<%BANNER%>

Cropping System Complexity for Suppressing Pests in Organic Vegetable Production

Permanent Link: http://ufdc.ufl.edu/UFE0041224/00001

Material Information

Title: Cropping System Complexity for Suppressing Pests in Organic Vegetable Production
Physical Description: 1 online resource (220 p.)
Language: english
Creator: Bhan, Manish
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2010

Subjects

Subjects / Keywords: cover, cropping, nematodes, organic, weed, weeds
Horticultural Science -- Dissertations, Academic -- UF
Genre: Horticultural Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: TITLE CROPPING SYSTEM COMPLEXITY FOR SUPPRESSING PESTS IN ORGANIC VEGETABLE PRODUCTION ABSTRACT Two field experiments were initiated in summer 2006 to compare the effects of crop rotation, cover crops, living mulches, and intercropping on pest populations. Treatments consisted of cropping systems with summer fallow followed by fall and spring vegetables. Yellow squash and bell pepper were planted in experiment I during year 1 and rotated with broccoli and sweet corn in year 2. In experiment II, broccoli and sweet corn were planted in year 1, and squash and bell pepper in year 2. Cropping systems represented three levels of complexity. The simple cropping system was a summer fallow followed by sole fall and spring vegetables. Four intermediate cropping systems utilized summer cover crops of pearl millet (PM), sorghum-sudangrass (SS), sunn hemp (SH), or velvetbean (VB) followed by sole fall and spring vegetables. Two complex systems included either pearl millet-sunn hemp (PMSH) or sorghum sudangrass-velvetbean (SSVB) mixtures. In the complex systems, row middles of fall squash and broccoli were planted with rye-hairy vetch and crimson clover as living mulches, and bush beans were intercropped with spring vegetables. Weeds and nematode populations were monitored during each season and insect pests in spring only. Soil samples were collected annually for evaluating the weed seedbank. Systems planted with SS or PM increased root-knot nematodes while the SS system also increased ring and lesion nematode populations. Cropping systems failed to suppress aphid populations. PM and SS systems decreased thrips populations while PM and SH systems reduced whitefly populations in sweet corn. In experiment I, fewer grasses, broad-leaf weeds and total weed biomass were observed with the SSVB system than the WF system. In experiment II, the SSVB system resulted in fewer grass weeds between beds than the WF system; however, no differences were observed among systems for broad-leaf and sedge weed densities and total weed biomass. Cropping systems did not change the composition of the weed seedbank. Squash and sweet corn marketable yields were highest in the PM system while no differences were observed between complex and WF systems. In experiment II, bell pepper marketable yield was higher in complex than WF systems. Predicted population dynamics of southern crabgrass and Florida pusley indicated no differences among cropping systems.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Manish Bhan.
Thesis: Thesis (Ph.D.)--University of Florida, 2010.
Local: Adviser: Chase, Carlene A.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2011-04-30

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2010
System ID: UFE0041224:00001

Permanent Link: http://ufdc.ufl.edu/UFE0041224/00001

Material Information

Title: Cropping System Complexity for Suppressing Pests in Organic Vegetable Production
Physical Description: 1 online resource (220 p.)
Language: english
Creator: Bhan, Manish
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2010

Subjects

Subjects / Keywords: cover, cropping, nematodes, organic, weed, weeds
Horticultural Science -- Dissertations, Academic -- UF
Genre: Horticultural Science thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: TITLE CROPPING SYSTEM COMPLEXITY FOR SUPPRESSING PESTS IN ORGANIC VEGETABLE PRODUCTION ABSTRACT Two field experiments were initiated in summer 2006 to compare the effects of crop rotation, cover crops, living mulches, and intercropping on pest populations. Treatments consisted of cropping systems with summer fallow followed by fall and spring vegetables. Yellow squash and bell pepper were planted in experiment I during year 1 and rotated with broccoli and sweet corn in year 2. In experiment II, broccoli and sweet corn were planted in year 1, and squash and bell pepper in year 2. Cropping systems represented three levels of complexity. The simple cropping system was a summer fallow followed by sole fall and spring vegetables. Four intermediate cropping systems utilized summer cover crops of pearl millet (PM), sorghum-sudangrass (SS), sunn hemp (SH), or velvetbean (VB) followed by sole fall and spring vegetables. Two complex systems included either pearl millet-sunn hemp (PMSH) or sorghum sudangrass-velvetbean (SSVB) mixtures. In the complex systems, row middles of fall squash and broccoli were planted with rye-hairy vetch and crimson clover as living mulches, and bush beans were intercropped with spring vegetables. Weeds and nematode populations were monitored during each season and insect pests in spring only. Soil samples were collected annually for evaluating the weed seedbank. Systems planted with SS or PM increased root-knot nematodes while the SS system also increased ring and lesion nematode populations. Cropping systems failed to suppress aphid populations. PM and SS systems decreased thrips populations while PM and SH systems reduced whitefly populations in sweet corn. In experiment I, fewer grasses, broad-leaf weeds and total weed biomass were observed with the SSVB system than the WF system. In experiment II, the SSVB system resulted in fewer grass weeds between beds than the WF system; however, no differences were observed among systems for broad-leaf and sedge weed densities and total weed biomass. Cropping systems did not change the composition of the weed seedbank. Squash and sweet corn marketable yields were highest in the PM system while no differences were observed between complex and WF systems. In experiment II, bell pepper marketable yield was higher in complex than WF systems. Predicted population dynamics of southern crabgrass and Florida pusley indicated no differences among cropping systems.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Manish Bhan.
Thesis: Thesis (Ph.D.)--University of Florida, 2010.
Local: Adviser: Chase, Carlene A.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2011-04-30

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2010
System ID: UFE0041224:00001


This item has the following downloads:


Full Text

PAGE 1

1 CROPPING SYSTEM COMPLEXITY FOR SUPPRESSING PESTS IN ORGANIC VEGETABLE PRODUCTION By MANISH BHAN A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORID A IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2010

PAGE 2

2 Manish Bhan

PAGE 3

3 To my beloved parents, Vishnu and Rama Bhan; my wife, Kanchan; and daughter, Roma

PAGE 4

4 ACKNOWLEDGMENTS I would like to acknowledge my major pr ofessor Dr. Carl ene A. Chase for her support, guidance, and providing an assistantsh ip for my graduate training program. I would also like to thank the other members of my committee, Drs. R. McSorley, O. E. Liburd, D. D. Treadwell, and W. P. Cropper, Jr. for their s upport, and assistance during this program. I would also thank the personn el and staff of the Pl ant Science Research and Education Unit at Citra for their kind sup port in providing every facility for my field experiment. I want to further thank Khalid Omer and Michael Alligood for helping in the field and laboratory. In addition, thanks to Marc Frank and Ba rry Davis from the Florida Museum of Natural History for identifying w eed specimens. Beside this, many thanks to Aditya Singh, Meghan Brennan and Nicacio-Cruz Huerta for helping with analyzing the data. I also want to thank other lab. members, Stuar t Weiss, Mariana Riehm, Alyssa Cho and Pei-wen Huang for helping in the field and greenhouse. I also value the friendship and help of Daljeet Singh, Bijay Tamang, Ashish Gupta, Sachin Gadekar, Atul Puri, Amit Sethi, Sharan Asundi, Amit Dhingra, Mukesh Jain, Sunil Joshi, Joshua Adkins, and Teddy McAvoy during my stay in Gainesville and supporting in difficult moments. Finally, I want to express my gr atitude to my family members for supporting me during every part of my PhD program.

PAGE 5

5 TABLE OF CONTENTS page ACKNOWLEDG MENTS .................................................................................................. 4 LIST OF TABLES............................................................................................................ 8 LIST OF FIGURES ........................................................................................................ 12 ABSTRACT................................................................................................................... 15 CHA PTER 1 INTRODUCTION.................................................................................................... 17 2 EFFECT OF CROPPING SYSTEM COMP LEXITY ON PLANT-PARASITIC NEMATODES ASSOCIATED WITH ORGANICALL Y GROWN VEGETABLES IN FLOR IDA............................................................................................................ 24 Introduc tion ............................................................................................................. 24 Materials and Methods............................................................................................ 27 Experiment I (Squash Bell P epper) ................................................................ 28 Squas h....................................................................................................... 28 Bell pe pper ................................................................................................. 29 Experiment II (Brocco li Sweet Corn) .............................................................. 30 Brocco li...................................................................................................... 30 Sweet corn................................................................................................. 31 Data collecti on and anal ysis ............................................................................. 32 Results.................................................................................................................... 33 Root-Knot Nematodes ...................................................................................... 33 Ring Nema todes ............................................................................................... 34 Lesion Ne matodes ........................................................................................... 35 Spiral Ne matodes ............................................................................................. 36 Stubby Root Nematodes .................................................................................. 36 Discuss ion .............................................................................................................. 36 Conclu sion .............................................................................................................. 40 3 EFFECT OF COVER CROPS AND INTE RCROPPING ON THE POPULATION DENSITIES OF WHITEFLIES, APHIDS AND THRIPS IN ORGANICALLY GROWN SWEET CORN AND BELL PEPPER ....................................................... 51 Introduc tion ............................................................................................................. 51 Materials and Methods............................................................................................ 54 Monitoring of Aphids, Whiteflies and Thrips with Unbaited Yellow Sticky Traps ............................................................................................................. 56 Statistical analysis ............................................................................................ 57 Results.................................................................................................................... 57

PAGE 6

6 Sweet Corn....................................................................................................... 58 Bell P epper ....................................................................................................... 58 Discuss ion .............................................................................................................. 59 Conclu sion .............................................................................................................. 60 4 IMPACT OF CROPPING SYSTEM COMPL EXITY ON GROWTH AND YIEL D OF ORGANICALLY PRO DUCED VEGET ABLES.................................................. 66 Introduc tion ............................................................................................................. 66 Materials and Methods............................................................................................ 69 Results.................................................................................................................... 72 Experiment I: Cover Crops-Squash-P epper; Cover Crops-Broccoli-Sweet corn ............................................................................................................... 72 Experiment II: Cover Crops-Broccoli-Sw eet Corn; Cover Crops-Squ ash-Bell Pepper .......................................................................................................... 74 Discuss ion .............................................................................................................. 76 Experiment I: Cover Crops-SquashBell Pepper; Cover Crops-BroccoliSweet Corn ................................................................................................... 76 Experiment II: Cover Crops-Broccoli-Sw eet Corn; Cover Crops-Squ ash-Bell Pepper .......................................................................................................... 78 Conclu sion .............................................................................................................. 80 5 WEED COMMUNITY RESPONSE TO ORGANIC VEG ETABLE CROPPING SYSTEM COMPLEXITY IN FL ORIDA.................................................................... 97 Introduc tion ............................................................................................................. 97 Materials and Methods............................................................................................ 99 Results and Discussion......................................................................................... 106 Experiment I: 2006 Cover Crop-Squash-Pepper; 2007 Cover CropBroccoli-Sw eet Corn ................................................................................... 106 Weeds bet ween beds .............................................................................. 106 Weeds within crop ro ws ........................................................................... 108 Weed biom ass ......................................................................................... 110 Experiment II: 2006 Cover Crop-Broccoli-Corn; 2007 Cover Crop-SquashBell P epper .................................................................................................. 112 Weeds bet ween beds .............................................................................. 112 Weeds within crop ro ws ........................................................................... 114 Weed biom ass ......................................................................................... 116 Hand weed ing. ......................................................................................... 117 Conclu sion ............................................................................................................ 117 6 IMPACT OF MULTIPLE CROPPING SYSTEM S ON WEED FLORA SHIFTS AT DIFFERENT S OIL D EPTHS ................................................................................. 139 Introduc tion ........................................................................................................... 139 Materials and Methods.......................................................................................... 141 Soil Sample Collection ................................................................................... 143

PAGE 7

7 Data Anal ysis: ................................................................................................ 144 Results.................................................................................................................. 145 Discuss ion ............................................................................................................ 147 Conclu sion ............................................................................................................ 149 7 IMPACT OF CROPPING SYSTEM COMP LEXITY ON THE POPULATION DYNAMICS OF SOUTHERN CRABG RASS AND FL ORIDA PUSLEY IN ORGANIC VEGETABLE PRODUCTION UNDER NORTH FLORIDA CONDITIONS....................................................................................................... 161 Introduc tion ........................................................................................................... 161 Materials and Methods.......................................................................................... 163 Collection of Soil Samp les .............................................................................. 164 Greenhouse Weed S eedbank St udy .............................................................. 164 Field Weed D ensity Study .............................................................................. 165 Data A nalysis ................................................................................................. 165 Climat e..................................................................................................... 165 Seedbank................................................................................................. 166 Till age...................................................................................................... 166 Tillage fa ctor ............................................................................................ 166 Seed mort ality .......................................................................................... 166 Emergence rate....................................................................................... 167 Southern Crabgr ass M odel ............................................................................. 167 Florida Pusl ey Model ...................................................................................... 168 Results and Discussion......................................................................................... 168 Simulati ons ..................................................................................................... 169 Southern cr abgrass .................................................................................. 169 Florida pusley ........................................................................................... 170 Model descr iption ........................................................................................... 171 Southern cr abgrass .................................................................................. 171 Florida pusley ........................................................................................... 172 Conclu sion ............................................................................................................ 173 APPENDIX A SOUTHERN CRABG RASS PR OGRAM ............................................................... 197 B FLORIDA PUSL EY PROGR AM ............................................................................ 199 C NATIONAL ORGA NIC PR OGRAM ....................................................................... 201 LIST OF RE FERENCES ............................................................................................. 203 BIOGRAPHICAL SKETCH .......................................................................................... 220

PAGE 8

8 LIST OF TABLES Table page 2-1 Cropping systems used as treatments z............................................................ 41 2-2 Cover crop treatm ents and seed sources used. ................................................ 42 2-3 Maximum and minimum soil temperatures (20 cm depth) during cover crop growing seasons in 20 06 and 2007 at Citra, FL ................................................. 43 2-4 Maximum and minimum soil temperat ures (20 cm depth) during growing season of both fall vegetables of both years at Citra FL.................................... 44 2-5 Root-knot nematode popul ation density in both ex periments and years at Citra, FL z........................................................................................................... 45 2-6 Ratio of final (Pf) to initial (Pf) root-knot nematode population lev els in soil at different cropping se asons in 2007-08................................................................ 46 2-7 Ring nematode population density in both experiments and years in Citra, FL z..................................................................................................................... 47 2-8 Lesion nematode populatio n density in both experiments and years in Citra, FL z..................................................................................................................... 48 2-9 Spiral nematode population density in both experiments and years in Citra, FL z..................................................................................................................... 49 2-10 Stubby-root nematode population density in both ex per iments and years in Citra, FLz............................................................................................................ 50 3-1 Cover crop treatments planted in this ex periment at Citra, Fl orida.................... 61 3-2 Management practices with their dat es in s pring crops in 2007 and 2008........ 62 3-3 Maximum, minimum air temperatur es ( C) and relativ e humidity (%) observed during sp ring 2007 and 2008.............................................................. 63 3-4 Aphid, thrips, and whitefly populations per trapa in sweet corn in spring 2007 and 2008 b.......................................................................................................... 64 3-5 Aphid, thrips and whitefly populations per trapa in bell pepper in spring 2007 and 2008 b.......................................................................................................... 65 4-1 Cropping system treatments used in experiments I and II a............................... 81 4-2 Details of cover crops planted in this ex periment at Citra, FL............................ 82

