Treatment Water Savings Compared to I5 (%) Total irrig. events (#) Total of skipped events (#) Irrigation set point (%) Average VWC at start of irrigation event (%) Average irrigation initiation range (%) C.V. of VWC measured by TDR (%) I1 171 44 175 145 (45%) 811.2 9.8.310.4 I2 190 43 (60)* 175 145 (45%) 1012.8 10.6 15.0 18.4 I3 261 15 253 67 (21%) 1213.4 11.3 16.5 11.7 I4 277 17 (33)* 296 25 (8%) 1012.2 10.7 14.8 13.3 I5 308 0 64n/an/a13.3 n/a n/a

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135 I5B1 VWC (v/v) 0.0 0.1 0.2 0.3 0.4 F.C. = .113 I5B2 VWC (v/v) 0.0 0.1 0.2 0.3 0.4 F.C. = .162 I5B3 VWC (v/v) 0.0 0.1 0.2 0.3 0.4 F.C. = .106 I5B4 VWC (v/v) 0.0 0.1 0.2 0.3 0.4 F.C. = .152 I5 Field Average 5/17 5/21 5/25 5/29 6/2 6/6 6/10 6/14 VWC (v/v) 0.0 0.1 0.2 0.3 0.4 Rainfall (mm) 0 5 10 15 20 25 F.C. = .133Date Figure 4. Volumetric water content (VWC) meas ured at 15 cm for May 15 to June 15, 2007 (35 to 66 DAT) along with rainfall even ts. Horizontal lines indicate the approximated field capacity (VWC) for each replicate.

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136 I1, 8% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I2, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I3, 12% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I4, 10 % VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I5, time based 5/9 5/10 5/11 5/12 5/13 5/14 5/15 5/16 Date VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 maximum VWC % minimum VWC %F.C. = .133 soil moisture content irrigation event skipped event Figure 4. Volumetric water co ntent (VWC) measured at 15 cm for May 9 to May 15, 2007 (29 to 35 DAT) with scheduled irrigation events and rainfall during vegetative development for pepper. The double hor izontal lines indicate minimum and maximum soil moisture content at which i rrigation was initiated. Approximated field capacity is represented by a single bold line on th e I5 graph.

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137 I1, 8% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Col 1 vs Col 2 Plot 1 Upper control line Plot 1 Lower control line I1-Date/Time vs I1-SMC I1-Date/Time vs smc red I2, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I3, 12% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I4, 10 % VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I5, time based 5/30 5/31 6/2 6/3 6/4 6/5 6/6 6/1 Date VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 maximum VWC % minimum VWC %F.C. = .133 soil moisture content irrigation event skipped event Figure 4. Volumetric water content (VWC) meas ured at 15 cm for May 30 to June 5, 2007 (50 to 56 DAT) with scheduled irrigation events and rainfall during flowering period for pepper. The double horizontal lines indicate minimum and maximum soil moisture content at which irrigation was initiated. Approximated field capacity is represented by a single bold line on the I5 graph.

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138 I1, 8% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Plot 1 Lower control line I1-Date/Time vs I1-SMC I1-Date/Time vs smc red I2, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I3, 12% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I4, 10 % VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I5, time based 6/20 6/21 6/22 6/23 6/24 6/25 6/26 6/27 Date VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 maximum VWC % minimum VWC %F.C. = .133 soil moisture content irrigation event skipped event Figure 4. Volumetric water content (VWC) meas ured at 15 cm for June 20 to June 26, 2007 (71 to 77 DAT) with scheduled irrigation events and rainfall during harvest period for pepper. The double horizontal line s indicate minimum and maximum soil moisture content at which irrigation was initiated. Approximated field capacity is represented by a single bold line on the I5 graph.

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139 I4, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I2, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I3, 12% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I1, 8% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 TDR A TDR B TDR C TDR D F.C. = .133 I5, time based 5/9 5/10 5/11 5/12 5/13 5/14 5/15 5/16 Date VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall ( mm ) 0 5 10 15 20 25 F.C. = .133 Figure 4. Volumetric water content (VWC ) measured by four TDR probes installed adjacent to the buried Acclima sensor s for May 9 to May 15, 2007 (29 to 35 DAT) along with seasonal rainfall.

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140 I4, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I2, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I3, 12% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I1, 8% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I5, time based 5/30 5/31 6/2 6/3 6/4 6/5 6/6 6/1 Date VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall ( mm ) 0 5 10 15 20 25 F.C. = .133 TDR A TDR B TDR C TDR D Figure 4. Volumetric water content (VWC ) measured by four TDR probes installed adjacent to the buried Acclima sensors for May 30 to June 5, 2007 (50 to 56 DAT) along with seasonal rainfall.

