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New Irrigation-Plant Production System for Water Conservation in Ornamental Nurseries

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New Irrigation-Plant Production System for Water Conservation in Ornamental Nurseries
Copyright Date:
2008

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Boxes ( jstor )
Crops ( jstor )
Growing seasons ( jstor )
Irrigation systems ( jstor )
Irrigation water ( jstor )
Plants ( jstor )
Rain ( jstor )
Seasons ( jstor )
Summer ( jstor )
Water temperature ( jstor )
City of Gainesville ( local )

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University of Florida
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University of Florida
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8/8/2007
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84957892 ( OCLC )

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NEW IRRIGATION-PLANT PRODUCTION SYSTEM FOR WATER CONSERVATION IN ORNAMENTAL NURSERIES By SUAT IRMAK 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 2002

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Copyright 2002 by Suat Irmak

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I dedicate this dissertation to my wife and best friend, Ayse.

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iv ACKNOWLEDGMENTS I express my sincere appreciation to Dr. Dorota Z. Haman, who served as chair of my dissertation committee. I would like to thank her for her guidance and support during the course of this research. IÂ’m also thankful to her for welcoming me into her academic environment. It was a great pleasure and precious experience working with her. I thank my committee members Drs. James W. Jones, Kenneth L. Campbell, Thomas L. Crisman, and Thomas H. Yeager for their support and guidance throughout this research. My special gratitude goes to the late Dr. Allen G. Smajstrla (1948-1999) who served as a cochair during the first two years of my Ph.D. program. I would like to express my deepest sympathy, admiration, and respect to him in every possible way. His friendship will be missed. I thank the Agricultural and Biological Engineering Department for giving me access to use its resources and facilities. My special thanks go to Mr. Danny Burch and Mr. Bob Tonkinson for their technical assistance and warm friendship. I am grateful to my mother, Seher, and father, Yusuf, for their extraordinary support and love. My eternal gratefulness goes to my wife, Ayse, for her courage and endless support. I benefitted from much of her expertise throughout my career. I am also thankful for her time and help in data collection during this research.

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v TABLE OF CONTENTS Page ACKNOWLEDGMENTS ................................................ iv LIST OF TABLES ...................................................... viii LIST OF FIGURES ..................................................... ix ABSTRACT ........................................................... xii CHAPTER 1. GENERAL INTRODUCTION ........................................... 1 2. QUANTIFICATION AND EVALUATION OF IRRIGATION, RUNOFF, PLANT BIOMASS, AND IRRIGATION EFFICIENCIES ......................... 5 Introduction ............................................................. 5 Materials and Methods ..................................................... 8 MPBS Description .................................................. 8 Modifications of the MPBS ........................................... 9 Description of the Conventional System (CS) ............................. 10 Field Experiments .................................................. 11 General experimental procedures ................................ 11 Irrigation applications ......................................... 13 Determination of SIWUE and IE ...................................... 14 Results and Discussion .................................................... 15 Seasonal Rainfall, Water Level Fluctuations, and Irrigations .................. 15 Amount of Rain Water Captured in the MPBS Reservoir .................... 18 Quantification and Comparison of Runoff ................................ 19 Plant Biomass .................................................... 21 Quantification of Irrigation Efficiencies and Water Savings of MPBS ............ 23 Conclusions ......................................................... 24

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vi 3. ANALYSIS OF GROWTH AND STRESS PARAMETERS OF Viburnum Odoratissimum (Ker-Gawl) GROWN IN WHITE AND BLACK MULTI-POT BOX SYSTEMS AND CONVENTIONAL SYSTEMS .............................39 Introduction ...........................................................39 Materials and Methods ...................................................44 Growth Index (GI)................................................44Crop Water Stress Index (CWSI).....................................45Stomatal Resistance (rs) Measurements................................46 Plant Water Potential (PWP) Measurements............................47Soil Matric Potential (SMP) Measurements............................47Substrate and Water Temperature Measurements........................48 Results and Discussion..................................................48 Growth Indices (GI)...............................................48Diurnal Pattern of Stomatal Resistance (rs).............................53 Crop Water Stress Index (CWSI).....................................56Diurnal Patterns of Plant Water Potential (PWP)........................59Daily Pattern of Soil Matric Potential (SMP)...........................61S ub s t r a t e T e m p e r a t u r e s ( S T ) ....................................... 6 2 C on c l u s i on s ........................................................... 6 5 4. CROP EVAPOTRANSPIRATION AND CROP COEFFICIENTS OF Viburnum Odoratissimum (Ker-Gawl) GROWN IN THE WHITE AND BLACK MULTIPOT BOX SYSTEM..............................................78 Introduction ...........................................................78 Materials and Methods ...................................................81 Results and Discussion..................................................84 Reference and Crop Evapotranspiration (ETo and ETc)....................84 Crop Coefficients (Kc).............................................86 Relationships Between Kc and GI..........................................90 Conclusions...........................................................915. QUANTIFICATION AND EVALUATION OF MULTIPLE LAYERS OFSUBSTRATE TEMPERATURES OF Viburnum odoratissimum GROWN IN THE WHITE AND BLACK MULTI-POT BOX SYSTEM AND CONVENTIONALSYSTEM.............................................................99Introduction ...........................................................99 Materials and Methods ..................................................102 R e s u lt s a n d D i s c u ss i o n ................................................. 10 4 S ea son a l P a tt e r n of D a ily M a x imum a nd Minimum ST a t Multiple L a y e r s ... 10 4 M a x im u m S T p a tt e r n s i n t h e s u mm e r g r o w i n g s ea s o n ............. 10 4

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vii Maximum ST patterns in the fall growing season.................106Ambient temperature inside the MPBS.........................108S ea s on a l p a tt e r n o f t h e w a t e r t e m p e r a t u r e i n t h e M P B S ............ 1 10 Minimum ST patterns in the summer and fall growing seasons......111 Diurnal Patterns of the ST.........................................112W a r m e s t D a y P a tt e r n ............................................. 11 3 Coldest Day Pattern..............................................114 C on c l u s i on s .......................................................... 11 6 6. PREDICTING ROOT-ZONE MEDIA TEMPERATURES OF Viburnum odoratissimum GROWN IN THE MULTI-POT BOX SYSTEM AND C ONVENT I ONAL S Y S TEM ...................................... 12 8 I ntroduction .......................................................... 12 8 Materials and Methods .................................................. 13 1 R e s u lt s a n d D i s c u ss i o n ................................................. 13 3 R Z T M od e l s f o r t h e W h it e a n d B l ac k M P B S s ......................... 13 5 R Z T Models for the Conventional Containers .......................... 13 8 C on c l u s i on s .......................................................... 1 40 7. C ON C L U S I ONS AND R E C OMMENDAT I ONS .......................... 14 8 R E F E R E N C E S ....................................................... 15 4 B I OG R A P H I C A L S K ET C H ............................................. 1 62

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viii LIST OF TABLES Table Page 2-1 Number of irrigation applications and total amount of irrigation water applied during the summer and fall.........................................35 2-2 Analysis of the shoot and root dry weights in the summer and fall ...........37 2-3 Total irrigation applied, amount of runoff (RO), total shoot and root dry weights, SIWUE, IE, and water savings of MPBS compared to the CS...............38 3-1 Statistical analysis of the GI, number of branch in each plant, shoot and root dry weights in the summer and fall ......................................67 4-1 Statistical analysis of the Kc values of the plants grown in the black versus white MPBS for the two growing seasons. ..................................97 5-1 S t a ti s ti cal ana l y s i s of t h e subs t r a t e t e m p era t ures for t h e su mm e r and fa l l . . . . 11 8 5-2 Maximum, minimum, and seasonal average values of the max ST in the control t r ea tm e n t i n t h e s u mm e r a n d f a l l . ................................... 11 9 5-3 Statistical analysis of the max ambient temperatures and water temperatures m ea s u r e d i n t h e r e s e r vo i r o f t h e M P B S s i n t h e s u mm e r a n d f a l l . ........... 11 9 6-1 Root mean square error (RMSE), seasonal average ratio of predicted to measured R Z T, r2, a n d t h e s i g n i f i ca n c e o f t h e i nd e p e nd e n t v a r i a b l e s ................ 14 3

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ix LIST OF FIGURES Figure Page 2-1 Original design of the black MPBS containing nine standard plastic containers (A) and some components of a white MPBS ...............................28 2-2 Modified MPBS components. Drainage tubes (A) and emitters on the main line (B).........................................................29 2-3 Level switch to control water level and irrigations (A) and poly pipe to connect the channels to enable a uniform water level in the reservoir (B)............30 2-4 Drainage pipes connected to the runoff tanks at the experimental site.........31 2-5 Daily and seasonal cumulative rainfall in the summer (A) and fall (B).......32 2-6 Water level fluctuations in the white (A) and black (B) MPBS in the summer.33 2-7 Water level fluctuations in the white (A) and black (B) MPBS during the fall ..34 2-8 Cumulative runoff from the white (W) and black (B) MPBS and control (CS) treatments in the summer ...........................................35 2-9 Cumulative runoff from the white (A) and black (B) MPBS and control (CS) treatments in the fall ...............................................36 3-1 Growth index (GI) throughout the summer (A) and fall (B) seasons .........66 3-2 Quantification of growth rates of plants grown in different treatments in the summer (A) and fall (B) seasons......................................68 3-3 Diurnal pattern of stomatal resistance of plants on July 21 (A) and July 25 (B) in the summer season. ...............................................69 3-4 Diurnal pattern of stomatal resistance of plants on September 20 (A) and December 20 (B) in the fall season. ..................................70

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x 3-5 Diurnal pattern of crop water stress index (CWSI) on July 21 (A) and July 25 (B) in the summer season..............................................71 3-6 Diurnal pattern of crop water stress index (CWSI) on September 20 (A) and December 20 (B) in the fall season. ...................................72 3-7 Diurnal pattern of plant water potential (PWP) on July 21 (A) and July 25 (B) in the summer season................................................73 3-8 Diurnal pattern of plant water potential (PWP) on September 20 (A) and December 20 (B) in the fall season. ...................................74 3-9 Daily changes in soil matric potential (SMP) during the summer (A) and fall growing seasons..................................................75 3-10 Diurnal pattern of the substrate temperatures (ST) on July 21 (A) and July 25 (B) in the summer season..............................................76 3-11 Diurnal pattern of the substrate temperatures (ST) on September 20 (A) and December 20 (B) in the fall season. ...................................77 4-1 Total surface area of the MPBS (A) and the reservoir (B) used to calculate crop evapotranspiration (ETc)............................................92 4-2 Some of the daily climate variables measured at the experimental site during the summer (May 17 August 9) and fall (August 28 December 21) ...........93 4-3 Reference evapotranspiration, ETo, (A) crop evapotranspiration (ETc) of plants grown in the black (B) and white (C) MPBS during the summer ............94 4-4 Reference evapotranspiration, ETo, (A) crop evapotranspiration (ETc) of plants grown in the black (B) and white (C) MPBS during the fall season...........95 4-5 Crop coefficients (Kc) of Viburnum odoratissimum grown in the black and white MPBS during the summer (A) and fall (B) seasons. ......................96 4-6 Relationship between crop coefficients (Kc) and growth index (GI) of plants grown in white (A) and black (B) MPBS in summer and fall ..............98 5-1 Seasonal pattern of daily maximum substrate temperature (ST) in the black (A) a n d w h it e ( B ) M P B S , a n d c on t r o l ( C ) du r i n g t h e s u mm e r ................ 1 20

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xi 5-2 Seasonal pattern of daily maximum substrate temperature (ST) in the black (A) a n d w h it e ( B ) M P B S , a n d c on t r o l ( C ) du r i n g t h e f a l l . ................... 12 1 5-3 Daily max ambient temperature inside the black and white MPBS and daily max a i r t e m p e r a t u r e i n t h e s u mm e r ( A ) a n d f a l l ( B ) s ea s on s .................. 12 2 5-4 Daily maximum and minimum water temperature in the white and black MPBS in t h e s u mm e r ( A ) a n d f a l l ( B ) g r o w i n g s ea s on s . ......................... 12 3 5-5 Seasonal pattern of daily minimum substrate temperature (ST) in the black (A) a n d w h it e ( B ) M P B S , a n d c on t r o l ( C ) du r i n g t h e s u mm e r s ea s o n ........... 12 4 5-6 Seasonal pattern of daily minimum substrate temperature (ST) in the black (A) a n d w h it e ( B ) M P B S , a n d c on t r o l ( C ) du r i n g t h e f a l l g r o w i n g s e a s on . ....... 12 5 5 7 D i u r n a l s ub s t r a t e t e m p e r a t u r e s ( w a r m e s t d a y p a tt e r n ) i n t h e s u mm e r ....... 12 6 5 8 D i u r n a l s ub s t r a t e t e m p e r a t u r e s ( c o l d e s t d a y s p a tt e r n ) i n t h e f a l l ............ 12 7 6-1 Relationships between maximum and minimum ambient air temperatures measured on the experimental plot and in the reference weather station for thef a l l ( A ) a n d s u mm e r ( B ) s ea s on s . .................................... 14 2 6-2 Calibration curves for the RZT models for predicting average min RZT in the w h it e a n d b l ac k M P B S s ( C ) i n t h e f a l l g r o w i n g s ea s on . .................. 14 4 6-3 Validation results of the RZT models for predicting max RZT in the white (A) and black (B) and for predicting average min RZT in the white and black MPBSs( C ) i n t h e s u mm e r g r o w i n g s ea s o n .................................. 14 5 6-4 Calibration curves for the RZT models for predicting max (A) and min (B) RZTs in the conventional containers in the fall g r owing season. ................ 14 6 6-5 Validation results of the RZT models for predicting max (A) and min (B) RZTs in the conventional containers in the summer g r owing season. ............... 14 7

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xii Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy NEW IRRIGATION-PLANT PRODUCTION SYSTEM FOR WATER CONSERVATION IN ORNAMENTAL NURSERIES By SUAT IRMAK August 2002 Chair: Dorota Z. Haman Department: Agricultural and Biological Engineering The objectives of this study were to quantify and analyze the performance of the black and white Multi-Pot Box Systems (MPBS) in regard to efficient use of irrigation and rain water and growth of Viburnum odoratissimum (Ker-Gawl) and compare the results with the performance of the conventional system (CS) for the summer and fall growing seasons under north-central Florida climate conditions. The substrate temperature (ST) in all systems were also evaluated. Models were developed to predict maximum and minimum root-zone temperatures (RZT) in the center of the containers placed in the MPBSs and CS. Results showed that in both growing seasons, plants grown in the white MPBS had significantly higher root and stem dry weights, growth index (GI), and growth rates compared to the plants grown in the black MPBS and CS. Plants in the white MPBS reached marketable size approximately 17 days and 86 days earlier (in the summer season) and 25

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xiii and 115 days earlier (in the fall season) than the plants grown in the black MPBS and CS, respectively. Results indicated that the MPBSs were very successful with regard to efficient use of irrigation and rainfall for Viburnum odoratissimum. Significant portions of the total rainfall were captured in the reservoir of the MPBSs during both growing seasons and later contributed to the plants increasing rainfall effectiveness and irrigation water use efficiency. The seasonal irrigation water use efficiency (SIWUE) was significantly higher for the plants grown in the white MPBS compared to the plants in the black MPBS and CS. The irrigation efficiency (IE) values for the white and black MPBS treatments were higher than 100% whereas it was only 19% in the summer and 15% in the fall season for the CS. At least 75% of water saving was achieved by using MPBS. However, in both seasons, the white MPBS treatments resulted in higher water savings compared to the black MPBS. The white MPBS provided more optimum growing media in terms of modifying extreme (hot and cold) ambient air temperatures in both seasons. Using the maximum and minimum air temperature and/or solar radiation as inputs, the models developed in this study were able to predict at least 74% and 90% of the variability of the max and min RZT, respectively. Results suggest the potential of MPBS for efficient use of water resources for container-grown ornamental plants. Results also suggest that under these experimental and climatic conditions, the white MPBS is superior to the black one and should be the first choice for growing Viburnum odoratissimum .

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1 CHAPTER 1 GENERAL INTRODUCTION The efficient use of water for plant production in irrigated agriculture has been a major concern for many years. Today, this concern is greater than before because of the increasing trend of decreasing fresh water resources and increasing water quality problems in many areas. In Florida, withdrawal of fresh water for irrigation, including container-grown ornamental plants, represents the largest of the stateÂ’s water pumping demands. The container nursery industry is an important source of ornamental plant production systems in Florida and this industry has increased dramatically in the last decade. The state of Florida is the second largest producer of nursery plants in the U.S., with an industry value of $1.3 billion in 1998 (Hodges et al., 1999) and more than 5,000 registered wholesale nursery growers (DPI, 1995). Approximately 85% of the value of Florida landscape and foliage crops is from container-produced material (Ingram and Henley, 1991). The acreage of container-grown nursery plants in Florida was approximately 15,000 ha in 1995 (USGS, 1999) and this production should continue to increase as FloridaÂ’s population increases. In Florida, most of the container-grown ornamental plants are being irrigated with overhead sprinkler systems. With these systems, the percentage of irrigation water actually reaching the container medium surface ranges from 12% to 50% (Beeson and Knox, 1991).

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2 Over the course of a production period, only 13% to 20% of the water applied overhead is retained for plant growth and the rest becomes runoff or evaporation (Weatherspoon and Harrell, 1980). Recently, environmental concerns have caused the container-grown nursery industry to consider changing some of the current agricultural practices. Major concerns include inefficient irrigation water management and runoff. Runoff decreases the efficiency of water use and results in contamination of other water resources with fertilizers, pesticides, and other chemicals. In Florida, water management agencies are recommending that nursery growers consider changing some of their operations and increase the efficiency of the irrigation systems they use. Future water regulations affecting FloridaÂ’s nursery industry may require an application efficiency of 75% for overhead sprinkler irrigation systems (Haman et al., 1998). In Florida, overhead irrigation has been restricted during midday since 1991. In certain regions, restrictions on annual irrigation volumes have been enacted and will likely expand. Thus, developing new irrigation/plant production systems that optimize plant growth and water conservation are crucial to Florida nursery industry and for the other water users. Recently, a new irrigation/plant production system, Multi-Pot Box System (MPBS), for increasing irrigation efficiencies and using rainfall harvesting techniques for containergrown nursery plants has been introduced. This system was designed to capture the rain and excess irrigation water, which usually runs off between the containers in conventional irrigation/production systems. Increases in irrigation efficiency can result in water conservation (desired by the water management districts) and can be economically feasible for the nursery industry.

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3 The overall objective of this research is to evaluate the effectiveness of the white and black MultiPot Box System (MPBS) for efficient use of irrigation and rainfall and plant growth for Viburnum odorati ssimum , Ker-Gawl. (Sweet viburnum) under north-central Florida climate conditions. The performance of the MPBSs was compared with the conventional system (CS) which represents a typical nursery plant production practice in Florida and in other states in the U.S. An additional objective was to provide practical suggestions to growers and users in terms of which color MPBS would be more feasible to use under these climate conditions. This dissertation consists of five chapters that address a specific objective. The overall materials and methods used in the studies are outlined in Chapter 2 and are not repeated in other chapters. In general, introduction, results and discussion, and conclusion sections of each chapter are organized independently. However, in some cases, the knowledge of the results of the previous chapters is required so that the next chapter can be better understood. The results of each chapter are based on the experiments carried out in the summer and fall growing seasons of 2001 in the campus of University of Florida, Gainesville, Florida. The organization and specific objective of each chapter can be summarized as follows: In Chapter 2, the seasonal irrigation water use efficiency (SIWUE), irrigation efficiency (IE), and efficient use of rain of black and white MPBS were quantified. The performance of the MPBSs was compared with the conventional system. The optimum depth for installing the level

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4 switches to obtain a minimal runoff and to increase irrigation efficiency were studied. In Chapter 3, the growth parameters [growth indices (GI), number of branches in each plant, and stem and root dry weights] of the plants grown in the white and black MPBSs and CS were analyzed. The plant stress parameters [stomatal resistance (rs), crop water stress index (CWSI), plant water potential (PWP), soil matric potential (SMP), and substrate temperature (ST)] were quantified and compared. Practical suggestions were outlined for the growers and users on the selection of which color MPBS would be more feasible to use under north-central Florida climate conditions. Chapter 4 studies measurement of crop water use and development of crop coefficients (Kc) of Viburnum odoratissimum. It also investigates the relationship between the Kc and the growth index (GI) to determine whether GI values can be used to accurately estimate Kc values. Chapter 5 evaluates the seasonal and diurnal pattern of multiple-layers of substrate temperatures in the containers and water temperatures in the reservoir of the MPBSs to determine the effectiveness of the black and white MPBSs and CS in terms of modifying the root-zone temperature of Viburnum odoratissimum against extreme ambient temperatures. In Chapter 6, practical models were developed using a multiple-regression technique for predicting maximum and minimum root-zone temperatures in the MPBSs and CS. Models were calibrated for the fall season and validated for the summer. Finally, Chapter 7 summarizes the conclusions of each chapter.

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5 CHAPTER 2 QUANTIFICATION AND EVALUATION OF IRRIGATION, RUNOFF, PLANT BIOMASS, AND IRRIGATION EFFICIENCIES Introduction Although the statewide average annual rainfall in humid subtropical Florida is relatively high (1,372 mm), because of uneven distribution of the rainfall in time and space, supplemental irrigation is needed for most plant production systems, including containergrown nursery plants. In Florida, withdrawal of fresh water for irrigation represents the largest of the stateÂ’s water-pumping demands. The state of Florida is the second largest producer of nursery plants in the U.S., with an industry value of $1.3 billion in 1998 (Hodges et al., 1998) and more than 5,000 registered wholesale nursery growers (DPI, 1995). Approximately 85% of the value of Florida landscape and foliage crops is from container-produced material (Ingram and Henley, 1991). The acreage of container-grown nursery plants in Florida was approximately 15,000 ha in 1995 (USGS, 1999) and this production should continue to increase as FloridaÂ’s population increases. As the population and industrial developments increase, water supply will likely become a major constraint in future irrigation developments. Therefore, future irrigation systems must use water resources more efficiently. In Florida, most of the container-grown ornamental plants are being irrigated with overhead sprinkler systems. However, with these systems, the percentage of irrigation water

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6 actually reaching the container medium surface ranges from 12% to 50% (Beeson and Knox, 1991). Over the course of a production period, only 13% to 20% of the water applied overhead is retained for plant growth and the rest becomes runoff or evaporation (Weatherspoon and Harrell, 1980). Recently, environmental concerns have caused the container-grown nursery industry to consider changing some of the current agricultural practices. Major concerns include inefficient irrigation water management and runoff. Runoff decreases the efficiency of water use and results in contamination of other water resources with fertilizers, pesticides, and other chemicals. In Florida, water management agencies are recommending that nursery growers must consider changing some of their operations and increase the efficiency of the irrigation systems they use. Future water regulations affecting FloridaÂ’s nursery industry may require an application efficiency of 75% for overhead sprinkler irrigation systems (Haman et al., 1998). In Florida, overhead irrigation has been restricted during midday since 1991. In certain regions, restrictions on annual irrigation volumes have been enacted and will likely expand. Thus, developing new irrigation/plant production systems that optimize plant growth and water conservation are crucial to Florida nursery industry and for the other water users. An efficient water management system should permit the following Application of irrigation water without allowing any water to leave the system due to runoff or deep percolation. Conjunctive use of rainfall by eliminating or minimizing runoff, even when rainfall closely follows an irrigation. Efficient use of applied water for crop production.