PAGE 9

9 4-3 Management practices with their dat es in squash and bell-pepper from 2006 to 2008............................................................................................................... 83 4-4 Management practices with their dates in broccoli and sweet corn from 2006 to 2008 ............................................................................................................... 84 4-5 Cover crop height and percent light interception in 2006 and 2007 in experiment Ia...................................................................................................... 85 4-6 Cover crop height and percent light interception in 2006 and 2007 in experiment IIa..................................................................................................... 86 4-7 Total and marketable yields of bush bean intercropped with bell pepper and sweet corn in 2007 an d 2008 ............................................................................. 86 5-1 Cropping system treatm ents used in experiments a........................................ 118 5-2 Details of cover crops planted in this ex periment at Citra, FL.......................... 119 5-3 Influence of cropping syst em on grass weed population (m-2) between beds in experiment I a................................................................................................ 120 5-4 Influence of cropping system on broad-leaf w eed population (m-2) between beds in expe riment I......................................................................................... 121 5-5 Influence of cropping systems on sedge population (m-2) between beds in experiment I a................................................................................................... 122 5-6 Cover crop and crop biomass throughout 2-year cropping system i n experiment I a.................................................................................................... 123 5-7 Influence of cropping syst em on grass weed population (m-2) within crop rows in experiment I ab...................................................................................... 124 5-8 Influence of cropping system on broad-leaf w eed population (m-2) within crop rows in experiment I ab...................................................................................... 125 5-9 Influence of cropping system on sedge population (m-2) within crop rows in experiment I ab.................................................................................................. 126 5-10 Influence of cropping system on total weed biomass (g m-2) between beds in experiment I a................................................................................................... 127 5-11 Influence of cropping system on total weed biomass (g m-2) within crop rows in experiment I ab.............................................................................................. 128 5-12 Influence of cropping syst em on grass weed population (m-2) between beds in experiment II a............................................................................................... 129

PAGE 10

10 5-13 Influence of cropping system on broad-leaf w eed population (m-2) between beds in experiment IIa....................................................................................... 130 5-14 Influence of cropping system on sedge population (m-2) between beds in experiment IIa................................................................................................... 131 5-15 Influence of cropping syst em on grass weed population (m-2) within crop rows in experiment II ab..................................................................................... 132 5-16 Influence of cropping system on broad-leaf w eed population (m-2) within crop rows in experiment II ab..................................................................................... 133 5-17 Influence of cropping systems on sedge population (m-2) within crop rows in experiment II ab................................................................................................. 134 5-18 Influence of cropping system on total weed biomass (g m-2) between beds in experiment II a.................................................................................................. 135 5-19 Influence of cropping system on total weed biomass (g m-2) within crop rows in experiment II ab............................................................................................. 136 5-20 Cover crop and crop biomass throughout the 2-year cropping system in Experiment II a.................................................................................................. 137 5-21 Hand weeding time (man-hours/ha) at different time intervals in spring 2007 and 2008a......................................................................................................... 138 6-1 Cropping system treatm ents used in experiments a........................................ 150 6-2 Details of cover crops planted in this ex periment at Marion County, FL.......... 151 6-3 Management practices with their dates of fall and sp ring vegetables .............. 152 6-4 Maximum and minimum soil temperat ure (20 cm depth) during cover crop growing season, 2006 and 2007, at ex per imental field, Marion County, FL..... 153 6-5 Maximum and minimum soil temperature (20 cm depth) during growing season of both fall vegetable crops for both years in experimental field, Marion Count y, FL ............................................................................................ 154 6-6 Major weed species at differ ent s oil depths, May 2006 and July 2008............ 155 6-7 Weed species populations/254.8 cm2 at different soil depths in Experiment I (cover crop-squash-pepper; cove r crop-broccolisweet corn)........................... 156 6-8 Weed species richness, diversity, and evenness at different soil depths in Experiment I (cover c rop-squash-pepper; cover crop-broccoli-sweet corn)...... 157

PAGE 11

11 6-9 Weed species populations/254.8 cm2 at different soil depth in Experiment II (cover crop-Broccoli-sweet co rn-cover cropsquash-pe pper)........................... 158 6-10 Weed species richness, diversity, and evenness at different soil depths in Experiment II (cover crop-broccoli-sweet corn; cover crop-squashpepper)..... 159 6-11 Comparison of weed species density/254.8 cm2 in summer 2006 and summer 2008, in both experiments a................................................................ 160 7-1 Cropping system treatm ents used in experiments a........................................ 174 7-2 Cover crop treatments planted in this ex periment at Citra, Florida.................. 175 7-3 Management practices with their dates of the cropping system from 2006 to 2008 at Cit ra, FL ............................................................................................... 176 7-4 Effect of increasing or decreasing model parameters on the ratio of final state variable number s relative to unaltered state variable of southern crabgrass afte r 128 w eeks............................................................................... 195 7-5 Simulated cover crop systems effect on numbers relative to WF system of germinated seedlings of sout hern crabgrass a fter 128 w eeks.......................... 195 7-6 Effect of increasing or decreasing model parameters on the ratio of final state variable number s relative to unalte red state variable of Florida pusley after 128 weeks................................................................................................ 196 7-7 Simulated cover crop systems effect on numbers relative to WF system of germinated seedlings of Florida pusley afte r 128 w eeks .................................. 196

PAGE 12

12 LIST OF FIGURES Figure page 4-1 Cover crop biomass in 2006 and 2007 in experiment I ...................................... 87 4-2 Total and marketable yield of fall squash 2006 in different cropping systems in experiment I .................................................................................................... 88 4-3 Total and marketable yield of fall br occoli 2007 in different cropping systems in experiment I .................................................................................................... 89 4-4 Total and marketable yield of spri ng bell pepper 2007 in different cropping systems in ex periment I...................................................................................... 90 4-5 Total and marketable yield of spri ng sweet corn 2008 in different cropping systems in ex periment I...................................................................................... 91 4-6 Cover crops biomass in summer 2006 and 2007 in experiment II ..................... 92 4-7 Total and marketable yield of fall br occoli 2006 in different cropping systems in experiment II ................................................................................................... 93 4-8 Total and marketable yield of fall squash 2007 in different cropping systems in experiment II ................................................................................................... 94 4-9 Total and marketable yield of spri ng sweet corn 2007 in different cropping systems in ex periment II..................................................................................... 95 4-10 Total and marketable yield of spri ng bell pepper 2008 in different cropping systems in ex periment II..................................................................................... 96 7-1 Multiple cropping systems in organic vegetable production in Experiment...... 178 7-2 Diagrammatic model showing weed seedbank and seedling levels of southern crabgrass an d Florida pusley ............................................................. 179 7-3 Maximum and minimum air temperatur es and rainfall in the exper iment field during the cropping seas on (CC=Cove r crops)................................................ 180 7-4 Simulation of germinated seedlin gs and seed bank populations of Southern Crabgrass dynamics in PM cropping systems (X1= We ed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lowe r (10-15 cm) laye r)......................................................... 181 7-5 Simulation of germinated seedlin gs and seed bank populations of Southern Crabgrass dynamics in SH cropping systems (X1= We ed seedlings in the

PAGE 13

13 field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lowe r (10-15 cm) laye r)......................................................... 182 7-6 Simulation of germinated seedlin gs and seed bank populations of Southern Crabgrass dynamics in SS cropping systems (X1= We ed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) laye r. Number of seedlings was in 10000 /m2 on Y-axis)................................................................................................... 183 7-7 Simulation of germinated seedlin gs and seed bank populations of Southern Crabgrass dynamics in SSVB cr opping syst ems (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) laye r. Number of seedlings was in 10000 /m2 on Y-axis)................................................................................................... 184 7-8 Simulation of germinated seedlin gs and seed bank populations of Southern Crabgrass dynamics in VB cropping systems (X1= We ed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) laye r. Number of seedlings was in 10000 /m2 on Y-axis)................................................................................................... 185 7-9 Simulation of germinated seedlin gs and seed bank populations of Southern Crabgrass dynamics in PMSH cropping systems (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= S eed bank population in the lower (10-15 cm) laye r. Number of seedlings was in 10000 /m2 on Y-axis.................................................................................................... 186 7-10 Simulation of germinated seedlin gs and seed bank populations of Southern Crabgrass dynamics in WF crop ping syst ems (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lowe r (10-15 cm) laye r)......................................................... 187 7-11 Simulation of germinated seedlings and seed bank populations of Florida Pusley dynamics in PM cropping systems (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lowe r (10-15 cm) laye r) ......................................................... 188 7-12 Simulation of germinated seedlin gs and seed bank populations of Florida Pusley dynamics in SH cropping systems (X 1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lowe r (10-15 cm) laye r)......................................................... 189 7-13 Simulation of germinated seedlings and seed bank populations of Florida Pusley dynamics in SS cropping systems (X 1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lowe r (10-15 cm) laye r) ......................................................... 190

PAGE 14

14 7-14 Simulation of germinated seedlings and seed bank populations of Florida Pusley dynamics in VB cropping systems (X 1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lowe r (10-15 cm) laye r) ......................................................... 191 7-15 Simulation of germinated seedlings and seed bank populations of Florida Pusley dynamics in PMSH cropping systems (X1= We ed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lowe r (10-15 cm) laye r)......................................................... 192 7-16 Simulation of germinated seedlings and seed bank populations of Florida Pusley dynamics in SSVB cropping systems (X1= Wee d seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lowe r (10-15 cm) laye r)......................................................... 193 7-17 Simulation of germinated seedlings and seed bank populations of Florida Pusley dynamics in WF cropping systems (X 1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lowe r (10-15 cm) laye r)......................................................... 194

PAGE 15

15 Abstract of Dissertation Pr esented to the Graduate School of the University of Florida in Partial Fulf illment of the Requirements for t he Degree of Doctor of Philosophy CROPPING SYSTEM COMPLEXITY FOR SUPPRESSING PESTS IN ORGANIC VEGETABLE PRODUCTION By Manish Bhan May 2010 Chair: Carlene A. Chase Major: Horticultural Science Two field experiments were initiated in summer 2006 to compare the effects of crop rotation, cover crops, living mulc hes, and intercropping on pest populations. Treatments consisted of cropping systems with summer fallow followed by fall and spring vegetables. Yellow squash and bell pepper were planted in experiment I during year 1 and rotated with broccoli and sweet corn in year 2. In exper iment II, broccoli and sweet corn were planted in year 1, and s quash and bell pepper in year 2. Cropping systems represented three levels of comple xity. The simple cropping system was a summer fallow followed by sole fall and sp ring vegetables. Four intermediate cropping systems utilized summer cover crops of pear l millet (PM), sorghum-sudangrass (SS), sunn hemp (SH), or velvetbean (VB) followed by sole fall and spring vegetables. Two complex systems included either pearl m illet-sunn hemp (PMSH) or sorghum sudangrass-velvetbean (SSVB) mi xtures. In the complex systems, row middles of fall squash and broccoli were planted with rye-hai ry vetch and crimson clover as living mulches, and bush beans were interc ropped with spring vegetables. Weeds and nematode populations were monitored during each season and insect pests in spring

PAGE 16

16 only. Soil samples were collected annually for evaluating the weed seedbank. Systems planted with SS or PM increased root-knot nematodes while the SS system also increased ring and lesion nematode populations Cropping systems failed to suppress aphid populations. PM and SS systems decreased thrips populations while PM and SH systems reduced whitefly populations in sweet corn. In experiment I, fewer grasses, broad-leaf weeds and total weed biomass we re observed with the SSVB system than the WF system. In experim ent II, the SSVB system resulted in fewer grass weeds between beds than the WF system; however no differences were observed among systems for broad-leaf and sedge weed densit ies and total weed biomass. Cropping systems did not change the composition of the weed seedbank. Squash and sweet corn marketable yields were highest in the PM system while no differences were observed between complex and WF systems. In exper iment II, bell pepper marketable yield was higher in complex than WF systems. Pr edicted population dynamics of southern crabgrass and Florida pusley indicated no differences among cropping systems.

PAGE 17

17 CHAPTER 1 INTRODUCTION Organic agriculture employs a holisti c production management system, which aims to pro mote biodiversity, including biological cycles, and enhances soil biological activity while minimizing the use of ex ternal inputs (NOSB, 2001). It is managed in accordance with the act and regulations in re sponse to site-specific conditions by integrating cultural, biological, and mechanical practices that foster cycling of resources, promote ecological balance, and conserve biodiversit y (Greene and Kremen, 2003). It depends on ecologically based management prac tices for controlling pests and avoids the use of synthetic chem icals, antibiotics, hormones, and genetically modified organisms in crop production (NOSB, 2001). Growing concern about adverse effects of conventional agriculture on the environment and increasing consumer demand for organic food have shifted some members of the farming community to adopt organic farming (Offner, 2000). This has resulted in an increase in certified organic land for crop production in the United States (U.S.) and Florida by 30 percent and 39 percent, respectively from 2000 to 2005 (USDA-ERS, 2005). However, acreage for or ganic vegetable production increased by only 4 percent in Florida from 2000 to 2005 (USDA-ERS, 2005). In the U.S., sales of organic food have jumped from $3.5 billion in 1997 to nearly $10.4 billion in 2003 (or about 1.8 percent of the total U.S. retail sales of food) wit h an annual growth rate of around 20 percent (Nutrition Business Journal, 2004). In 2003, sales of organic produce were $4.3 b illion (or 42 percent of the U.S. total organic food sales) of which fresh produce was 93 percent. It is estimated that the sales of organic fruits and vegetables could reac h $8.5 billion by 2010 (Nutrition Business

PAGE 18

18 Journal, 2004). Currently, conventional market s in Florida are importing organic produce from California (Blumenthal, 2007; Thu-Vi Nguyen et al., 2008), which suggests a greater demand for more organic produce than supply in this region. Therefore, it can be anticipated that organic farming acreage will in crease in this region. This will require science-based management strategies, specif ic for organic farming systems in this region. Pest infestation tends to be greater with high temperature and rainfall, particularly in tropical and sub-tropical regions (Oerke 2006) like Florida. Since, weeds can adversely affect crop yield (Cousens, 1987) their control is important for crop production. Currently, many conventional growers are tr ansitioning their farming operations to organic producti on but are confronting many problems, of which weed control is vital (OFRF, 1998). A national survey reported weed control as the major challenge for organic growers (Sooby, 2003). In organic agriculture, weed management strategies depend upon weed and crop ecology in a given agro-ecosystem (Brber i, 2002). Brberi (2002) suggested a holistic approach to weed management in organic agricultur e that integrates cultural practices in a cropping system for managing weeds. Oerke (2006) recommended the use of diverse agro-ecosystem, which should be less su sceptible to pest attack than a simple agro-ecosystem. Liebman and Staver (2001) also recommended crop diversification with crop rotation and intercropping in order to suppress germination, establishment, growth, competitive ability, and reproduction of weeds. An increase in biodiversity at any level (crops, weeds, arthropods, soil microbes, etc) has the potential to promote a stable agro-ecosystem in terms of health and pr oductivity (Brberi, 2002; Altieri, 1995).