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141 I4, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I2, 10% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I3, 12% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I1, 8% VWC VWC (v/v) 0.05 0.10 0.15 0.20 0.25 I5, time based 6/20 6/21 6/22 6/23 6/24 6/25 6/26 6/27 Date VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 F.C. = .133 TDR A TDR B TDR C TDR D Figure 4. Volumetric water content (VWC ) measured by four TDR probes installed adjacent to the buried Acclima sensors for June 20 to June 26, 2007 (71 to 77 DAT) along with seasonal rainfall.

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142 Table 4. Summary of successful SMS treatments over spring 2005, spring 2006, fall 2006, and spring 2007 growing seasons, with tota l and daily average irrigation water and water savings compared with the time based treatment, I5. Treatment and Season Treatment Description Threshold Setting (VWC) Total Treatment Application (mm) Average Daily Application (mm/d) Water Savings (%) I2, spring 2005 Acclima RS500 0.1 53 0.88 79 I3, spring 2005 Acclima RS500 0.12 138 2.3 45 I4, spring 2005 Acclima C3500 0.12.14 131 2.2 48 I1, spring 2006 Acclima RS500 0.08 156 2.6 53 I3, spring 2006 Acclima RS500 0.12 287 4.7 13 I4, spring 2006 Acclima C3500 0.12.14 169* 2.8* 49* I1, fall 2006 Acclima RS500 0.08 244 3.2 19 I2, fall 2006 Acclima RS500 0.1 213 2.8 30 I1, spring 2007 Acclima RS500 0.08 171 2.3 44 I2, spring 2007 Acclima RS500 0.1 190 2.5 38 I3, spring 2007 Acclima RS500 0.12 261 3.4 15 Values adjusted for programming error fixed DAT 29. Table 4. Average daily and total irrigation an d water savings for each treatment type across all four growing seasons. Threshold Setting Average Treatment Application (mm) Average Daily Application (mm/d) Average Water Savings (%) 8% 190 2.5 36 10% 152 2.1 49 I2% 229 3.5 23 12% 150 2.5 50 Time-based 298 4.4 0

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143 Table 4. Summary of successful SMS treatments over spring 2005, spring 2006, fall 2006, and spring 2007 growing seasons, detailing initiated and bypassed irrigation event totals, along with the average soil moisture content (SMC) at the start of the event. Treatment Treatment Description Threshold Setting (%) Total Initiated Events (#) Total Bypassed Events (#) Avg. VWC at Start of Initiated Event (%) Avg. VWC of Initiation Start Range (%) I2, spring 2005 Acclima RS500 1039261 (87%)12.9 11.3.4 I3, spring 2005 Acclima RS500 12138162 (54%)16.7 14.5.6 I4, spring 2005 Acclima CS3500 1257n/a 18.8 20.2* 17.5 16.4.6 I1, spring 2006 Acclima RS500 8137195 (58%)10.5 9.3.5 I3, spring 2006 Acclima RS500 1230228 (8%)12.1 10.8.4 I4, spring 2006 Acclima CS3500 12240*n/a 9.9 10.3** 8.8.9 7.9.1** I1, fall 2006 Acclima RS500 826496 (27%) 9.1 7.9.6 I2, fall 2006 Acclima RS500 10217143 (40%)11.6 9.9.2 I1, spring 2007 Acclima RS500 8175145 (45%)11.2 9.8.3 I2, spring 2007 Acclima RS500 10175145 (45%)12.8 10.6.0 I3, spring 2007 Acclima RS500 1225367 (21%)13.4 11.3.5 *Value adjusted for programming error fixed DAT 29. ** Values reflect SMC at the end of irrigation event.

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144 Table 4. Average bypassed and initiated irri gation event totals, along with average soil moisture content (SMC) at th e start of the events for each treatment type across the four growing seasons. SMS Threshold Setting Average Total Initiated Events (#) Average Total Bypassed Events (#) Average VWC at Start of Initiated Event (%) Average VWC of Initiation Start Range (%) 8% 192 145 (43%) 10.3 9.0.8 10% 144 183 (57%) 12.4 10.6.2 I2% 231 86 (28%) 14.1 12.2.8 12% 149 n/a 14.4 15.3* 13.2.0 12.2.4* Time-based 59 n/a 10.1 13.5* n/a *Values reflect SMC at th e end of irrigation event

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145 Date Estimated Field Capacity Spring 2005 5/17 5/21 5/25 5/29 6/2 6/6 6/10 6/14 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 F.C. = .147 Estimated Field Capacity Spring 2006 5/17 5/21 5/25 5/29 6/2 6/6 6/10 6/14 6/18 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 F.C. = .082 Estimated Field Capacity Fall 2006 11/9 11/13 11/17 11/21 11/25 11/29 12/3 12/7 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 F.C. = .109 5/17 5/21 5/25 5/29 6/2 6/6 6/10 6/14 VWC (v/v) 0.05 0.10 0.15 0.20 0.25 Rainfall (mm) 0 5 10 15 20 25 F.C. = .133 Estimated Field Capacity Spring 2007 F.C. = .109 F.C. = .109 F.C. = .075 F.C. = .109 Figure 4. Volumetric water content (VWC) fo r the I5 time based treatment averaged over all four replicates for a one month peri od during the growing seasons along with recorded rainfall events. Horizontal lines indicate the approximate field capacity (F.C.) VWC, with dashed lines depicti ng the individual season average and solid lines showing the average over all four seasons.