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7 Developing techniques for capturing and using rain water for irrigation will result in increased efficiency of the irrigation systems for container-grown nursery plants. This will also result in savings of both energy and water and will increase the amount of water resources available to the other sectors. A new irrigation/plant production system, Multi-Pot Box System (MPBS), for increasing irrigation efficiencies and using rainfall harvesting techniques for container-grown nursery plants was recently introduced (Haman et al., 1998; Irmak et al., 2001). This system was designed to capture the rain and excess irrigation water, which usually runs off between the containers in conventional irrigation/production systems. Haman et al. (1998) evaluated the MPBS and reported that by using this system for container-grown plants, the supplemental irrigation was significantly reduced. The quantity of irrigation water applied to the MPBS was approximately 84% less than that applied using the conventional irrigation practice with overhead sprinklers delivering 13 mm day-1. Irmak et al. (2001) evaluated the MPBS for efficient use of irrigation and rainfall in containergrown nursery plant production. They reported that significant portions of the total rainfall were captured (71.3% in the fall 1996 and 54% in fall 1997) and later supplied to plants increasing rainfall effectiveness and irrigation water use efficiency. They further reported that the seasonal irrigation water use efficiency (SIWUE) was significantly higher for MPBS compared to the conventional system, demonstrating that significantly less irrigation water was necessary to produce a higher or the same amount of plant dry mass (shoot and root). The original MPBS was black and irrigated with overhead sprinkler system. Since the development of the original system, significant modifications were implemented to the

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8 MPBS to be able to collect and quantify the amount of runoff from the system. The system irrigation was fully automated by installing level switches to control the water level in the MPBS and trigger irrigations. The optimum depth at which the level switches should be installed needs to be studied, because controlling the water level at different depths will result in different irrigation demands and runoff. The irrigation system was changed from overhead irrigation to drip irrigation which provided further water savings. Water savings using the drip irrigation need to be quantified. A white color MPBS was added to investigate the effect of the color of the system on plant growth and water use. Also, the amount of runoff from the MPBS and conventional system, and additional indicators to evaluate the efficiency of a given irrigation/plant production system, such as irrigation efficiency have not been studied. The objectives of this study were as follows: • To quantify the seasonal irrigation water use efficiency (SIWUE), irrigation efficiency (IE), and efficient use of rain water of black and white MPBS and compare with the conventional overhead-irrigated system. • To quantify and evaluate the plant biomass of the plants grown in the black and white MPBS and in the conventional system for container-grown Viburnum odoratissimum, Ker-Gawl.), a specie widely grown in peninsula Florida, under field conditions. • To determine the optimum depth for installing the level switch. • To develop practical suggestions to the MPBS users. Materials and Methods MPBS Description The original MPBS consisted of two sections (lower and upper) made of fiberglass painted black for UV protection (Fig. 2-1A and B). The surface area of the system was 0.787

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9 m2 (0.82 m x 0.96 m). The lower section (reservoir) had four longitudinal channels (approximately 0.106 m high) that formed water reservoirs with three ridges, sized so that the box can be moved by placing forklift tongues under the outer ridges. Each ridge was covered with 3-mm thick unsupported polyester (Troy Mills, Inc., Troy, NH) to serve as the wicking material. The wicking material kept the substrate wet (with capillarity) and enabled plant roots to extract water from the reservoir as needed. The upper section (0.35 m high) supported the containers and prevented or minimized the evaporation losses from the reservoir. This section fitted within the reservoir and had drainage channels (15 mm in diameter). Boxes were designed to be placed end to end. The surface of the upper section was concave around each opening to increase the effective surface area and capture the rain and irrigation water (if overhead irrigation is used). The lower section (reservoir) stored the captured water and this water was available to plants as needed. Each box contained nine plastic standard containers (C-650 The Lerio Corporation, El Campo, TX) with a volume, height, and diameter of 3.8 L, 0.17 m, and 0.15 m, respectively. Containers were modified by drilling four equally spaced holes (0.013 m in diameter) at the bottom of the containers to enable the substrate to be in contact with the wicking material for water absorption. Modifications of the MPBS The original MPBS was 0.35-m high and the plastic containers placed in the system were not supported by the upper section of the box properly. This resulted in containers being displaced on the ridge during windy conditions and it was difficult to remove the containers from the box (increasing labor demands). The upper section of the system was shortened by 0.05-m and, thus 0.05-m of the container was sitting above the surf ace of the box and

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10 supported by the upper section. To be able to collect and quantify the amount of runoff from the MPBS, four drainage tubes (25.4-mm in diameter) were installed to each side (a total of four tubes) at the surface of the reservoir. The drainage tubes then connected to the runoff collection tanks using a 12.7-mm diameter poly pipe (Fig. 2-2A and B). In the original MPBS the channels in the reservoir were not connected. In this study, the channels were connected to each other using a 12.7-mm diameter poly pipe to enable a uniform and equal level of water in each channel (Fig. 2-3B). A drip irrigation system was designed and used to irrigate the boxes for further water savings. Note that in the original design the MPBS was irrigated using an overhead sprinkler system. Each channel in the reservoir was equipped with a pressure-compensating drip irrigation emitter (Chapin Watermatics Inc., Watertown, NY). The emitters with an 7.6 L hr-1 flow rate were installed directly on the main line (Fig. 2-2B) and water was delivered to the box using a spaghetti tube and a lead tube weight placed in each channel. Thus, each box had four emitters with a total of 30.4 L hr-1 flow rate delivery capacity. The experimental plot (covered with a black polypropylene ground cloth) was leveled to a 3% slope at the beginning of the experiment so that the runoff would be collected by gravity. The runoff collection tanks (76 L by volume) were buried in the ground and located on the side of the experimental plot with the lowest elevation (Fig. 2-4). Description of the Conventional System (CS) The conventional system (CS) served as the control treatment in this study and represented the irrigation system commonly used by the nursery growers in Florida. Conventional containers in the CS were spaced in three rows 0.30-m apart and were set

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11 directly on separate black polypropylene ground cloth. To be able to collect the runoff from the CS, 0.82-m by 0.96 m trays were placed under nine c onventional containers and trays were connected to the runoff collection tanks using a 12.7-m diameter poly pipe. Field Experiments General experimental procedures Field experiments were carried out on the campus of the University of Florida, Gainesville, Florida (latitude 29o 38', longitude 82o 22', elevation 29.3-m) in the summer and fall 2001. Unless noted otherwise, the experimental procedures were the same for the two growing seasons. Viburnum odoratissimum, Ker-Gawl. (sweet viburnum) was used as the plant material. Seven treatments were imposed: White color MPBS with Model LS-7 side-mount level switches (State Instruments, Inc., Tampa, FL) installed at 0.01, 0.02, and 0.03 m (W1, W2, and W3) from the bottom of the reservoir. Black color MPBS with level switches installed at 0.01, 0.02, and 0.03 m (B1, B2, and B3). The conventional system (CS), control treatment, spaced on 0.30-m centers, treated as a control treatment. The level switches served two objectives: (i) to trigger irrigations automatically whenever the water level in the reservoir dropped to 0.01, 0.02, or 0.03 m (depending on the treatment), and (ii) to determine the optimum depth to install the level switches which results in minimum irrigation demand and runoff from the rainfall. In all treatments black #1 3.8-L modified plastic containers were used. Experiments in two seasons were designed as a randomized complete block and the treatments were replicated three times with the exception of the CS. The CS in each season were replicated six times. There were nine plants in each

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12 replication. When the plants in the MPBS treatments reached marketable size the experiment was terminated. However, at that time, plants in the CS were not at marketable size. Therefore, an additional three replications in the CS were used to monitor plant growth and to determine the shoot and root dry weights when the plants were at marketable size, because the total plant biomass was needed to quantify the SIWUE of the CS. Standard plastic containers were filled with a substrate of pine bark, Canadian peat, and sand (2:1:1 by volume) mix, amended with 4.2 kg m-3 of dolomitic James River Limestone and 0.9 kg m-3 of Micromax (The Scotts Company, Marysville, OH) and placed in each MPBS. The same substrate was used for the containers in the CS. Healthy and uniform size plants were transplanted into substrate-filled containers and grown for four weeks under the shaded-house (30% shade) and were hand-watered as needed. Four hundred sixty milligrams per container of liquid fertilizer (300 ppm of nitrogen, Peters 20-10-20) were applied to each pot before experiments began. Plants were top dressed with 0.014 kg container-1 of Osmocote 18N-2.6P-9.7K (18-6-12) controlled (slow)-release fertilizer (The Scotts Company, Marysville, OH) at the beginning of each experiment. Experiment starting and termination dates for the summer and fall seasons, respectively, were May 17, 2001 to August 9, 2001; and August 28, 2001 to December 21, 2001. Experiments were terminated whenever plants grown in the MPBS treatments reached approximately a marketable size based on the Florida Grades and Standards (Anonymous, 1997) at the grade of “Florida Fancy” for 3.8 to 7.6 L containers category. At termination, plants grown in the CS were not at a marketable size. Measurements, including plant growth, in this treatment were continued using the second sets (additional) of replications until the plants reached marketable size.

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13 Thus, at termination, half of the CS (three replications, 27 plants) were terminated for statistical analysis. At the termination, shoots of all plants were severed above the uppermost roots, the roots were cleaned from the substrate, and shoot and root dry weights were determined after drying to a constant weight at 70 oC. Shoot and root dry weights and other responses to treatments were analyzed by ANOVA (Analysis of Variance). When ANOVA identified treatment effects, DuncanÂ’s Multiple Range Test (DMRT) was used to identify which treatments differed at the 5% significance level. Irrigation applications The irrigated area of the CS was 6.0 m x 6.0 m. The CS plot was irrigated with four sprinkler heads (PGM-04-A, Hunter Industries, San Marcos, CA) mounted on a 1.3-m raiser and located at the corners of the plot. Water was applied daily for one hour with an irrigation application rate of 18 mm hr-1. The coefficients of uniformity for sprinkler irrigation system, Cu, (Christiansen, 1942) were 94% for the summer and fall seasons. Subsequent irrigations were applied to MPBSs whenever the reservoir in the bottom of the boxes receded to 0.01, 0.02, and 0.03-m, depending on the treatment. Irrigation was applied for 30 min to deliver approximately 16-L (20-mm) of water. The main purpose of not irrigating the boxes to the full depth (0.106-m) was to keep part of the reservoir empty to provide storage for the rain water. The Cu values of the drip irrigation systems used in MPBS were 97% for both seasons. Four water level measurements (one from each channel) in each box were taken and averaged. The volume of irrigation water applied to each box was measured with a Model C-700 precision flow-meter (ABB Water Meters, Inc, Ocala, FL). Thus, each box was irrigated individually. A rain sensor was installed to both the MPBS and

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14 CS treatments to shut off the irrigations when 12.7 mm rain occurred. Rainfall was recorded using a rain gauge at the experimental site. An irrigation controller and solenoid valves controlled irrigations. After each rain event, the runoff tanks were checked and the runoff water, if any, was pumped out of the tank into a graduated container (using a vacuum pump) and was measured. The depth of water in the reservoir was recorded on a daily basis by placing a scaled wood dowel vertically through a hole opened in the box surface to quantify the amount of rain water captured in the MPBS during both growing seasons. Determination of SIWUE and IE Irrigation efficiencies provide a basis for the comparison of different irrigation systems and water management tools from the standpoint of water beneficially used and crop yield per unit of water used. Irrigation efficiency can be calculated in number of ways and can be misinterpreted unless the specific usage of the term is carefully defined. The seasonal irrigation water use efficiency (SIWUE) generally refers to the ratio of crop yield to the volume of water delivered to produce the crop (Schneider et al., 1976; Stewart et al., 1981; Smajstrla et al., 1991). The SIWUE can be expressed as kilograms per cubic meter (kg m-3) in metric units. The most commonly used form of the SIWUE, as used in this study, can be written as follows SIWUE = Yi / Vi (2-1) where Yi is the irrigated crop yield or biomass (unit of mass), and Vi is the volume of irrigation water applied (unit of volume) in a growing season. The irrigation efficiency (IE) as defined by the American Society of Civil Engineers (ASCE) On-Farm Irrigation Committee (ASCE, 1978), and as used in this study, is the ratio

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15 of the volume of water which is beneficially used to the volume of irrigation water applied and is expressed as a percentage (Heermann et al., 1992) IE = Vb / Vf (2-2) where Vb is the volume of water beneficially used, and Vf is the volume of irrigation water delivered to the field or system. Results and Discussion Seasonal Rainfall, Water Level Fluctuations, and Irrigations The daily and seasonal cumulative rainfall for the summer and fall seasons, respectively, are given in Figs. 2-5A and B. Figure 2-5A shows that the summer season was quite wet and rainfall was distributed relatively uniformly throughout the season. The total rainfall for the summer growing season was 600-mm. This is a relatively high amount of rainfall because the statewide average annual rainfall of the state of Florida is 1,372-mm and, in this study, approximately 44% of the long-term annual average rainfall occurred from May 17 to August 8 (approximately in three months). Large rainfall events occurred on June 18 (36-mm), June 29 (44-mm), July 20 (102-mm), and July 30 (39-mm). No rainfall occurred at the beginning of the growing season (May 15 May 29). The fall season was dry compared to the summer time, with a seasonal total rainfall of 308 mm (Fig. 2-5B). Large rainfall events occurred on August 30 (28-mm), September 14 (78-mm), and September 22 (73.5-mm). The rainfall was not uniformly distributed throughout the fall season; most of the rainfall occurred at the beginning of the season and some occurred toward the end of the season. There was not much rainfall from Sep 25 to Nov 14.

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16 The daily water level fluctuations and irrigation events (IR) in the white and black MPBSs for the summer season are shown in Figs. 2-6A and B, respectively. Note that in Figs. 2-6A and B, the letters W and B indicate white and Black MPBSs, and the treatments W3, W2, W1, B3, B2, and B1 indicate the depth at which the level switches are installed (0.03, 0.02, and 0.01-m from the bottom of the reservoir, respectively). In the summer season, both white and black MPBS treatments showed similar patterns of water level fluctuations (Figs. 2-6A and B). The arrows on the lower left side of the X-axis show irrigation events. The water level in the MPBS treatments fluctuated, as expected, decreasing each day as the water in the reservoir was depleted by plants and/or evaporated from the container surface and increasing when irrigation or rain occurred. Early in the growing season, because of the lack of rainfall, the water level in the white and black MPBSs, respectively, dropped to a given treatment level only three and four times, respectively, and thus, there were only three irrigation applications in the white MPBS (Fig. 2-6A) and four applications in the black MPBS (Fig. 2-6B) in the summer growing season. The irrigation water applications were the same for all white box (three irrigations) treatments and for the black box treatments (four irrigations). A total of 96-mm (76-L) and 118-mm (93-L) of irrigation water was applied to the white and black MPBS, respectively, (Table 2-1). There were no irrigation applications after June 2 because the water level never dropped below 0.045 and 0.051-m in the white and black MPBS, respectively. There were 75 irrigations in the CS and a total of 1,425-mm water was applied during the fall. Note that the total water applied to the white and black MPBS treatments, respectively, was only 7%

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17 and 8% of the total water applied to the CS. Note that the same surface are (0.787 m2) was considered in the water applications to the MPBS and CS in both seasons. In the fall season, water levels in the MPBSs fluctuated more frequently compared to the summer season because of the dry conditions and more frequent irrigations in both white (Fig. 2-7A) and black (Fig. 2-7B) MPBSs. Because there were more than 45 irrigation events during the fall season in each treatment, the irrigation events are not shown. Figures 2-7A and B illustrate that the water levels in white and black box treatments showed similar patterns during the early growing season. The water level was high early in the growing season because of the extensive rainfall. There was no irrigation application to any treatment until early October. Unlike the summer season, starting from early October, frequent irrigation applications took place in both white and black box treatments. The water level in W3 treatment (white box, level switch at 0.03-m) was generally higher than in W2 (level switch at 0.02-m) and W1 (level switch at 0.01-m) throughout the fall season for both white and black box treatments. The number of irrigation applications and the total amount of irrigation water applied to each treatment are given in Table 2-1. This table shows that the irrigation applications varied somewhat within treatments. As expected, the W3 and B3 treatments resulted in the greatest number of irrigation applications (17 and 18 irrigations, respectively) and the least irrigation amounts were applied in W1and B1 treatments (14 and 15 irrigations, respectively). The number of irrigations in W2 and B2 treatments was 16. Total irrigation water applied varied from 400-mm in W3 and 414-mm in B3 treatments to 362-mm in W1 and 375-mm in B1 treatments. Total of 382-mm and 385-mm of water were applied to the

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18 W2 and B2 treatments, respectively. There were 101 irrigation applications in the CS and a total of 1,920 mm applied during the fall season. It is important to note that the total amounts of irrigation water applied to the MPBS treatments varied from only 19% of the total water applied to the CS in W1 to 22% of the CS in B3 treatments. Amount of Rain Water Captured in the MPBS Reservoir The water fluctuations in the MPBSs (Figs. 2-6A and B and 2-7A and B) indicated that the maximum reservoir capacity (approximately 106-mm) was reached several times during the summer and fall seasons. This indicates that runoff occurred during heavy rainfall event and a portion of the rainfall was lost from the MPBS reservoirs. However, relatively small rainfall events were highly effective because a minimum or no r unoff occurred, and rain water was collected in the reservoir of the MPBS and later supplied to plants by subirrigation. Because the MPBS is a semi-closed system, the evaporation losses from the water surface in the reservoir are minimal and most of the rain water collected in the reservoir was available to plants. The amount of rain water was captured in each MPBS reservoir was calculated from the water level measurements, on a daily basis, for the two seasons. Based on the statistical analysis, because there was no difference within the treatments in terms of the water levels in the box systems within the white and black box treatments in the summer season, the rain water was calculated for each white and black MPBS treatments and averaged. The total rainfall in the summer season was 600-mm. Results showed that 317-mm (53% of the total rainfall) and 328-mm (55% of the total rainfall) were captured in the reservoir of the white and black MPBSs, respectively, during the growing season.

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19 In the fall season, because the water fluctuations varied within and between treatments, the amount of rain water captured also varied slightly and, thus, the captured amount was calculated for each treatment. The total rainfall in the fall season was 308-mm. Results indicated that in the white box treatments for W3, W2, and W1, respectively, a total of 89, 92, and 85-mm of rain water were captured and later used by plants. The captured amounts were 29, 30, and 28% of the total rainfall. The captured amount of rain water was slightly higher in the black box treatments (B3, B2, and B1) compared to the white box treatments. A total of 105-mm (34% of the total rain), 101-mm (33% of the total rain), and 89-mm (29% of the total rain) were captured in the B3, B2, and B1 treatments, respectively. The lower rates of the captured rain water in the fall season were due to the higher water level in the reservoirs, compared to the summer season, because more frequent irrigation applications kept the water level higher in the reservoir. The captured amounts of rain water were considerable portions of the total rainfall that occurred in both seasons. Hence, the irrigation demand of plants grown in the MPBSs decreased significantly relative to the CS. In each irrigation, water was applied to refill the system reservoir up to approximately 60-mm water level so that a part of the reservoir was reserved for capturing and storing the rain water. If full irrigation was practiced (increasing water level to 106-mm), then the probability of runoff from the MPBS after the rainfall would be higher, and this could result in higher irrigation demand. Quantification and Comparison of Runoff In order to quantify the irrigation efficiency (IE) of the MPBSs and the conventional system (CS), the amount of water lost from the systems due to runoff was determined. As

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20 mentioned earlier, the runoff collection tanks (76-L by volume), buried into the ground and located on the side of the experimental plot, were used to collect and measure the runoff from each treatment and replication after each rain event. Figure 2-8 shows the measured runoff from the white (W) and black (B) MPBS and from the CS during the summer season. Because the summer was a very wet season, there was only slight differences in water level fluctuations within and among the boxes throughout the growing season (Figs. 2-6A and B). Thus, the amount of runoff within the white and black box treatments were similar. Therefore, in Fig. 2-8, the average runoff of three white (W3, W2, and W1) and three black box (B3, B2, and B1) treatments were plotted. The runoff occurred from the MPBS treatments when the water level in the box exceeded the maximum capacity (106-mm). Because the CS was being irrigated on a daily basis, with the exception of the days when 12.7-mm rain occurred, runoff occurred every day. Figure 2-8 shows that a total of 1,541-mm of water was lost between the containers to runoff in the CS because the CS does not have the capability of capturing and/or storing rain or excess irrigation water. The MPBS treatments resulted in much less runoff compared to the CS treatment. The average runoff measured from the white boxes was 283-mm and 272-mm from the black boxes. The maximum runoff from the CS and the MPBS treatments were measured on July 20 when 102-mm of rain occurred. The total runoffs on a depth basis (mm) from the white and black boxes, respectively, were only 18% and 22% of the runoff that occurred from the CS. The water level fluctuations showed slight variations among and within the box treatments, thus, runoff also varied slightly among the treatments in the fall growing season

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21 (Figs. 2-9A and B). However, the differences in measured total runoff within the white and black box treatments were not significantly different (p>0.05). Figure 2-9A shows that a total of 225, 219, and 216-mm of runoff occurred from the W3, W2, and W1 treatments, respectively. The runoff was slightly lower in the black box treatments; they were 210, 207, and 197-mm for the B3, B2, and B1 treatments, respectively, with W1 and B1resulting in the lowest runoff. The maximum runoff from all treatments was measured on Sep 14 when 78mm of rain occurred. As expected, the CS resulted in the greatest amount of runoff (2,040mm). On the average, the total runoff from the MPBS was only approximately 10% of the runoff that occurred from the CS. The amounts of runoff from the black box treatments were approximately 7-8% lower than those measured from the white box treatments in the fall season. Plant Biomass Shoot and root dry weights of the plants grown in the MPBS and CS for the summer and fall growing seasons are given in Table 2-2. Note that in Table 2-2, shoot and root dry weights of the CS plants are listed twice. This is because in both seasons, plants grown in the MPBS treatments reached marketable size much earlier than those grown in the CS. When the plants in the MPBS treatments were harvested, the first replication (27 plants) in the CS was harvested to have an equal number of data points for statistical analysis. At this time, plants in the CS were not at the marketable size. However, to quantify the SIWUE of the plants in the CS when they were at the marketable size, the knowledge of shoot and root dry weights were needed. Therefore, the measurements in the second sets of the replication in the CS were continued until plants reached marketable size.

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22 Table 2-2 shows that in both summer and fall seasons, the plants grown in the white MPBS resulted in significantly higher (p<0.05) shoot and root dry weights than the plants grown in the black MPBS and CS. However, neither shoot nor root dry weights within the both white and black box treatments were significantly different (p>0.05) in both growing seasons. Thus, these findings suggest that the controlling depth of the water at 0.01, 0.02, and 0.03-m level did not affect the plant growth in both seasons. It is also important to note that the plants grown in white and black MPBS resulted in significantly higher (p<0.05) shoot and root dry weights than the plants grown in CS in both seasons. The shoot dry weights of the plants in the white box system in the summer season were approximately 1.5 times larger than those obtained from the plants grown in the black box system, and, they were about 2.5 times larger than the plants in the CS. On the average, shoot dry weights of the plants in the black box system were approximately 1.8 times larger than those in the CS. The root dry weights showed similar results with root dry weights of the plants in the white box having about 1.5 times more weight than the black box plants and about 3 times more than those in the CS. The black box plants had 1.7 times higher root weights than the plants in the CS. Similar results were observed in the fall growing season. Both shoot and root dry weights of the plants grown in all treatments were higher in the summer season compared to the fall. Note that in most cases, the standard deviations (SD) of the shoot and root dry weights in the white box treatment were slightly higher compared to the black box and the CS. The above-mentioned plant dry weights in the CS were obtained when the plants grown in the MPBS reached marketable size. Note that plants are considered at the

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23 marketable size when they had growth index (GI) value of 40. When the plants in the MPBS were harvested, the CS had not reached marketable size. However, results in Table 2-2 showed that the plants in the CS produced significantly lower (p<0.05) shoot and root dry weights in both seasons compared to the white and black box treatments even when they reached marketable size. Quantification of Irrigation Efficiencies and Water Savings of MPBS Total irrigation applied, amount of runoff, total shoot and root dry weights, SIWUE, IE, and water savings of MPBS treatments are given in Table 2-3. Water savings of the MPBS treatments were compared with the CS. Results in Table 2-3 indicated that the MPBSs were much more effective in regard to SIWUE for container-grown Viburnum Odoratissimum compared to the CS. In the summer, the SIWUEs were significantly higher (p<0.05) for plants grown in white MPBS treatments (W3 = 0.791 kg m-3; W2 = 0.789 kg m-3; and W1 = 0.745 kg m-3) compared to the plants grown in black MPBS (B3 = 0.447 kg m-3; B2 = 0.420 kg m-3; and B1 = 0.440 kg m-3) and CS (0.022 kg m-3). Because the summer season was wetter than the fall the irrigation applications were fewer, resulting in higher SIWUE of the MPBSs. The SIWUEs were not significant (p>0.05) within the white and black MPBS treatments. The IE values for the white and black MPBS treatments were 100%, whereas it was only 19% for the CS indicating that only 19% of the water applied to the CS was beneficially used by the plants. Note that in IE calculations (Eq. 2-2) the total amount of irrigation water applied to the MPBS was assumed to be beneficially used and evaporation losses assumed to be negligible. Thus, IE for the MPBS treatments resulted in 100% efficiency. The water savings

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24 of the white and black MPBSs, respectively, were 92.2% and 90.4 relative to the CS treatment. Similar results were observed in the fall growing season. Due to the lower rainfall in the fall season compared to the summer (308 mm vs. 600 mm) the SIWUE and water savings were lower in this season (Table 2-3). The SIWUE were significantly higher (p<0.05) for plants grown in white MPBS treatments (W3 = 0.196 kg m-3; W2 = 0.191 kg m-3; and W1 =0.204 kg m-3) compared to the plants grown in black MPBS treatments (B3 = 0.141 kg m-3; B2 = 0.157 kg m-3; and B1 = 0.153 kg m-3) and CS (0.023 kg m-3). The SIWUEs were not significant (p>0.05) within the white and black MPBS treatments. The IEs for the white and black MPBS treatments were 100% whereas it was only 19% for the CS treatment. The water savings of the white MPBS treatments (W3, W2, and W1), respectively, were 76.3, 77.1, and 78.2%; and they were 75.2, 76.9, and 77.5% for the black MPBS treatments (B3, B2, and B1), respectively. In general the white MPBS treatments resulted in higher water savings compared to the black box treatments in both seasons. The W1 and B1 treatments resulted in higher water savings in the fall season. Conclusions The black and white color Multi-Pot Box Systems (MPBS) were investigated during the two growing seasons (summer and fall) in 2001 in north-central Florida climate for efficient use of irrigation and rainfall for container-grown nursery plant production. The systems were compared to the CS, consisting of black containers spaced on 0.30 m centers. The CS represents a typical system used by the majority of the nursery growers in Florida. Overall results showed that the MPBS was very effective in regard to irrigation water use

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25 efficiencies, rainfall harvesting, and plant biomass production compared to the CS. However, the irrigation efficiencies and plant biomass production of the white MPBS were significantly greater compared to the black MPBS. The specific findings and conclusions of the two experiments are summarized as follow: 1. The total water applied to the white and black MPBS treatments, respectively, were only 7% and 8% of the total water applied to the CS in the summer season, and in the fall, they were only 19% and 22%, respectively. In both seasons, the W1 and B1 (level switches installed at 0.01-m) treatments resulted in the least irrigation applications. 2. The total rainfall in the summer season was 600-mm. Results showed that 317-mm (53% of the total rainfall) and 328-mm (55% of the total rainfall) were captured in the reservoir of the white and black MPBSs, respectively, during the summer growing season. The total rainfall in the fall season was 308-mm. Results indicated that in the white box treatments, W3, W2, and W1, respectively, a total of 89, 92, and 85-mm of rain water was captured and later used by plants. The captured amounts were 29, 30, and 28% of the total rainfall. The captured amount of rain water was slightly higher in the black box treatments (B3, B2, and B1) compared to those captured in the white box treatments. A total of 105-mm (34% of the total rain), 101-mm (33% of the total rain), and 89-mm (29% of the total rain) were captured in the B3, B2, and B1 treatments, respectively. The captured amounts of rain water were considerable portions of the total rainfall that occurred in both seasons. Hence, the irrigation demand of plants grown in the MPBSs decreased significantly. 3. In the summer season, a total of 1,541-mm of water was lost to runoff in the CS because the CS does not have the capability of capturing and/or storing rain or excess

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26 irrigation water and because significant amount of irrigation and rain did not reach the containers due to container spacing. The MPBS treatments resulted in much less runoff compared to the CS treatment. The average runoff measured from the white boxes was 283mm and it was 272-mm from the black box. The total runoff from the white and black boxes was only 18% of the runoff from the CS treatment. In the fall, a total of 225, 219, and 216-mm of runoff occurred from the W3, W2, and W1 treatments, respectively. The runoff was slightly lower in the black box treatments, which were 210, 207, and 197-mm for the B3, B2, and B1 treatments, respectively, with W1 and B1resulting in the lowest runoff. As expected, the CS resulted in the greatest amount of runoff (2,040-mm). On the average, the total runoff from the MPBS was only approximately 10% of the runoff occurring from the CS. 4. In both seasons, plants grown in the white MPBS resulted in significantly higher (p<0.05) shoot and root dry weights than the plants grown in black MPBS and CS. However, neither shoot nor root dry weights within the white and black box treatments were significantly different in both growing seasons. Plants grown in white and black MPBSs resulted in significantly higher (p<0.05) shoot and root dry weight than the plants grown in conventional system in both seasons. 5. The SIWUEs were significantly higher (p<0.05) for plants grown in white MPBS treatments compared to the plants grown in black MPBS and CS. The SIWUEs were not significant within the white and black MPBS treatments. The IE values for the white and black MPBS treatments were 100% whereas it was only 19% in the summer and 15% in the fall season for the CS. The water savings of the white and black MPBSs was at least 75%

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27 relative to the CS. In both seasons, the white MPBS treatments resulted in higher water savings compared to the black boxes, and the W1 treatment had the highest water saving in the Fall season. In summary, the white MPBS with the control level switch at 0.01-m resulted in lower irrigation demand and less runoff compared to the other treatments, and the plant biomass production was not significantly different than the other white box treatments (W3 and W2). Thus, the overall experimental results suggested that under these experimental and similar climatic conditions, the white MPBS is superior to the black one and should be the first choice of the growers/users. The level switch installed at 0.01-m in the MPBS is a proper selection when irrigation scheduling, minimizing the runoff from the system, and the plant growth are considered.