PAGE 19

19 Diversifying cropping systems in north Florida also may be an option to manage insect pest populations. There were studies that s uggest that a diversif ied cropping system or vegetables intercropped with cover crops suppressed whiteflie s populations (Gold et al., 1989; Frank and Liburd, 2005). This approach shoul d minimize the use of external farm inputs; increase dependence on ec ological processes like resource competition with cover crops or intercropping, post dispersa l weed seed predation, and soil solarization; and weed management should be designed as one component in the integrated agricultural system that impr oves crop productivity, farm revenues and environmental quality (Liebman and Gallandt, 1997; Buhler et al., 2000; Liebman and Davis, 2000, and Mortensen et al., 2000). Vegetable crops are susceptible to w eed infestation because they are generally not very competitive against weeds and because of high interand intra-row spacing (Baumann et al., 2000). In addition, few her bicides are registered in vegetable production. Chemical and mechanical ap proaches favor erosion, ground water contamination, development of herbicide resistance, and soil degr adation (Pimental et al., 1992). Crop rotation can improve soil characte ristics, reduce pest pressure, and increase crop yield as com pared with continuous monocult ures (Liebman and Staver, 2001). Continuous production of a single crop with similar management practices increases the number of weed species that thrive under those conditions (Liebman and Staver, 2001). Diverse rotation with different dates of planting and harvesting, crop growth habits, and cultivati on equipment increase stress and mortality risk to weeds (Liebman and Dyck, 1993; Liebman and Ohno, 1998).

PAGE 20

20 Summer cover crops can be planted duri ng the fallow period between spring and fall vegetable crops in the southeastern U.S (Creamer and Baldwin, 2000). Both living cover crops and their residues suppress weed seed germination and emergence (Teasdale, 1993). Cover crops can also serve as a food source for generalist predators, which attack insect pests of vegetables (S cott, 2008; Bugg et al., 1991; Lu et al., 2000; Sullivan, 2003; Costello and Altieri, 1995). Cover crops in organic agricultural systems also provide habitats for weed seed predators (Gallandt, 2006; Carmona and Landis, 1999). Cover crops reduce the weed seedbank directly by occupying space and resources otherwise used by weeds (Gallandt, 2006). Operations used to kill cover crops also terminate weeds before mature seeds are set (Gallandt, 2006). Beside weed control, cover crops may also be an im portant tool for nematode management in sustainable agricultural syst ems (Wang et al., 2004; McSorley and Porazinska, 2001). Suppression of plant-parasitic nematodes has been reported with many cover crops like sunn hemp, velvetbean, pearl millet, and so rghum sudangrass (Wang et al., 2004; Qunherv et al., 1998; McSorley et al ., 1994b; Ball-Coelho et al., 2003). This research may be helpful in further understandi ng population dynamics of plant-parasitic nematodes in cover crop based cropping systems. The benefits of cover crops may be optimiz ed when mixtures of cover crops are used (Creamer et al., 1997). Legume cover crops fix more nitrogen from the atmosphere when planted in mixtures with non-legume cover crops (Ofori and Stern, 1987). Non-legume cover crops deplete nitrogen from the soil, which causes associated legumes to increase nitrogen fixation. Cover crop mixtures of grass and legumes also maintain C:N ratios favorable for mi neralizing nitrogen, and suppress a broader

PAGE 21

21 spectrum of weeds through allelopathy if the component crop of the mixtures are allelopathic (Creamer et al ., 1997). Cover crops suppressed insect pests by altering host-plant nutrition or change in micro-c limate, and improve natural enemy abundance (Bugg and Waddington, 1994). They also ha rbor general pests, which damage the target crop due to luxury c onsumption of nitrogen particula rly in legume cover crops. This can lead to an outbreak of pests (Bugg and Waddington, 1 994). Therefore, an understanding of the effect of cover crop based cropping systems on whitefly and aphid populations will be required. There may be a need to develop systems with mixed grassy and legume cover crops, living mulche s, and intercrops that may mitigate whitefly and aphid populations. Intercropping increases the ecological di versity of farms and crop competitive ability against weeds and thereby deprives weeds by light, water, and nutrients (Liebman and Dyck, 1993). Soil and crop management factors have indirect effects on weeds due to crop-crop interactions in in tercropping systems (Vandermeer, 1989). In addition, intercrops also reduce insect and disease damage of an associated crop by providing favorable environments for insect -pest predators, and disrupt insect-pest ability to locate, feed upon or infect host plants (Liebman and Staver, 2001; Vandermeer, 1989; Trenbath, 1993; Altieri, 1994). Living mulches are a special case of intercropping in which a non-cash crop is grown for ecological purposes during part or all of the cash cropping period. Living mulch vegetation inhibits light-mediated weed seed germination as it lowers the red-tofar red ratio of light (higher ra tios can trigger a phytochrome re ceptor in seeds to initiate germination) (Teasdale and Daughtry, 1993) Living mulches reduce population

PAGE 22

22 densities of multiple pest complexes (Hook et al., 1998) and signific antly increase the abundance of natural enemies (Frank and Liburd, 2005). The following research was done to examine the effect of various cropping systems on the population densities of weeds plant-parasitic nematodes, and insectpests in organic vegetable cropping systems in North-Central Florida. Crop rotation, cover crops, living mulches, and intercropping were integrated in seven different cropping systems representing three levels of complexity. The simple cropping system included weedy fallow during summer followed by fall and spring vegetable crops grown as sole crops; Intermediate systems ut ilized grass and legume cover crops planted during summer followed by fall and spring vegetables grown as sole crops; and complex systems included grass and legume cover crop bicultures during the fallow period. In the complex cropping systems, row middles of fall vegetables were planted with living mulches, and spring vegetables were strip in tercropped. This research was supported by the Integrated Organic Program of the USDA, Cooperativ e State Research Education and Extension Service with the grant entitled, Crop Diversification Complexity and Pest and Beneficial Organism Communities in Humid Tropical and SubTropical Climatic Regimes. The general objecti ves of my research were to evaluate 1) the effect of cropping system complexity on the population densities of selected plantparasitic nematodes; 2) the ef fect of cropping system comp lexity on aphid, thrips, and whitefly populations in organi cally planted sweet corn and bell pepper; 3) the impact of crop rotation, cover crops, living mulch, and intercrop systems on gr owth and yield of organically produced vegetables; 4) the effect of cropping system complexity on weed population densities; 5) the impact of cropping system complexity on weed seedbank

PAGE 23

23 composition; and; 6) the population dynamics of southe rn crabgrass and Florida pusley weeds in different cropping systems. The corresponding hypotheses were: (1) increased cropping system complexity will reduce nematode populat ion density as a result of poor or non-hosts included in the multiple cropping systems; (2) increase in cropping system complexity will suppress aphid, thrips, and whitefly populations in or ganically grown bell pepper and sweet corn; (3) multiple cropping systems improve veget able growth and yield due to reduced weed population; (4) complex cropping systems suppress weed density and biomass more effectively compared to simple systems; (5 ) increase in cropping system complexity depletes the weed seedbank and causes we ed flora shifts; and (6) cropping system complexity will affect the population dynam ics of the southern crabgrass and Florida pusley.

PAGE 24

24 CHAPTER 2 EFFECT OF CROPPING SYSTEM COMP LEXITY ON PLANT-PARASITIC NEMATODES ASSOCIATED WITH OR GANICALL Y GROWN VEGETABLES IN FLORIDA Introduction Organic farming has increased rapidly du e to increasing consumer demand and growing concerns for the environment (Offner, 2000). It c onsists of both traditional methods and modern farming techniques without the use of synthetic pesticides and fertilizers (Hallmann et al., 2007) In the US alone, sales of organic food have jumped from $3.5 billion in 1997 to nearly $10.4 billion in 2003 (or about 1.8% of the total US retail sales of food) with an annual growth rate of about 20% (Nutrition Business Journal, 2004). Constraints in organic farming like absence of synthetic nematicides and soil fumigants make vegetable crops vulnerable to important pests like weeds, insects, and plant-parasitic nematodes. The incidence of pest problems might be greater with high temperature and rainfall, particularly in tropical and sub-tropical regions (Oerke, 2006) like Florida. Root-knot ( Meloidogyne spp.) and reniform ( Rotylenchulus spp.) nematodes are probably the most important nematode pests of vegetable crops in tropical and warm temperate areas (Sasser and Freckman, 1986). Overall, plantparasitic nematodes are estimated to c ause a loss of 12.3% on the worlds major agricultural crops (Sasser and Freckman, 1986). In practice, nematode infestations may be overlooked or misidentified as other pest symptoms, and as a result they may not be properly managed, allowing increases in population and damage to crops (Hallmann et al., 2007). Several different types of cultural practices can be used for nematode management including resistant cultivars, and elements of multiple cropping systems

PAGE 25

25 such as cover crops, crop rotation, and nematode-antagonistic crops (McSorley, 1998). Crop sequences should be designed in a croppi ng system in a manner to minimize the damage caused by plant-parasitic nematodes by including nematode resistant plants as rotational crops (Noe, 1988; Noe et al., 1991; McSorley and Gallaher, 1991). Crop rotation is ideal for managi ng plant-parasitic nematode populations by planting susceptible and non-susceptible crops in an alternate sequence (Trivedi and Barker, 1986; Noe, 1988); however, use of a rotati onal crop depends on the economics and adaptability for a specific region (McSorley 1998). In organic farming, rotations are longer with shorter fallow periods to minimize nutrient leaching, which may affect plantparasitic nematodes in the soil (Hallm ann et al., 2007). Hallmann et al. (2007) recommended that crop rotation with a broad crop species spectrum is good for organic farming. Sometimes, crop rotation can becom e complex when a crop resistant to one nematode species acts as a host for another nematode species (McSorley et al., 1994b). Incorporating cover crops for ne matode management may be an important approach for developing sustainable agricultu ral systems (Wang et al., 2004; McSorley and Porazinska, 2001). Several different grassy and legume cover crops have been used to maintain low numbers of plant-parasitic nematodes. Sunn hemp ( Crotalaria juncea L.) cover crops planted in fall main tained lower population densities of both M. incognita and Helicotylenchus dihystera (Wang et al., 2004). Velvetbean ( Mucuna pruriens DC also known as M. deeringiana (Bort.) Merrill) suppressed population densities of both M. incognita and R. reniformis prior to the cultivation of susceptible short-term vegetable crops (Qunher v et al., 1998). Sorghum-sudangrass ( Sorghum

PAGE 26

26 bicolor x S. sudanense [Stapf] Hitchc.) was effective in maintaining low population densities of Meloidogyne spp. but increased the population levels of Paratrichodorus minor (McSorley et al., 1994b) and Mesocriconema spp. (Crow et al., 2001). Forage pearl millet Pennisetum glaucum L. (CFPM 101) (Ball-Coelho et al., 2003) and grain pearl millet (CGPMH-1) have potential for managing lesion nematodes in the potato production system in Quebec (Belair et al., 2006). Another useful grass cover crop is rye ( Secale cereale L., cv Wrens Abruzzi), whic h resulted in decline of M. incognita when grown as a winter cover crop (Opperman et al., 1988). The current study focused on under standing population dy namics of plantparasitic nematodes as a result of integr ating cultural practices like crop rotation, summer cover crops, living mulch, and interc rops in multiple cropping systems for organic vegetable production. This information will be useful for anticipating nematode population buildup over time, re cognizing suppressive effects of poor or non-hosts, and ultimately in designing cropping systems wit h minimal nematode impact. Therefore, the objective of the current research is to examine the effect of cr opping systems of various levels of complexity on the densities of selected plant-parasitic nematodes in organic vegetable production systems. Specifically, the impact of summer cover crops and vegetable cropping sequences on plant-parasit ic nematodes are examined. In addition, the buildup of root-knot nematode populati on levels on different fall and spring vegetables was also examined because t hey are the key nematode pest of most vegetable crops. Two hypotheses are exam ined: 1) components of cropping systems may affect population densities of plant-parasitic nematodes in summer cover crops and subsequent falland spring-planted organic vegetables, and 2) planting different

PAGE 27

27 vegetables in the cropping system may affect population multiplication rates of root-knot nematodes. Materials and Methods Two experiments were established concurrently in summer 2006 on certified organic land at the Plant Science Research and Education Unit, Marion County, Florida. The cropping system for each experiment c onsisted of a summer cover crop, fall vegetable, and spring vegetable in 2006-07, with the entire sequen ce repeated in 200708. The field site was used fo r the production of bahiagrass ( Paspalum notatum Flgg) prior to establishing the experiment. The soil is Candler sand (Hyperthermic, uncoated Lamellic Quartzipsamment) with 7.1 soil pH. Prior to the experiments, the field was dominated by ring ( Mesocriconema spp.) (54/100 cm3 soil, 93% of all nematodes) followed by lesion ( Pratylenchus spp., 2.2/100 cm3), spiral ( Helicotylenchus spp., 0.8/100cm3), stubby-root ( Paratrichodorus spp., 0.5/100 cm3), and sheath ( Hemicycliophora spp., 0.2/100 cm3) nematodes. Because of the low incidence of root-knot nematodes, the field was planted in May 2006 to a rootknot nematode susceptible crop, southern pea ( Vigna unguiculata Walp ) cultivar White Acre and then inoculated with Meloidogyne incognita to increase the nematode population. It was mowed on 13 July 2006 with a New Holland 918H flail mower (Purdy Tractor and Equipment, Inc. Hillsdale, MI) follow ed by application of finished mushroom compost (Quincy Farms, Quincy, FL) at 2500 kg/ha through a check drop spreader (Newton Crouch Inc., Griffin, GA). The fi eld was disked and compost incorporated to a depth of about 20 cm. Both ex periments were started on 27 July 2006 with a summer fallow consisting of either summer cover cr ops or a weedy fallow. The experimental design was a randomized complete block with se ven treatments and four replications

PAGE 28

28 (Table 2-1). Plots measured 12 m x 12 m and were separated by 12-m alleys. Cultivars, seed sources, and seeding rates of cover crops are summarized in Table 2-2. Pearl millet and sorghum sudangrass were planted with a Sukup 2100 planter (Sukup Manufacturing Company, Sheffield, IA) at 17 cm distance between plants in the row and 5 cm soil depth. Sunn hemp and velv etbean seeds were inoculated (Rhizobium sp., cowpea type, Nitragin Inc., Brookfield, WI) before broadcasting on the plot. Later, between beds area were rolled to ens ure adequate seed to soil contact. Overhead irrigation was used occasionally during the fi rst three days after planting to promote germination and establishment of the cover crops. Above-ground biomass of summer cover crops was flail mowed on 2 October 2006 and disked to incorporate into the soil. Th is was followed by the application of lime (Aglime Sales Inc., Babson Park, FL) to the entire field at 2500 kg/ha. Fall vegetables were planted with four beds (1.8 m bed-center size) per plot (12 m length x 7.2 m width plot size). Before planting fall vegetables, fertilizer (10-2-8 N-P2O5-K2O, NatureSafe, Griffin Industries, Cold Spri ng, KY) was applied at the rate of 1685 kg/ha in squash and 1976 kg/ha in broccoli based on the conventi onal fertilizer recommendations for these crops (Olson and Simonne, 2006). It was appli ed as a 30-cm band over the center of the bed and incorporated befor e planting vegetables. Experiment I (Squash Bell Pepper) Squash Yellow squash ( Cucurbita pepo L. cv. Cougar F1 untreated; Harris Seeds, Rochester, NY) was direct seeded on 19 Oct ober 2006 as single row per bed with an inrow plant distance of 45 cm (12,037 seeds /ha) in one experiment. Squash was irrigated daily through a drip irrigation system. A combination of rye ( Secale cereale cv Wrens