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146 LIST OF REFERENCES Allen, R.G., L.S. Pereira, D. Raes, and M. Sm ith, 1998. Crop evapotranspiration: Guidelines for computing crop water requirements. Irr. Drain. Pape r 56. UN-FAO, Rome. Amayreh, J., and N. Al-Abed. 2005. Developing crop coefficients for field grown tomato under drip irrigation with black plastic mulch. Agricultural Water Management 73:247-254. Babiker, I.S., A.A. Mohamed, H. Terao, K. Kato, and K. Ohta. 2004. Assessment of groundwater contamination by nitrate leaching from intens ive vegetable cultivation using geographical information system. Environ Int. 29:1009-1017. Blonquist, J.M., Jr., S.B. Jones, and D.A. Robi nson. A time domain transmission sensor with TDR performance characteristics. J. Hydrol. (2005). Bouchard, D.C., M.K. Williams and R.Y. Sura mpalli, Nitrate contamination of groundwater: sources and potential health effects. J. Am. Water Works Assoc., September 1992 84 9 (1992), pp. 85. Buster, T.P. 1979. Soil survey of Marion County, Florida. Soil C onservation Service, Washington, D.C. Clark, G.A., E.E. Albregts, C.D. Stanley, A.G. Smajstrla and F.S. Zazueta. 1996. Water requirements and crop coefficients of drip-irrigated strawberry plants. Trans. ASAE 39 3 (1996), pp. 905-912. Dedekorkut, Aysin, J. Scholz, B. Stiftel (eds.). 2003. Adaptive Governance and Floridas Water Conflicts: The Case Studies. Tallahassee, FL: Florida State University DeVoe L. Moore Center. Dukes, M.D., E.H. Simonne, W.E. Davis, D.W. Studstill, and R. Hochmuth. 2003. Effect of sensor-based high frequency irrigation on bell pepper yield and water use, P. 665-674. In: Proc. 2nd Int. Conf. Irr. And Drainage, 12-15 May, Phoenix, Ariz. Fares, A., and A.K. Alva. 2000. Soil water components based on capacitance probes in a sandy soil. Soil Sci. Soc. Am. J. 64:311-318. Fernandandez, M.D., M. Gallardo, S. Bonachela, F. Orgaz, and E. Federes. 2000. Crop coefficients of a pepper crop gr own in plastic greenhouses in Al meria, Spain. Acta Hort. (ISHS) 537:461-469. Haman, D.Z., and F.T. Izuno. 1993. Soil Plant Wate r Relationships. Fl. Coop. Ext. Serv. Circ. 1085 Hanson, B.R., and D.M. May. 2006. Crop coefficients for drip irrigated processing tomato. Agricultural Water Management 81: 381-399.