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Upper section Lower section Ridges Channels 28Figure 2-1. Original design of the black MPBS containing nine standard plastic containers (A) and some components of a white MPBS placed on

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29 Drainage tubes A BEmitters Main line Figure 2-2. Modified MPBS components. Drainage tubes (A) and emitters on the main line (B).

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30 Level switch Drainage tube A Wicking material Poly pipe connecting the channels for a uniform water level BFigure 2-3. Level switch to control water level and irrigations (A) and poly pipe to connect the channels to enable a uniform water level in the reservoir (B).

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31 Runoff collection tanks Drainage pipes Figure 2-4. Drainage pipes connected to the runoff collection tanks at the experimental site.

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32 0 10 20 30 40 50 60 70 80 90 100 110 15-May30-May14-Jun29-Jun14-Jul29-Jul13-Aug DateRainfall (mm)0 100 200 300 400 500 600Cumulative rainfall (mm ) Rainfall Cumulative rainfal l SummerA 0 10 20 30 40 50 60 70 80 25-Aug9-Sep24-Sep9-Oct24-Oct8-Nov23-Nov8-Dec23-Dec DateRainfall (mm)0 50 100 150 200 250 300 350Cumulative rainfall (mm ) Rainfall Cumulative rainfal l FallBFigure 2-5. Daily and seasonal cumulative rainfall in the summer (A) and fall (B) growing seasons.

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33 0 10 20 30 40 50 60 70 80 90 100 110 15-May30-May14-Jun29-Jun14-Jul29-Jul13-Aug DateWater level (mm) W3 W2 W1 Summer IR A 0 10 20 30 40 50 60 70 80 90 100 110 15-May30-May14-Jun29-Jun14-Jul29-Jul13-Aug DateWater level (mm) B3 B2 B1 Summer IRB Figure 2-6. Water level fluctuations in the white (A) and black (B) MPBSs during the summer growing season. Each data point is an average of four measurements. Arrows on the lower left side of the X-axis show irrigation events (IR). Letters W and B represent white and black MPBS treatments, respectively. Numbers 1, 2, and 3 represent level switch installed at 0.01, 0.02, and 0.03m from the bottom of the reservoir, respectively.

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34 0 10 20 30 40 50 60 70 80 90 100 110 25-Aug9-Sep24-Sep9-Oct24-Oct8-Nov23-Nov8-Dec23-Dec DateWater level (mm) W3 W2 W1 FallA 0 10 20 30 40 50 60 70 80 90 100 110 25-Aug9-Sep24-Sep9-Oct24-Oct8-Nov23-Nov8-Dec23-Dec DateWater level (mm) B3 B2 B1 FallBFigure 2-7. Water level fluctuations in the white (A) and black (B) MPBS during the fall growing season. Each data point is an average of four measurements. Letters W and B represent white and black MPBS treatments, respectively. Numbers 1, 2, and 3 represent level switch installed at 0.01, 0.02, and 0.03-m from the bottom of the reservoir, respectively.

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35 0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 15-May30-May14-Jun29-Jun14-Jul29-Jul13-Aug DateCumulative runoff (mm) W (average) B (average) Contro l SummerTable 2-1. Number of irrigation applications and total amount of irrigation water applied to the treatments during the Summer and Fall growing seasons.Treatment Summer seasonFall season Number of irrig.*Total irrig. water applied (mm) Number of irrig.*Total irrig. water applied (mm) W339617400 W239616382 W139614362 B3411818414 B2411816385 B1411815375 Control751,4251011,920(*) The total irrigation includes 64-mm of water applied to fill up the reservoir at the beginning of the experiments in both seasons.Figure 2-8. Cumulative runoff measured from the white (W) and black (B) MPBS and control (CS) treatments in the Summer growing season.

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36 0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 25-Aug9-Sep24-Sep9-Oct24-Oct8-Nov23-Nov8-Dec23-Dec DateCumulative runoff (mm) W3 W2 W1 Control FallA 0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 25-Aug9-Sep24-Sep9-Oct24-Oct8-Nov23-Nov8-Dec23-Dec DateCumulative runoff (mm) B3 B2 B1 Control FallBFigure 2-9. Cumulative runoff measured from the white (A) and black (B) MPBS and control (CS) treatments in the Fall growing season.

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37 Table 2-2. Statistical analysis of the shoot and root dry weights of the plants grown in the white and black MPBSs and control (CS) treatments in the summer and fall growing seasons. Letters W and B represent white and black MPBS treatments, respectively. Numbers 1, 2, and 3 represent level switch installed at 0.01, 0.02, and 0.03 m from the bottom of the reservoir, respectively.Treatment Summer growing seasonFall growing season Shoot dry weight (g)†‡Root dry weight (g)†‡Shoot dry weight (g)†‡Root dry weight (g)†‡W346.4 (8.3)a*12.9 (2.5)a41.0 (7.7)a19.8 (3.0)a W246.3 (8.0)a12.9 (2.9)a38.6 (7.0)a18.8 (2.8)a W144.4 (8.2)a11.5 (3.0)a39.1 (7.1)a19.0 (2.9)a B332.7 (7.5)b8.90 (1.9)b32.4 (6.8)b13.5 (2.6)b B230.9 (7.5)b8.20 (1.6)b34.3 (7.2)b13.4 (2.2)b B131.9 (6.9)b9.10 (1.9)b32.3 (6.8)b12.9 (1.9)b Controlw17.7 (5.5)c4.30 (1.6)c21.0 (5.1)c10.1 (2.2)c Controlx21.0 (5.3)d5.60 (1.4)d24.0 (5.3)d11.2 (2.0)d (†) Average of 27 plants from three replications (nine plants in each replication). (‡) Values in parenthesis indicate standard deviations (SD). (*) Means followed by different letters among the treatments are significantly different (p<0.05). (w) Dry weights of the plants in control treatment harvested whenever the plants grown in the MPBS reached marketable size based on the Florida Grades and Standards (Anonymous, 1997) at the grade of “Florida Fancy” for 3.8 to 7.6-L container category. (x) Dry weights of the plants in the second sets of the replication (three replications, 27 plants). Since the plants in the control treatment were not at marketable size when the plants grown in the MPBSs were harvested, measurements were being taken from the second sets of the replication in the control treatment until the plants reached marketable size.

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38 Table 2-3. Total irrigation applied, amount of runoff (RO) due to irrigation, total shoot and root dry weights, SIWUE, IE, and water savings of MPBS compared to the CS. Letters W and B represent white and black MPBS treatments, respectively. Numbers 1, 2, and 3 represent level switch installed at 0.01, 0.02, and 0.03-m from the bottom of the reservoir, respectively.SeasonTRTuTot. Irrig. applied (m3)†RO due to irrig.uRain water beneficially used (m3) Shoot+root dry weight (kg)‡*SIWUE (kg m-3)wIE (%)yWater saving (%)SummerW30.0750.00.2490.05930.791a10092.2 W20.0750.00.2490.05920.789a10092.2 W10.0750.00.2490.05590.745a10092.2 B30.0930.00.2580.04160.447b10090.4 B20.0930.00.2580.03910.420b10090.4 B10.0930.00.2580.04100.440b10090.4 Control0.9700.8060.0200.02200.022c19.0-Fall W30.3100.00.0700.06080.196a10076.3 W20.3000.00.0720.05740.191a10077.1 W10.2850.00.0670.05810.204a10078.2 B30.3250.00.0830.04590.141b10075.2 B20.3030.00.0790.04770.157b10076.9 B10.2950.00.0700.04520.153b10077.5 Control1.3101.1300.0160.03110.023c15.0-(†) The amount of runoff due to only irrigation water applied. (‡) Ratio of the total dry mass to seasonal total irrigation water applied. (*) Means followed by different letters among the treatments are significantly different (p<0.05) as indicated by DMRT (Duncan’s Multiple Range Test). (u) In the calculations, only 0.787 m2 of irrigated area was considered for both MPBS and CS treatments. (w) Ratio of irrigation water beneficially used to irrigation water applied. All of the irrigation water applied to the MPBSs was assumed to be beneficially used. Evaporation losses were assumed to be negligible. (x) There was no runoff from the MPBSs due to irrigation. (y) Water savings of MPBS treatments relative to the control (CS) treatment.

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39 CHAPTER 3 ANALYSIS OF GROWTH AND STRESS PARAMETERS OF Viburnum Odoratissimum (Ker-Gawl) GROWN IN WHITE AND BLACK MULTI-POT BOX SYSTEMS AND CONVENTIONAL SYSTEMS Introduction One of the major challenges confronting nursery growers is to conserve water and minimize or prevent runoff while meeting the water requirements of plants growing in the containers. Currently, most of the nursery growers in Florida use overhead sprinkler irrigation system to irrigate nursery plants. However, studies (Weatherspoon and Harrell, 1980; Beeson and Knox, 1991; Karam and Niemiera, 1994) suggest that an overhead sprinkler system is a very inefficient method to irrigate container-grown nursery plants due to significant amounts of runoff and evaporation losses. However, in general, the overhead sprinkler system is the only economically feasible method of irrigating plants in small containers, # 12 L, (Karam and Niemiera, 1994) when material, labor costs, and projected plant market values are considered (Weatherspoon and Harrell, 1980). Improving the efficiency of the irrigation systems used in container nursery industry and developing new irrigation systems that utilize water resources more efficiently is not only a challenge to FloridaÂ’s growers, but to water management agencies and nursery growers in other states in the US as well. For example, Kabashima (1993) reports that growers throughout California are required to evaluate the potential liability of runoff from their operations because of California Safe Drinking Water and Toxic Enforcement Act of 1986, The Ground Water Protection Program (California Pesticide Contamination Prevention

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40 Act of 1985), and zero tolerance limits set by local agencies and advocated by environmental groups. Similar problems are being studied in other states. Recently, a new irrigation/plant production system (Multi-Pot Box System, MPBS) has been developed (Haman et al., 1998). A detailed description of the MPBSand CS are given by Irmak et al. (2001) and in Chapter 2. The seasonal irrigation water use efficiency (SIWUE) of plants grown in this system was analyzed by Irmak et al. (2001). Also, results in Chapter 2 showed that the irrigation efficiency (IE) of the white and black MPBSs were significantly higher compared to the conventional system (CS). The CS represented the typical irrigation/plant production system used by the nursery growers in Florida. By using MPBS, at least 75% of water saving was achieved compared to the CS. Because the MPBS was designed to capture rain and excess irrigation water, the irrigation demand of the plants grown in these systems was significantly reduced. In addition, in Chapter 2, the results also indicated that the white MPBS produced significantly higher plant biomass (stem and root dry matter) compared to the black MPBS and CS. In order to evaluate the growth and stress parameters of plants grown under different irrigation/plant production system, various indexes and/or indicators, such as growth index (GI), crop water stress index (CWSI), plant water potential (PWP), soil matric potential (SMP), and substrate temperature (ST) in the MPBSs and CS can be used. It is known that water stress can cause significant yield or plant biomass reductions. The degree of yield/biomass reduction can be more severe if plants experience water stress during the early growth stages. Thus, quantification of the amount of stress would help to evaluate and compare different irrigation/plant production systems in terms of which system provides optimum environments for plant growth.

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41 Canopy temperature (Tc) offers a good indication of plant stress. This approach is based on the assumption that, as water becomes a limiting factor, transpiration rate is reduced causing less evaporative cooling of leaves and increases Tc in relation to air temperature (Ta). Two approaches to quantifying the CWSI are available. In the empirical approach, the CWSI determined from measured canopy temperature, using infrared thermometers or other instruments, air temperature, and other climate variables was introduced by Idso et al. (1981). The method based on theoretical equations was developed by Jackson et al. (1981). In JacksonÂ’s method, the difference between canopy and air temperature (Tc Ta) is estimated from energy balance equations and is related to the CWSI. These two CWSI methods yield similar results under complete sun or complete shade (Reginato, 1983). Both CWSI concepts have been used by many researchers for many years to quantify crop water stress and for irrigation scheduling of agronomic crops (Pinter and Reginato, 1982; Reginato, 1983; Howell et al., 1984; OÂ’Toole et al., 1984; Reginato and Howe, 1985; Nielsen and Gardner, 1987; Reginato and Garrett, 1987; Wanjura et al., 1990; Irmak et al., 2000). However, the use of CWSI to quantify the stress of horticultural crops grown under different irrigation/production systems has been limited. This might be due to the complexity of the method. In this study, the method outlined by Jackson et al. (1981) was used to quantify the level of crop stress. The basic energy balance for a crop canopy surface, as derived by Jackson (1982), can be written as (3-1)RGHEn

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42 where Rn is the net radiation (MJ m-2 d-1), G is the heat flux below the canopy (MJ m-2 d-1), H is the sensible heat flux from the canopy to the air (MJ m-2 d-1), ! E is the latent heat flux to the air (MJ m-2 d-1). In their simplest forms, H and ! E can be expressed as (3-2)HcTTrpcaa ()/(3-3) Eceerrpsaas()/[()]where " = density of air (kg m-3) cp= heat capacity of air (MJ kg-1 oC-1) Tc= canopy surface temperature (oC) Ta= air temperature (oC) es= saturated vapor pressure (kPa) at Tcea= vapor pressure of the air (kPa) # = psychrometric constant (kPa oC-1) ra= aerodynamic resistance (s m-1) rs= stomatal resistance to vapor transport (s m-1). Combining Eqs. 3-1 to 3-3, assuming that G is negligible and defining $ as the slope of the saturated vapor pressure-temperature relation (es ea) / (Tc Ta) in units of kPa oC-1, the difference between the canopy and the air temperatures can be related to the vapor pressure deficit of the air (es ea), net radiation, and the aerodynamic and stomatal resistances (Jackson et al., 1982) as

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43 (3-4) TT rR c rr rr ee rrca an p sa sa sa sa (/) (/)(/) 1 11Under constant environmental conditions, the value of Tc Ta will vary with rs, and thus rs determines the upper (UP) and lower (LL) limits of the Tc Ta. Therefore, the upper limit of Tc Ta can be determined from Eq. 3-4 by allowing the rs to increase without bound, i.e., as rs 64 (3-5)()/ TTrRccaULanp The lower limit of the Tc -Ta can be determined by setting rs = 0 in Eq. 3-4: (3-6) () TT rR c eecaLL an p sa Then, using the Tc Ta, (Tc Ta)UL, and (Tc Ta)LL, the CWSI value can be calculated as (3-7) CWSI TTTT TTTTcacaLL caULcaLL ()() ()()Idso et al. (1981) and Jackson et al. (1981) indicated that the values of Tc-Ta and es-ea are linearly related for well irrigated plants transpiring at potential rate during the daylight hours. As soil moisture is depleted, the Tc-Ta versus es ea relationship deviates from the lower limit (non-stressed) of the Tc Ta condition, thus, the CWSI increases. The lower limit (LL) represents the maximum rate of transpiration of a well watered crop and the upper limit

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44 (UL) represents the Tc-Ta of a canopy with no transpiration and for which the canopy temperature does not respond to es ea. The CWSI varies from 0 to 1 with 1 representing a plant having no transpiration loss and 0 representing a plant transpiring at the maximum rate. The objectives of this chapter were to: (i) analyze growth parameters [growth indices (GI), number of branches in each plant, and stem and root dry weights] of the plants grown in the white and black MPBSs and CS, (ii) quantify plant stress parameters [stomatal resistance (rs), crop water stress index (CWSI), plant water potential (PWP), soil matric potential (SMP), and substrate temperature (ST)] and discuss possible reasons of why white MPBS produces higher plant biomass compared to the black MPBS and CS, and (iii) make practical suggestions to the growers/users on the selection of which color MPBS would be more feasible to use under north-central Florida climate conditions. Materials and Methods General experimental procedures are given in detail in Chapter II. Thus, in this chapter, experimental procedures related to determination of growth and stress parameters will be included. Growth Index (GI) Growth index (GI) can be used as an quantitative indicator of plant growth rate and to compare the size of the plants grown under different systems. Florida Grades and Standards (Anonymous, 1997) suggests that nursery plants are considered at marketable size when they reach GI value of 40 at the grade of “Florida Fancy” for 3.8 to 7.6 L containers category. In this study, plant heights, by measuring from the substrate surface to the tip of the tallest leaf, were taken on selected dates. On the same day, plant widths were measured in both EW and NS directions. In the summer and fall growing seasons, six growth

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45 measurements (height and width) were taken from the plants grown in the white and black MPBSs. Eleven and nine growth measurements were taken from the control treatment (conventional system, CS) in the summer and fall seasons, respectively. All plants were measured in all replications. Thus, a total of 189 plants were measured in each sampling date. Growth indices (GI) for each plant are calculated as GI = (H + (WEW + WNS) / 2) / 2(3-8) where, H is the plant height (m), WEW is the canopy width in east-west direction (m), and WNS is the canopy width in north-south direction (m). Crop Water Stress Index (CWSI) To determine the CWSI, several weather parameters were measured. An automated weather station was set on the short green grass site approximately 30 m from the experimental site. The grass was irrigated as needed and clipped when the grass was approximately 0.12 m tall to represent the reference conditions (Allen et al.,1994a, 1994b). The data collected at the weather station were: air temperature, relative humidity, total incoming solar radiation, wind speed at 2 m, and rainfall. All measurements were taken on hourly basis. To calculate CWSI values using Eqs. 3-4 through 3-7, the values of $ , Rn, es, and eawere calculated using equations 13, 21, 37, 38, 39, and 40 for % = 0.23; and 11, 12, respectively, as outlined in the Food and Agriculture Organization Paper No. 56 (FAO-56) (Allen et al., 1998). The von Karman constant (k) in the calculation of aerodynamic resistance (ra), and Stefan-Boltzmann constant ( & ) for the calculation of the net outgoing longwave radiation (Rnl) were taken as 0.41 and 4.903X10-9 MJ K-4 m-2 d-1, respectively. The values of zero plane displacement height (d) and roughness length governing momentum

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46 transfer (zom) in the calculation of ra were determined as d = 0.67 h, and zom = 0.123 h, where h is the plant height (m). The plant height (h) measurements taken on the same day as rsmeasurements were used in ra calculations rather than using a constant plant height (0.12 m). A value of 1.013X10-3 MJ kg-1 oC-1, which represents an average value of specific heat at constant pressure (cp), was used in the calculations. The latent heat of vaporization ( ! ) was taken as 2.45 MJ kg-1. Soil heat flux density (G) was assumed to be negligible. Stomatal Resistance (rs) Measurements The rs measurements in both seasons (summer and fall) were taken on selected days (two days in each season) when clear sky conditions were observed using a Model AP4 steady-state porometer (Delta-T Devices, Ltd., Cambridge, UK). The CWSI values for each treatment (W2, B2, and CS) were determined on hourly basis to observe diurnal pattern of the CWSI for a given treatment. Therefore, in summer season, the rs measurements were taken from 7 AM to 7 PM every hour on July 21 and July 25. In the fall season, the hourly rs measurements were taken from 7 AM to 7 PM on September 20, and from 9 AM to 5 PM on December 20. The number of measurements on December 20 were fewer compared to the other days due to the shorter daytime hours in the winter. The rs measurements were taken from 3 leaves (by taking 5 readings from each leaf) and from 7 plants in each treatment to obtain a good indication of the plant stress. Thus, a total of 105 measurements were taken for each treatment and averaged for every hour. The measurements were taken from the same leaf each hour. The porometer was calibrated based on the manufacturerÂ’s recommendations before the measurements. Precautions were taken to maintain each leafÂ’s natural orientation during the measurements. Finally, Eqs. 3-4 through 3-7 were used to calculate the CWSI values for each treatment.

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47 Plant Water Potential (PWP) Measurements On the same day that rs measurements were taken (July 21 and July 25 in summer growing season, and September 20 and December 20 in fall season), the plant water potential (PWP) measurements were taken on hourly basis using a Model 3005 plant water status console (pressure chamber) (Soil Moisture Equipment Corp., Santa Barbara, CA). Measurements were taken from 7 AM to 7 PM on all sampling dates, with the exception of December 20. On this day, measurements were taken from 8 AM to 5 PM. In each measurement, in order to prevent evaporative loss of stem and leaves water during measurements, the pressure chamber was set on the experimental plot and measurements were taken just after excision of stems (with two leaves attached) from the plant. Thus, approximately only 30 sec was spent from the excision to inserting the stem into the pressure chamber. After inserting the stem into the chamber, the pressure was increased slowly and the PWP was recorded from the pressure read-out gauge when sap first appeared at the cut end of the sample. Three stems were cut and sampled from each treatment (W2, B2, and CS) and then averaged within each treatment. Soil Matric Potential (SMP) Measurements To measure SMP in the containers, two Model LT (0.15 m tall) mini-tensiometers (Irrometer Company, Inc., Riverside, CA) were installed in White (W2) and Black (B2) MPBSs and CS at 0.08 m depth and recorded on a daily basis in the late afternoon hours between June 5 and August 8 in the summer season and between September 3 and December 19 in the fall season. These tensiometers were designed by the manufacturer specifically to operate at high SMP ranges in coarse sand and non-soil planting mixes (substrate) used in the container nursery industry.