PAGE 29

29 Abruzzi; Alachua County Feed and Seed Store, Gainesville, FL) and hairy vetch ( Vicia villosa, cultivar unknown; Adams Briscoe Seed Company, Jackson, GA) was planted between beds as living mulch in mixed cover crop plots. The seeding rates were 48 kg/ha for rye and 22 kg/ha for hairy vetch. Be fore planting, hairy vetch was inoculated with Rhizobium leguminosarum bv viceae (Nitragin C, Nitragin Inc, Brookfield, WI). Both types of living mulch seeds were mixed and broadcasted on 9 November 2006 by hand on a shallow tilled soil fo llowed by covering the seeds with the help of roller. Row covers were placed on squash plots on 8 December 2006 to protect from frost. Squash was harvested from 14 December 2006 to 9 January 2007 with six harvests. Methods used for the squash crop in 2007-08 were similar to those of previous year, with minor exceptions. It was direct seeded on 10 October 2007. Row covers were placed on 16-19 November 2007. Squash was harvested from 21 November to 14 December 2007 with 8 harvests. Bell pepper Squash plots were rotated with green bell pepper ( C apsicum annuum L. cultivar Red Knight F1 untreated; Johnnys Selected Seeds, Winslow, ME). A compliant blended fertilizer (NatureS afe, 10-2-8 N-P2O5-K2O, Cold Springs, KY) was applied at the rate of 2232 kg/ha based on University of Floridas synthetic fertilizer recommendations for these crops (Olson and Simonne, 2006). Fertilizer was broadcast and incorporated with a rototiller prior to planting on 7 March. Remaining nitrogen was bunded and lightly incorporated on 10 April 2007. Forty-five -day-old bell pepper seedlings were transplanted on 15 March 2007 in double rows per bed. There were four beds per plot (12m x 7.2 m plot area) with distances of 45 cm between plants in rows and between rows (24,074 plants/ha). Green bush beans (Phaseolus vulgaris cultivar Bronco

PAGE 30

30 untreated, Seedway E lizabethtown, PA) were interc ropped with pepper in mixed cover crop plots. On 16 March 2007, bush bean wa s direct-seeded between bell pepper beds using a manual push planter at a distance of 15 cm between seeds. Both bell pepper and bush beans were irrigated daily using dr ip irrigation. Bell pepper was harvested from 21 May to 20 June 2007 with four harve sts. Bush bean was harvested on 16 May and 30 May 2007. In spring 2008, bell pepper was transpl anted on 13 March and bush bean on 14 March, while bell pepper was harve sted from 13 May to 9 June with four harvests and bush bean on 13 May. Experiment II (Broccoli Sweet Corn) Broccoli Thirty-day-old broccoli ( Brassica oleracea L. cv. Marathon F1, untreated; Harris Seeds, Rochester, NY) seedlings were transp lanted on 31 October 2006 in double rows (30 cm distance between rows) per bed at a distance of 45 cm between plants in rows, and a total of 8 rows per plot (24,074 pl ants/ha). Broccoli was drip irrigated daily. Crimson clover ( Trifolium incarnatum cv Dixie; Adams Br iscoe Seed Company, Jackson, GA) was planted as living mulch betw een beds in mixed cover crop plots. The seeding rate was 28 kg/ha. Crimson clover was inoculated with R. leguminosarum biovar trifolii (Nitragin R/WR, Nitragin Inc, Brookfi eld, WI) before planting. Crimson clover was broadcasted on 9 November 2006 by hand onto shallowly tilled soil followed by covering the seeds with the help of roller. Broccoli was harvested from 4 January to 16 January 2007 with three harvest s. On 5 March 2007, the fi eld was flail mowed and disked to 20-cm soil depth to prepare a seedbed for planting spring vegetables.

PAGE 31

31 Similar methods were used for management of the broccoli crop in the second year. In 2007-08, thirty-five-day-old brocco li seedlings were transplanted on 16 October 2007. It was harvested from 20 December 2007 to 2 January 2008 with 3 harvests. Sweet corn Broccoli plots were rotated with sweet corn ( Zea m ays L. cultivar Montauk F1 untreated; Johnnys Selected Se eds, Winslow, ME). A compliant blended fertilizer 10-28 N-P2O5-K2O (NatureSafe, Cold Springs, KY) was app lied at the same rate and time as in bell pepper. Sweet corn was direct-seeded on 12 March 2007 with a seed drill (Monosem Inc., Edwardsville, KS) at 76 cm between rows and plant distances of 18 cm within in rows, with a plot size of 144 m2 (74,444 plants/ha). Bush beans were also intercropped with sweet corn in mixed co ver crop plots. Bush bean was direct-seeded on 12 March 2007 with a monosem planter in four strips (4 rows/strip) arranged alternately with strips of sweet corn. Bush bean inter-row and inter-plant distances of 76 cm and 13 cm were used. Sweet corn wa s harvested on 31 May and 12 June 2007 while bush bean was harvested on 16 May and 30 May 2007. During spring 2008, sweet corn and bush beans were direct-seeded on 11 March. Potassium fertilizer, 0-0-6 N-P2O5 -K2O (Biolink, Westbridge Agricultural Products, CA) was applied over the bean plants in spring 2008 through a CO2 sprayer at a nozzle rate of 190 ml/15 seconds and 50 gallons/ha water. This was applied to correct potassium levels in response to a tissue sample analysis in bush bean plants. Sodium nitrate (Probooster, 10-0-0 N-P2O5 -K2O, North Country Organics, Bradford, VT) was also applied in sweet corn plots at 868 kg/ha on 7 May 2008 in response to nitrogen deficiency symptoms. Sweet corn was harvested on 29 May and 4 June and bush bean on 13 May 2008.

PAGE 32

32 Both experiments were rotated in the second year using methods described for the previous seasons. The field was mowed on 6 July 2007 followed by elemental sulfur (Tiger 90 with 90% sulfur, Tiger-Sul Produc ts, Atmore, AL) application at 250 kg/ha using drop spreader to lower soil pH. To avoi d having the same cover crop in the same plot in both years, the pear l millet cover crop was rota ted with sorghum sudangrass while sunn hemp was rotated with velvetbea n and vice versa. Similarly, sorghum sudangrass-velvetbean was rotated with pea rl millet-sunn hemp mixtures and vice versa. The cover crops were planted on 31 July 2007; sorghum-sudangrass and pearl millet were direct seeded with a John Deere 450 planter while sunn hemp was planted with a Sukup 2100 planter at an 18-cm row distance. Prio r to planting cover crops, sulpomag (0-0-21 N-P2O5-K2O, Diamond R Fertilizer, Winter Garden, FL) was applied at 257 kg/ha by hand. The same application was repeated after mowing the cover crops. Data collection and analysis Soil temperatures were monitored throughout each year at a depth of 20 cm using a Watchdog datalogger, Model 100 8k (Spectrum Technologies, Inc. East Plainfield, IL) at 30-minute time intervals. Soil was sa mpled from each plot after each cover crop and vegetable to estimate populati on densities of plant-parasitic nematodes. Six soil cores (2.54-cm diameter, 20-cm dept h) were collected randomly from each plot near the plant roots and composited to form a single sample. Nematodes were extracted from a subsample of 100 cm3 soil by a sieving and centrifugal flotation method (Jenkins, 1964). Nematode counts were log-transformed (log10[x+1]) to normalize the data and to accommodate zero counts. A nalysis of variance was performed on transformed values using the GLM procedure of the Statistical A nalysis System (SAS,

PAGE 33

33 2008). Means were separated by the least signifi cant difference (LSD) test at 5% level of significance. The data are re ported as untransformed means. Non-zero observations of initial (Pi) and final (Pf) populations of root-knot nematode were used to calculate multiplicat ion rate (Pf/Pi) for different cropping systems in 2007-08. Initial nemat ode population for the first vegetable crop is equal to the final nematode population fr om the summer cover crop, since the vegetables are planted right after the summer cover crops. Results Soil temperatures under cover crops ranged from <23 C in September 2006 to >37 C in August 2007 (Table 2-3). Temper atures under vegetable crops ranged from a low of 9.1 C in winter to a high of 38.7 C in bell pepper in June (Table 2-4). Plantparasitic nematodes recovered in thes e cropping systems include d root-knot, ring, lesion, spiral, and stubby-root nematodes. Root-Knot Nematodes Root-knot nematode populations remained low (< 10 per 100 cm3) and did not differ significantly among cropping systems by the end of the summer cover crops and fall season during 2006-07 in both experiments (Table 2-5) Their populations were highest in sorghum-sudangrass and lowest in sunn hemp, velvetbean, and sorghum sudangrass-velvetbean systems by the end of the spring pepper season on 22 June 2007 in the squash-pepper experiment. In the same season, root-knot nematode numbers were significantly higher in s unn hemp than pearl milletsunn hemp systems in the broccoli-sweet corn experiment. Howe ver, no cropping systems were significantly different from weedy fallow in either ex periment. After mowing of cover crops on 3 October 2007, root-knot nematode populat ions remained low and did not differ

PAGE 34

34 significantly among systems in the squash-pepper experiment while the sorghum sudangrass-velvetbean system had a signific antly higher population than systems containing pearl millet or sunn hemp in the broccoli-sweet corn experiment. By the end of the fall squash season on 18 December 2007, root-knot populations were highest in pearl millet and pearl millet-s unn hemp systems and lowest in weedy fallow and sunn hemp systems. Sunn hemp alone had lower number s of root-knot nematodes but failed to reduce root-knot nematode popul ations if planted in a mixt ure with pearl millet as a summer cover crop. In the sa me experiment at the end of the bell pepper crop, sole plantings of sorghum sudangr ass and velvetbean had signifi cantly higher root-knot populations than systems with these two crops planted together. However, in all three of these systems, numbers were not significantly different than those in the weedy fallow system. In the broccoli-sweet corn experiment, the root-k not population reached its highest level by the end of the spring sweet corn crop in the sorghum sudangrass system and lowest in the sunn hemp and pearl millet-sunn hemp systems. Population multiplication rate s of root-knot nematodes are shown in Table 2-6, which includes final nematode populations from one and two crop sequences in the second year of both experiments. The lowest multiplication rate was obtained following a single crop of broccoli. Ring Nematodes Ring nemat ode populations were signific antly higher in sorghum sudangrass velvetbean and sorghum sudangrass systems t han other cropping systems by the end of summer cover crop on 29 S eptember 2006 in both the experiments (Table 2-7). Although ring nematode population was lowe st in pearl millet and pearl millet-sunn hemp systems at that time it was not significantly differ ent from the population in weedy

PAGE 35

35 fallow. Similar high levels in systems t hat had contained sorghum-sudangrass persisted to the end of fall squash and broccoli seas ons on 18 January 2007 in both experiments. Differences became less distinct by the end of the spring vegetable crop in June 2007, although population levels remained highest in the sorghum-sudangrass system in both experiments. It is interesting that in the broccoli-sweet corn expe riment at this time, numbers in the pearl millet-s unn hemp system were lower (P < 0.05) than in weedy fallow. In the second year in both exper iments, the sorghum-sudangrass system contained significantly higher numbers of ri ng nematodes than most other cropping systems including weedy fallow by the end of the summer cover crop season on 3 October 2007. Numbers in the sor ghum sudangrass-velvetbean system were statistically similar to those in the syst em with sorghum-sudangrass alone. Differences among treatments disappeared after the fall v egetable season of the second year in both experiments, and population levels followi ng broccoli were especially low (< 5 ring nematode per 100 cm3). A few inconsistent differences among treatments occurred following the spring crops of pepper and sweet corn; however, the ring nematode population level in the weedy fallow was not significantly different from other cropping systems at that time. Lesion Nematodes The sorghum sudangrass system c ontained the highest lesion nem atode populations on all sampling dates except 22 June 2007 in squash-bell pepper and 3 October 2007 in broccoli-sweet corn experiments (Table 2-8). The sorghum sudangrass-velvetbean system also had high lesion nematodes by the end of cover crop season in both years in both experiments. Lesion nematode population levels were

PAGE 36

36 lowest in pearl millet and pearl millet-sunn hemp systems; however, they were not significantly different from weedy fallow in both experiments. By the end of the spring bell pepper crop, lesion populations were very low (< 1 nematode/100cm3) in all the cropping systems in both years. Similar resu lts were observed by the end of the fall broccoli and spring sweet corn seasons in 20 08 in the broccoli-sweet corn experiment. Spiral Nematodes Spiral nem atode population levels were low (< 5 per 100 cm3) and rarely affected by the treatments (Table 2-9). They did not build up in any of the cropping systems as the experiments progressed. Stubby Root Nematodes Stubby-root population levels were low (< 4 per 100 cm3) and showed few differences among cropping systems in the squash-bell pepper experiment (Table 210). Similarly, in the broccoli-sweet corn experiment, stubby-root nematode levels were very low (< 2 /100cm3) and not significantly different among cropping systems during the first year of the experim ent. Numbers were significant ly different among cropping systems during the second year of the expe riment; however, numbers remained very low. By the end of summer cover crop on 3 October 2007, the sorghum sudangrassvelvetbean system had significantly higher stubby-root nematode population levels than several other cropping syst ems including weedy fallow. Discussion There was no detectable population level of root-knot nematodes prior to the beginning of the experiment. This may be because of bahiagrass production before beginning of the experiment. Bahiagr ass was effective in managing Meloidogyne arenaria in peanut and soybean (Rodrguez-Kbana et al ., 1994). The root-knot

PAGE 37

37 nematode population was eit her absent or so small that it was statistically not possible to detect differences among cropping systems in both experiments by the end of the cover crop and fall vegetable seasons duri ng first year. One reason for the low population densities in soil samples collect ed on 18 January 2007 in both experiments may be due to the fact that nematode growth and development are directly affected by temperature (Noe, 1988). Root -knot nematodes typically have larger numbers of egg bearing forms at 30 to 35 oC (Carter, 1982). Meloidogyne hapla and M. incognita females reached maturity at a temperature range of 25 to 30 oC (Irrizarry et al ., 1971). The low soil temperatures recorded during t he winter months in the current experiments are well below optimum temperatures for nematode reproduction (Tables 2-3 and 2-4). Although somewhat inconsist ent, there was some evidence that the presence of sorghum-sudangrass in the cropping system resulted in higher numb ers of root-knot nematodes in some instances. The same o ccurred with pearl millet, especially in the squash-pepper experiment in the second s eason. This is unusual because sorghumsudangrass and pearl millet are cons idered useful cover crops for suppressing root-knot nematodes (Ball-Coelho et al., 2003; Bela ir et al., 2006; McSorley et al., 1994b), although the cultivars used in those studies we re different from the cultivars used in these experiments. Although cropping system treatments af fected root-knot nematode numbers, rarely did the number s obtained differ from those in the weedy fallow system. The only systems that showed long-term s uppression (through both vegetable crops) of root-knot nematodes below levels in weedy fallow were systems that contained sunn hemp, in the broccoli-sweet corn experi ment. These results suggest that sunn hemp planted alone as a summer cover crop or even in mixture with pearl millet had the ability