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147 Hanson, T.R., L. Hatch, and H.C. Clonts. 2002. Reservoir water level impacts on recreation, property, and nonuser values. Journal of the American Water Resource Association. Vol. 3, No. 4, 1007-18. Hochmuth, G.J., and A.G. Smajstrla. 1997. Fertilizer application and management for micro (or drip) irrigated vegetables in Florid a. Fla. Coop. Ext. Serv. Circ. 1181. Howell, T.A., 1996. Irrigation scheduling research and its impact on water use. In: Proceedings of the International Conference, 3-6 November 1996, Ev apotranspiration and Irrigaiton Scheduling, ASAE, San Antonio, TX, pp. 21-33. Hutson, S.S., N.L. Barber, J.F. Kenny, K.S. Linsey, D.S. Lumia, and M.A. Maupin. 2004. Estimated use of water in the United States in 2000: Reston Virg inia, U.S. Geological Survey, Circular 1268, 46 p. Icerman, J., 2007. Approaches for two-dimensional monitoring and numerical modeling of drip systems. Agricultural and Biological Eng. Dept. University of Florida, Gainesville, p.148. (MS Thesis). Jabar, F., S. Shukla, and S. Srivastava. 2007. Evaporation losses for drip-irrigated watermelon in shallow water table and sandy soil conditions. Paper No. 062084. 2006 Annual ASABE Meeting, Portland, OR. Ley, T.W., R.G. Stevens, R.R. Topielec, and W.H. Neibling. 1994. Soil water monitoring and measurement. A Pacific Northwest Publica tion. Washington, Or egon and Idaho. PNW 475, Oregon State University, Corvallis, OR. Marella, R.L., 2004, Water withdrawals, use, di scharge, and trends in Florida, 2000: U.S. Geological Survey Scientific Inve stigations Report 2004-5151, 136 p. Martin, D.L., E.C. Stegman, and E. Fereres. 1990. Irrigation scheduling principles. In Management of Farm Irrigation Systems, 153-203. Maynard, D.N. and B.M. Santos. 2007. Yields of vegetables. Chapter 13 in: Vegetable production guide for Florida 2007-2008. IF AS, Citrus and Vegetable Magazine Mossler, M., M.J. Aerts, and O.N. Nesheim. 200 6. Florida Crop/Pest Management Profiles: Bell Peppers. Fla. Coop. Ext. Serv. Circ. 1240. Munoz-Carpena, R. 2004. Field devices for soil water content. Bull. 343. Fl. Coop. Extension Serv. IFAS, University of Florida, Gainesville. Munoz-Carpena, R., M.D. Dukes, Y.C. Li, and W. Klassen. 2008. Design and field evaluation of a new controller for soil moisture-based ir rigation control. A pplied Engineering in Agriculture. 24(2) pp. 183-191.

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148 Paramasivam, S., A.K. Alva, and A. Fares. 2000. An evaluation of soil water status using tensiometers in a Sandy soil profile unde r citrus production. Soil Sci. 165:343-353. Paramasivam, S., A.K. Alva, A.Fares, and K.S. Sa jwan. 2001. Estimation of n itrate in an entisol under optimum citrus production. So il Sci. Soc. Am. J. 65914-921. Schroder, J. 2006. Soil moisture-based drip irrigati on for efficient use of wa ter and nutrients and sustainability of vegetables cropped on coar se soils. Agricultural and Biological Eng. Dept. University of Florida, Gainesville, p.95. (MS Thesis). Simonne, E.H., and G.J. Hochmuth. 2004. Soil a nd fertilizer management for vegetable production in Florida. In Vegetable production handbook for Florida. 2004-2005, eds. S.M. Olsen and E.H. Simmone, 3-16. Lenexa, KS: Vance Publishing. Simonne, E.H., M.D. Dukes, and D.Z. Haman. 20 04. Principles and practices of irrigation management for vegetables. Chapter 8 in: Vegetable production guide for Florida 20032004. IFAS, Citrus and Vegetable Magazine. Simonne, E.H., M.D. Dukes, B. Hochmuth, D. Studstil l, and W. Davis. 2002. Principles of drip irrigation scheduling for vegetables in the TMDL and BMP era. In Vegetarian Newsletter. February 02. FL. Coop. Extension Serv. IFAS, University of Florida, Gainesville. Smajstrla, A.G., and S.J. Locascio. 1996. Tensio meter-controlled, drip ir rigation scheduling of tomato. Applied Eng. Agric. 12:315-319 Shukla, S, S. Srivastava, and J. D. Hardin. 2006. Design, construction, an d installation of large drainage lysimeters for wate r quantity and quality studies. Applied Engineering in Ag. In Press. Spalding, R.F., D.G. Watts, J.S. Schepers, M.E. Burbach, M.E. Exner, R.J. Poreda, and G.E. Martin. 2001. Controlling nitr ate leaching in irrigated agri culture. J. Environ. Qual. 30:1184-1194. St. Johns River Water Management District. (2001). East-central Florida Water Supply Initiative. Palatka, FL: St. Johns River Water Management District. Topp, G.C. and J.L. Davis. 1985. Measuremen t of soil water content using time-domain reflectometry (TDR): a field evaluation. Soil Sci. Soc. Am. J. 49, pp. 19. U.S. Geological Survey, 2004. Estimated Use of Water in the United States in 2000, U.S. Geological Survey Circular 1268. Zotarelli, L., J.M. Scholberg, M.D. Dukes, and R. Munoz-Carpena. 2007. Monitoring of nitrate leaching in sandy soils: comparison of three methods. J. Environ. Qual.

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149 BIOGRAPHICAL SKETCH Born in Mor ristown, New Jersey, in January 1982, Kristen Femminella was raised and educated in Vero Beach, Florida. It was here she spent most of her days outdoors developing a deep love and respect for the natural resources th at make Florida so uniquely beautiful. After graduation she decided to pursue a degree in land and water resources engineering, and graduated from the University of Florida in 2005 with her bachelors degree. She decided to continue her studies in this field and went on to receive her Master of Engineering degree.