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48 Substrate and Water Temperature Measurements Substrate temperature measurements were made every ten minutes and averaged on an hourly basis throughout the two growing seasons. The center container in each replication in the W2, B2, and CS treatments was equipped with thermocouples for substrate temperature measurements. Copper-constantan (0.0005 m) thermocouples were placed at middle depth (approximately 0.08 m from the bottom of the container) in the center of each container and the substrate was hand packed to enable adequate contact with the thermocouples. An additional thermocouple was placed at 1 m height above ground in the middle of the experimental plot to measure ambient air temperature. Additional thermocouples were placed in the reservoir of the white and black MPBSs reservoirs to measure water temperature. Two thermocouples were placed in each reservoir and temperature readings were then averaged. Thermocouples were connected to the data acquisition systems and measurements were recorded using a Model CR-10 datalogger and a model 32 M multiplexer (Campbell Scientific Inc., Logan, UT). Results and Discussion Growth Indices (GI) The amount of rainfall, daily water level fluctuations in the reservoirs of the MPBSs, and the number and total amount of irrigation applied to each treatment in each season are given in Chapter 2, and, therefore, it will not be repeated here. The growth indices (GI) of plants grown in the white and black MPBSs (W2 and B2) and CS throughout summer and fall growing seasons, respectively, (calculated from measured plant height and width using Eq. 3-8) are given in Figs. 3-1A and B, respectively. Other plant growth parameters, including stem and root dry weights at harvest, are also

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49 included in Table 3-1 for comparison. The GI values were calculated as average of three replications (nine plants in each replication) for each treatment. Figure 3-1A shows that plants grown in the white MPBS treatments reached marketable plant size earlier compared to the plants grown in the black MPBS and CS treatments. In the summer season, the final GI values of the plants grown in all white MPBS treatments (W1, W2, and W3) were significantly greater (p<0.05) (GIW1 = 48.4, GIW2 = 49.2, and GIW3 = 50.4), than those of plants grown in the black MPBS (GIB1 = 41.7, GIB2 = 40.0, and GIB3 = 43.1) and in the CS (GICS = 33.2) (Table 3-1). Note that at the time when plants in the MPBSs were harvested (August 9, 2001), the CS plants were not at marketable size. However, the growth measurements were continued from the plants in the second sets of the replication until they reached marketable size on October 10, 2001 (Fig. 3-1A). Analysis in Table 3-1 showed that the GI value of the plants in the CS was 40.1 on October 10. The number of branches in each plant were counted before the harvest and the average values are listed in Table 3-1. The plants grown in the white MPBS had significantly higher (p<0.05) number of stems compared to the other treatments. It is important to note in Table 3-1 that, in the summer season, none of the growth parameters of the plants within the white or black MPBS treatments were significantly different (p>0.05). Similar results were observed in the fall growing season. Figure 3-1B shows that plants grown in the white MPBS treatments reached marketable plant size earlier compared to the plants grown in the black MPBS and CS treatments. In the fall season, the final GI values of the plants grown in all white MPBS treatments (W1, W2, and W3) were also significantly greater (p<0.05) (GIW1 = 42.6, GIW2 = 42.5, and GIW3 = 43.0), than those grown in the black MPBS (GIB1 = 40.8, GIB2 = 41.1, and GIB3 = 40.5) and CS (GICS = 30.8) (Table

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50 3-1). Note that at the time when plants in the MPBSs were harvested (December 21, 2001), the CS plants were not at marketable size. However, the growth measurements were continued to be taken from the plants in the second sets of the replication until January 29. Even at this time CS plants did not reach marketable size (Fig. 3-1B), and GI value on that day was 34.6 (Table 3-1). The number of branches of the plants grown in the white and black MPBSs were not significantly different (p>0.05). However, both treatments had significantly higher (p<0.05) number of branches compared to the CS. It is important to note in Table 3-1 that, in the fall, none of the growth parameters of the plants within the white or black MPBS treatments were significantly different (p>0.05). Although Figs. 3-1A and B can provide useful information on the change in plant size and the date when plants reached marketable size (GI = 40), they do not provide quantitative information on the growth rate of the plants grown under different treatments. In Figs. 3-2A and B, the GI values are graphed as a function of days after transplanting (DAT, X-axis) for the summer and fall seasons, respectively, showing the difference in plant growth rates between the treatments. Because the growth parameters, including the GI values, were not significantly different within the white or black MPBS treatments, in Fig. 3-2A, the average GI values from white (average of W1, W2, and W3) and black (average of B1, B2, and B3) MPBS treatments were calculated and plotted. Figure 3-2A clearly indicates that, in the summer, plants grown in the white and black MPBSs showed exponential growth rate with plants grown in the white MPBS having higher growth rate (greater slope) compared to the plants grown in the black MPBS. The growth rate of the plants grown in the CS was linear. The

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51 resulting exponential and linear GI equations for the plants in the white and black MPBSs, and CS, respectively, as a function of days after transplanting (DAT) are (3-9)GIewhite DAT1841900105..(3-10)GIeblack DAT1963700081..(3-11)GIDATCS0129620034 ..The coefficients of determination (r2) of the Eqs. 3-9, 3-10, and 3-11, respectively, are 0.97 (n = 7), 0.98 (n = 7), and 0.98 (n = 11). Figures 3-2A and B allow for determination of the number of days required for the plants to reach marketable size (GI = 40). The dashed lines indicate exact dates when GI = 40. Figure 3-2A indicates that the plants grown in the white MPBS reached marketable size approximately 70 days after transplanting (DAT) whereas the plants in the black MPBS required 87 days. Plants in the CS required 156 days to reach marketable size in the summer season. Thus, plants in the white MPBS reached marketable size 17 days, and 86 days earlier than those in the black MPBS and CS, respectively. Figure 3-2B showed that, in the fall growing season, plants grown in the white and black MPBSs and CS had linear growth rate with plants grown in the white MPBS having higher growth rate (greater slope) compared to the other two treatments. Note that the plants in the white and black MPBSs had exponential growth in the summer season. The lower rates of plant growth in the fall season are attributed to the shorter day length, lower temperature, and lower solar radiation compared to the summer season. The coefficient determination (r2) value was used as an indicator to determine whether the growth rates were exponential or linear. In Fig. 3-2A, the exponential curve fit for the white and black MPBS treatments

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52 resulted in higher r2 value as compared to the linear whereas in Fig. 3-2B, the linear fit gave higher r2 than the exponential fit. The resulting linear GI equations for the plants in the white and black MPBSs, and CS, respectively, as a function of DAT are (3-12)GIDATwhite0271291115 ..(3-13)GIDATblack021710361 ..(3-14)GIDATCS0117413946 ..The r2 values of the Eqs. 3-12, 3-13, and 3-14, respectively, are 0.90 (n = 6), 0.92 (n = 6), and 0.98 (n = 9). Figure 3-2B indicates that the plants grown in the white MPBS reached marketable size approximately 103 DAT whereas the plants in the black MPBS reached marketable size 128 DAT, and plants in the CS never reached marketable size during the time period of the experiment. However, the measurements were continued from the plants in the CS until January 29, and after this day, the experiment had to be terminated. Therefore, the number of days that the CS plants reached marketable size needed to be estimated. Because the regression line of CS did not intercept with the “marketable plant size” line in Fig. 3-2B, the regression line was extended starting from the day of approximately 175 and intercepted (estimated) to the “marketable plant size” line. Then, the number of days required for the CS plants to reach marketable size was determined as 218 days. Thus, results indicated that the plants grown in the white MPBS treatments reached marketable size 25 days earlier than those of plants grown in the black MPBS. Based on the estimates, the CS plants would have reached marketable size 115 days (approximately 4 months) later.

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53 It is important to note that because of the nature of the color, the plants grown in the white MPBS treatments might have received and utilized more radiant energy compared to those of plants grown in the black MPBS and CS because plants in the white MPBS might have been able to utilize the radiant energy which was reflected from the white MPBS surface. Usually, higher radiant energy received on the canopy surface would eventually cause higher rates of photosynthesis and transpiration and, thus, this might have also accelerated plant growth and contributed to the significantly higher GI values of the plants grown in the white MPBS treatments. The results of plants grown in the white MPBS producing significantly higher (p<0.05) stem and root dry weights and having significantly higher GI values and growth rates compared to the other treatments provide significant information on which color of MPBS should be suggested to the growers/users under these climatic and experimental conditions. Growing the plants in a significantly shorter period of time is important and preferable for the growers when labor, energy costs, water savings, and other factors are considered. Diurnal Pattern of Stomatal Resistance (rs) As mentioned before, all r s measurements were made under generally clear sky conditions. The hourly maximum air temperatures ranged from about 22.4 to 36.8 oC on July 21; from 22.6 to 38.9 oC on July 25; from 21.7 to 36.2 oC on September 20; and from 7.4 to 22.0 oC on December 20 during the course of the measurements. The average wind speed on the day of measurements showed some variations. The average wind speed values on July 21, July 25, September 20, and December 20, respectively were 2.2, 3.3, 1.1, and 3.2 m sec-1.

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54 Diurnal patterns of r s measurements for summer and fall growing seasons, respectively, are given in Figs. 3-3A and B, and Fig. 3-4A and B. Similar patterns of diurnal changes in rs were obtained on all measurement dates. The rs values showed some variations during the day. In all measurement dates, with the exception of the December 20, plants grown in the white MPBS had significantly lower (p<0.05) stomatal resistances to vapor transport compared to the other two treatments, and plants grown in the black MPBS had significantly lower (p<0.05) rs values compared to the plants grown in the CS. On December 20, the rs values of the plants in the white and black MPBS were not significantly different (p>0.05). Results suggest that the plants in the white MPBS had less resistance to the water vapor transport and, thus, higher photosynthesis and transpiration rate and less plant stress. Generally, the rs values were found to be lowest in the morning hours and increased with time as the air temperature increased during the day. For example, the rs values were lowest for the plants grown in the white and black MPBS, and CS and they were 30, 46, 60 s m-1, respectively, at 7 AM on July 21 (Fig. 3-3A). Similar patterns, with different rs values, were observed on the other sampling dates. Although the time of the day with the highest rsvaried among the CS and MPBS treatments, they were usually similar for the white and black MPBS treatments. For example, the highest rs value of the plants grown in the white and black MPBS treatments were usually obtained in the late afternoon hours. The highest rsvalue for the plants in the white MPBS were at 6 PM (125 s m-1) on July 21, at 6 PM on July 25 (146 s m-1), at 6 PM (135 s m-1) on September 20, and at 5 PM (436 s m-1) on December 20 (Figs. 3-3A and B, and Figs. 3-4A and B, respectively). The highest rs value of the plants in the black MPBS were at 5 PM (150 s m-1) on July 21, at 6 PM on July 25 (188 s m-1), at 6 PM (166 s m-1) on September 20, and at 6 PM (320 s m-1) on December 20 (Figs. 3-3A and

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55 B, and Figs. 3-4A and B, respectively). On the other hand, the highest rs value of the plants in the CS showed significant variations and they were at 3 PM (340 s m-1) on July 21, at 7 PM on July 25 (493 s m-1), at 7 PM (380 s m-1) on September 20, and at 5 PM (1588 s m-1) on December 20 (Figs. 3-3A and B, and Figs. 3-4A and B, respectively). The plants grown in all treatments had considerably higher rs values on December 20 compared to those obtained in other sampling dates. This might be due to the lower air temperatures on December 20. Kramer (1983) reported that at low temperatures, responses to light and humidity are slower, and stomatal resistance usually increases. Note that the daily maximum air temperature ranged from low 20's to high 30's on July 21, July 25, and September 20 whereas the air temperature was much lower and ranged from 7.4 to 21.8 oC on December 20. It is also important to note that although rs measurements of the plants grown in the MPBS treatments were taken under well-watered, actively growing, and disease free conditions, they showed some resistance to water vapour transport. This is not surprising because while all above-mentioned conditions/variables are assumed to be constant, hourly rs measurements occurred under variable climate conditions. Also, stomatal activity is affected not only by the water availability to the plants, but is also affected by numerous internal (plant cell membranes have a natural resistance to water transports) and external factors, including, leaf water status, leaf temperature, substrate and irrigation water temperature, solar radiation and humidity, internal and external CO2 concentration, growth regulators, and more importantly interactions of these factors which are challenging to determine.

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56 Crop Water Stress Index (CWSI) The hourly CWSI values calculated using hourly rs measurements, Tc Ta, and upper and lower limits, UL and LL, (Eqs. 3-4 through 3-7) on July 21, July 25, September 20, and December 20 are shown in Figs. 3-5A and B, and 3-6A and B, respectively. Note that, on the day of each measurement, the plants grown in the white and black MPBS were assumed to have no water limiting conditions because water level in the reservoir of each MPBS was never dropped below 0.01m (depending on the treatment, as explained in the materials and methods section). An irrigation (18-mm) was applied at 6:30 AM on the day of each measurement to the plants grown in the CS. Results of four hourly measurements were similar for four sampling dates with plants grown in the white MPBS having the lowest CWSI values at all times. The CWSI values of plants in the white and black MPBSs were not significantly different (p >0.05). However, the CWSI values of the plants grown in both white and black MPBSs were significantly lower (p<0.05) than the values obtained from the plants in the CS. The hourly fluctuations of the CWSI for the plants in the CS were much larger compared to the CWSI of the plants in the white and black MPBS in all measurement dates. The general pattern of the hourly CWSI in all treatments were similar with lowest CWSI occurring in the early morning hours and increasing with time during the day and decreasing in the late afternoon hours. It has been reported (Idso et al., 1981; Jackson et al., 1981; Idso, 1982; Jackson, 1982; Reginato, 1983; and others) that for many agronomic crops, the maximum CWSI, CWSImax, usually occur at 12 PM to 2 PM. The maximum CWSI for the plants of this study usually occurred between 2 PM and 4 PM for the CS and between 12 PM and 3 PM for the MPBS treatments. Although, the max CWSI for all treatments were

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57 observed in the afternoon hours, the occurrence of the max stress level showed variations between the treatments and for the same treatment between the measurements dates. For example, on July 21, the CWSImax for the plants in the white and black MPBS occurred at 1 PM as 0.24 and 0.41, respectively, whereas the CWSImax for the CS was at 2 PM as 1.0 (Fig. 3-5A). On July 25, the CWSImax for the plants in the white MPBS was 0.26 at 2 PM, and it was 0.43 at 3 PM for the plants in the black MPBS (Fig. 3-5B). On the same day, for the plants in the CS, the stress level reached upper limit (UL = 1.0) two times at 2 and 3 PM, indicating that the plants grown in the CS were under severe stress at these times and they were not transpiring water because the canopy temperature (Tc) was not responding to the changes in vapor pressure deficit of the air (es ea). The CWSI value of 1.0 was also observed on July 21 at 2 PM for the plants grown in the CS (Fig. 3-5A). On September 20, the max CWSI for the CS was 0.86 and observed at 3 PM (Fig. 3-6A). The least difference in CWSI between the white and black MPBSs was observed on December 20. The daily average values of the CWSI of the plants in the white MPBS ranged from 0.08 on September 20 to 0.17 on July 25; for the plants in the black MPBS, they ranged from 0.13 on September 20 to 0.24 on July 25; and for the plants grown in the CS it ranged from 0.37 on September 20 to 0.56 on December 20. The hourly and daily average CWSI of all treatments were slightly higher on July 25 with the exception of CS. This is due to the higher temperature and solar radiation on that day compared to the other sampling dates. Also, as reported earlier, the daily average wind speed on July 25 was higher (3.3 m sec-1) than those measured on the other sampling dates (2.3 m sec-1 on July 21, 1.1 m sec-1 on September 20, and 3.2 m sec-1 on December 20). The wind speed effects on stomatal closure and on the

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58 degree of plant stress are discussed by Knoerr (1967), Caldwell (1970), Davies et al. (1974), and Kramer (1983). It is important to mention that each crop has a unique productivity response to water stress. Consequently, the value of maximum allowable CWSI for maximizing yield or dry matter production varies from crop to crop. For many agronomic crops, the maximum allowable CWSI values have been studied. For example, for wheat ( Triticum aestivum L.), corn ( Zea mays L.), and cotton ( Gossypium hirsutum L.) crops the CWSI value can be allowed to increase to 0.2 -0.3 index units (Gardner et al. 1992) between the irrigations without causing significant economic losses on the yield. There is a lack of research in determining the maximum allowable CWSI value that does not cause significant reduction in plant growth and/or in plant biomass for the ornamental plants. However, when the maximum CWSI values are considered, based on the results in Figs. 3-5 and 3-6, it would be appropriate to suggest that allowing Viburnum odoratissimum grown in the white MPBS to experience a maximum stress level of 0.30 during the growing season would not cause significant reductions in plant growth and dry matter production. The maximum CWSI values of 0.45 and 1.0 experienced by the plants grown in the black MPBS and CS during the two growing seasons and growth indices and root and shoot dry matters of these treatments were significantly lower than the plants grown in the white MPBS in two seasons. One might question why the CWSI of the plants grown in the MPBSs were not closer to zero because these plants were not under water limiting conditions and there was always an adequate water supply in the reservoir of the MPBS to be utilized by the plants as needed. However, one should also note that several other environmental variables, such as substrate temperature in the container, water temperature in the MPBS reservoir, root-zone

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59 temperature, etc., which can affect the root water uptake even if the water is available, are not considered in the determination of the CWSI (Eqs. 3-4 through 3-7). Also, Jackson (1982) points out that the relationship between CWSI and soil water content (or substrate water content in this case) is not unique, and it is affected greatly by the rooting volume and distribution, stress conditions of the root systems, and evaporative demand. Because precise information on the rooting volume and distribution are not available in this study, the exact correspondence of CWSI and soil water content in the substrate should not be expected. However, the diurnal changes of substrate and water temperatures, for the days that the CWSI values were determined and the rs measurements were made, are available and their effects on the plant stress will be discussed later in the chapter. Part of the CWSI values of the plants grown in the MPBSs might be associated with the heat-induced stress caused by the high substrate temperatures. It should be noted that the main objective of using CWSI in this study was only to quantify the stress level of plants in response to the treatments. Suggesting the use of CWSI for irrigation scheduling was not the intention because although the CWSI method was proven to be an effective method for scheduling irrigations in arid and semi-arid climates, in humid climates such as Florida, cloud cover observed in significant portion of the summer months can be an impediment for this method to be used for irrigation scheduling effectively. However, results indicated that the method can successfully be used to quantify the stress levels of plants grown under different plant production systems. Diurnal Patterns of Plant Water Potential (PWP) The diurnal changes in plant water potential (PWP) for each treatment (W2, B2, and CS) on July 21, July 25, September 20, and December 20 are presented in Figs. 3-7A, B and

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60 3-8A, B, respectively. Each data point for each hour represent an average of three measurements for each treatment. Generally, the diurnal trends of PWP were similar for all treatments with plants grown in the white MPBS showing higher (less negative) PWP values compared to the plants grown in other treatments in all sampling dates, with the exception of December 20 measurements. On December 20, white and black MPBS treatment plants had almost identical PWP values at each hour. The PWP values of white and black MPBS plants were not significantly different (p>0.05), however, they both were significantly higher (p<0.05) than those of values obtained from the CS plants on all sampling dates. These findings suggested that plants in the CS were under severe stress because water stress decreases PWP (Kirkham, 1990). The PWP was generally at the highest level early in the morning and decreased (greater negative values) during the day reaching the lowest values at around 4-5 PM in all treatments, and increasing later in the day as plants recovered from the stress. The lowest values of PWP were similar for each treatment on different days, with the exception of December 20, but they were different between the treatments. For example, the lowest PWP for the white MPBS plants were -620, -760, -690, and -600 kPa on July 21, July, 25, September 20, and December 20, respectively, the lowest values of PWP for the plants in the black MPBS were -800, -950, -845, and -630 kPa on the same days, respectively, whereas they were -1400, -1250, -1325, and -900 kPa being significantly lower for the plants in the CS. Note that the PWP values for all treatments were approximately 13, 27, and 32% lower for the plants in white and black MPBS, and CS, respectively, on December 20 when the air temperature and solar radiation were lower compared to the other sampling dates.

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61 The significantly lower PWP values in the CS plants, especially in the afternoon hours, are most likely due to the changes in water content in the containers during the day. Although the plants in the CS are irrigated daily, because of the very low water holding capacity of the substrate, the water content in the container decreases because of the rapid drainage, evaporation losses, and plant uptake. Thus, late in the afternoon, usually, there is not enough moisture left in the substrate resulting in lower PWP and plant stress. However, this may not be the only reason for low PWP of the plants because other environmental factors such as high substrate and root-zone temperatures can influence the root water uptake even if the water is available. The diurnal changes in root-zone temperatures of the plants in the white and black MPBSs, and CS will be discussed later. The PWP results support the previous findings in terms of diurnal patterns of the rsand CWSI and plants grown in the white MPBS experiencing less stress at all times compared to the plants grown in the black MPBS and CS. Daily Pattern of Soil Matric Potential (SMP) Daily changes in SMP for the summer and fall growing seasons are given in Figs. 39A and B, respectively. As expected, in both seasons, SMP showed more frequent fluctuations in the CS containers compared to the containers in the MPBSs. The SMP values for the white and black MPBS showed similar patterns during the two seasons, and they were not significantly different (p>0.05). The SMP values were significantly lower (p<0.05) (drier substrate) in the CS treatment compared to the other two treatments, ranging from -5.2 to 7.9 kPa (seasonal average -6.1 kPa) in summer and from -5.2 to -7.3 kPa (seasonal average = -6.4 kPa) in the fall growing season. The SMP in the white MPBS higher (wetter substrate) ranged from -1.2 to -2.9 kPa (seasonal average = -2.4 kPa) in the summer and from -2.3 to

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62 -3.6 kPa (seasonal average = -3.1 kPa) in the fall, and in the black MPBS, it ranged from -1.4to -3.1 kPa (seasonal average = -2.4 kPa) in summer and from -2.3 to -3.4 kPa (seasonalaverage = -3.1 kPa) in the fall. Because SMP is a good indicator of the availability of thewater to the plants, it can be seen from Figs. 3-9A and B that at any given day, there wasmore water available to the plants grown in the MPBSs compared to those plants grown inthe CS. The higher SMP values were expected for the substrate in the MPBSs because water level in the reservoir of each MPBS was never allowed to drop below 0.01 m or higher(depending on the treatment) during both growing seasons. Thus, a part of the substrate wasalways kept wet due to the capillarity forces via the wicking material that was placedbetween the container and the ridges of the reservoir. The lower SMP values obtained in thesubstrate of the CS containers were due to the rapid drainage, evaporation losses, anddepletion of the morning irrigation water by the plants. Note that the tensiometer readingswere usually taken in the afternoon hours and at that time most of the irrigation water in thecontainers was utilized and/or evaporated from the container surface. Earlier in the chapter,it was shown that the rs and CWSI values were significantly higher and PWP values were significantly lower, especially in the afternoon hours, for the plants grown in the CScompared to the plants in the white and black MPBSs. These higher degree of plant stresses,in part, can be attributed to the lower soil water content of the substrate in the CS throughoutthe two growing seasons, with the exception of the days when most of day was rainy.Subs t r a t e T e m p er a t u re s ( S T) The hourly substrate temperatures (ST) measured at 0.09 m depth in the containers for each treatment (W2, B2, and CS) for each plant stress sampling date (July 21, July 25,

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63 September 20, and D ecember 20) are presented in Figs. 3-10A and B, and 3-11A and B, respectively. Air temperatures were also included in the figures for comparison. Because ST patterns were similar for all measurement dates, only one day of hourly patterns of the STs will be discussed in detail. All figures showed that the ST of the plants grown in the white MPBS had lower temperatures throughout the day compared to the plants grown in the black MPBS and CS. On July 21 (Fig. 3-10A), the maximum ST was about 42.8 oC in the CS at 6 PM whereas the maximum ST of the white and black MPBSs, respectively, were 32.5 and 34.9 oC. The maximum air temperature on that day was 36.8 oC at 4 PM. Thus, the ST in the white MPBS was 10.3, 2.4, and 4.3 oC lower than the STs of CS, black MPBS, and air temperatures, respectively. Note that the maximum ST of CS was 6 oC higher than the air temperature. All temperatures, including the air temperature, started rising around noon and the rate of temperature rising in the white MPBS was slowest. The white and black MPBSs and the CS responded similarly to maximum ambient temperature with 4 (white and black MPBSs) and 3-hour (CS) phase delays. The ambient temperature started decreasing rapidly at 5 PM. The STs in the white and black MPBSs started to decrease slowly after 8 PM and the ST in the CS started decreasing after 7 PM with the ST in the MPBSs cooling down at a slower rate than the CS. This is an important buffering response of the MPBS because s udden temperature fluctuations can cause significant stress on plant roots and can negatively influence plant growth. Results indicated that the white MPBS successfully protected the root-zone against the extremely high ambient temperature. Similar results were apparent on July 25 (Fig. 3-10B) and September 20 (Fig. 3-11A). On these days, the STs of the white MPBS were up to 3.4 and 2.7 oC lower than the STs in

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64 the black MPBS in the afternoon hours, and they were up to 13.6 and 9.9 oC lower than the STs in the CS. On December 20 (Fig. 3-11B), the STs and air temperature were much lower compared to those obtained on the other sampling dates and the STs in the white and black MPBS were closer and the difference between the two STs were lower. The analysis of the seasonal pattern of the STs (results are not shown) indicated similar patterns of STs throughout the two seasons that were obtained on four sampling dates. Thus, results indicated that the white color MPBS provided more optimum environment for the root and plant growth when effectiveness of buffering against extreme ambient temperatures are considered. Levitt (1972) and Nielsen (1974) stated that the optimum root temperature is lower than the optimum leaf and stem temperatures for plant growth. However, roots are less adaptive to temperature extremes (low and high), and are more sensitive to sudden temperature fluctuations. The roots of most plants would be injured or the level of plant stress would increase if the root-zone was exposed to the same variations and durations of temperature to which the stems are subjected. Kramer (1983) reported that at extremely hot temperatures, the surface soil becomes hot enough to affect or even stop root growth, affect CO2 assimilation, and reduce root water absorption, thus, causing severe stresses on the plants. This is evident in these results that the root dry weights of the plants grown in the white MPBS, which always had lower substrate temperatures, had significantly higher root dry weights in both seasons compared to those of plants grown in the black MPBS and CS which had much higher substrate temperatures. As reported earlier in the CWSI section, plants grown in the white and black MPBSs were under some stress even though they were not under water-limiting conditions. Thus,

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65 based on the STs in the containers, part of the level of the CWSI values of the plants grown in the white and black MPBSs as well as the plants grown in the CS was attributed to heatinduced stresses caused by high STs. Conclusions The black and white color Multi-Pot Box Systems (MPBS) were investigated during two growing seasons (summer and fall) in 2001 in north-central Florida climate to quantify and analyze plant growth and stress parameters. The specific findings, conclusions, and recommendations from the two experiments are summarized as follows: 1. In both growing seasons, plants grown in the white MPBS had significantly higher growth index (GI) and growth rates compared to the plants grown in the black MPBS and conventional system (CS). Thus, plants grown in the white MPBS reached marketable size approximately 17 days and 86 days earlier (in the summer season) and 25 and 115 days earlier (in the fall season) than those in the black MPBS and CS, respectively. 2. In both growing seasons, plants grown in the white MPBS had lower stomatal resistances (rs), lower crop water stress index (CWSI) values, and higher (wetter) plant water potential (PWP) values compared to the plants grown in the black MPBS and CS. Thus, plants in the white MPBS were exposed to lower levels of plant stresses. The CWSI values of the plants grown in the white and black MPBSs as well as for the plants grown in the CS were partially attributed to heat-induced stress caused by high substrate temperatures. 3. The white color MPBS provided a better environment for root development and plant growth. Based on the experimental results of the two growing seasons, it is concluded that the use of white color MPBS is preferable to the black MPBS and CS for growing Viburnum odoratissimum under these climate conditions.

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15 20 25 30 35 40 45 50 55 ControlB1B2B3W1W2W3 TreatmentGrowth index (GI) 17-May-01 3-Jun-01 24-Jun-01 8-Jul-01 22-Jul-01 6-Aug-01 10-OctSummer Marketable plant sizeA 15 20 25 30 35 40 45 50 55 ControlB1B2B3W1W2W3 TreatmentGrowth index (GI) 31-Aug 20-Sep 25-Oct 10-Nov 24-Nov 20-Dec 29-JanFall Marketable plant sizeB 66Figure 3-1. Growth index (GI) values measured throughout the summer (A) and fall (B) growing seasons. The letters B and W represent black and white MPBS, respectively. The numbers 1, 2, and 3, represent the depths at which the level switches were installed (0.01, 0.02, and 0.03-m from the bottom of the reservoir, respectively).