PAGE 38

38 to suppress populations of root-knot nemat odes in the organic broccoli-sweet corn cropping system. Wang et al ., (2004) and McSorley et al. (1994a) also suggested that sunn hemp maintains low population densities of Meloidogyne spp. Sunn hemp as a cover crop can reduce plant-parasitic nemat ode populations as a poor host (RodrguezKbana et al ., 1994), producing allelochemicals that could be toxic or inhibitory (Halbrendt, 1996), providing a niche to antagoni sts that repel or inhibit nematodes (Kloepper et al ., 1991), and encouraging major gr oups of nemat ode-antagonistic fungi (Wang et al ., 2002). The relationship between nematode populati on growth and initial population density provides a good description of resist ance or susceptibilit y of a suitable host (McSorley, 1998). The multiplication rate of root-knot nematode was lowest in the single sequence of broccoli. This impl ies that broccoli, although a host of the nematode since Pf/Pi = 2.0, may maintain root-knot nematode populations at lower levels than the other winter and spring vegetable crops. A si ngle sequence of spring bell pepper also increased root-knot nematode multip lication at a relatively low rate, but this followed the high population levels t hat built up on squash. Among the double vegetable crop systems, squash-pepper increased root-knot levels nearly four times as much as the broccoli-sweet corn system, which reflect ed the advantage of including broccoli in the system. The sorghum-sudangrass system resulted in significantly higher ring nematode populations as compared to the weedy fallow during first year in both the experiments. Ring nematode numbers were also higher in sorghum sudangrass-velvetbean systems by the end of the cover crop and subsequent fall vegetables during the first year;

PAGE 39

39 however, the nematode population was not significantly higher than that in the weedy fallow system during later stages of cropping systems. No cropping systems resulted in significantly fewer ring nematodes than the weedy fallow except the pearl millet-sunn hemp system by the end of spring sweet corn in 2007. These results suggest that sorghum-sudangrass has the ability to in crease the ring nematode population while other cropping systems failed to suppress i t. Pearl millet alone and pearl millet-sunn hemp systems were not effective in decr easing the ring nematode populations but maintained existing low densities. Crow et al (2001) observed increased population densities of ring and lesion nematodes w hen sorghum-sudangrass was planted as a summer cover crop in a potato cropping system. Sorghum-sudangrass and sorghum sudangr ass-velvetbean systems increased the lesion population by the end of summer cover crop in the first year in both experiments. The increased levels of le sion nematodes persisted through the fall vegetable crops in the first year. These results suggest that sorghum-sudangrass has the potential to increase lesi on populations if planted dur ing a summer fallow period, and are consistent with findings by McSorl ey et al. (1994 b) that sorghum-sudangrass increases the population density of lesi on nematodes. Although several cropping systems, particularly those wit h pearl millet, resulted in lower lesion nematode levels than sorghum-sudangrass, none were significant ly lower than the weedy fallow system at later stages in both experiments. These re sults suggest that pearl millet alone and in mixture with sunn hemp in the cropping system were not effective in decreasing lesion populations compared to weedy fallow, but instead maintai ned existing low densities. Amankwa et al. (2006) indi cated that pearl millet as a rotation crop with tobacco

PAGE 40

40 suppressed lesion nematode popul ation with equivalent gross returns. Dauphinais et al (2005) reported that pearl m illet had a suppressive effect on lesion nematode when rotated with potato. It is interesting that in the current study, lesion nematode populations declined to very low levels ( 1 per 100 cm3) in several of the vegetable crops, including pepper in both years. Spiral nematode population levels were too small to observe consistent cropping systems effects. Stubby-root nematode populations were lik ewise quite small, but occasionally showed increases when sorghum-sudangrass was included in the cropping system. Conclusion In some instances, increased numbers of root-knot nematodes were observed in cropping systems that contai ned sorghum-sudangrass or pearl millet as summer cover crops. A summer cover crop of sunn hemp appeared to be suppressive to root-knot nematodes in the broccoli-sweet corn exper iment. Sorghum-sudangrass also resulted in consistent increases in numbers of ring nematodes and lesion nematodes, and occasional increases in stubby-root nematodes. Cover crops that increased nematode numbers when planted alone tended to do the same thing when planted in a mixture with another cover crop. Rarely did any of th e cropping systems result in suppression of plant-parasitic nematodes; instead they main tained low numbers of nematodes similar to weedy fallow.

PAGE 41

41 Table 2-1. Cropping systems used as treatments z Summer Fall Spring Experiment I (Squash-bell pepper ) Weedy fallow Squash Bell pepper Pearl millet Squash Bell pepper Sorghum sudangrass Squash Bell pepper Sunn hemp Squash Bell pepper Velvetbean Squash Bell pepper Pearl millet-sunn hemp Squash + Ryehairy vetch Bell pepper + bush beans Sorghum sudangrass-velvetbean Squash + Rye-hairy vetch Bell pepper + bush beans Experiment II (Broccoli-sweet corn) Weedy Fallow Broccoli Sweet corn Pearl millet Broccoli Sweet corn Sorghum sudangrass Broccoli Sweet corn Sunn hemp Broccoli Sweet corn Velvetbean Broccoli Sweet corn Pearl millet-sunn hemp Broccoli + crimson clover Sweet corn + bush beans Sorghum sudangrass-velvetbean Broccoli + crimson clover Sweet corn + bush beans z For convenience, cropping systems referred in text using summer cover crop name

PAGE 42

42 Table 2-2. Cover crop treat ments and seed sources used. Cover crops Botanical name Cultivar Source Seed-rate (kg/ha) Pearl millet Pennisetum glaucum Tifleaf 3 Production Plus, Plainview, TX 4.5 Sorghum sudangrass Sorghum bicolor x S. bicolor var sudanense Brown Midrib Production Plus, Plainview, TX 7.2 Sunn hemp Crotalaria juncea Unknown Kaufman Seeds, Haven, KS 7.2 Velvetbean Mucuna pruriens var pruriens Georgia Bush Georgia Seed Development Commission, Athens, GA 18.0 Pearl millet sunn hemp 3.0 PM + 3.6 SH Sorghum sudangrass velvetbean 4.8 SS + 12.0 VB

PAGE 43

43 Table 2-3. Maximum and minimum soil temper atures (20 cm depth) during cover crop growing seasons in 20 06 and 2007 at Citra, FL September 2006 August 2007 September 2007 Cover crops Maximum ( C) Minimum ( C) Maximum ( C) Minimum ( C) Maximum ( C) Minimum ( C) Weedy fallow 33.1 22.6 38.7 26.7 36.2 24.2 Pearl millet 27.3 22.7 37.6 26.7 31.1 24.2 Sorghum sudangrass 29.2 22.7 37.6 27.1 31.1 24.1 Sunn hemp 28.7 22.7 37.2 26.7 33.2 24.2 Velvetbean 33.7 22.7 38.6 25.7 34.7 23.7 Pearl milletsunn hemp 27.7 22.2 37.1 27.2 30.7 23.7 Sorghum sudangrassvelvetbean 28.7 21.7 37.1 27.2 32.7 24.2

PAGE 44

44 Table 2-4. Maximum and minimum soil temperatures (20 cm depth) during growing season of both fall vegetables of both years at Citra, FL 2006-07 2007-08 Experiment I Experiment II Experiment I Experiment II Month Maximum ( C) Minimum ( C) Maximum ( C) Minimum ( C) Maximum ( C) Minimum ( C) Maximum ( C) Minimum ( C) Squash Broccoli S quash Broccoli October 29.2 20.7 29.7 20.2 November 23.7 10.6 24.2 10.6 24.7 15.7 24.7 13.2 December 23.2 10.1 23.2 9.1 22.7 11.6 23.2 10.6 January 24.2 10.6 23.7 11.7 20.2 10.1 19.7 9.1 Bell Pepper Sweet corn Bell Pepper Sweet corn March 28.7 20.7 27.7 19.7 25.2 16.2 25.2 15.7 April 33.2 14.2 29.7 13.7 29.7 17.2 30.2 17.2 May 34.7 23.2 30.2 13.7 33.7 20.7 32.2 22.7 June 38.7 22.7 35.2 13.7 34.7 25.7 32.7 26.2

PAGE 45

45 Table 2-5. Root-knot nematode population density in both exper iments and years at Citra, FL z Nematodes /100 cm 3 soil Experiment I (Squash-bell pepper) Experiment II (Broccoli-sweet corn) Cover crop Squash Bell Pepper Cover crop Squash Pepper Cover crop Broccoli Sweet corn Cover crop Broccoli Sweet corn Treatments 29 Sep 2006 18 Jan 2007 22 Jun 2007 03 Oct 2007 18 Dec 2007 04 Jun 2008 29 Sep 2006 18 Jan 2007 22 Jun 2007 03 Oct 2007 09 Jan 2008 04 Jun 2008 Weedy Fallow 0 a 1 a 7 ab 4 a 19 b 46 ab 0 a 0 a 1 ab 9 ab 9 ab 65 ab Pearl millet 0 a 2 a 14 ab 0 a 160 a 57 ab 1 a 0 a 7 ab 13 ab 1 b 83 ab Sorghumsudangrass 6 a 3 a 53 a 5 a 53 ab 142 a 9 a 0 a 5 ab 4 ab 3 ab 88 a Sunn hemp 0 a 0 a 0 b 1 a 21 b 37 b 3 a 0 a 13 a 0 b 0 b 4 d Velvetbean 0 a 0 a 0 b 8 a 26 ab 110 a 2 a 0 a 3 ab 2 ab 7 ab 63 ab Pearl milletSunn hemp 2 a 3 a 2 ab 1 a 91 a 85 ab 1 a 0 a 0 b 1 b 1 b 10 cd Sorghumsudangrass -Velvetbean 3 a 0 a 0 b 2 a 88 ab 12 b 8 a 0 a 3 ab 37 a 13 a 23 bc z Data are means of four replications. Data are final population levels on each crop shown, collected on the date indicated. On each sampling date, means in columns followed by the same letters were not different according to least significant difference (LSD) at P 0.05 based on the log10 transformed value. Untransformed means are presented in columns.

PAGE 46

46 Table 2-6. Ratio of final (Pf) to initial (Pf) root-knot nematode population levels in soil at different cropping seasons in 2007-08. Initial population (Pi) Final Population (Pf) Number of observations y Pf/Pi z Experiment I (Squash-bell pepper for the year 2007-08) Squash Squash 11 46.1 Squash Bell pepper 11 43.0 Bell pepper Bell pepper 20 4.2 Experiment II (Broccoli-sweet corn for the year 2007-08) Broccoli Broccoli 14 2.0 Broccoli Sweet corn 14 13.0 Sweet corn Sweet corn 14 11.2 y Maximum non-zero observations present in both initial (Pi) and final (Pf) population. z Average multiplication rate of Pf/Pi values based on the number of observations.

PAGE 47

47 Table 2-7. Ring nematode popula tion density in both experiments and years in Citra, FL z Nematodes /100 cm 3 soil Experiment I (Squash-bell pepper) Experiment II (Broccoli-sweet corn) Cover crop Squash Bell Pepper Cover crop SquashPepper Cover crop Broccoli Sweet corn Cover crop Broccoli Sweet corn Treatments 29 Sep 2006 18 Jan 2007 22 Jun 2007 03 Oct 2007 18 Dec 2007 04 Jun 2008 29 Sep 2006 18 Jan 2007 22 Jun 2007 03 Oct 2007 09 Jan 2008 04 Jun 2008 Weedy Fallow 15 bc 2 c 3 bc 27 cd 25 a 3 ab 15 b 3 bc 4 bc 14 bc 2 a 7 ab Pearl millet 9 c 1 c 1 c 16 d 16 a 3 ab 13 b 1 c 3 cd 38 ab 2 a 13 a Sorghumsudangrass 280 a 50 a 16 a 228 a 19 a 1 b 267 a 37 a 12 a 106 a 4 a 11 a Sunn hemp 38 b 15 b 5 ab 31 cd 22 a 7 a 28 b 2 bc 2 cd 5 c 2 a 3 ab Velvetbean 14 bc 2 c 4 ab 47 bc 22 a 4 ab 20 b 5 b 9 ab 17 bc 1 a 6 ab Pearl milletSunn hemp 12 c 1 c 1 c 30 cd 11 a 2 b 11 b 1 c 0 d 22 bc 1 a 1 ab Sorghumsudangrass -Velvetbean 176 a 29 a 4 ab 144 ab 17 a 1 b 190 a 46 a 5 bc 40 ab 1 a 0 b z Data are means of four replications. Data are final population levels on each crop shown, collected on the date indicated. On each sampling date, means in columns followed by the same letters were not different according to least significant difference (LSD) at P 0.05 based on the log10 transformed value. Untransformed means are presented in columns.

PAGE 48

48 Table 2-8. Lesion nematode population density in both experim ents and years in Citra, FL z Nematodes /100 cm 3 soil Experiment I (Squash-bell pepper) Experiment II (Broccoli-sweet corn) Cover crop Squash Bell Pepper Cover crop Squash Pepper Cover crop Broccoli Sweet corn Cover crop Broccoli Sweet corn Treatments 29 Sep 2006 18 Jan 2007 22 Jun 2007 03 Oct 2007 18 Dec 2007 04 Jun 2008 29 Sep 2006 18 Jan 2007 22 Jun 2007 03 Oct 2007 09 Jan 2008 04 Jun 2008 Weedy Fallow 5 b 1 b 0 b 3 b 3 bc 0 a 5 c 1 d 3 bc 0 b 0 a 0 b Pearl millet 1 c 0 b 0 b 2 b 3 bc 0 a 2 c 0 d 2 bc 1 b 1 a 0 b Sorghumsudangrass 37 a 8 a 0 b 25 a 6 ab 0 a 73 a 10 a 11 a 1 b 0 a 1 a Sunn hemp 10 b 3 ab 0 b 8 ab 1 c 0 a 18 b 1 d 1 bc 1 b 0 a 0 b Velvetbean 3 b 4 ab 0 b 4 b 2 c 0 a 13 b 3 c 5 ab 1 b 0 a 0 b Pearl milletSunn hemp 6 b 1 b 0 b 5 b 1 c 0 a 3 c 0 d 0 c 1 b 0 a 0 b Sorghumsudangrass -Velvetbean 47 a 6 ab 1 a 13 ab 20 a 0 a 48 a 5 b 1 c 11 a 1 a 0 b z Data are means of four replications. Data are final population levels on each crop shown, collected on the date indicated. On each sampling date, means in columns followed by the same letters were not different according to least significant difference (LSD) at P 0.05 based on the log10 transformed value. Untransformed means are presented in columns.