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67Table 3-1. Statistical analysis of the GI at harvest, number of branch in each plant, shoot and root dry weights of the plants grown in the white and black MPBSs and control treatments (CS) in the summer and fall growing seasons. TRTSummer growing seasonFall growing season GI at harvest †# of branch in each plant †Shoot dry weight (g)†‡Root dry weight (g)†‡GI at harvest †# of branch in each plant †Shoot dry weight (g)†‡Root dry weight (g)†‡ W350.4 (4.0)a*10.1 (1.7)a46.4 (8.3)a12.9 (2.5)a43.0 (3.1)a8.3 (1.6)a41.0 (7.7)a19.8 (3.0)a W249.2 (3.8)a9.6 (1.6)a46.3 (8.0)a12.9 (2.9)a42.5 (5.4)a8.3 (1.4)a38.6 (7.0)a18.8 (2.8)a W148.4 (4.6)a9.4 (1.8)a44.4 (8.2)a11.5 (3.0)a42.6 (4.1)a7.9 (1.3)a39.1 (7.1)a19.0 (2.9)a B343.1 (4.6)b4.4 (2.0)b32.7 (7.5)b8.90 (1.9)b40.5 (7.2)b7.4 (1.4)a32.4 (6.8)b13.5 (2.6)b B240.0 (4.5)b4.3 (1.9)b30.9 (7.5)b8.20 (1.6)b41.1 (4.0)b7.4 (1.4)a34.3 (7.2)b13.4 (2.2)b B141.7 (4.7)b4.4 (1.4)b31.9 (6.9)b9.10 (1.9)b40.8 (5.7)b7.5 (1.2)a32.3 (6.8)b12.9 (1.9)b CSw33.2 (3.7)c2.4 (0.6)c17.7 (5.5)c4.30 (1.6)c30.8 (4.3)c5.0 (1.2)b21.0 (5.1)c10.1 (2.2)c CSx40.1 (3.8)NA21.0 (5.3)5.60 (1.4)34.6 (4.2)NA24.0 (5.3)10.8 (2.0) †) Average of 27 plants from three replications (nine plants in each replication). (‡) Values in parenthesis indicate standard deviations (SD). (*) Means followed by different letters among the treatments are significantly different (p<0.05). (w) Dry weights, GI, and number of branch of plants in the CS. These plants were harvested whenever the plants in the white MPBS reached marketable size based on the Florida Grades and Standards (Anonymous, 1997) at the grade of “Florida Fancy” for 3.8 to 7.6 -L container category. (x) Dry weights, GI, and number of stems of the plants in the second sets of the replication. Because plants in the CS were not at marketable size when the plants grown in the MPBSs were harvested, measurements were continued from the second sets of the replication in the CS until the plants reached marketable size. (NA) Not available.

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68 Y = 18.419e0.0105xr2 = 0.97 Y = 19.637e0.0081xr2 = 0.98 Y = 0.1296x + 20.034 r2 = 0.9815 20 25 30 35 40 45 50 55 020406080100120140160 Days after transplantingGrowth index (GI) White Black Control Summer Marketable plant size A Y = 0.1174x + 13.946 r2 = 0.97 Y = 0.2712x + 9.1115 r2 = 0.90 Y = 0.217x + 10.361 r2 = 0.9215 20 25 30 35 40 45 50 55 020406080100120140160180200220 Days after transplantingGrowth index (GI) White Black Control Fall Marketable plant size BFigure 3-2. Quantification of growth rates of plants grown in different treatments in the summer (A) and fall (B) growing seasons.

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69 0 100 200 300 400 500 78910111213141516171819 Time (hr)Stomatal resistance (s m-1) Control Black WhiteSummer, July 25 Noo n B 0 100 200 300 400 500 78910111213141516171819 Time (hr)Stomatal resistance (s m-1) Control Black WhiteSummer, July 21 NoonAFigure 3-3. Diurnal pattern of stomatal resistance of plants on July 21 (A) and July 25 (B) in the summer growing season.

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70 0 100 200 300 400 500 78910111213141516171819 Time (hr)Stomatal resistance (s m-1) Control Black WhiteFall, September 20 NoonA 0 200 400 600 800 1000 1200 1400 1600 78910111213141516171819 Time (hr)Stomatal resistance (s m-1) Control Black WhiteFall, December 20 NoonBFigure 3-4. Diurnal pattern of stomatal resistance of plants on September 20 (A) and December 20 (B) in the fall growing season.

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71 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 78910111213141516171819 Time (hr)CWSI Control Black WhiteSummer, July 21 N oo n A 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 78910111213141516171819 Time (hr)CWSI Control Black WhiteSummer, July 25 N oo n BFigure 3-5. Diurnal pattern of crop water stress index (CWSI) on July 21 (A) and July 25 (B) in the summer growing season.

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72 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 78910111213141516171819 Time (hr)CWSI Control Black WhiteFall, September 20 N oo n A 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 78910111213141516171819 Time (hr)CWSI Control Black WhiteFall, December 20 N oo n BFigure 3-6. Diurnal pattern of crop water stress index (CWSI) on September 20 (A) and December 20 (B) in the fall growing season.

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73 0 200 400 600 800 1000 1200 1400 78910111213141516171819 Time (hr)PWP (-kPa) Control Black WhiteSummer, July 21 NoonA 0 200 400 600 800 1000 1200 1400 78910111213141516171819 Time (hr)PWP (-kPa) Control Black WhiteSummer, July 25 NoonBFigure 3-7. Diurnal pattern of plant water potential (PWP) on July 21 (A) and July 25 (B) in the summer growing season. Each data point represent an average of three measurements.

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74 0 200 400 600 800 1000 1200 1400 78910111213141516171819 Time (hr)PWP (-kPa) Control Black WhiteFall, September 20 NoonA 0 200 400 600 800 1000 1200 1400 78910111213141516171819 Time (hr)PWP (-kPa) Control Black WhiteFall, December 20 N oo n BFigure 3-8. Diurnal pattern of plant water potential (PWP) on September 20 (A) and December 20 (B) in the fall growing season. Each data point represent an average of three measurements.

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75 0 1 2 3 4 5 6 7 8 5-Jun20-Jun5-Jul20-Jul4-Aug DateSMP (-kPa) Control Black WhiteSummerA 0 1 2 3 4 5 6 7 8 25-Aug9-Sep24-Sep9-Oct24-Oct8-Nov23-Nov8-Dec23-Dec DateSMP (-kPa) Control Black WhiteFallBFigure 3-9. Daily changes in soil matric potential (SMP) during the summer (A) and fall growing seasons. Each data point represent an average of two tensiometer readings for each treatment.

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76 10 15 20 25 30 35 40 45 50 1357911131517192123 Time (hr)Temperature (oC) Control Air Black WhiteJuly 21 N oo n A 10 15 20 25 30 35 40 45 50 1357911131517192123 Time (hr)Temperature (oC) Control Air Black WhiteJuly 25 N oo n BFigure 3-10. Diurnal pattern of the substrate temperatures (ST) at 0.09-m from the surface of the container on July 21 (A) and July 25 (B) in the summer growing season.

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77 10 15 20 25 30 35 40 45 50 1357911131517192123 Time (hr)Temperature (oC) Control Air Black WhiteSeptember 20 NoonA 0 5 10 15 20 25 30 35 40 45 50 1357911131517192123 Time (hr)Temperature (oC) Control Air Black WhiteDecember 20 NoonBFigure 3-11. Diurnal pattern of the substrate temperatures (ST) at 0.09-m from the surface of the container on September 20 (A) and December 20 (B) in the fall growing season.

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78 CHAPTER 4 CROP EVAPOTRANSPIRATION AND CROP COEFFICIENTS OF Viburnum Odoratissimum (Ker-Gawl) GROWN IN THE WHITE AND BLACK MULTI-POT BOX SYSTEM Introduction Determination of irrigation water requirements of nursery plants is of great importance as nursery growers are being challenged to conserve water and minimize runoff while meeting the plant water needs. Accurate estimates of plant water use are also important for efficient use of irrigation water and for calculation of regional water budgets. In the state of Florida, in 1995, a total of 630,000 m3 d-1 of fresh water was withdrawn for irrigation of container and field-grown nursery plants and 435,000 m3 d-1 (69% of the total) water withdrawn was used for irrigation of container-grown nursery plants (USGS, 1999). Problems in water allocation due to the limited water resources and increased water quality problems in many areas force decision makers to accurately determine the amount of water used by nurseries. An effective water management and water allocation require the knowledge of evapotranspiration of a particular crop (ETc) at various growth stages. Crop coefficient (Kc) relates reference evapotranspiration (ETo) to actual crop evapotranspiration accounting for crop characteristics and phenological growth stages. Dimensionless Kc values can be calculated as (Doorenbos and Pruitt, 1975; 1977) Kc = ETc / ETo(4-1) Jensen et al. (1990) stated that “ideally, ETo characterize the evaporative demand determined by meteorological conditions and a standard crop surface and Kc indicates the

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79 relative ability of a specific crop-soil surface to meet that demand.” Many factors affect the value of Kc such as crop characteristics, crop planting and sowing date, rate of crop development, length of growing season, and climate conditions (Doorenbos and Pruitt, 1977). Extensive research has been carried out on ETo methods and Kc because of their use in irrigation scheduling, water resources allocation, management, and planning (Jensen et al., 1990). Reference evapotranspiration (ETo) can be estimated using meteorological observations such as air temperature, solar radiation, wind speed, etc. The difficulty in Eq. 4-1 is the availability of the ETc values for a given crop at different growth stages because these values need to be measured experimentally to determine Kc. Various methods have been used during the past four decades to determine the experimental ETc and ETo data needed to develop Kc values for various crops (Jensen et al., 1990). ETo is usually calculated based on grass (ETo) or alfalfa (ETr) crop. The major advantage in using grass as the reference crop is the availability of a wide range of grass ET data from around the world representing many different climates (Jensen et al., 1990). Several sets of either alfalfa or grass-based Kc curves derived from these data have been published (Pruitt et al., 1972; Jensen, 1974; Doorenbos and Pruitt, 1977; Burman et al., 1980; Wright, 1979, 1981, 1982). However, most of these Kc values have been determined for agronomic crops, and the availability of experimentally determined Kc values for nursery plants is very limited. This is, in part, because the nursery industry produces hundreds of species and cultivars of ornamental plants that are very diverse in their cultural practices and water requirements.

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80 Burger et al. (1987) studied the stability of Kc values of different ornamental plants in four different locations in California and calculated Kc for two different container spacings (16/m2 container-width spacing, and 36/m2 container-to-container spacing) grown in 3-L containers. Kc values of 36/m2 spacing varied from 1.1 to 4.5 whereas they were higher for the 16/m2 spacing ranging from 1.7 to 5.1. They did not observe significant differences in Kcvalues across the locations. Schuch and Burger (1997) determined water use and Kc values of twelve species of woody ornamentals grown in containers in two locations (Riverside and Davis) in California. They reported that Kc values fluctuated seasonally from as much as 1 to 4.7 for plants with high water requirements and the values were stable for the plants with the low water requirements. They indicated that the Kc values were lower during periods of low ET, especially in fall and winter. They concluded that the Kc values of plants with high water demand need to be modified for different growth stages and growing locations. Because the measurement of ETc to calculate Kc is a difficult and time consuming task and often not possible, Kc values of crops have been estimated from climate, crop characteristics, and other variables. As indicated by Amos et al. (1989), various base scales have been used in normalizing Kc including days after emergence (Stegman et al., 1977), crop growth stage (Doorenbos and Kassam, 1979), percentage time from harvest to harvest by cutting in alfalfa (Medicago, sativa L.) (Wright, 1982), percent of time from planting to full cover and then elapsed days after full cover (Wright and Jensen, 1978), cumulative ETo(Hill et al., 1983), fraction of thermal units (Amos et al., 1989), and leaf area development (Wright, 1982).

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81 There is a need to determine Kc values for different ornamental plants grown under different management and climate conditions because the Kc values are affected considerably by many factors including crop type, climate, management c onditions, and others. The objectives of this study were to: (i) measure crop water use and develop crop coefficients of Viburnum odoratissimum ( Ker Gawl) grown in the white and black Multi-Pot Box Systems (MPBS) under north-central Florida climate conditions, (ii) investigate the relationship between the Kc and the growth index (GI) of Viburnum odoratissimum to determine whether GI values can be used to accurately estimate Kc values because GI value is used extensively in nursery industry to determine whether plants are at marketable size. Materials and Methods The general experimental procedures and other management practices including irrigation applications, measurements of water level fluctuations in the white and black MPBS, and growth index (GI) and plant biomass measurements, have been described in detail in Chapters 2 and 3. To determine water use by plants, the depth of water in the reservoir of both black and white MPBSs was recorded on a daily basis by placing a scaled wood dowel vertically through a hole in the box surface. These measurements were used to determine ETc and Kcon a daily basis. Measurements were taken from three replications and averaged for each treatment. For each day, the water level in a box was subtracted from the previous dayÂ’s water level and the amount of water used from the reservoir was calculated. To determine daily ETc (mm d-1), this change in water depth was converted to the water loss over the surface area of the entire box (production area) using the following equation ETc = crop water use @ (SAR / SAMPBS)(4-2)

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82 where SAR is the surface area of the reservoir (m2) and SAMPBS is the surface area of the MPBS (m2). The surface area of the reservoir is 0.4462 m2 (Fig 4-1A) and the surface area of the MPBS is 0.787 m2 (Fig. 4-1B). Thus, daily water use was multiplied by a constant (0.567) to calculate ETc on a daily basis. Daily values of ETo were calculated from the climate variables collected at the weather station using the modified Penman-Monteith equation as given by the Food and Agriculture Organization Paper No. 56 (FAO56-PM) (Allen et. al., 1998). The FAO56-PM equation has been recommended to be used to standardize the calculation of ETo that can be used to improve transferability of Kc values across different locations (Allen et al, 1994a, 1994b, Walter et al., 2000, Itenfisu et al., 2000). The equation is (4-3) ET= 0.408(RG) 900 T273 U(ee) (10.34U)o n2sa 2 where ETo= grass reference evapotranspiration (mm d-1) $ = slope of vapour pressure curve (kPa oC-1) Rn = mean daily net radiation (MJ m-2 d-1) G= soil heat flux (MJ m-2 d-1) # = psychrometric constant (0.0671 kPa oC-1) T= mean daily air temperature (Tmax + Tmin) /2, oC U2= wind speed at 2 m height (m s-1) es= saturation vapor pressure (kPa)

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83 ea= actual vapor pressure (kPa) es ea= saturation vapor pressure deficit (kPa) An automated weather station was set on the short green grass site approximately 30 m from the experimental site. The grass was irrigated as needed and clipped when it was approximately 0.12 m tall to represent the reference conditions (Allen et al.,1994a,b). The data collected at the weather station on hourly basis were: air temperature, dew point temperature, relative humidity, total incoming solar radiation, wind speed at 2 m, and rainfall. Daily values of $ , Rn, es, and ea were calculated using the equations 13; 21, 37, 38, 39, and 40 for albedo ( % = 0.23); and 11, 12, respectively, from FAO56-PM as given in Allen et al. (1998). The von Karman constant (k) in the calculation of aerodynamic resistance (ra), and Stefan-Boltzmann constant ( & ) for the calculation of the net outgoing longwave radiation (Rnl) were taken as 0.41 and 4.903X10-9 MJ K-4 m-2 d-1, respectively. A value of 1.013X10-3MJ kg-1 oC-1, which represents an average value of specific heat at constant temperature (cp), was used in the calculations. The latent heat of vaporization ( ! ) was taken as 2.45 MJ kg-1. Soil heat flux density (G) was assumed to be zero for daily time step. After estimating daily ETo and determining ETc, daily Kc values were calculated using Eq. 4-1. Kc values were then averaged over one week period. As a last step, Kc values were related to the growth index (GI) values. The GIs for the plants in the black and white MPBSs, respectively, were calculated as a function of days after transplanting (DAT) using the following equations developed in Chapter 3. The GIs for the summer season were calculated using the equations

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84 (4-4)GIewhite DAT1841900105..(4-5)GIeblack DAT1963700081..The coefficients of determination (r2) of the Eqs. 4-4, and 4-5, respectively, were 0.97 (n = 7) and 0.98 (n = 7). The GIs of the plants in the white and black box, respectively, for the fall season were calculated using the following equations (4-6)GIDATwhite0271291115 ..(4-7)GIDATblack021710361 ..The r2 values of the Eqs. 4-6 and 4-7, respectively, were 0.90 (n = 6) and 0.92 (n = 6). ETc and Kc responses to treatments (plants grown in the black and white MPBSs), and the relationships between Kc and GI in each growing season (summer and fall) were analyzed by ANOVA (Analysis of Variance) at the 5% significance level. Results and Discussion Reference and Crop Evapotranspiration (ETo and ETc) Some of the climate variables measured at the experimental site in both growing seasons included air temperature, solar radiation (Rs), relative humidity (RH), and wind speed at 2 m (U2) are given in Fig. 4-2A, B, C, and D, respectively. These daily values were used to estimate ETo. Note that the experiment start and termination dates for the summer and fall seasons, respectively, were May 17, 2001 August 9, 2001; and August 28, 2001 December 21, 2001. Air temperatures (Fig. 4-2A) in the summer season were higher than fall

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85 with Tmax ranging from 24.8 to 36 oC whereas they ranged from 10.4 to 35 oC in the fall season. Solar radiation (Fig. 4-2B) was also higher in the summer season compared to the fall, ranging from 5.3 to 27 MJ m-2 d-1 in the summer and from 1.9 to 22.7 MJ m-2 d-1 in the fall season. Average RH (Fig. 4-2C) and wind speed (Fig. 4-2D) were similar in both growing seasons. The highest wind speeds (1.54 m s-1) were observed from mid-September to mid-October. Daily ETo and ETc of plants grown in the black and white MPBSs, respectively, are presented in Figs. 4-3A, B, and C for the summer and in Figs. 4-4A, B, and C for the fall season, respectively. During the summer season, daily ETo values were higher compared to those obtained for the fall season due to the higher solar radiation and air temperature (Figs. 4-2A and B). The summer growing season had 32 mm higher seasonal total ETo than fall (360 mm vs. 328 mm) (Figs. 4-3A and 4-4A). ETo in fall season showed decreasing trend starting from late September. Because ETc is a function of daily ETo and plant growth, the increasing trend in ETcof plants in black and white MPBSs throughout both growing seasons is noticeable (Figs. 43B and 3C for summer and Figs. 4-4B, and 4-4C for the fall) as the plants size increased. In the summer season, ETc of plants in the black MPBS ranged from 2.4 mm on June 29 to 5.4 mm on August 1 whereas it ranged from 2.3 mm on June 5 to 6.8 mm on July 28 for the plants grown in the white MPBS. In general, plants in the white MPBS had higher ETc values compared to those in the black MPBS during the summer. The seasonal total ETc of the plants grown in the black MPBS was 26 mm lower than those of plants grown in the white MPBS (308 mm vs. 334 mm). However, daily ETc of the plants in black and white MPBS were not significantly different (p>0.05).

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86 In the fall growing season, ETc of plants in the black and white MPBS were similar, having lower values early in the growing season and increasing with time (Figs. 4-3B, 4-3C, 4-4B, and 4-4C). The minimum ETc of plants in the black MPBS was measured on September 13 as 1.3 mm and the maximum was on November 26 as 4.7 mm (Fig. 4-4B). The minimum ETc of plants in the white MPBS was also measured on September 13 as 0.7 mm and the maximum value (4.5 mm) was observed several times (October 16, October 25, November 26, and December 4) throughout the growing season (Fig. 4-4C). The seasonal total ETc of plants in the black and white box were similar (346 mm vs. 351 mm) and they were approximately 20 mm higher than ETo (328 mm). Daily ETc of the plants in black and white MPBS were not significantly different (p>0.05). It should be noted that, in the fall growing season, the seasonal total ETc values were higher than those measured in the summer. This is due to the total length of the growing season. Although the solar radiation and air temperature were higher in the summer growing season, the total length of the fall growing season was five weeks longer than the summer season (from May 17 through August 9 for the summer vs. from August 28 through December 21 for the fall growing season). Crop Coefficients (Kc) Kc values for the plants grown in the black and white MPBSs are plotted as a function of weeks after transplanting for summer and fall seasons in Figs. 4-5A and B, respectively. Kc values in figures were calculated on a daily basis and averaged on a weekly basis. Statistical analysis of the Kc values of plants in the black versus white MPBS within and between the growing seasons are presented in Table 4-1.

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87 The total growing period in the summer season was thirteen weeks. Kc of plants in the black and white MPBS yielded similar values in the summer season with Kc of plants in the black MPBS ranging from 0.64 two weeks after transplanting (WAT) to 1.29 just before the harvest whereas Kc of the plants in the white MPBS ranged from 0.51 two WAT to 1.50 just before the harvest (thirteen WAT) (Fig. 4-5A). As expected, for both treatments, the highest Kc values were obtained at the end of the growing season. In general, for agronomic crops, when plants are small after germination, Kc has a relatively small value that increases as plants grow until they reach maximum vegetative development. From maximum vegetative development to maturity Kc is typically observed to decrease (Guitjens, 1990) whereas unlike the annual agronomic crops, most of the nursery plants are perennial and continue growing; the ETc and Kc increases accordingly. Note that in the early growing season, the Kc of the plants in the black MPBS was slightly higher (0.64) than those of plants in the white MPBS (0.51). This is due to the plant sizes in the second week of the experiment. The plants in the black MPBS were slightly larger than those in the white MPBS (growth index results Chapter 3), thus, their ETc was slightly higher. Between the second and seventh week of the summer season, Kc of the plants in the black and white MPBS were similar and after the seventh week, Kc of the plants in the white MPBS started to increase and had higher values throughout the rest of the season as compared to Kc of the plants in the black MPBS. However, when all growing season is considered, Kc values of the plants grown in the black and white MPBS throughout the summer season were not significantly different (p>0.05) (Table 4-1). The growing period in the fall season was eighteen weeks. Kc values of both treatments were similar until the eleventh week ranging from 0.55 in the second WAT to

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88 1.33 in the eleventh WAT (Fig. 4-5B). After the eleventh week, ETc of plants in the white MPBS started to increase with a higher rate compared to those Kc values of the plants in the black MPBS. At the end of the season, plants in the white MPBS had a Kc value of 1.68 whereas it was 1.54 for the plants in the black MPBS. Kc values between the treatments were not significantly different (p>0.05) (Table 4-1). Statistical analysis of the Kc values between the summer and fall growing seasons in Table 4-1 showed that the Kc values of the plants grown in the black MPBS had significantly higher (p<0.05) values in the fall compared to the summer season. However, although the Kc values of the plants in the white MPBS were also higher in the fall season, differences were not significant (p>0.05) (Table 4-1) between the fall and summer. It is important to note that in Figs. 4-5A and B, when the Kc values for the plants grown in the white and black MPBSs are evaluated for the same growing period (from the beginning of the season to the end of the 13th WAT) in the summer and fall seasons, it appears that the Kc values within the treatments were similar in the two seasons, but were different between the treatments. For example, at the end of the 13th WAT, plants in the white MPBS had the Kc values of 1.5 in the summer and 1.44 in the fall, and the plants in the black MPBS had the Kc values of 1.29 in the summer and 1.32 in the fall. This is related to the ratio of the ETc to the ETo for a given treatment in the same growing period (until the end of the 13th WAT). For example, in the summer, the total Kc and ETo (until the end of the 13thWAT) of the plants in the white MPBS were 334 mm and 360 mm, respectively, and in the fall, they were 265 mm and 280 mm, respectively, (Figs. 4-4 and 4-5). Thus, the ratio of Kcto ETo for the plants grown in the white MPBS in the summer and fall seasons, respectively, were similar (0.93 and 0.95, respectively). Similar results were observed for the plants grown

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89 in the black MPBS. Although the plant water use and ETo were higher in the summer season compared to the fall, the ratio of ETc to ETo was similar due to the lower ETc and ETo in fall and this resulted in similar Kc values for the same growing period. Results in Chapter 3 showed that the plants grown in the white MPBS had significantly higher GI and growth rates compared to plants grown in the black MPBS in both seasons. Thus, higher Kc values of the plants grown in the white MPBS in both seasons are, in part, due to the higher growth rate of the plants grown in the white MPBS (Doorenbos and Pruitt, 1977) because higher growth rate usually result in higher ETc. It is important to note that the Kc values of the plants of these experiments were slightly higher, especially starting from the mid-growing season to the end of the season, than those reported by Doorenbos and Pruitt (1977) for most of the agronomic crops which rarely exceed 1.25. Schuch and Burger (1997) stated that “the plants growing in containers seem to have more similarities to isolated stands of vegetation than a uniform crop canopy. Isolated or nonuniform vegetation has a greater Kc value than large, continuous areas of plant cover.” This might be because, under normal conditions, single nursery plants capture and utilize higher amount of net radiation (Allen, 1993). In contrast, the Kc values obtained in this study (from 0.51 to 1.68) were considerably lower than those reported by Burger et al. (1987), Regan (1994), and Schuch and Burger (1997) which ranged from less than 1 to greater than 5. This is due to the difference in procedure that was used to determine the Kc values. Note that, in this study, Kc values were calculated using Eq. 4-1 after determining ETc values using Eq. 4-2 based on the ratio of the surface area of the water collection reservoir in the MPBS to the surface area of the MPBS whereas the Kc values in above-mentioned studies were calculated by dividing the crop water

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90 use by the surface area of the container to normalize the crop water use to a uniform surface area which is very different from the methods used in FAO56 (Allen et al., 1998) for agronomic crops. Also, it is important to mention that the spacing between the containers (in this study, the spacing in the conventional containers was 0.30 m container-to-container), the method used to calculate ETo, plant specie, climate, irrigation method used, and other factors will also contribute to the differences in Kc values. Relationships Between Kc and GI Schuch and Burger (1997) point out that the Kc values of the nursery plants are not often correlated to the area that is covered by the plant canopy and no adjustments are made for the change in canopy cover percentage when Kc values are calculated in their study. In this case, correlating the Kc values to an index which represent the size of the plant such as growth index (GI) would be an alternative and/or another option to estimate Kc because GI value is an indication of both canopy width and height of the plant and used extensively in horticultural research and other practices and often available. Thus, the possibility of using GI values to estimate Kc values of the Viburnum odoratissimum in both growing seasons is of interest. The relationship between experimentally derived Kc and GI values of plants grown in the white and black MPBS in summer and fall seasons, respectively, are plotted in Fig. 46A and B. Note that the GI values that were measured on selected days (six times in each growing season) were used and other values were estimated using Eqs. 4-4 and 4-5 for the summer and Eqs. 4-6 and 4-7 for the fall growing seasons, respectively, for the plants in the white and black MPBS, respectively. Figures 4-6A and B showed that good relationships existed between Kc and GI and as the GI increased the Kc values increased linearly in both

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91 seasons. The linear regression equations for estimating Kc from GI for the plants in the white MPBS for summer and fall growing seasons, respectively, are Kc-white-summer = 0.032GI 0.1546(r2 = 0.96, n = 12)(4-8) Kc-white-fall = 0.038GI + 0.0804(r2 = 0.96, n = 17)(4-9) The resulting linear regression equations for estimating Kc from GI for the plants in the black MPBS for summer and fall growing seasons, respectively, are Kc-black-summer = 0.0307GI 0.0785(r2 = 0.92, n = 12)(4-10) Kc-black-fall = 0.0415GI + 0.0701(r2 = 0.95, n = 17)(4-11) Regression results indicated that using only GI values, at least 92% of the variability can be explained when estimating Kc. Note that the slope of the regression lines of the plants grown in the white and black MPBS in the summer and fall growing seasons are different. This indicates that the relationship between Kc and GI is a function of the growing season and the Eqs. 4-8 through 4-9 should be used accordingly. Equations 4-8 through 4-11 were developed based on the GI values ranging from 13.2 to 48.4, thus, results of these equations should not be extrapolated beyond these boundaries. Conclusions Crop evapotranspiration (ETc) and crop coefficients (Kc) were quantified for Viburnum odoratissimum grown in white and black MPBS in summer and fall seasons under north-central Florida climatic conditions. Relationships between growth index (GI) and Kcwere investigated. Experimentally derived Kc values of this study add useful information to the nursery industry in terms of collection of ETc and Kc data for nursery crops and are among the first ETc and Kc data specifically for the Viburnum odoratissimum grown in the black and white MPBS. Variations were observed between the ETc and Kc values of the two

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92 Upper sectionsurface area = 0.787 m2 Lower section Ridges Channels (reservoir) Area = 0.4462 m2/4 channelsA Btreatments in the same season and for the same treatment between the seasons. Linearrelationships were obtained between GI and Kc (r2 $ 0.92) and equations were developed to estimate Kc using GI in two growing seasons (summer and fall) for the plants grown in the white and black MPBS. Equations developed to estimate Kc from GI would have a significant advantage over the method of estimating Kc from measured ETc and estimated ETo relation to water use determinations by regulatory agencies, because, in practice, measuring GI values is much more easier than measuring the ETc.Fi g u re 4 1. T o tal surface area of the MP B S ( A ) and the reser v oir ( B ) used to calculate crop e v apo t r a nsp i r a t i on ( E Tc).

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93Figure 4-2. Daily climate variables measured at the experimental site during the summer (May 17 August 9) and fall (August 28 December 21) seasons including air temperature (A), solar radiation, Rs, (B), relative humidity, RH, (C), and wind speed at 2 m, U2, (D). -5 0 5 10 15 20 25 30 35 40 1-May1-Jun2-Jul2-Aug2-Sep3-Oct3-Nov4-Dec DateTemperature (oC) Tmax Tmin TavgA 0 5 10 15 20 25 30 1-May1-Jun2-Jul2-Aug2-Sep3-Oct3-Nov4-Dec DateRs (MJ m-2 d-1)B 0 10 20 30 40 50 60 70 80 90 100 1-May1-Jun2-Jul2-Aug2-Sep3-Oct3-Nov4-Dec DateAverage RH (%)C 0.0 0.5 1.0 1.5 2.0 1-May1-Jun2-Jul2-Aug2-Sep3-Oct3-Nov4-Dec DateAverage U2 (m s-1)D

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94 ETo0 1 2 3 4 5 6 7Evapotranspiration (mm d-1) EToSummerASeasonal total = 360 mm 0 1 2 3 4 5 6 7Evapotranspiration (mm d-1) ETc (Black)BSeasonal total = 308 mm 0 1 2 3 4 5 6 7 15-May30-May14-Jun29-Jun14-Jul29-Jul13-Aug DateEvapotranspiration (mm d-1) ETc (White)CSeasonal total = 334 mmFigure 4-3. Reference evapotranspiration, ETo, (A) crop evapotranspiration (ETc) of plants grown in the black (B) and white (C) MPBS during the summer growing season.

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95 0 1 2 3 4 5 6 7Evapotranspiration (mm d-1) EToFallASeasonal total = 328 mm 0 1 2 3 4 5 6 7Evapotranspiration (mm d-1) ETc (Black)BSeasonal total = 346 mm 0 1 2 3 4 5 6 7 25-Aug9-Sep24-Sep9-Oct24-Oct8-Nov23-Nov8-Dec23-Dec DateEvapotranspiration (mm d-1) ETc (White)CSeasonal total = 351 mmFigure 4-4. Reference evapotranspiration, ETo, (A) crop evapotranspiration (ETc) of plants grown in the black (B) and white (C) MPBS during the fall growing season.

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96 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 123456789101112131415161718 Weeks after transplanting (WAT)Kc Kc (Black) Kc (White)SummerA 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 123456789101112131415161718 Weeks after transplanting (WAT)Kc Kc (Black) Kc (White)FallBFigure 4-5. Crop coefficients (Kc), as a function of weeks after transplanting (WAT), of Viburnum odoratissimum grown in the black and white MPBS during the summer (A) and Fall (B) growing seasons.

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97 Table 4-1. Statistical analysis of the Kc values of the plants grown in the black versus white MPBS for the two growing seasons. Growing seasonSS†MS ‡FFcriticalp Summer0.0140.0150.2334.3000.633 Fall0.0130.0130.1064.1490.747 Summer x Fall0.4960.0796.2434.2100.018 Summer x Fall0.4610.1193.8714.2100.059 (†) Sum of squares. (‡) Mean square.

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98 Kc = 0.0323GI 0.1546 r2 = 0.96 Kc = 0.0387GI + 0.0804 r2 = 0.960.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 101520253035404550 Growth index (GI)Kc Fall SummerAWhite box Kc = 0.0307GI 0.0785 r2 = 0.92Kc = 0.0415GI + 0.0701 r2 = 0.950.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 101520253035404550 Growth index (GI)Kc Fall SummerBlack boxBFigure 4-6. Relationship between crop coefficients (Kc) and growth index (GI) of plants grown in white (A) and black (B) MPBS in summer and fall growing seasons.

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99 CHAPTER 5 QUANTIFICATION AND EVALUATION OF MULTIPLE LAYERS OF SUBSTRATE TEMPERATURES OF Viburnum odoratissimum GROWN IN THE WHITE AND BLACK MULTI-POT BOX SYSTEM AND CONVENTIONAL SYSTEMIntroductionContainer-grown nursery plants have important production, marketing, and establishment advantages compared to field production. Substrate (container-medium) temperature (ST) is an important environmental variable that has a distinct effect on container-grown plant production. In ornamental industry, black plastic polyethylene containers have been used for raising the majority of the container-grown ornamental plants. One of the problems associated with the plant production in container-grown ornamental plants is exposure of the root system to extreme (high and low) temperatures during the growing season (Ruter, 1993) affecting the root distribution and plant growth. For example, roots are absent from the outer layers of the substrate of plants grown in the containers due to high temperatures in these zones, resulting from excessive heating caused by solar radiation (Young, and Hammett, 1980). In the conventional nursery containers, root-zone temperatures will often experience significant fluctuations and impose stress on plants unless the containers are insulated or some other precautions are taken. In general, the optimal temperature for root growth is less than for foliage and stems (Nielsen and Humphries, 1966; Pellett, 1971; Nielsen 1974; Havis, 1976; Levitt, 1980) and roots are more sensitive to sudden temperature fluctuations. Kramer (1940; 1949) reported that the root growth at soil temperatures above 29 oC may be retarded, while total cessation

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100 in many plant species occurs above 38 oC and the optimum root growth generally occurs at soil temperatures between 25 29 oC. In container-grown ornamental plant operations, it is suggested that the root-zone temperatures should be maintained below 40 oC to attenuate root injury and preserve optimum plant growth (Ingram et al., 1989; Martin et al., 1989, 1991; Wong et al., 1971). However, in the black plastic containers for growing ornamental plants, the extreme temperatures higher than the suggested optimum value are often reported. In Florida, substrate temperatures as high as 58 oC in container grown plants have been reported (Martin and Ingram, 1988). Ingram (1981) reported that substrate temperatures in black plastic containers can reach 45 oC for several hours per day during summer months causing root injury. Daily maximum temperatures greater than 50 oC have been reported in the substrate at the east and west black plastic container walls (Martin and Ingram, 1988). Fretz (1971) and Young and Hammett (1980) observed maximum temperatures in the black polyethylene containers during the summer as 49.5 oC and 50.8 oC. Several management practices and specially designed plant production systems are available to improve or optimize the root zone temperatures. In an attempt to address some of the extreme temperature impediments to container-grown plant production, Parkerson (1990) developed an in-ground pot-in-pot (IGPIP) system where a holder pot is permanently placed in the ground with the upper rim remaining above grade. The container-grown plant is then placed inside the holder pot for the growing season (Ruter, 1993). Studies showed that the IGPIP system insulates roots from high and low temperature extremes (Young and Bachman, 1996; Schluckebier and Martin, 1997). In another attempt for moderation of extreme temperature effects on the roots, a production system, similar to IGPIP system,

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101 above-ground pot-in pot (AGPIP) has been introduced (The Lerio Corporation and Nursery Supplies, Inc.) (London et al., 1998). Ingram (1981) suggested that 6 LT white poly bag can be successfully used as an alternative to conventional black rigid containers for three ornamental plant species when plant growth response, the range and distribution of substrate temperatures, and container durability are considered. Fretz (1971) studied temperature distributions in the nursery containers and reported that white, silver, and yellow exterior colors significantly reduced substrate temperatures when compared to darker colored metal containers. Young et al. (1987) compared white copolymer and clear poly plastics, single and double wall, on hoop houses for cold protection of ornamental plants in South Carolina. They reported that white copolymer was more effective in terms of freeze protection. Double-layered coverings resulted in higher soil and canopy temperatures compared to single-layered coverings. Martin and Ingram (1993) simulated the effect of container volume and shape on summer temperature patterns for black polyethylene containers in Arizona and Kentucky. As container volume increased, predicted daily maximum substrate temperature decreased at the center of the container. They found that the container shape has an effect on temperature patterns in the substrate as simulated temperature patterns adjacent to the container wall decreased as the wall tilt angle increased. They suggested that large containers with walls tilted outward may be practical for container nursery production in hot climates to lower root-zone temperatures because of the high ambient air temperatures during the summer. Ingram et al. (1988) studied container spacing strategies effects on modifying substrate temperatures.

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102 Recently, a new irrigation/plant production system (Multi-Pot Box System, MPBS) has been developed (Haman et al., 1998) for container-grown ornamentals. A detailed description of the MPBS is given by Irmak et al. (2001) and in Chapter 2. In Chapter 2, growth of Viburnum odoratissimum grown in the black and white MPBS and conventional system (CS) was investigated. The white MPBS produced significantly higher plant dry matter (shoot and root) and growth indices (GI) compared to the black MPBS and CS in the summer and fall seasons. The objectives of this study were: (i) to quantify and compare the seasonal and diurnal pattern of multiple-layers of substrate temperatures in the containers and water temperatures in the reservoir of the MPBSs for Viburnum odoratissimum grown in the black and white MPBS and CS.Materials and MethodsExperiments were conducted under field conditions in the summer and fall seasons of 2001 on the campus (Environmental Horticulture Greenhouse Complex) of the University of Florida, Gainesville, FL. General experimental procedures and design and other management practices including irrigation applications, measurements of growth index (GI) and plant biomass, have been described in detail in Chapter 2. Therefore, in this part, only the practices related to the temperature measurements will be discussed. Substrate temperature (ST) measurements were made every ten minutes and averaged on an hourly basis throughout the two growing seasons. Measurements were taken from May 23 to August 9 in summer and from August 29 to December 20 in fall growing season. The center container in two replications in the white and black MPBSs (W2 and B2, respectively), and conventional (control) (CS) treatments were equipped with thermocouples for ST measurements. Copper-constantan (0.0005-m) thermocouples were placed at depths

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103 of 0.03, 0.06, 0.09, 0.12, and 0.15-m from the surface. The substrate was hand packed to assure an adequate contact with the thermocouples. A thermocouple was placed at 1-m height above ground in the middle of the experimental plot to measure ambient air temperature. Additional thermocouples were placed in the reservoirs of the white and black MPBSs to measure water temperature every ten minutes. Two thermocouples were placed in each reservoir and temperature readings were then averaged. In addition, two thermocouples in center containers of the two replications of the black and white MPBS treatments were placed at the center to measure the ambient temperature inside the box systems. Thermocouples were connected to the data acquisition systems and measurements were recorded using a Model CR-10 datalogger and a model 32 M multiplexer (Campbell Scientific Inc., Logan, UT). An automated weather station was set on the short green grass site approximately 30 m from the experimental site to record necessary climate variables for model development. The grass was irrigated as needed and clipped when the grass was approximately 0.12 m tall to represent the reference conditions (Allen et al.,1994a, 1994b). The data collected at the weather station were: air temperature, relative humidity, total incoming solar radiation, wind speed at 2 m, and rainfall. All measurements were taken on hourly basis. Temperature responses to treatments were analyzed by ANOVA (Analysis of Variance). When ANOVA identified treatment effects, DuncanÂ’s Multiple Range Test (DMRT) was used to identify which treatments differed at the 5% significance level.

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104Results and Discussion Seasonal Pattern of Daily Maximum and Minimum ST at Multiple Layers Maximum ST patterns in the summer growing seasonFigures 5-1A, B, and C represent seasonal pattern of daily maximum ST at 0.03, 0.06, 0.09, 0.12, and 0.15 m depths for the containers placed in the black and white MPBS and CS, respectively, in the summer growing season. Statistical analysis of the differences in STs are given in Table 5-1. Figures 5-1A and B showed that the max ST in the black MPBS varied from 27.7 oC on June 1 to 41.1 oC on June 17 whereas seasonal STs were usually lower for the white MPBS ranging from 26.4 oC on July 31 to 38.7 oC on June 4. Statistical analysis showed that the STs at multiple layers were not significantly different (p>0.05) for the black or white MPBS during the growing season. However, when these STs for all layers were averaged for the black and white MPBS, results indicated that the average STs in the white MPBS were as much as 1.6 oC (seasonal average) significantly lower (p<0.05) than those in the black MPBS throughout the summer growing season (Table 5-1). During the period of May 23 to July 14, the STs in the black MPBS showed similar trend with the max air temperature, however, on the seasonal average, the STs were 2 oC to 3 oC higher than the air temperature (Fig. 5-1A). Starting from June 15, the STs in the black MPBS maintained 2 oC to 4 oC lower STs than the max air temperature for the rest of the growing season. In general, the white MPBS maintained 3 to 5 oC lower STs than the max air temperature throughout the growing season (Fig. 5-1B) indicating that the roots in the plastic container placed in the white MPBS were better protected from high temperatures compared to the plant roots in the black MPBS and control.

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105 The max STs at multiple layers showed significant variations in the control treatment in the summer season (Fig. 5-1C) and the magnitude of daily ST fluctuations were greater than those in the black and white MPBS throughout the growing season. Statistical analysis of the max STs between the layers are given in Table 5-1. The maximum, minimum, and seasonal average of the max ST at five different depths and the DuncanÂ’s Multiple Range Test results for the two seasons (to determine which layers are different from each other) are given in Table 5-2. Figure 5-1C showed that the max ST decreased with depth and the top layer (0.03 m) resulted in the highest ST throughout the season. Although the ST at this depth was higher than those in all other layers, it was only significantly higher (p<0.05) than the STs in 0.15 m depth (Table 5-2). The max, min, and seasonal average ST at 0.03 m were 48.4 oC, 28.3 oC, and 40.5 oC, respectively. ST at 0.06 m was higher than those in all other depths with the exception of the 0.03 m, however, it was only significantly higher (p<0.05) than the 0.15 m. The max ST at 0.06 m was 0.4 oC lower than the ST in the 0.03 m, and it was 1.2 oC, 3.1 oC, and 6.0 oC higher than those in the 0.09 m, 0.12 m, and 0.15 m depths, respectively. ST in the middle of the container (0.09 m) was lower than those in the 0.03 m and 0.06 m and higher than the ST in 0.12 m (Fig. 5-1C) throughout the season and these differences were not significant. However, ST in 0.09 m was significantly higher (p<0.05) than the ST in bottom layer (0.15 m). The max ST at 0.09 m was 1.6 oC and 1.2 oC lower than those in the 0.03 m and 0.06 m, respectively, and it was 1.9 oC and 4.8 oC higher than those in the 0.12 m and 0.15 m depths, respectively (Table 5-2). The min and seasonal average max ST at 0.09 m were 28.7 oC and 40.2 oC, respectively (Table 5-2). Although, in the summer, the ST at the 0.12 m depth was always lower than all other upper layers, differences were not significant (Table 5-1). However, ST at this depth was

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106 significantly warmer than the ST in the 0.15 m depth and the max, min, and seasonal average max ST, respectively, were 44.9 oC, 28.5 oC, and 39.3 oC (Table 5-2). The bottom layer (0.15 m) maintained consistently and significantly cooler ST than in all other layers. Note in Fig. 5-1C that the STs in 0.03 m, 0.06 m, 0.09 m, and 0.12 m layers were always higher than the air temperature throughout the season whereas the ST at the 0.15 m layer was usually cooler with the exception of the period between June 3 June 27 and July 17 July 28 where the ST at 0.15 m was 1.0 to 3.5 oC higher than the max air temperature. The max, min, and seasonal average max ST for the 0.15 m were the lowest (42.0 oC, 28.1 oC, and 36.8oC, respectively) among all layers (Table 5-2). Maximum ST patterns in the fall growing seasonSimilar results with lower STs due to the lower air temperature and solar radiation were obtained in the fall season. The ST in the black MPBS (Fig. 5-2A) ranged from 19.7oC to 42.1 oC. The ST between the layers were not significantly different. From August 29 to October 30, the ST in all layers followed similar values as the max air temperature. Starting from October 31 to the end of the season, the ST in all layers were 1.0 oC to 2.6 oC lower than the air temperature. In the early growing season (from August 29 to September 27), STs in the white MPBS were similar to the air temperature and starting from early October, white MPBS maintained 1.0 oC to 3.6 oC lower STs than the air temperature for the rest of the growing season (Fig. 5-2B). The STs between the layers were not significantly different. When the STs in all layers in each treatment (black and white MPBS) were averaged and analyzed, results in Table 5-1 showed that the averaged ST in the black MPBS was 1.3 oC (seasonal

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107 average) significantly higher (p<0.05) than those measured in the white MPBS in the fall season. STs in different layers in the control treatment were different from those obtained in the summer growing season (Fig. 5-2C). Statistical analysis of the STs in five layers for the control treatment are presented in Table 5-1 and the max, min, and seasonal average ST values and DMRT results are given in Table 5-2. STs were lower compared to those measured in the summer season for all layers. In contrast to the results in summer season, the ST in 0.06 m was the highest in the fall season (Fig. 5-2C), and it was only significantly higher than the STs in 0.12 m and 0.15 m layers (Table 5-1). This might indicate that a heat buildup occurred in this layer. The max, min, and seasonal average of max ST for the 0.06 m depth were 47.4 oC, 20.0 oC, and 33.8 oC, respectively (Table 5-2). Top layer (0.03 m) had significantly higher max STs than those measured in the 0.12 m. STs in 0.09 m were significantly higher than those measured in the 0.12 m and 0.15 m depths (Table 5-1). The differences in STs between the 0.12 and 0.15 m depths were not significant and 0.15 m maintained the coolest temperatures compared to all other layers during the fall season. All layers showed significant reduction in temperature starting from October 25 and continued until the end of the growing season due to the lower air temperature and solar radiation in this period of the season. In general, until November 23, all layers maintained 1.0 oC to 3.4 oC higher STs than the air temperature. After November 23 the STs in all layers had similar values as the air temperature until the end of the season. Overall results of the max ST patterns indicated that during the extremely warm periods in summer and fall growing season the ST in the white MPBS was significantly cooler than the black MPBS and the conventional system (control). The ST in the black

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108 MPBS and control exceeded the critical value (40 oC) cited in the literatures as negatively impacting root growth (Johnson and Ingram, 1984), leaf area (Graves et al., 1989), plant survival (Martin et al., 1991), root and shoot dry weights (Yeager et al., 1991), water status (Graves et al., 1989), and photosynthesis (Ruter and Ingram, 1992). Root death and/or injury, depending on the plant specie, often occurs when root-zone is exposed repeatedly to >40 oC (Johnson and Ingram, 1984; Ingram and Ramcharan, 1988; Martin et al., 1989). Root-zone temperatures below 40 oC is often reported as a value for optimum plant growth (Martin and Ingram, 1992). The ST in the control was above 45 oC for most of the summer season. These results suggest that the white MPBS successfully insulated the plant root-zone against extremely high ambient air temperatures in all five layers during the summer season providing optimum environment and enhancing plant growth significantly. Note that the results in Chapter 3 showed that the plants grown in the white MPBS had significantly higher root and shoot dry weights and growth indices in both growing seasons compared to the plants grown in the black MPBS and control. Ambient temperature inside the MPBSThe max ST being significantly higher in the control treatment compared to the MPBS treatments are mainly due to the fact that the containers in the control treatment are exposed to the direct effect of the extreme ambient temperature and solar radiation. The max ST in black MPBS being higher than those in the white MPBS is, in part, due to the black color absorption of radiant energy and increased ambient air temperature in the MPBS and consequently elevated ST in the black MPBS. It would be appropriate to assume that the white MPBS reflects more radiant energy received at the surface of the box compared to the black MPBS resulting in lower ambient and ST. In addition, the ST is a function of the soil

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109 moisture. In the MPBS, the irrigation water is supplied to the plants by subirrigation from the system reservoir. Thus, plants never experience water-limiting conditions and the water content of the root-zone in this system is usually higher compared to the other freely-drained conventional production systems. This high water content moderates the effect of the high air temperature. Soil moisture in the control containers decreases with time during the day and it reaches the minimum value in the late afternoon hours (personal observation) contributing to the high ST in the container. To further explore above-mentioned hypothesis, daily maximum ambient temperature measured in the center and half distance between the top and bottom of the box of the black and white box systems in the summer and fall growing seasons are graphed in Figs. 5-3A and B, respectively. In Figs. 5-3Aand B, the max air temperature was also included for comparison. Statistical analysis of the ambient temperatures in the MPBSs are given in Table 5-3. Figures 5-3A and B showed that the black MPBS maintained significantly higher (p<0.05) max ambient temperature compared to the white MPBS in the summer and fall growing seasons (Table 5-3). In the summer season, from the beginning of the season until July 2, the ambient temperature in the black MPBS showed almost identical trend to the max air temperature. After July 2, it maintained 0.5 oC to 3.5 oC lower temperatures than the air temperature for the rest of the season. Similar results obtained in the fall season. The max temperature inside the black MPBS had similar values from the beginning of the season until the end of the September, and it maintained 0.4 oC to 3.5 oC lower temperatures for the rest of the season. The white MPBS had 0.5 oC to 5.4 oC and 0.5 oC to 4.3 oC lower ambient temperatures than the air temperature in the summer and fall seasons, respectively. On the

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110 seasonal average, the ambient temperatures in the white MPBS were 1.8 and 1.7 oC lower than those measured in the black MPBS in the summer and fall seasons, respectively. Seasonal pattern of the water temperature in the reservoir of the MPBSThe significantly higher STs in the black MPBS during the periods of extremely high air temperature may also be due to the temperature of the irrigation water stored in the reservoir of the MPBSs. Figures 5-4A and B show the pattern of the water temperature in the reservoir of the black and white MPBSs in the summer and fall growing seasons, respectively. Statistical analysis of the water temperatures in the MPBSs are given in Table 5-3. In both seasons, water temperature in the black MPBS was significantly higher than in the white MPBS (Table 5-3). The minimum water temperatures were the same in both seasons. In the summer, the max water temperature in the black MPBS was up to 5.5 oC higher (June 5) than those in the white MPBS. On the seasonal average, the water temperature in the black box was 2.3 oC higher than in the white MPBS. The min water temperature ranged from 15.3 oC (May 25) to 24.4 oC (July 12). In the fall season, the water temperatures fluctuated much more than those in the summer and the max water temperature was up to 3.8 oC higher in the black MPBS than in the white. On the seasonal average, the water temperature in the black MPBS was 1.8 oC higher than in the white MPBS. The min water temperature ranged from 3.3 oC (November 7) to 23.4 oC (August 29). It is important to mention that the effect of irrigation water temperature upon the substrate or plant root-zone temperature depends on the temperature of both water and rootzone and the heat capacity of the soil (substrate) used in the containers. In addition, water has a much higher specific heat than soil minerals, and heat conductance through soils varies directly with soil moisture. During a sunny summer day, the temperature of water may well

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111 exceed the soil temperature. For example, analysis indicated that the water temperature in the black MPBS during the summer season was up to 2.2 oC higher than the substrate temperature at 0.09 m (results are not shown). During that season, the water temperature was higher than the substrate temperature for 44 days out of 79 days (total growing season). Thus, because plants in the black MPBS uptake the water from the system reservoir, in this case the irrigation water which had higher temperature than the substrate in the root-zone, will increase in root-zone temperature due to the flow of heat into the root-zone from the irrigation water.Minimum ST patterns in the summer and fall growing seasonsSeasonal pattern of min ST in the black and white MPBS and control for the summer season are given in Figs. 5-5A, B, and C, respectively. The min ST in the same treatment between the layers were not significantly different (p>0.05). Thus, all the temperature data from all layers in each treatment were averaged and analyzed. Statistical analysis in Table 5-1 showed that the averaged min ST between the treatments were not significantly different (p>0.05) for the summer or fall growing seasons. The min ST in the black MPBS ranged from 16.5 oC on May 25 to 24.5 oC on July 12. The min ST in the white MPBS also occurred on May 24 as 0.9 oC lower (15.6 oC) than the ST in the black MPBS. The highest min ST occurred on July 13 as 24.1 oC (0.4 oC lower than the black MPBS). On May 25 when the black and white MPBS had the lowest min ST, the ST in the control treatment was 17.7 oC (1.5 oC and 2.1 oC higher than those measured in the black and white MPBS, respectively). The lowest min ST in the control occurred on June 25 as 15.1 oC and the highest values were on July 12 as 23.9 oC.