PAGE 49

49 Table 2-9. Spiral nematode population density in both experiments and years in Citra, FL z Nematodes per100 cm 3 soil Experiment I (Squash-bell pepper) Experiment II (Broccoli-sweet corn) Cover crop Squash Bell Pepper Cover crop Squash Pepper Cover crop Broccoli Sweet corn Cover crop Broccoli Sweet corn Treatments 29 Sep 2006 18 Jan 2007 22 Jun 2007 03 Oct 2007 18 Dec 2007 04 Jun 2008 29 Sep 2006 18 Jan 2007 22 Jun 2007 03 Oct 2007 09 Jan 2008 04 Jun 2008 Weedy Fallow 1 b 1 a 0 a 1 a 0 a 0 a 0 a 0 a 0 a 0 a 0 a 0 a Pearl millet 1 b 0 a 0 a 0 a 0 a 0 a 0 a 0 a 0 a 0 a 0 a 0 a Sorghumsudangrass 1 b 0 a 0 a 1 a 0 a 0 a 0 a 0 a 0 a 0 a 0 a 0 a Sunn hemp 0 b 0 a 0 a 2 a 1 a 0 a 2 a 1 a 1 a 0 a 0 a 0 a Velvetbean 0 b 0 a 0 a 2 a 1 a 0 a 1 a 1 a 0 a 0 a 0 a 0 a Pearl milletSunn hemp 0 b 1 a 1 a 1 a 0 a 1 a 0 a 0 a 0 a 0 a 0 a 0 a Sorghumsudangrass -Velvetbean 4 a 1 a 0 a 0 a 0 a 0 a 1 a 1 a 0 a 0 a 1 a 0 a z Data are means of four replications. Data are final population levels on each crop shown, collected on the date indicated. On each sampling date, means in columns followed by the same letters were not different according to least significant difference (LSD) at P 0.05 based on the log10 transformed value. Untransformed means are presented in columns.

PAGE 50

50 Table 2-10. Stubby-root nematode population densit y in both experiments and years in Citra, FLz Nematodes per100 cm 3 soil Experiment I (Squash-bell pepper) Experiment II (Broccoli-sweet corn) Cover crop Squash Bell Pepper Cover crop Squash Pepper Cover crop Broccoli Sweet corn Cover crop Broccoli Sweet corn Treatments 29 Sep 2006 18 Jan 2007 22 Jun 2007 03 Oct 2007 18 Dec 2007 04 Jun 2008 29 Sep 2006 18 Jan 2007 22 Jun 2007 03 Oct 2007 09 Jan 2008 04 Jun 2008 Weedy Fallow 0 b 0 a 1 a 0 a 0 a 1 ab 0 a 0 a 1 a 0 b 5 ab 11 a Pearl millet 0 b 0 a 0 a 1 a 1 a 0 b 0 a 0 a 1 a 2 ab 1 ab 10 a Sorghumsudangrass 2 a 0 a 0 a 2 a 1 a 1 ab 1 a 0 a 2 a 0 b 1 ab 2 a Sunn hemp 0 b 0 a 0 a 0 a 0 a 0 b 0 a 0 a 1 a 0 b 0 b 1 a Velvetbean 0 b 0 a 0 a 2 a 1 a 1 ab 1 a 0 a 0 a 1 b 0 b 7 a Pearl milletSunn hemp 1 b 0 a 3 a 1 a 1 a 2 a 0 a 0 a 0 a 2 ab 1 ab 1 a Sorghumsudangrass -Velvetbean 0 b 0 a 0 a 2 a 1 a 1 ab 0 a 0 a 0 a 8 a 11 a 4 a z Data are means of four replications. Data are final population levels on each crop shown, collected on the date indicated. On each sampling date, means in columns followed by the same letters were not different according to least significant difference (LSD) at P 0.05 based on the log10 transformed value. Untransformed means are presented in column

PAGE 51

51 CHAPTER 3 EFFECT OF COVER CROPS AND INTE RCROPPING ON THE POPULATION DENSITIES OF WHITEFLIES, APHIDS A ND THRIP S IN ORGANICALLY GROWN SWEET CORN AND BELL PEPPER Introduction Florida produced $157 million of sweet corn and $267 million of bell peppers in 2008 with harvested acreages of 29,500 and 17,500 acres respectively (Florida Agriculture Statistical Directory, 2008). Ther e are many insect-pests that affect the productivity and quality of these crops in cluding key pests such as aphids ( Aphis spp.), whiteflies ( Bemisia spp.) and thrips ( Frankliniella spp.). Aphids have been considered a major hindrance for sweet corn production during the last several years because they feed on emerging tassels causing poor pollen shed and fertilization (Nuessly and Webb, 2007). Both immature and mature aphids deposit honeydew on the leaves and husks of sweet corn on which black sooty mold fungi ( Capnodium spp.) grow causing husk disco loration, and reduced ear grade, plant vigor and yield (Byrne and Miller, 1990; Frank and Liburd, 2005). Aphids multiply rapidly with adults producing 3 to 5 nymphs per day and each nymph developing into an adult in 7 to 10 days (Nuessly and Webb, 2007) They transmit cucumber mosaic virus that reduces yield in bell pepper in Southern Illinois (Kagezi et al., 1999). Whiteflies ( Bemisia argentifolii Bellows and Perring) act as a vector of numerous geminiviruses that cause plant disorder s and mechanical damage (Nyoike et al., 2008; Smith and McSorley, 2000) resulting in economical losses to horticultural crops throughout warm regions of the world (Brown et al., 1995; Smith and McSorley, 2000). Whiteflies are also a major pest of agronomic and horticultur al crops in north-western US (Perring et al., 1993; Palumbo et al. 2000) and Florida (Nyoike et al., 2008). They

PAGE 52

52 are multivoltine with 2 to 6 generations per year with a 2 week short life-cycle under favorable climatic conditions (Byrne and Bellows, 1991). The adult whitefly female produces 252 eggs at 28.5 C (Byrne and Bellows, 1991; Webb, 2006). Both aphids and whiteflies have sucking mouth parts, secr ete honeydew, and serve as vectors of plant viral diseases, which eventually reduce vigor and market quality of affected vegetables (Barlow et al., 1977, Buntin et al. 1993, Scott 2008). Western flower thrips Frankliniella occidentalis (Pergande) damaged bell peppers either by feeding or by ovipositing on the fruit (Tommasini and Maini, 1995). Their high population not only af fect pepper yields but also spread tomato spotted wilt virus causing annual economic loss of $100 million in southern US (Pappu, 1997; Beaudoin et al., 2009). Many species of aphids and whiteflies have acquired resistance to insecticides like neonicotinoids and western flower th rips have developed resistance to spinosad and pyrethroid insecticides (Frantz and Mellinger, 2009). These insecticides also adversely affect natural enemies and thr eaten environment. Beside this, the reducedrisk insecticide indoxacarb for controlling European corn borer ( Ostrinia nubilalis Hubner) (Lepidoptera: Crambidae) in bell pepper also increas es the population of green peach aphids (Chapman et al., 2009). Researchers are interested in non-insecticidal tactics for managing whiteflies such as host-plant resistance and beneficial organisms (Simmons et al., 2002). Cultural control comprises crop rotation, intercroppi ng, planting trap crops, use of living and synthetic mulches for managing aphid and wh itefly populations, which reduce the incidence and spread of insect-bor ne diseases (Frank and Liburd, 2005). Arachis pintoi

PAGE 53

53 Krap & Greg planted as living mulch with bell pepper reduced Bemisia tabaci (Gennadius) population and improv ed bell pepper yield significantly compared to plots without living mulch (Rafie et al., 1999). The use of synthetic insecticides is not permitted in organic crop production. Therefore, there is a need to develop strategies to manage pests in a sustainable manner in organic farming by using cultural c ontrol techniques like planting cover crops and intercropping with species that act as a non-host to pests and thus thus suppress their populations (Manandhar et al., 2009). Ear lier studies suggest that mixed cropping systems (Gold et al., 1989) or vegetables interplanted with living mulches (Frank and Liburd, 2005) suppress whitefly populations. Diversifying cropping systems by intercr opping with living mulches or rotating cash crops with cover crops may be an opt ion to manage pest insect populations in north Florida. Cover crops can be useful for insect suppression by not harboring or diverting pests, reducing pest colonization through visual or olfactory confusion, altering host-plant nutrition, or changing the micr o-climate and by improving natural enemy abundance (Bugg and Waddington 1994). Aphid predators like hoverflies (Diptera:Syrphidae) can be attracted to cabbage ( Brassica oleracea L.) fields by planting phacelia ( Phacelia tanacetifolia Benth.) in strips along field borders (White et al. 1995). An experiment was established in summe r 2006 with an overall objective of comparing the effects of cropping system complexity on pest and beneficial organism populations. The specific objective of the st udy was to evaluate the effects of cropping systems on aphid, thrips and whitefly populati ons in organically grown sweet corn and

PAGE 54

54 bell pepper. It was hypothesized that pest populations would respond differently in systems with summer cover crops than a si mple system with no cover crops. Materials and Methods A field experiment was established in summer 2006 at the Plant Science Research and Education Unit, Citra, Mari on County, Florida. Air temperature and relative humidity were monitored throughout each year at 30 cm above soil surface using a Watchdog datalogger, Model 100 8k (Spectrum Technologies, Inc. East Plainfield, IL) at 30-minute time intervals. The previous crop before the experiment was a cover crop of White Acre southern pea ( Vigna unguiculata Walp.) planted in May 2006. After mowing and incorporating the southern pea crop in July 2006, finished mushroom compost (Quincy Farms, Quincy, Fl orida) was applied at the rate of 2500 kg/ha using a drop spreader (Newton Crouch Inc., Griffin, GA) to improve the organic matter content of the soil. Th is was followed by planting su mmer cover crops on 27 July 2006. The experimental design was a randomized complete block with four replications. The plot size was 12 m x 12 m while distance between the plots was 12 m to reduce the movement of insects fr om one plot to another. Two grass cover crops, pearl millet (P M), sorghum sudangrass (SS), and two legume cover crops sunn hemp (SH) and ve lvetbean (VB), and their mixtures pearl millet-sunn hemp (PMSH) and sorghum sudangr ass velvetbean (SSVB) were planted along with weedy fallow (WF). Each cove r crop, their mixtures, and weedy fallow consists of significant cropping systems. Th e seed-rate applications were described in Table 3-1. Grass cover crops were planted with Sukup 2100 planter (Sukup Manufacturing Company, Shefield, IA) at 17 cm apart and 5 cm deep. Sunn hemp and velvetbean seeds were inoculated with Rhizobium sp. (Cowpea type, Nitragin Inc.,

PAGE 55

55 Brookfield, WI) before broadcasti ng on the field. This was followed by rolling the field to cover the seeds. Cover crops were flail mowed and incorporated into the soil on 2nd October 2006. Yellow squash ( Cucurbita pepo L. cv. Cougar F1 untreated, Harris Seeds, Rochester, NY) was direct seeded on 19 October 2006 and broccoli ( Brassica oleracea L. cv. Marathon F1 untreated, Harris Seeds) was transplanted on 31 October 2006. Before planting fall vegetables, lime (Aglime Sales Inc., Babson Park, FL) was applied to the field at the rate of 2500 kg /ha. Living mulches were plan ted on 9 November 2006 in mixed cover crop plots in-between bed centers. A mixture of rye (Secale cereale L. cv. Wrens Abruzzi, Alachua County Feed and Seed St ore, Gainesville, FL) and hairy vetch ( Vicia villosa Roth, cv. unknown, Adams Brisc oe Seed Company, Jackson, GA) were planted in mixed cover crop pl ots with squash at the rate of 48 and 22 kg/ha. Crimson clover (Trifolium incarnatum cv. Dixie, Adams Briscoe Seed Company, Jackson, GA) was planted at 28 kg/ha in mixed cover cr op plots with broccoli. Both fall vegetable crops were harvested by 16 January 2007. Before sowing the spring crops in 2007, t he field was flail-mowed on 5 March and disked to a depth of 20 cm. The details of management practices with planting dates were given in Table 3-2. Sweet corn was planted with an approximate population of 74,444 plants/ha (76 cm between rows; 18 cm between plants) wh ile bell pepper with 24,074 plants/ha (72 cm between beds; 2 rows per bed; 45 cm between rows as well as plants). The plot area for sweet corn was 12 m x 12 m, and 12 m x 7.2 m for bell pepper. Bush bean was planted using a monosem planter (Monosem Inc., Edwardsville, KS) in sweet corn while a manual push planter was used in bell pepper. Organic

PAGE 56

56 fertilizer (NatureSafe 10-2-8 of N2, P2O5, K2O, Griffin Industries, Cold Spring, KY) was applied (Table 3-2) as per nitrogen re commendations by IFAS (Olson and Simonne, 2006). Both crops were irrigated by drip method. In the second year, pearl millet cover crop was rotated with sorghum sudangrass and vice versa. Similarly, sunn hemp cove r crop was rotated with velvetbean and vice versa. Pearl millet-sunn hemp was rotat ed with sorghum sudangrass-velvetbean cover crops and vice versa in the second year. Squash was rotated with broccoli as fall vegetable in the second year while spring bell pepper was rotated with sweet corn in the second year. Methods used were similar to th ose described in the previous season. In addition, elemental sulfur (Tiger 90 with 90% sulfur, Tiger-Sul Products, Atmore, AL) was applied at the rate of 250 kg/ha using a check-drop spreader three weeks prior to planting the cover crops. Sulpomag (0-0-21 of N, P2O5, K2O, Diamond R Fertilizer, Winter Garden, FL) was also applied before planting and after mowing cover crops at 257 kg/ha by hand and catch drop spreader. Monitoring of Aphids, Whiteflies and Thrip s with U nbaited Yellow Sticky Traps Aphids, whiteflies (adults) and thrips were monitored using unbaited yellow sticky traps (Great Lakes IPM, Vestaburg, MI) in spring vegetables in 2007 and 2008. Pest insects from fall vegetable crops were repor ted in Scott (2008). This type of trap has been used for monitoring and managing whitefly adults (Ekbom and Xu, 1990; Hoelmer et al., 1998; Smith and McSorley, 2000; Sco tt, 2008). Additionally, these traps also had the ability to catch thrips (Hoelmer et al., 1998). Yellow sticky cards were placed in the center of each plot (to eliminate the border effect) with height relative to the plant height on 30 March, 30 April, and 30 May in spring 2007 and on 4 April, 5 May, and 30 May in spring 2008. After one week, traps were removed and wrapped in transparent plastic

PAGE 57

57 film and placed in a Ziploc bag and stored in a refrigerator. Aphid, whitefly and thrips populations were assessed over the next few weeks from the stored traps. Every square in alternate rows of the traps were used for monitoring aphid and whitefly populations. There were 8 rows per trap with each row containing 8 squares of 6.45-cm2 area. These squares were viewed at X40 magnification with a dissecting microscope to identify and assess populations of aphids and whiteflies. This method has been used previously to monitor aphid and whitefly populations (Scott, 2008). The relative abundance of thrips was assessed using a sub-sampling technique outlined by Finn (2003) due to their high popula tions. This technique eliminates counting errors with less time involved. A gridded transparent plastic sheet was placed on each trap. Of the 63 squares, 48 were colored or opaque while another 15 were transparent, so only 15 squares were actually count ed per trap. Thrips were counted through transparent squares of the trap at a magnificantion of X 40 using a dissecting microscope. Statistical analysis Aphid, thrips, and whitefly counts we re log transformed (log10[x+ 1]) before analysis to evaluate the effect of croppi ng system treatments and time of sampling using GLM in SAS software. Analysis of va riance was performed on logtransformed counts using GLM and means were separated by least significant difference at 5% level of significance. Untransformed means are presented in tables along with standard errors. Results Monthly maximum and minimum air tem peratures during planting season ranged from 38.6 C to 2.1 C in bell pepper and 42.6 C to 1.6 C in sweet corn in both years