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112 Daily patterns of the min ST in the fall season for the black and white MPBS and control are presented in Figs. 5-6A, B, and C, respectively. Fall season patterns were similar to those measured in the summer with lower min STs in all treatments. In all treatments, the daily min ST fluctuated more in fall as compared to the summer. The min ST between the treatments were not significantly different (Table 5-1). The min ST also showed almost identical patterns between the layers in each treatment and they were not significantly different. However, on the days that the lowest and highest values of min STs occurred, there were noticeable differences between the treatments. For example, the lowest min ST in the black MPBS was on November 7 as 2.4 oC and the highest value was measured on October 25 as 23.7 oC whereas the lowest value in the white MPBS occurred on the same day as 1.9oC (0.5 oC lower than the black MPBS) and the highest value was similar (23.4 oC). However, in the control treatment, the min ST on November 7 was very close to freezing point as 0.2 oC and it was 2.2 oC and 1.7 oC lower than those measured in the black and white MPBSs, respectively. The highest min ST was also observed on October 25 and it was similar (23.3 oC) to those obtained in the black and white MPBS treatments. The min ST was never below freezing point in any of the treatments during the season. The diurnal pattern of the max and min STs relative to the ambient air temperatures on the warmest day in the summer season and on the coldest day in the fall season will be discussed in the next section in order to better assess the performance of the buffering capability of each treatment against the extreme ambient temperatures.Diurnal Patterns of the ST Diurnal patterns of the ST in different treatments can provide important information on the buffering capability of the black and white MPBS as compared to the control

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113 containers. For this reason, four extreme days (warmest and coldest) (two hottest days in summer and two coldest days in fall) were graphed in order to evaluate the diurnal ST patterns in all treatments. However, the pattern of one of the each warmest and coldest days will be discussed in detail because the patterns are similar.Warmest Day PatternJune 17 and July 7, two days when the ambient max air temperature reached 40.0 oC and 40.1 oC, respectively, were selected in the summer season. Diurnal pattern of max temperatures on only June 17 will be discussed in detail. Figure 5-7A and B represents diurnal ambient temperature, ST of black and white MPBS, and conventional (control) production systems at 0.09 m depth for the two of the warmest days of the summer growing season. Figure 5-7A shows that the ST in the black and white MPBSs had identical values from 1 AM to 7 AM maintaining approximately 2.3 oC higher temperatures than the air temperature. ST in the control container had identical values to the air temperatures in this period. The air temperature started increasing at 8 AM whereas the control and MPBSs started rising in temperature at 10 AM with 2-hour phase delay. The rate of temperature rising in the white MPBS was the slowest. STs in the control and black MPBS were similar from 10 AM until noon maintaining 6.1 oC to 7.2 oC lower temperatures than the air. The white MPBS had 1.7 oC to 3.9 oC lower temperature than the control and black MPBS in the same period. The highest ST in the control containers reached a max ST value of 46.8 oC at 5 PM. ST in the black MPBS reached a maximum value of 40.8 oC at 6 PM and the white MPBS had the highest temperature as 38.1 oC at the same time. However, the ST in the white MBPS was 2.7 oC cooler than the black MPBS and 6.9 oC cooler than the control at 6 PM.

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114 The maximum ambient temperature (40.0 oC) occurred at 2 PM. Both MPBSs responded similarly to the maximum ambient temperature with 4-hour phase delays. The phase delay in the control was 3-hour because the max ST in the control occurred at 5 PM. The ambient temperature started decreasing rapidly at 3 PM. The max ST in the white and black MPBSs started to decrease slowly at the same time at 7 PM with the ST in the white MPBS cooling at a slower rate than the black MPBS and control treatment and maintaining 0.7 oC to 2.3 oC cooler ST than the black MPBS and 1.6 oC to 6.9 oC cooler than the control treatment until 9 PM. The ST in the control started to decrease one hour earlier (6 PM) than the MPBSs. Results indicated that the white MPBS successfully buffered the extremely high ambient temperature and the system was more effective than the black MPBS and the conventional system providing more optimum environment for root and plant growth.Coldest Day PatternAlthough the coldest ambient air temperature (1.9 oC) was recorded on November 7 (Fig. 5-6C), the hourly temperature data for this day was not available. Therefore, two other cold days, October 28 and December 19, when the minimum ambient air temperature dropped to 5.1 oC and 6.0 oC, respectively, were selected and graphed in Figs. 5-8A and B, respectively. Only the diurnal pattern of STs on October 28 will be discussed in detail. Figure 5-8A compares the diurnal ambient temperature, STs in the black and white MPBSs, and control treatment. On this day, the lowest ambient temperature occurred at 8 AM as 5.1 oC. STs in the black and white MPBS were 2.1 oC to 4.7 oC higher than the air temperature from 1 AM to 8 AM and the ST in the control was 0.4 oC to 2.1 oC lower than the air temperature during the same period. ST responses were similar for both black and white MPBSs during the day with black MPBS maintaining 0.5 oC to 2.4 oC higher

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115 temperatures than the white MPBS during the day. Both treatments had lowest STs at 10 AM with two-hour phase delay relative to the lowest ambient air temperature. Note that the ST in the black MPBS dropped to 3.4 oC at 10 AM whereas the ST in the white MPBS was 0.8oC lower (2.6 oC) than the black MPBS, but they were both higher than the control. The min ST in the conventional containers occurred at 9 AM (2.3 oC) with one-hour phase delay relative to the lowest ambient air temperature. These results suggest that during the coldest days of the fall growing season, the black MPBS was more effective in moderating the cold ambient temperature in the plant root-zone as compared to the white MPBS and control. After 10 AM, ST in the control rapidly increased to 7.1 oC at 11 AM whereas the temperature in the black and white MPBSs increased with much slower rate reaching 5.4 oC and 3.9 oC, respectively. After 11 AM, both black and white MPBSs showed similar trend in respect to temperature increase and decrease during the day. In the black and white MPBSs, the maximum temperature occurred at 7 PM as 21.9 oC and 20.9 oC, respectively. The max in the control treatment reached 28.3 oC one hour earlier (6 PM). After 10 AM until 8 PM, the control containers maintained higher temperatures than those in the black and white MPBSs. Similar results of trend of diurnal patterns of the STs in all treatments is apparent on December 19 (Fig. 5-8B). Overall results indicated that the white MPBS successfully moderated root-zone temperatures against extremely high ambient temperatures during the warm periods in the summer and fall growing seasons. However, black MPBS was more effective in moderating the cold temperature on the cold days of the fall season. On October 28, the lowest temperature in the black MPBS was 0.8 oC higher than the ST in the white MPBS. Similar results were obtained on the other cold day of the season (December 19). On this day, the ST

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116 in the black MPBS was 6.3 oC and it was 1.1 oC higher than the ST in the white MPBS (5.2oC) (Fig. 5-8B). These results suggest that in the cold climates, the black MPBS might have an advantage over the white MPBS in protecting the root-zone against the cold ambient air temperature. The comparison of the performance of the ST moderation of the black and white MPBSs under colder conditions needs to be further investigated.ConclusionsIn Florida, container-grown ornamental plants are exposed to high ambient temperatures in summer months and wide and rapid temperature fluctuations in winter months. This study compared substrate temperatures (ST) for container-grown Viburnum odoratissimum, Ker-Gawl. (sweet viburnum) grown in the black and white MPBS, and conventional (control) containers in summer and fall of 2001 in north-central Florida climatic conditions. The specific findings and conclusions can be summarized as follow: 1. The max STs at multiple layers were not significantly different within the black or white MPBS treatments during the summer or fall growing season. The max STs at multiple layers showed significant variations in the control treatment in the summer and fall season. The average STs in the white MPBS were significantly lower than those in the black MPBS throughout the summer and fall growing seasons. No significant differences were obtained between the min STs between the treatments. 2. In both seasons, water temperature in the black MPBS was significantly higher than the white MPBS. Minimum water temperatures were not different in both types of boxes in both seasons. Black MPBS maintained significantly higher max ambient temperature compared to the white MPBS in the summer and fall growing seasons.

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117 3. The ST in the black MPBS and control exceeded the critical value (40 oC) which is cited in the literature as negatively impacting root growth, leaf area,, plant survival, root and shoot dry weights, and photosynthesis. The ST in the control was above 45 oC for most of the summer. Results suggest that the white MPBS successfully insulated the plant rootzone against extremely high ambient temperatures in all five layers during both seasons providing more optimum environment and enhancing plant growth significantly. In conclusion, for regions where ambient air temperature range between 2 to 41 oC, the white MPBS can provide adequate and effective root-zone temperature protection for Viburnum odoratissimum grown in #1, 3.8 L standard black conventional containers.

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118 Table 5-1. Statistical analysis of the substrate temperatures between the black and white MPBS treatments and between the multiple layers in the control treatment for the summer and fall growing seasons.Growing season † MSFFcriticalp‡Summer averaged STmax(black vs. white) 106.2114.8613.9010.000169‡Fall averaged STmax (black vs. white) 97.415.0433.8820.02573 Summer averaged STmin(black vs. white vs. control) 7.682.7623.0340.06563 Fall averaged STmin (black vs. white vs. control) 10.160.3013.0340.74020 Analysis of STmax between the layers in the Control treatmentSummer0.03 m vs. 0.06 m0.6450.0313.9010.86077 0.03 m vs. 0.09 m2.4680.1233.9010.72613 0.03 m vs. 0.12 m51.4822.8463.9010.09355 0.03 m vs. 0.15 m550.34335.6083.9011.6E-80.06 m vs. 0.09 m5.6390.2843.9010.59468 0.06 m vs. 0.12 m63.6583.5613.9010.06098 0.06 m vs. 0.15 m588.68938.6163.9014.5E-90.09 m vs. 0.12 m31.4031.8473.9010.17609 0.09 m vs. 0.15 m479.09233.3303.9014.1E-80.12 m vs. 0.15 m265.17721.3713.9017.9E-6Fall0.03 m vs. 0.06 m58.0921.6183.8820.20464 0.03 m vs. 0.09 m20.3070.6133.8820.43461 0.03 m vs. 0.12 m120.6474.0943.8820.04420 0.03 m vs. 0.15 m36.5901.2983.8820.25569 0.06 m vs. 0.09 m9.7060.2833.8820.59527 0.06 m vs. 0.12 m346.17411.3063.8820.00091 0.06 m vs. 0.15 m186.8896.3723.8820.01227 0.09 m vs. 0.12 m239.958.6113.8820.00368 0.09 m vs. 0.15 m111.4154.1923.8820.04176 0.12 m vs. 0.15 m24.3541.0643.8820.30349 (‡) Mean square. (‡) Average values of substrate temperatures in all layers in the black and white MPBS treatments.

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119 Table 5-2. Maximum, minimum, and seasonal average values of the max ST in the control treatment in summer and fall growing seasons.GrowingLayer†MaxMinSeasonalSummer0.0348.4a28.340.5 0.0648.0a28.940.6 0.0946.8a28.740.2 0.1244.9a28.539.3 0.1542.0b28.136.8Fall0.0347.4a20.033.8 0.0647.9ac20.434.9 0.0946.8ad21.034.4 0.1243.6b20.832.4 0.1542.2ab20.733.0(†) Layers followed by different letters are significantly different in terms of max STs as indicated by Duncan’s Multiple Range Test (DMRT) at 5%significance level. Table 5-3. Statistical analysis of the max ambient temperatures measured in the black and white MPBSs and water temperatures measured in the reservoir of the MPBSs in the summer and fall growing seasons.Growing season † MSFFcriticalpSummer max ambient temp. in the MPBSs (black vs. white) 107.9214.9873.9020.00016 Fall max ambient temp. in the MPBSs (black vs. white) 163.079.6593.8820.00213 Summer max water temp. (black vs. white) 202.1830.4043.9021.4E-7Fall max water temp. (black vs. white) 183.9410.1073.8820.00168 (†) Mean square.

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120 15 20 25 30 35 40 45 50Tmax (oC) 0.03 m 0.06 m 0.09 m 0.12 m 0.15 m AirBlack SummerA 15 20 25 30 35 40 45 50Tmax (oC)WhiteB 15 20 25 30 35 40 45 50 20-May30-May9-Jun19-Jun29-Jun9-Jul19-Jul29-Jul8-Aug DateTmax (oC)ControlCFigure 5-1. Seasonal pattern of daily maximum substrate temperature (ST) in the black (A) and white (B) MPBS, and control (C) during the summer growing season.

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121 15 20 25 30 35 40 45 50Tmax (oC) 0.03 m 0.06 m 0.09 m 0.12 m 0.15 m Air Black FallA 15 20 25 30 35 40 45 50Tmax (oC)WhiteB 15 20 25 30 35 40 45 50 25-Aug9-Sep24-Sep9-Oct24-Oct8-Nov23-Nov8-Dec23-Dec DateTmax (oC)ControlCFigure 5-2. Seasonal pattern of daily maximum substrate temperature (ST) in the black (A) and white (B) MPBS, and control (C) during the fall growing season.

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122 15 20 25 30 35 40 4520-May30-May9-Jun19-Jun29-Jun9-Jul19-Jul29-Jul8-Aug DateTmax (oC) Black White Air Max ambient temperature inside the MPBS SummerA 15 20 25 30 35 40 45 25-Aug9-Sep24-Sep9-Oct24-Oct8-Nov23-Nov8-Dec23-Dec DateTmax (oC)FallBFigure 5-3. Daily max ambient temperature measured inside the black and white MPBS and daily max air temperature in the summer (A) and fall (B) growing seasons.

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123 0 5 10 15 20 25 30 35 40 20-May30-May9-Jun19-Jun29-Jun9-Jul19-Jul29-Jul8-Aug DateTemperature (oC) Black-Max White-Max Black-Min White-Min Water temperature SummerA 0 5 10 15 20 25 30 35 40 25-Aug9-Sep24-Sep9-Oct24-Oct8-Nov23-Nov8-Dec23-Dec DateTemperature (oC) Black-Max White-Max Black-Min White-Min Water temperature FallBFigure 5-4. Daily maximum and minimum water temperature in the white and black MPBS in the summer (A) and fall (B) growing seasons.

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124 0 5 10 15 20 25Tmin (oC) 0.03 m 0.06 m 0.09 m 0.12 m 0.15 m Air Black SummerA 0 5 10 15 20 25Tmin (oC)WhiteB 0 5 10 15 20 25 20-May30-May9-Jun19-Jun29-Jun9-Jul19-Jul29-Jul8-Aug DateTmin (oC)ControlCFigure 5-5. Seasonal pattern of daily minimum substrate temperature (ST) in the black (A) and white (B) MPBS, and control (C) during the summer growing season.

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125 0 5 10 15 20 25Tmin (oC) 0.03 m 0.06 m 0.09 m 0.12 m 0.15 m Air Black FallA 0 5 10 15 20 25Tmin (oC)WhiteB 0 5 10 15 20 25 25-Aug9-Sep24-Sep9-Oct24-Oct8-Nov23-Nov8-Dec23-Dec DateTmin (oC)ControlCFigure 5-6. Seasonal pattern of daily minimum substrate temperature (ST) in the black (A) and white (B) MPBS, and control (C) during the fall growing season.

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126 15 20 25 30 35 40 45 50 1357911131517192123 TimeTemperature (oC) Black White Control Air Summer June 17 N oo n A 15 20 25 30 35 40 45 50 1357911131517192123 TimeTemperature (oC) Black White Control Air Summer July 7 N oo n BFigure 5-7. Diurnal substrate temperatures (warmest days pattern in the summer growing season) of the black and white MPBS and conventional (control) system on June 17 (A) and July 7 (B) when the ambient air temperature reached 40.0 oC and 40.1 oC, respectively.

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127 0 5 10 15 20 25 30 1357911131517192123 TimeTemperature (oC) Black White Control Air Fall October 28 N oo n A 0 5 10 15 20 25 30 1357911131517192123 TimeTemperature (oC) Black White Control Air Fall December 19 N oo n BFigure 5-8. Diurnal substrate temperatures (coldest days pattern in the fall growing season) of the black and white MPBS and conventional (control) system on October 28 (A) and December 19 (B) when the ambient air temperature dropped to 5.1 oC and 6.0 oC, respectively.

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128 CHAPTER 6 PREDICTING ROOT-ZONE MEDIA TEMPERATURES OF Viburnum odoratissimumGROWN IN THE MULTI-POT BOX SYSTEM AND CONVENTIONAL SYSTEMIntroductionRoot-zone temperature (RZT) of container-grown ornamental plants is one of the critical environmental factors that affects plant growth. RZT has a distinct effect on the processes at the cellular level such as osmotic potential, hydration of ions, matric potential, stomatal activity and transpiration, membrane permeability, solute solubilities, diffusion, and enzymatic activity (Voorhees et al., 1981). Although the temperature at which root death and/or injury occur varies with the plant specie, in general, the RZT greater than 40 oC has been suggested to cause root death and/or injury for several container-grown plants (Ingram, 1981; Johnson and Ingram, 1984; Ingram and Ramcharan, 1988; Martin et al., 1989; Martin, 1990; Martin and Ingram, 1992). RZT above 40 oC has been reported to influence root growth (Johnson and Ingram, 1984), leaf area (Graves et al., 1989), plant survival (Martin et al., 1991), root and shoot dry weights (Yeager et al., 1991), water status (Graves et al., 1989), and photosynthesis (Ruter and Ingram, 1992) of container grown plants. RZTs below 40 oC is often reported as a value for optimum plant growth (Levitt, 1980; Ingram et al., 1986; Ruter and Ingram, 1990; Martin and Ingram, 1992). The RZT of container-grown plants differs greatly from that of plants grown in the ground (Yeager et al., 1991). The ground naturally moderates the extreme temperatures and insulates the roots. In practice, black polyethylene containers have been used extensively for

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129 growing ornamental plants. High RZTs due to the incoming or reflected solar radiation on sidewalls of the containers can be dramatically increased during the summer months and affect plant growth. In the winter months, the roots of the plants in the container are usually colder than the roots of plants grown directly in the soil. Although the RZT is a very critical variable in container-grown ornamental plant production, direct measurement of this variable is not always possible due to practical, financial, or other reasons. With the exception of a few studies, a literature review revealed that not enough attention has been given to developing and using models to predict RZT of container-grown ornamental plants. Simulation models allow researcher to study response of RZT to different ambient air temperatures and to other variables without conducting time consuming, difficult, and even sometimes impossible field studies with significantly lower time, cost, and resources. In a detailed study, Martin and Ingram (1992) developed a three dimensional model using an energy balance approach to simulate numerically the thermal environment of a polyethylene container-root medium (substrate) system in 10 L containers in Gainesville, FL. They studied the effect of the net radiation, convection, evaporation, and conduction on thermal energy exchanges at the top surfaces of the substrate. The effect of volumetric water content on substrate temperature patterns for different container substrate (pine bark and pine bark supplemented with sand) was also researched. Thermal energy exchanges at the systemÂ’s boundaries were a function of solar radiation, convection, evaporation, and conduction energy fluxes. Conduction and evaporation had little effect on thermal energy flows to and from the substrate surface. Their model required the thermal conductivity, bulk density, specific heat capacity of the container substrate, solar radiation, wind speed, relative

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130 humidity, and maximum and minimum air temperature as inputs to the model. Their model validation results were in a very good agreement with the measured values of the temperatures at the exterior container wall (0.02 m inside the container wall at north, south, east, and west sides) and the root medium (0.02 m above the container bottom, in the center of the container, and 0.02 m below the substrate surface). They reported that the thermal diffusivity of the container substrate as volumetric water content increased. They suggested that the irrigations applied in the afternoon hours would help to moderate high temperatures in pine bark substrate. Martin and Ingram (1993) used the model developed by Martin and Ingram (1992) to simulate the effect of container volume and shape on summer temperature patterns for black polyethylene nursery containers filled with a pine bark in Phoenix, AZ, and Lexington, KY. They found that, for both locations, predicted temperature patterns in rooting medium adjacent to the container wall decreased as the wall tilt angle increased. Predicted temperature patterns at the center of the container profile were lower with increased container height and wall tilt angle. As the container volume decreased, the temperature at the center of the container substrate increased. Based on the simulation results, they suggested that large containers with walls tilted outward may be practical for container nursery production in hot climates to lower RZT because of the high ambient air temperatures during the summer. A more practical model for predicting RZT should provide consistent and reliable predictions by requiring only commonly available data (i.e. max and min air temperature) and a minimum of computation. The objectives of this study were to develop and validate a series of models for predicting max and min RZTs for Viburnum odoratissimum grown in

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131 the white and black MPBSs and conventional containers under the North-central Florida humid climate conditions. Materials and MethodsExperiments were conducted under field conditions in the summer and fall seasons of 2001 in the campus of the University of Florida, Gainesville, FL. General experimental procedures and design and other management practices including, RZT measurements, irrigation applications, measurements of growth index (GI) and plant biomass, have been described in detail in Chapter 5. Therefore, in this part, only model development procedures will be outlined. In the earlier study (Chapter 5), results showed that the maximum temperatures measured in five different layers (0.03, 0.06, 0.09, 0.12, and 0.15 m) in the container substrate of the black and white MPBSs were not significantly different between the layers. However, when these temperatures in five layers were averaged for the season, the black MPBS had significantly higher max container substrate temperatures compared to the white MPBS in the fall and summer growing seasons. The min temperatures were not significantly different between the layers and between the black and white MPBSs in both seasons. Therefore, two different models were developed to predict max RZT at the center of the container (0.09 m from the surface) for each MPBS and only one model was developed to predict min RZT at the same location. In the model development, the average values of all layers were used to calibrate the models for predicting max RZT in the black and white MPBSs. In the validation these models were used to predict max RZT at 0.09 m depth in the containers.

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132 Results in Chapter 5 also indicated that there were significant differences in max substrate temperatures between the layers for the conventional containers. However, the min substrate temperatures between the layers were the same. For the conventional containers (control), two models were developed to predict max and min RZTs at the center (0.09 m from the surface) of the conventional containers. An automated weather station was set on the short green grass site approximately 30 m from the experimental site to record necessary climate variables for the model development. The grass was irrigated as needed and clipped when it was approximately 0.12 m tall to represent the reference conditions (Allen et al.,1994a, 1994b). The data collected at the weather station were: air temperature, relative humidity, total incoming solar radiation, wind speed at 2 m, and rainfall. All measurements were taken on hourly basis. Ambient air temperature on the experimental plot placed at 1 m height was also measured using a thermocouple to determine whether there was any differences between ambient air temperatures measured in the weather station and on the experimental plot. Unless mentioned otherwise, the same procedures were used to develop the models for the white and black MPBS and CS. A multi-linear regression technique was used to develop the coefficients in the models. The measured RZT values in the fall growing season (from August 29 to December 20) were used to calibrate the coefficients. Then, the models were validated using the measured data from the summer growing season (May 23 to August 9). In the multi-linear regression analysis, the measured RZT values were used as dependent variables. Depending on the treatment (white and black MOBS, and CS), the solar radiation, Rs, maximum air temperature, Tmax, and minimum air temperature, Tmin, were used as independent variables to determine the coefficients in the models. For this purpose, the

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133 coefficients were determined to adjust Rs, Tmax, and Tmin to obtain the best fit to the measured RZT. The general form of the multi-linear equation that relates a dependent variable (RZT,oC) to a set of quantitative independent variables (Rs, Tmax, and Tmin) is a direct extension of a polynomial regression model with one independent variable. The general form of the multilinear regression model used in this study was RZT = '0 + '1X1 + '2X2 + '3X3(6-1) where '0 is the intercept, '1,, '2, and '3 represent the slope of the regression line, and X1, X2, and X3 are the independent variables (Tmax, oC; Tmin, oC; and Rs, MJ m-2 d-1). The root mean square error (RMSE), coefficient of determination (r2) between predicted and measured RZTs, and the seasonal average ratio of predicted RZT to measured RZT were calculated to be used as indicators of accuracy and consistency of the models estimate. The RMSE (oC) values were calculated as (6-2) RMSE n yyi p i m i n12 1()where n is the number of observations, yi p and yi m are the predicted and measured RZT (oC), respectively.Results and DiscussionIn practice, most of the conventional nursery containers are placed on the black polyethylene ground cover for weed protection and other purposes. The ground cover may influence the pattern of ambient temperature in the surrounding microclimate of the plants and, thus, this might cause differences in temperatures measured on the black ground cover and at the reference weather station. In the model development, the decision of whether

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134 using the max and min ambient air temperatures measured on the experimental plot or in the reference weather station needed to be made. To analyze whether the ambient air temperatures measured in two different locations were different or not, the max and min ambient air temperatures measured in two locations were graphed in Figs. 6-1A and B for the fall and summer growing seasons, respectively. Figures 6-1A and B show that the max air temperatures measured on the experimental plot were consistently and significantly (p<0.05) higher than those measured in the reference weather station in both seasons. On the seasonal average, the max air temperature on the plot was 3.5 oC (standard deviation, SD, = ±4.2 oC, n = 114) and 3.6 oC (SD = ± 3.0 oC, n = 79) higher than the temperatures measured in the station in the fall and summer seasons, respectively. This suggests that the color and type of the ground cover increased the air temperature on the black polyethylene ground cover due to higher amount of absorption of the solar and thermal energy. The minimum air temperatures in both locations were not significantly different (p>0.05) in both seasons. Although the max ambient air temperatures measured on the experimental plot and in the weather station were significantly different, measurement of air temperature on the black polyethylene ground cover to use it for prediction of RZT is not very practical because few nurseries collect their own climate data. Air temperature data are available from various sources and automated weather stations. For example, in Florida, Florida Automated Weather Network, FAWN, under the Institute of Food and Agricultural Sciences (IFAS), University of Florida, provides real time climate data, including max and min air temperature and solar radiation, for many locations. Therefore, in this study, the max and min air temperatures measured at the reference weather station were used for model development.