PAGE 58

58 (Table 3-3). Relative humidity ranged from 69 to 90% in bell pepper and 70 to 80% in sweet corn (Table 3-3). There was no significant interaction between cropping system treatments and sampling dates for aphids, thri ps, and whitefly populations in both 2007 and 2008. Therefore, the main effects of cropping system and sampling dates were presented by year. Sweet Corn Aphids. In 2007, aphid populations in sweet corn ranged from 20 to 42 per trap.The population wit h WF was not signific antly different from cropping systems with summer cover crops. In 2008, aphid populati ons ranged from 11 to 28 per trap and again the populations with WF systems was significantly not different from cover crop systems (Table 3-4). Thrips. Thrips population in the WF system was observed to be 1342 per trap in spring 2007. Only the PMSH syst em resulted in a thrips population higher than the WF system. In 2008, the thrips popul ation in the WF system was 930 per trap. Unlike 2007, the PMSH, PM, and SS systems had thrips populations that were significantly lower than the WF system. Whiteflies. In 2007, whitefly populations ranged from 6 to 24 per trap, with the population in WF system not significantly di fferent from those of cover crop-planted cropping systems. In 2008, whitefly populations ranged from 3 to 7 per trap and again the population with the WF system was not signi ficantly different from those with the cover crop systems. Among cover crop-pl anted systems in sweet corn, SSVB system had a significantly higher whitefly popul ation than PM, and SH systems in 2007 and 2008. Bell Pepper

PAGE 59

59 Aphids. In 2007, aphid populations ranged from 20 to 38 per trap. Only the SSVB system resulted in a significantly lower aphid population than the WF system (Table 3-5). In 2008, the aphid population wi th the WF system was not significantly different from those with cropping systems planted with cove r crops (Table 3-5). Thrips. Thrips populations observed ranged from 1415 to 2440 per trap in 2007. Only the PMSH system resulted in a thri ps population higher t han other cropping systems. In 2008, the thrips population in the WF system was not significantly different from cover crop-planted systems. Whiteflies. Whitefly populations in the WF syst em were not significantly different from other cropping syst ems in both 2007 and 2008. Discussion The results suggest that aphid populatio ns were not controlled by systems planted with cover crops in 2007 and 2008 in sweet corn. However, in bell pepper, the SSVB system had significantly lower populati ons than the WF system in 2007. This suggests that aphid populations were dete rmined more by the vegetable crops planted in the cropping system than by the cover cr ops used in these syst ems. Manipulating crop diversity by planting vegetables of di fferent families may benefit natural enemies (Landis et al., 2005). In 2007, the PMSH system attracted more thrips than other cropping systems in both sweet corn and bell pepper. However, in 2008, the PMSH, PM, and SS systems contained lower thrips populations than the WF system in sweet corn. Chamberlin et al. (1992) reported occasional occurr ence of thrips in a peanut field that was planted after a pearl millet crop.

PAGE 60

60 In sweet corn, PM and SH cover crop systems reduced whitefly numbers more than other cover crop systems. In a previous study, pearl millet reduced whitefly populations in cowpea by acting as a barri er (Sharma and Varma, 1984). Scott (2008) observed that pearl millet can suppress whitefly populations by harboring higher numbers of predators and parasit oids. Manandhar et al. (2009) reported that sunn hemp intercropped with zucchini had si gnificantly lower populations of all life stages of whitefly (egg, immature and adult) although no signific ant difference was reported in marketable yield with other crops. They also mentioned that sunn hemp pr ovided nutrients and served as a windbreak for zucchini plants, which improved zucchini growth to sustain higher whitefly counts. Conclusion Although, we saw some effect of syst ems on aphids, thrips, and whiteflies, population level of thrips still remained quite high suggesting that previous cover crop has limited use in managing thrips populations. In sweet corn and bell pepper, no significant differences were observed between cover crop systems and weedy fallow for managing aphid and whitef ly populations.

PAGE 61

61 Table 3-1. Cover crop treatments planted in this experiment at Citra, Florida Treatments Botanical name Cultivar Source Seed-rate (kg/ha) Weedy Fallow (WF) Pearl millet (PM) Pennisetum glaucum Tifleaf 3 Production Plus, Plainview, TX 4.5 Sorghum sudangrass (SS) Sorghum bicolor x S. bicolor var sudanense Brown Midrib Production Plus, Plainview, TX 7.2 Sunn hemp (SH) Crotalaria juncea Unknown Kaufman Seeds, Haven, KS 7.2 Velvetbean (VB) Mucuna pruriens var pruriens Georgia Bush Georgia Seed Development Commission, Athens, GA 18.0 Pearl millet sunn hemp (PMSH) 3.0 PM + 3.6 SH Sorghum sudangrass velvetbean (SSVB) 4.8 SS + 12.0 VB

PAGE 62

62 Table 3-2. Management practices with their dates in spring crops in 2007 and 2008 Crop management practices 2006-07 2007-08 GREEN BELL PEPPERa NatureSafee (10-2-8 N-P2O5-K2O) fertilizer broadcasted at the rate of 1116 kg/ha 7 March 2007 4 March 2008 Forty-five-day-old bell pepper seedlings transplanted in double rows per bed with 45 cm plant distance within a row. 15 March 2007 13 March 2008 Green bush bean direct seeded between bell pepper bed centers as intercropped in mixed cover crop plots 16 March 2007 14 March 2008 Band applied NatureSafe (10-2-8 N-P2O5-K2O) fertilizer at rate of 1116 kg/ha 10 April 2007 1 April 2008 Hand weeding 2 April,18 April, and 30 May 2007 14 April and 14 May 2008 Green bush bean harvested on the following dates 16 May and 30 May 2007 13 May 2008 Bell pepper harvested between the following dates, four harvests total 21 May 20 June 2007 13 May 9 June 2008 SWEET CORNb Broccoli plots flail mowed and disked to 20 cm soil depth for planting sweet corn 5 March 2007 4 March 2008 NatureSafee (10-2-8 N-P2O5-K2O) fertilizer broadcasted at the rate of 1116 kg/ha 7 March 2007 4 March 2008 Sweet corn direct-seeded at 76 cm row distance and 18 cm plant distance 12 March 2007 11 March 2008 Bush bean direct seeded in strips (4 rows/strip) arranged alternately with strips of sweet corn in mixed cover crop plots. 12 March 2007 11 March 2008 Hand weeding 2 April and 18 April 2007 14 April 2008 Band applied NatureSafe (10-2-8 N-P2O5-K2O) fertilizer at rate of 1116 kg/ha 10 April 2007 1 April 2008 Biolinkc (0-0-6 N-P2O5 -K2O applied over bean plants at nozzle rate of 760 ml/min and 50 gal/ha water 29 April 2008 Sodium nitrate (Proboosterd, 10-0-0 N-P2O5 -K2O) applied at 868 kg/ha in response to nitrogen deficiency symptoms 7 May 2008 Sweet corn harvested between the following dates, 2 harvests total 31 May12 June 2007 29 May -4 June 2008 Bush beans harvested on the following dates 16 May 30 May 2007 13 May 29 May 2008 a Capsicum annuum L. cv. Red Knight F1 untreated; Johnnys Selected Seeds, Winslow, ME b Zea mays L. cv. Montauk F1 untreated; Johnnys Selected Seeds, Winslow, ME c Westbridge Agricultural Products, Vista, CA d North Country Organics, Bradford, VT e Cold Spring, KY

PAGE 63

63 Table 3-3. Maximum, minimum air temperatures ( C) and re lative humidity (%) observed during spring 2007 and 2008 2007 2008 Month Maximum Minimum Relative humidity Maximum Minimum Relative humidity Bell pepper March 29.1 10.1 80 31.2 4.1 78 April 33.1 5.6 69 33.2 2.1 75 May 35.1 7.6 71 36.7 6.6 74 June 38.6 16.6 80 38.2 18.7 74 Sweet corn March 30.2 10.6 80 30.6 3.1 79 April 34.2 6.1 70 32.6 1.6 76 May 36.2 9.1 71 41.1 6.1 76 June 40.1 17.2 80 42.6 17.6 76

PAGE 64

64 Table 3-4. Aphid, thrips, and whitefly populations per trapa in sweet corn in spring 2007 and 2008 b 2007 (Mean SEM) 2008 (Mean SEM) Cropping system Aphids Thrips Whiteflies Aphids Thrips Whiteflies WF 23.8 ab 1342 b 10.6 ab 18.7 ab 930 a 5.3 ab PM 26.3 ab 1208 b 7.5 b 11.2 b 494 61 b 3.3 b SS 30.9 ab 1333 b 12.7 ab 12.9 b 468 b 6.0 ab SH 31.0 ab 1504 ab 6.5 b 15.2 ab 716 ab 3.2 b VB 20.4 b 1480 ab 8.7 b 13.5 ab 655 ab 5.4 ab PMSH 30.5 ab 2041 a 9.4 ab 28.7 a 465 b 4.4 ab SSVB 42.7 a 1650 ab 24.9 a 16.8 ab 645 ab 7.8 a a For aphid and whitefly populations, 32 squares each having an area of 6.45 cm2 were counted while thrips populatons were counted in 15 squares with the same area per trap. b Data are means of four replications and the sum of three sampling dates. Means in columns followed by the same letters were not different according to least significant difference (LSD) at P 0.05 based on the log-transformed [log10(x+1)] value. Means and SEM values were untransformed.

PAGE 65

65 Table 3-5. Aphid, thrips and whitefly populations per trapa in bell pepper in spring 2007 and 2008 b 2007 (Mean SEM) 2008 (Mean SEM) Cropping system Aphids Thrips Whiteflies Aphids Thrips Whiteflies WF 38.7 a 1567 b 14.8 a 21.9 a 780 a 9.7 a PM 36.1 a 1638 b 18.2 a 19.4 a 588 a 10.4 a SS 28.6 ab 1544 b 9.6 a 24.4 a 716 a 8.1 a SH 33.3 ab 1415 b 16.9 a 19.8 a 562 a 6.0 a VB 25.7 ab 1506 b 24.3 a 14.4 a 902 a 9.6 a PMSH 25.8 ab 2440 a 16.2 a 19.8 a 885 a 8.2 a SSVB 20.7 b 1694 b 18.4 a 18.3 a 832 a 7.6 a a For aphid and whitefly populations, 32 squares each having an area of 6.45 cm2 were counted while thrips populatons were counted in 15 squares with the same area per trap. b Data are means of four replications with sum of three sampling dates. Means in columns followed by the same letters were not different according to least significant difference (LSD) at P 0.05 based on the log-transformed [log10(x+1)] value. Means and SEM values were untransformed.

PAGE 66

66 CHAPTER 4 IMPACT OF CROPPING SYSTEM COMPLEXI TY ON GROWTH AND YIEL D OF ORGANICALLY PRODUCED VEGETABLES Introduction Due to the premium prices many c onsumers are willing to pay for organic produce, environmental risks of agrochemical exposure, and shift in pest populations towards pesticide-resistant genotype and species, farmers are shifting to organic farming (Benbrook, 1996; Geier, 1998). This has caused an increase in organic acreage of 30% in the US, and in Florida, of 43% from 2002 to 2007 (U SDA-ERS, 2005). In Florida, inadequate information on cropping syst ems and management practices for this sub-tropical region is thought to be a major constraint to greater expansion of organic vegetable production. This results in the impor tation to Florida of organic produce from California (Blumenthal, 2007; Nguyen et al., 2008). Consequently, there is a need to increase organic farming acreage based on scientif ic management strategies specific to this region (Rosen et al., 2007). Liebman and Davis (2000) suggested various practices for pest suppression, including weeds, in lo w external-input farming systems such as: diversifying crop sequences with multispecies rotations, planting cover crops and intercrops, and amending soil with crop residues, animal manures, and compost. These management practices can recover soil nutrients and improve vegetable yields, plus aid in weed control in organic vegetable production. A cover crop can be grassy or legume plant species. Fertilization is the most expensive cultural practice for organic veget able growers in the US (Gaskell and Smith, 2007). Legume cover crops are major consti tuents in organic farming systems because they provide supplemental nitrogen for succeeding crops if they are incorporated at the pre-heading stage (Rotar and Joy, 1983; Gaske ll and Smith, 2007). However, legumes

PAGE 67

67 are slow growers and expensive to establish (Snapp et al., 2005). Compared to legumes, grass cover crop species produce mo re biomass, which helps to build soil organic matter (Snapp et al., 2005), but they are high nitrogen scavengers (Fageria et al., 2005). A combination of cereal-legume cover crop species may produce maximum benefits by providing nutrients as well as organic matter to succeeding vegetable crops (Fageria et al., 2005). In addition, a mix ed cover crop covers the soil quickly, suppressing weeds equivalent to that of herbicides, produces large amounts of biomass with a C:N ratio of 22:1, and is easily managed by mechanical means (Creamer et al., 1996, 1997). There are several cover crop species adapted for use during summer growing season in Florida. Li et al. (2006) suggested different cover crop species, including sunn hemp ( Crotalaria juncea L.), velvetbean (Mucuna pruriens (L.) DC ), and sorghumsudangrass ( Sorghum bicolor (L) Moench x S. sudanense (P) Stapf ), can be planted in Florida. Sunn hemp and velvet bean are tropical legumes widely used as green manures and produces more biomass than winter legu me cover crops (Mansoer et al., 1997; Cherr et al., 2006). They can be planted during summer fallow period to suppress weeds through resource competition in Fl orida (Collins, 2004). Grass cover crops possess C4 pathways that help to produc e large amount of biomass. Sorghum species used as cover crops in the southern United States produce large amounts of biomass and possess the ability to suppr ess weeds (Forney et al., 1985). Sorghumsudangrass as a cover crop suppresses weeds, controls nematodes, produces large quantities of biomass (7.62 tons/ha) and reduces subsoil hardpans without mechanization (Valenzuela and Smith, 2002; Clark, 2007). Pearl millet ( Pennisetum

PAGE 68

68 glaucum (L). R. Br) accumulate good amount of nitrogen and dry biomass production (Torres et al., 2005). Winter-planted living mulches like hairy vetch ( Vicia villosa Roth ) and crimson clover (Trifolium incarnatum L.) fix more atmospheric nitrogen when intercropped with rye ( Secale cereale L.) (Karpenstein-Machen and Stuelpnagel, 2000). In addition, a ryehairy vetch mixture also improves soil or ganic matter and reduces nitrogen leaching as compared to hairy vetch alone (Sainju et al., 2005). Living mulches must be low-growing since mowing may be insufficient to prevent adverse effects on crop yield (Chase and Mbuya, 2008). Intercropping is the growing of different crops or different varieties of one crop simultaneously on the same piece of l and (Wubs et al., 2005; Ranganathan, 1993). Strip intercropping is the spatial arrangement of growing two or more crops in strips with space between strips sufficient to permit separate crop production but close enough for interaction between the crops (Sullivan, 2003). This spatial arrangement enhances cooperation and decreases com petition between crops, while planting crop mixtures increases diversity and stability in crop ecosystems (Sullivan, 2003). In addition, intercropping of field vegetables can suppr ess pests significantly (Theunissen, 1997). Although work on crop rotation, su mmer cover crops, living mulches, and intercropping has been carried out to improv e vegetable crop yields, there also is a need for a holistic approach that integrates t hese cultural practices to improve vegetable yields in the southern, sub-tropical region. There is little information on the sub-tropical climatic regime because this climate allo ws year-round cropping, but mild winters in northern Florida allow pests to persist from season to season. Research to develop

PAGE 69

69 better organic cropping systems for the north Florida region should result in improved vegetable yields. The overall objective of this study was to evaluate the effect of cover crop-based cropping system complexity and crop management practices on the growth and yield of organically grown vegetables. The hypothes is includes different cover crop-based cropping systems may improve growth and yield of vegetables compared with a fallow system. Materials and Methods Two field experiments were established concurrently in summer 2006 on certified organic land at the University of Florida-Pl ant Science Research and Education Unit in Marion County, Florida. Before establis hing the experiments, the field site was dominated by bahiagrass ( Paspalum notatum Flgg) and 93% infested with ring nematode ( Mesocriconema spp.). The soil type was a Candler sand (Hyperthermic, uncoated Lamellic Quartzipsamments; Entisol) with a pH of 7.1. The field was first planted with root-knot-susceptib le White Acre southern pea (Vigna unguiculata Walp) on 17 May 2006 to provide nutrients to t he succeeding crops. The crop was mowed on 13 July 2006, with a New Holland 918H flail mower (Purdy Tractor and Equipment, Inc., Hillsdale, MI). Finished mushroom compost (Quincy Farms, Quincy, FL) was applied at 2500 kg/ha using a check drop spreader (Newton Crouch, Inc., Griffi n, GA) to increase the organic matter in the soil and to provi de nutrients for cover crops. Compost was incorporated to a depth of 20 cm by diski ng. Summer cover crops were planted on 27 July 2006. Seven treatments as cropping syste ms were established arranged in a randomized complete block design with four r eplications (Table 4-1). The plot size was 12 m x 12 m; distance between the plots was 12 m.