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135RZT Models for the White and Black MPBSsThe RZT models were calibrated for the fall growing season and validated for the summer. The fall season was selected for calibration because the temperature range in this season was larger ranging from 1.9 oC to 40 oC as compared to the summer (17.4 oC to 40oC). The calibration equations for predicting max RZT (RZTmax, oC) for the container substrate at the 0.09 m from the surface in the white and black MPBS, respectively, were found as RZTmax-white = 1.184Tmax 0.058Tmin 2.938(6-3) RZTmax-black = 1.272Tmax 0.011Tmin 3.467(6-4) and the equation for predicting min RZT (RZTmin, oC) in either black or white MPBS was found as RZTmin = 0.082Tmax + 0.953Tmin 1.501(6-5) where RZT is the root-zone temperature at 0.09 m (oC), Tmax and Tmin are daily maximum and minimum air temperature (oC), respectively. The calibration curves for Eqs. 6-3, 6-4, and 6-5 are given in Figs. 6-2A, B, and C, respectively. The RMSE between the predicted and observed RZT, the seasonal average of predicted RZT to measured RZT, and the significance of the independent variables for the calibration season are presented in Table 6-1. Data analysis indicated that in Eqs. 6-3 and 6-4, Rs did not have a lot of influence on predicting max RZT in the MPBSs, thus, it was not included in the equations. This is related to the fact that the containers placed in the MPBSs were protected from the direct exposure to the solar radiation. In Eq. 6-3, the coefficient of determination (r2) value was 0.89 for the calibration season. The intercept and Tmax of the regression line were significant (p<0.05, n = 114) (Table 6-1) with the RMSE averaging 1.4 oC (Fig. 6-2A). In Eq. 6-4, the r2 was the

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136 same as Eq. 6-3 (0.89). The intercept, Tmax, and Tmin were significant with the RMSE averaging with a higher value (2.2 oC) compared to the Eq. 6-3. In the calibration equation of Tmin (Eq. 6-5), only the Tmin was significant and the RMSE was the lowest (1.3 oC). The seasonal average ratio of predicted RZT to measured values were 0.99, 1.05, and 1.02 for Eqs. 6-3, 6-4, and 6-5, respectively, with Eq. 6-4 overestimating Tmax for the black MPBS. It should be noted that although the Tmin in Eq. 3 and Tmax in Eq. 6-5 were not significant, they were included in the calibration equations because their inclusion increased the r2 value from 0.92 to 0.94 and decreased the RMSE of the predictions from 1.6 oC to 1.3 oC. In the calibration of Eq. 6-5, the deviations from the 1:1 line were the largest in the measured temperature range between approximately 10 oC and 20 oC. This might be due to the larger fluctuations in daily min RZT towards the end of the fall growing season. The measured RZT analysis (results are not shown) indicated that the largest fluctuations in daily min RZT occurred in November December period when the temperature difference between the daytime and nighttime min RZT was the greatest. Measured RZTs in the summer season were used to validate Eqs. 6-3, 6-4, and 6-5. The RZT predictions of Eqs. 6-3, 6-4, and 6-5 versus measured RZTs in the summer season are given in Figs. 6-3A, B, and C, respectively. The RMSE and the seasonal average ratio of predicted RZT to measured RZT are presented in Table 6-1. Results in Figs. 6-3A showed that the predicted RZTs using Eq. 6-3 were well correlated with the measured max RZTs (Fig. 6-3A). Equation 6-3 resulted in a reasonably low RMSE (1.0 oC) with an r2 value of 0.84 and the seasonal average ratio of 1.01 (Table 6-1). The results of the Eq. 6-4 were slightly poorer than the Eq. 6-3. Note that the calibration results of Eq. 6-4 in Table 6-1 showed that the Eq. 6-4 overestimated max RZT

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137 in the black MPBS with a seasonal average ratio of 1.05. This overestimation was consistent throughout the season. The overestimation of the Eq. 6-4 is related to the considerable differences in temperature range between the calibration and validation seasons. For example, in the calibration season (fall) the max RZT of the container substrate at 0.09 m in the black MPBS ranged from 19.8 oC to 40.6 oC whereas it ranged from 27.6 oC to 40.0 oC in the summer (validation). However, the magnitude of overprediction is in acceptable range. Results in Fig. 6-3B showed the predicted RZTs were well correlated with the measured RZTs with an r2 of 0.83, the average ratio of 1.05, and the RMSE of 2.1 oC. Equation 6-5 was very successful for predicting min RZT in the black and white MPBSs (Fig. 6-3C). The RMSE of predictions was the lowest (0.7 oC) and the r2 was the highest (0.90) among all equations. The average ratio was 1.02 indicating that the equation slightly overpredicted min RZT. The overpredictions were especially higher at lower min RZT range (approximately from 17 oC to 20 oC) (Fig. 6-3C). It should be noted that in the model calibration and validation the average of five layersÂ’s max and min RZTs were used because the max and min RZTs between the layers were not significant. This, in part, introduced some error to the model performance in the validation season. In addition, Eqs. 6-3, 6-4, and 6-5 use only max and min air temperatures to predict RZTs. They do not account for the other environmental variables such as vapour pressure deficit, evaporation, conduction, water content and thermal properties of the container substrate, and other variables that have influence on the RZT. The main objective of this study was to develop simple but practical models that can be used to predict RZTs using commonly available climate variables. However, overall, results showed that Eqs. 6-3,

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138 6-4, and 6-5 were effective and can be used to predict max and min RZTs with a sufficient accuracy for Viburnum odoratissimum grown in the black and white MPBSs.RZT Models for the Conventional ContainersThe calibration equations for predicting max and min RZT (RZTmax and RZTmin), respectively, for the container substrate at the 0.09 m from the surface in the conventional containers are RZTmax = 0.850Tmax + 0.026Tmin + 0.697Rs + 1.21(6-6) RTZmin = 0.106Tmax + 0.998Tmin 3.255(6-7) where Rs is the daily average solar radiation (MJ m-2 d-1). Using only Tmax and Tmin in the model of max RZT for the conventional containers resulted in poor predictions with r2 and RMSE of 0.64 and 4.0 oC, respectively. Therefore, an independent variable, Rs, was included in the calibration. The calibration curves for Eqs. 6-6 and 6-7 are given in Figs. 6-4A and B, respectively. In the calibration of Eq. 6-6, the r2 value was 0.83 and only Tmax and Rs were significant (p<0.05, n = 79) with the RMSE of 2.3 oC (Table 6-1). In Eq. 6-7, the r2 was the highest (0.95) and the RNSE was the lowest (1.2 oC) among all the calibration equations. Note that in Eq. 6-7, Rs was not included since it did not have a significant affect on predicting min RZT. All other variables were significant. The seasonal average ratio of predicted RZT to measured values for Eqs. 6-6 and 6-7, respectively, were 1.00 and 1.01. Martin and Ingram (1992) stated that the primary environmental factors causing changes in container substrate temperature patterns are solar radiation, wind speed, air temperature, and absolute air humidity. Analysis of this study indicated that the wind speed and humidity did not have considerable effect on predicting max RZT in the MPBSs or conventional

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139 containers at the 0.09 m depth from the container surface. However, these variables would most likely influence substrate temperature at the top layer (0.03 m from the surface) because this layer is in a direct contact with the surrounding environment and can be stronger influenced by these variables. The RZT predictions of Eqs. 6-6 and 6-7 versus measured RZTs in the summer season are presented in Figs. 6-5A and B, respectively. Results in Figs. 6-5A showed that the predicted RZTs using Eq. 6-6 were relatively well correlated with the measured max RZTs in the conventional container. Equation 6-6 predictions resulted in the highest RMSE (2.8oC) and the lowest r2 (0.74) among all other equations and the seasonal average ratio was 1.04 (Table 6-1) overpredicting RZT. Equation 6-7 was very successful for predicting min RZT in the conventional containers (Fig. 6-5B). The RMSE of predictions was the second lowest (0.9 oC) among all the equations with the r2 and average ratio of 0.84 and 1.02, respectively. Overall results indicated that Eqs. 6-3 through 6-7 can be successfully used to predict max and min RZTs in the white and black MPBSs and conventional containers at the 0.09 m (center of the container). Models were able to explain at least 74% of the variability in RZTs using only Tmax, Tmin, and Rs, depending on the equation. It is important to note that in the validation season, the accuracy of the RZT predictions of all equations was lower compared to the calibration season. This is expected since there are some management practices, such as thermocouple placement depths, that can affect the model performance in the validation season. In the validation season, the thermocouples might have been placed in a slightly different positions than the calibration season and effect the models performance. Models

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140 that were developed in this study are applicable for estimating RZTs in a 3.8 L standard black polyethylene container (conventional) container filled with a substrate of pine bark, peat, and sand (2:1:1 by volume) mix, amended with 4.2 kg m-3 of dolomitic limestone and 0.9 kg m-3of Micromax and for the irrigation regimes of this study. Container volume, physical characteristics of the substrate, and irrigation are particularly important since studies (Pertuit, 1972; Parikh et al., 1979; Sophocleous, 1979; Martin and Ingram, 1991; Martin and Ingram, 1992; Martin and Ingram, 1993) have shown that they significantly affect the temperature patterns of the substrate. In addition, the models are applicable to predict RZTs in the locations where the ambient air temperature ranges from 1.9 oC to 40 oC and should not be extrapolated beyond these boundaries. ConclusionsModels were developed to predict root-zone temperatures (RZT) at 0.09 m depth in the standard 3.8 L black polyethylene containers filled with a substrate of pine bark, peat, and sand (2:1:1 by volume) mix, amended with 4.2 kg m-3 of dolomitic limestone and 0.9 kg m-3of Micromax. Different models were developed to predict RZTs in the black and white MPBS and in the conventional containers. All models were calibrated for the fall growing season and validated for the summer. Results indicated that using only max and min air temperature, the models were able to explain 84% and 83% of the variability in max RZTs of container substrate in the white and black MPBSs, respectively. Using the max and min air temperature and solar radiation, the model for the conventional containers was able to predict 74% of the variability of the max RZT. The min RZT estimates in MPBSs and conventional containers were produced better results compared to the max RZTs. It was concluded that the models developed in this study can be used to accurately predict daily max

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141 and min RZT of the container substrate in the locations where ambient air temperature ranges from 1.9 oC to 40 oC.

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142 Y = 0.9896X + 0.6944 r2 = 0.95 Y = 1.0043X + 3.3813 r2 = 0.880 5 10 15 20 25 30 35 40 45 051015202530354045 Station air temperature (oC)Plot air temperature (oC) Max Min Fall 1:1 lineA Y = 0.8646X + 3.3005 r2 = 0.85 Y = 1.286X 5.8529 r2 = 0.810 5 10 15 20 25 30 35 40 45 051015202530354045 Station air temperature (oC)Plot air temperature (oC) Max Min Summer 1:1 lineBFigure 6-1. Relationships between max and min ambient air temperatures measured on the experimental plot (1 m above the black polyethylene ground cover) and in the reference weather station (30 m from the experimental plot) for the fall (A) and summer (B) growing seasons.

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143 Table 6-1. Root mean square error (RMSE), seasonal average ratio of predicted RZT to measured RZT, r2, and the significance of the independent variables of Eqs. 6-3, 6-4, and 6-5.Variable Calibration fallValidation summerEq.6-3Eq.6-4Eq.6-5Eq.6-6Eq.6-7Eq.6-3Eq.6-4Eq.6-5Eq.6-6Eq.6-7RMSE (oC)1.42.21.32.31.21.02.10.72.80.9†Avg. ratio0.991.051.021.001.011.011.051.021.041.02 r20.890.890.940.830.950.840.830.900.740.84 Tmax****NS**** TminNS****NS** Intercept****NSNS** Rs---**(†) Daily ratio of predicted RZT to measured RZT was calculated on a daily basis and then averaged to obtain seasonal average. (**) Significant at 5% significance level. (NS) Not significant.

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144 r2 = 0.890 5 10 15 20 25 30 35 40 45 051015202530354045 Measured Tmax (oC)Predicted Tmax (oC)White MPBS Tmax calibration fallA1:1 line r2 = 0.890 5 10 15 20 25 30 35 40 45 051015202530354045 Measured Tmax (oC)Predicted Tmax (oC)Black MPBS Tmax calibration fallB1:1 line r2 = 0.940 5 10 15 20 25 0510152025 Measured Tmin (oC)Predicted Tmin (oC)Average of black and white MPBS Tmin calibration fallC1:1 lineFigure 6-2. Calibration curves for the Eqs. 6-3, 6-4, and 6-5 for predicting max RZT in the white (A) and black (B) and for predicting average min RZT in the white and black MPBSs (C) in the fall growing season.

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145 r2 = 0.840 5 10 15 20 25 30 35 40 45 051015202530354045 Measured Tmax (oC)Predicted Tmax (oC)White MPBS Tmax validation summer 1:1 lineA r2 = 0.830 5 10 15 20 25 30 35 40 45 051015202530354045 Measured Tmax (oC)Predicted Tmax (oC)Black MPBS Tmax validation summerB1:1 line r2 = 0.900 5 10 15 20 25 0510152025 Measured Tmin (oC)Predicted Tmin (oC)Average of black and white MPBS Tmin validation summerC1:1 lineFigure 6-3. Validation results of the Eqs. 6-3, 6-4, and 6-5 for predicting max RZT in the white (A) and black (B) and for predicting average min RZT in the white and black MPBSs (C) in the summer growing season.

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146 r2 = 0.830 5 10 15 20 25 30 35 40 45 50 05101520253035404550 Measured Tmax (oC)Predicted Tmax (oC)Conventional containers Tmax calibration fallA1:1 line r2 = 0.950 5 10 15 20 25 0510152025 Measured Tmin (oC)Predicted Tmin (oC)Conventional containers Tmin calibration fallB1:1 lineFigure 6-4. Calibration curves for the Eqs. 6-6 and 6-7 for predicting max (A) and min (B) RZTs in the conventional containers at the 0.09 m from the surface in the fall growing season.

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147 r2 = 0.740 5 10 15 20 25 30 35 40 45 50 05101520253035404550 Measured Tmax (oC)Predicted Tmax (oC)Conventional containers Tmax validation summer 1:1 lineA r2 = 0.840 5 10 15 20 25 0510152025 Measured Tmin (oC)Predicted Tmin (oC)Conventional containers Tmin validation summerB1:1 lineFigure 6-5. Validation results of the Eqs. 6-6 and 6-7 for predicting max (A) and min (B) RZTs in the conventional containers at the 0.09 m from the surface in the summer growing season.

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148 CHAPTER 7 CONCLUSIONS AND RECOMMENDATIONS The major findings and conclusions from each chapter of this dissertation can be summarized as follows Chapter 2: The total irrigation water applied to the white and black MPBS treatments, respectively, were only 7% and 8% of the total water applied to the control treatment in summer season, and in the fall, they were only 19% and 22% of the control, respectively. In both seasons, the W1 and B1 (level switches installed at 0.01-m) treatments resulted in the least irrigation applications. The total rainfall in the summer season was 600 mm. A 317-mm (53% of the total rainfall) and 328 mm (55% of the total rainfall) were captured in the reservoir of the white and black MPBSs, respectively, during the summer growing season. The total rainfall in the fall season was 308 mm. The white box treatments, W3, W2, and W1, respectively, a total of 89, 92, and 85 mm of rain water captured and later used by plants. The captured amounts are 29, 30, and 28% of the total rainfall. The captured amount of rain water was slightly higher in the black box treatments (B3, B2, and B1) compared to those captured in the white box treatments. A total of 105 mm (34% of the total rain), 101 mm (33% of the total rain), and 89 mm (29% of the total rain) were captured in the

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149 B3, B2, and B1 treatments, respectively. The captured amounts of rain water were considerable portions of the total rainfall that occurred in both seasons. Hence, the irrigation demand of plants grown in the MPBSs decreased significantly. The MPBS treatments resulted in much less runoff compared to the CS. The total runoff from the white and black boxes, respectively were only 18% and 10% of the runoff occurred from the control in the summer and fall, respectively. In both summer and fall seasons, the plants grown in the white MPBS resulted in significantly higher both shoot and root dry weights than the plants grown in black MPBS and control treatments. However, neither shoot nor root dry weights within the both white and black box treatments were significantly different in both growing seasons. The SIWUEs were significantly higher for the plants grown in the white MPBS compared to the plants grown in black MPBS and CS. The SIWUEs were not significantly different within the white and black MPBS treatments. The IE values for the white and black MPBS treatments were higher than 100% whereas it was only 19% in summer and 15% in the fall season for the CS. The water savings of the white and black MPBSs was at least 75% relative to the CS. In both seasons, the white MPBS treatments resulted in higher water savings compared to the black boxes, and the W1 treatment had the highest water saving in the Fall season. The white MPBS with level switch installed at 0.01 m resulted in fewer irrigation demands and less runoff compared to the other treatments and the plant biomass production was not significantly different than the other white box treatments (W3 and W2). Thus, overall experimental results suggested that under these experimental and

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150 similar climatic conditions, the white MPBS is superior to the black one and should be the first choice of the growers/users. The level switch installed at 0.01 m in the MPBS is a proper selection when irrigation scheduling, minimizing the runoff, plant growth are considered. Chapter 3: In both growing seasons, plants grown in the white MPBS had significantly higher root and shoot dry weights, growth index (GI) and growth rates compared to the plants grown in the black MPBS and conventional system (CS). Plants grown in the white MPBS reached marketable size approximately 17 days and 86 days earlier (in the summer season) and 25 and 115 days earlier (in the fall season) than the plants grown in the black MPBS and CS, respectively. In both growing seasons, plants grown in the white MPBS had lower stomatal resistances (rs) to vapor transport, lower crop water index (CWSI) values, and higher (wetter) plant water potential (PWP) values compared to the plants grown in the black MPBS and CS. Thus, plants in the white MPBS were exposed to the lower levels of plant stresses. Based on the experimental results of the two growing seasons, it is concluded that there is enough evidence to suggest that the use white color MPBS is more feasible than the black MPBS and CS for growing Viburnum odoratissimum under these climatic conditions. Chapter 4: Crop evapotranspiration (ETc) and crop coefficients (Kc) were quantified. Relationships between growth index (GI) and Kc were investigated. Experimentally derived Kc values

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151 of this study add useful information to the nursery industry in terms of collection of ETcand Kc data for nursery crops and are among the first ETc and Kc data specifically for theViburnum odoratissimum. Variations were observed between the ETc and Kc values of the two treatments in the same season and for the same treatment between the seasons. Linear relationships were obtained between GI and Kc (r2 $ 0.92) and equations were developed to estimate Kc using GI in two growing seasons (summer and fall) for the plants grown in the white and black MPBS. Equations developed to estimate Kc from GI would have a significant advantage over the method of estimating Kc from measured ETcand estimated ETo since, in practice, measuring GI values are much more easier that measuring the Etc. Chapter 5: The max STs at multiple layers were not significantly different within the black or white MPBS treatments during the summer or fall growing season. The max STs at multiple layers showed significant variations in the control treatment in both seasons. The max STs in the white MPBS were significantly lower than in the black MPBS and CS throughout the summer and fall growing seasons. No significant differences were obtained between the min STs between the treatments. 2. In both seasons, water temperature in the black MPBS was significantly higher than the white MPBS. Minimum water temperatures were not different in both types of boxes in both seasons. Black MPBS maintained significantly higher max ambient temperature compared to the white MPBS in the summer and fall growing seasons.

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152 The ST in the black MPBS and control exceeded the critical value (40 oC) which is cited in the literatures as negatively impacting root growth, leaf area,, plant survival, root and shoot dry weights, and photosynthesis. The ST in the control was above 45 oC for most of the summer. Results suggest that the white MPBS successfully insulated the plant root-zone against extremely high ambient temperatures in all five layers during the both seasons providing more optimum environment and enhancing plant growth significantly. In conclusion, for regions where ambient air temperature range between 2 to 41 oC, the white MPBS can provide adequate and effective root-zone temperature protection forViburnum odoratissimum grown in #1, 3.8 L standard black conventional containers. Chapter 6 Models were developed to predict root-zone temperatures (RZT) at 0.09 m depth in the standard 3.8 L black polyethylene containers filled with a substrate of pine bark, peat, and sand (2:1:1 by volume) mix, amended with 4.2 kg m-3 of dolomitic limestone and 0.9 kg m-3 of Micromax. Different models were developed to predict RZTs in the black and white MPBS and in the conventional containers. All models were calibrated for the fall growing season and validated for the summer. Results indicated that using only max and min air temperature, the models were able to explain 84% and 83% of the variability in max RZTs of container medium in the white and black MPBSs, respectively. Using the max and min air temperature and solar radiation, the model for the conventional containers was able to predict 74% of the variability of the max RZT. The min RZT estimates in MPBSs and conventional containers were produced better results compared to the max RZTs. It was concluded that the models developed in this study can be used

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153 to accurately predict daily max and min RZT of the container medium in the locations where ambient air temperature ranges from 1.9 oC to 40 oC. Finally, evaluation of the performance of the white and black MPBS for growing different ornamental plant species under different climate conditions is recommended.

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161 Wong, T.L., R.W. Harris, and R.E. Fissell. 1971. Influence of high soil temperatures on five woody-plant species. J. Amer. Soc. Hort. Sci. 96:80-82. Wright, J.L. 1979. Recent developments in determining crop coefficient values. In Irrigation and drainage in the 1970s, Proc. ASCE Irrig. and Drain. Div. Spec. Conf. Wright, J.L. 1981. Crop coefficients for estimates of daily crop evapotranspiration. InIrrigation Scheduling for Water and Energy Conservation in the 80's. Am. Soc. of Agric. Eng., ASAE, St. Joseph, MI. Dec. 18-26. Wright, J.L. 1982. New evapotranspiration crop coefficients. J. Irrig. and Drain. Div., ASCE, 108(IR2):57-74. Wright, J.L. and M.E. Jensen. 1978. Development and evaluation of evapotranspiration models for irrigation scheduling. Trans. ASAE 21:88-91;96. Yeager, T.H., R.H. Harrison, and D.L. Ingram. 1991. Rotundifolia holly growth and nitrogen accumulation influenced by supraoptimal root-zone temperatures. HortSci. 26(11):1387-1388. Young, K., and K.R.W. Hammett. 1980. Temperature patterns in exposed black polyethylene plant containers. Agric. Meteorology 21:165-172. Young, R.E., and G.R. Bachman. 1996. Temperature distribution in large, Pot-In-Pot nursery containers. J. Environ. Hort. 14(4):170-176. Young, R.E., J.L. Dunlap, Jr., D.J. Smith, and S.A. Hale. 1987. Clear and white plastics for freeze protection of landscape plants in the southern to mid-atlantic region. J. Environ. Hort. 5:166-172.

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162 BIOGRAPHICAL SKETCH Suat Irmak was born on July 16, 1970, in a Mediterranean town, Adana, in Turkey. He received his bachelor’s degree from Cukurova University with a major in agricultural structures and irrigation in 1992. After graduation, he worked on several field projects related to the yield response to water and nutrients for various crops, including cotton, corn, and sunflower. Between 1993 and 1996 he was employed as a research and teaching assistant at the Mediterranean University in Antalya, Turkey, to pursue his master’s degree. His master’s degree was on developing strategies to use crop water stress index and soil matric potential values for irrigation scheduling of corn under Mediterranean semi-arid climate conditions. He enrolled in graduate school at the Agricultural and Biological Engineering Department of the University of Florida in 1998 to pursue his Ph.D. On May 2002, Suat received his Ph.D. degree after defending his dissertation titled “New Irrigation-Plant Production System for Water Conservation in Ornamental Nurseries.” While at the University of Florida, he was a member of the American Society of Agricultural Engineers (ASAE), American Water Work Association (AWWA), American Society of Agronomy (ASA), and Florida Irrigation Society (FIS). Suat is also a member of the Alpha Epsilon and Gamma Sigma Delta honor societies. During his Ph.D. program, he received several awards, including the Outstanding Graduate Student Award (April 1999, presented by Institute of Food and Agricultural Sciences, Agricultural and Biological

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163 Engineering Department), Outstanding Academic Achievement Award (April, 1999, presented by the College of Engineering, University of Florida), Presidential Recognition Award (April 2000, presented by Charles E. Young, president of the University of Florida), and “Young Researcher Award” (May 2002, presented by Florida Section ASAE).