PAGE 70

70 Cultural practices for cover crops are pr esented in Table 4-2. Pearl millet and sorghum-sudangrass were planted with a mechanical drill (Sukup 2100, Sukup Manufacturing Company, Shefield, IA) at 17 cm apart and 5 cm deep. Seeds of sunn hemp and velvetbean were inoculated with Rhizobium sp. (Cowpea type, Nitragin, Inc., Brookfield, WI) before broadc ast. This was followed by covering the seeds using a roller. Overhead irrigation was used occasio nally during the first three days after planting (DAP) to promote germination and establishment of the cover crops. Summer cover crops were flail mowed on 2 October 2006, and disked to incorporate into the soil. Lime (Aglime Sales, Inc., Babson Park, FL ) was applied and incorporated to the entire field at the rate of 2500 kg/ha. Fall vegetables were planted in four beds (1.8 m bed-center size) per plot (each plot 12 m long x 7.2 m wide). Before pl anting fall vegetables, compliant, blended fertilizer,10-2-8 N-P2O5-K2O (NatureSafe, Griffin Industries, Cold Spring, KY) was applied at the rate of 1685 kg/ha for squash and 1976 kg/ha for broccoli based on the conventional fertilizer recommendations fo r these crops (Olson and Simonne, 2006). Fertilizer was applied in a 30-cm band over the center of the bed and incorporated before planting vegetables. Both fall and spri ng vegetables were irrigated daily through a drip irrigation system. The details of manag ement practices of dates were given in Tables 4-3 and 4-4. Rye ( Secale cereale cv Wrens Abruzzi; Alachua County Feed and Seed, Gainesville, FL) and hairy vetch ( V. villosa cultivar unknown; Adams Briscoe Seed Company, Jackson, GA) were planted bet ween beds in mixed cover crop plots at 48 kg/ha rye and 22 kg/ha hairy vetch in squash. In broccoli, crimson clover ( T. incarnatum cv Dixie; Adams Briscoe Seed Company, Jackson, GA) was planted as

PAGE 71

71 living mulch between beds in mixed cover crop plots. The seeding rate was 28 kg/ha and seeds were inoculated with Nitragin R/WR ( Rhizobium leguminosarum biovar trifolii Nitragin, Inc, Brookfield, WI) before plant ing. Seeds of both living mulches were broadcast by hand onto shallowly tilled soil, which was followed by covering the seeds using a roller. In spring, green bush beans (Phaseolus vulgaris cv. Bronco untreated, Seedway, Elizabethtown, PA) were interc ropped with pepper and strip intercropped with sweet corn in mixed cover crop plots. Fall squash was rotated with spring bell pepper in experiment I and broccoli was rotated with sweet corn in experiment II (Table 4-1). On 5 March 2007, before planting spri ng vegetables, the field was flail-mowed and disked to a depth of 20 cm. The details of management practices with respective dates for both fall and spring vegetables are give n in Tables 4-3 and 4-4. In the second year (2007-08) of experim ent I, squash plots were rotated with broccoli and bell pepper with sweet corn. Simila rly for experiment II broccoli plots 2006 were rotated with squash in 2007 and sweet corn with bell pepper in 2008. The field was mowed on 6 July 2007, followed by an application of elemental su lfur (Tiger 90 with 90% sulfur, Tiger-Sul Products, Atmore, AL ) at 250 kg/ha on 10 July 2007, using a check drop spreader. This was done to lower soil pH. Before the cover crops were planted on 31 July 2007, Sulpomag (0-0-21 N-P2O5-K2O, Diamond R Fertilizer, Winter Garden, FL) was applied at 257 kg/ha by hand. The same application rate was repeated after mowing the cover crops. Data collection and analysis Cover cro ps: Cover crop height and light intensity below the cover crop canopy (photosynthetic active radiationPAR) was measured at 30 and 60 DAP in both years. Leaf area index was also measured at the same time in 2007. The light intensity

PAGE 72

72 measured was used to calculat e percent light interception using the following formula (Hall and Rao, 1996): [(Light intensity at top of the canopy-light intensity at base of the crop)/Light intensity at top of canopy] x 100. Both light intensity and leaf area i ndex were measured using an AccuPAR Ceptometer (Model LP-80, Decagon Device s, Inc. Pullman, WA). Above-ground biomass was collected within 1 m2 quadrat randomly placed within each plot, dried at 48 C for 10 days, and weighed. Vegetables: Plant heights of both fall and spri ng vegetables were measured at 20, 40, and 65 days after planting/transplanting. Light intensity and leaf area index were also measured in sweet corn and bell pepper using the ceptomet er at 40 and 65 days after planting. For all vegetables, above-ground biomass (5 plants/plot) was collected during the last harvest, dried at 48 C fo r 14 days, and weighed. Total and marketable yields were recorded and graded for marketab ility as per the USDA standards (USDA, 2009). Data were analyzed with the GLM proc edure using SAS/STAT software version 9.1 (SAS, 2008) of the SAS system for windows. Prior to analysis, light interception values were transformed to arc-sign (1/ sin X). Means were separated by least significant difference (LSD) at the 5% leve l of significance. The data are reported as untransformed means. Results Experiment I: Cover Crops-Squash-Peppe r; Cover Crops-Broccoli-S weet corn Cover crops: Cover crop plant heights were m easured at 30 and 60 DAP in all cropping systems. In 2006, the sorghum sudangrass an d the sorghum sudangrass-

PAGE 73

73 velvetbean mixture had significantly taller plant s than all other cover crops at 30 DAP. However, by 60 DAP, systems did not differ in plant height except for velvetbean, which was only 20 cm tall (Table 4-5). In 2007, at 30 DAP, plant hei ght was greatest with sorghum sudangrass and velvet bean was the shortest. At 60 DAP, velvetbean and sorghum sudangrass-velvetbean cover crops had the shortest plants (Table 4-5). In 2006, light interception with the pearl millet cover crop was 94% by 30 DAP, but was only significantly higher than the ve lvetbean cover crop, which intercepted 79%. In 2007, at 30 DAP, pearl millet light inte rception was 78%, significantly higher than velvetbean and sunn hemp cover crops and mixt ures. At 60 DAP, the sunn hemp and pearl millet-sunn hemp cover crops intercept ed more sunlight than velvetbean cover crop but were not different from the other cover crops and mixtures (Table 4-5). In 2006, cover crop biomass was hi ghest with pearl millet and sorghum sudangrass in mixtures and when planted alone. In 2007, pearl m illet had the highest cover crop biomass and velv etbean produced the lowest biomass (Fig. 4-1). Fall vegetable yields: In 2006, squash was planted as the fall vegetable, while in fall 2007, broccoli was planted. In 2006, th e PM system showed significantly greater squash total and marketable yields than ot her cropping systems except for the SH system (Fig. 4-2). In 2007, no significant difference was observed in the broccoli marketable yield. Total yield was significantly greater in the SS system than the PM and SH systems, but no cropping system had a yield si gnificantly different from that of the WF system (Fig. 4-3). Spring vegetable yields: In spring 2007, bell pepper was planted on squash plots and in spring 2008, sweet corn was planted on broccoli plots. In 2007, no

PAGE 74

74 significant difference was observed betwe en cropping systems in either total or marketable yields of bell pepper (Fig. 4-4). Bell pepper total yield ranged from 4922 to 6693 kg/ha, with marketable yield from 2411 to 3976 kg/ha in all the cropping systems. In 2008, total sweet corn yield was signifi cantly greater in the PM, SS, SH, and VB systems than remaining cropping systems. The WF system had a greater total yield than either the SSVB or PMSH system. Sweet corn marketable yield was significantly greater in the PM, SS, SH, and VB systems than in the PMSH and SSVB systems (Fig. 4-5). In sweet corn, total yields ranged from 2124 to 8144 kg /ha, with marketable yield from 1177 to 5126 kg/ha. Experiment II: Cover Crops-Broccoli-Sweet Corn; Cover Crops-Squash-Bell Pepper Cover cro ps: Cover crop plant heights were measured at 30 and 60 DAP. In 2006, at 30 DAP, sorghum sudangrass and sorghum sudangrass-velvetbean cover crops had significantly greater plant height than sunn hemp and velvetbean cover crops. At 60 DAP, plant height was greater in sunn hemp, pearl millet-sunn hemp, and sorghum sudangrass-velvetbean t han the velvetbean cover crops In 2007, at 30 DAP; sorghum sudangrass was the tallest cover cr op. However, by 60 DAP, sunn hemp with a height of 122 cm was the tallest cover crop (Table 4-6). In 2006, by 30 DAP, pearl millet-sunn hem p cover crop light interception was 95%, significantly higher than all other co ver crops except for sunn hemp. Similar results were obtained at 60 DAP. In 2007, at 30 DAP, light interception was again greatest with pearl millet-sunn hem p mixtures but not significa ntly different from that with pearl millet and sunn hemp as sole cover crops. At 60 DAP, the sunn hemp cover

PAGE 75

75 crop and the pearl millet-sunn hem p mixture at 93 and 94% respectively, intercepted more sunlight than the other cover crops (Table 4-6). In 2006, cover crop biomass was significant ly greater with pearl millet than all other cover crops except for the pearl m illet-sunn hemp mixture.Velvetbean resulted in the lowest biomass in both 2006 and 2007 com pared to the other cover crops. In 2007, pearl millet-sunn hemp mixture had greater biomass than all other cover crops except for pearl millet as a sole cover crop (Fig. 4-6). Fall vegetable yields: In 2006, broccoli was planted as a fall vegetable; squash was planted in fall 2007. There was no signi ficant difference amon g cropping systems in the total and marketable yields of broccoli (F ig. 4-7). The range of total yields was from 3295 to 3874 kg/ha, while marketable yields ranged from 2815 to 3691 kg/ha. In 2007, there was no significant effect of cropping sy stem on squash total yield. However, only the PM system had significantly greater market able yield than the WF system (Fig. 4-8). Spring vegetable yields: In spring 2007, sweet corn was planted in broccoli plots and in spring 2008, bell pepper was planted in squash plots. Sweet corn total yields ranged from 4025 to 8667 kg/ha and ma rketable yields ranged from 2571 to 5732 kg/ha (Fig. 4-9). On average, marketable yield was lower co mpared to total yield by 35%. In 2007, only the VB system had higher total sweet corn yields than the WF system. Only the marketable yi eld of the PM system was gr eater than that of the WF system (Fig. 4-9). In 2008, bell pepper total yi elds ranged from 3138 to 7440 kg/ha and marketable yields ranged from 2594 to 6077 kg/ha. Bell pepper total and marketable yields were significantly greater in t he VB and SSVB systems than in the WF, PM, SS, or SH systems (Fig. 4-10).

PAGE 76

76 Bean yields: Beans were planted as a strip intercrop with sweet corn and between bell pepper beds in both experiments There was no significant effect of cropping systems on bean yields (Table 4-7). Discussion Experiment I: Cover Crops-Squash-Bell Pepper; Cover Crops-Broccoli-Sw eet Corn In both years, cover crop biomass was gr eatest with pearl millet and lowest with velvetbean cover crops. This was due to the greater height of grass cover crop with their spreading canopies compared to the sm aller velvetbean plants. Generally, grass cover crops generate larger biomass than legume cover crops. Besides producing biomass, cover crop mixtures can also pr oduce nitrogen to support the growth of succeeding vegetables (Fageria et al., 2005; Creamer et al., 1996, 1997). Similarly, the results of light interception suggest that that the sunn hemp, so rghum sudangrass, and pearl millet cover crops intercepted more light because of their dense canopy cover. Dense canopies can help to suppr ess weeds (Nelson et al., 1991). Total and marketable yields of squash were greatest in the PM and SH systems. Torres et al. (2005) found t hat pearl millet and sunn hemp had high dry biomass yield and nitrogen accumulation and release. Previ ous research indicates that sunn hemp fixed around 72 and 91% of total nitrogen, depending on soil fertility and water availability (Seneratne and Ra tnasinghe, 1995; Ladha et al., 1996; Cherr et al., 2006). These may be the reasons for the higher squash yields with the PM and SH systems. Rotar and Joy (1983) also estimated ther e would be 150 to 165 kg/ha of nitrogen recovered from sunn hemp if incorporated at 60 DAP. On the other hand, the PMSH and SSVB systems lowered squash yield. This may be due to the competition from the

PAGE 77

77 rye-hairy vetch planted as living mulch in t he squash plots. Attempts should be made to reduce competition in inter-planting syst ems, including mechanical suppression, screening of less competitive mulches, and vari ation in mulch planting dates (Ammon et al., 1995; Nyoike et al., 2008). Broccoli was used as the fall vegetable in the second year of this experiment. The result suggests that no cropping systems in fluence the marketable yield in broccoli. This suggests that pearl millet planted in t he SS system improved broccoli total yield while sorghum sudangrass and velvetbean cove r crops planted in PM and SH systems had no impact on it. Velvetbean produced lower cover crop biomass, which may have resulted in less nitrogen release into the so il. Summers et al. (2009) observed an allelopathic effect of sorghum sudangrass on the subsequent broccoli crop as it decreased the broccoli yield. He suggest ed transplanting broccoli 6-8 weeks after incorporating residue of sor ghum sudangrass in the soil. Si milarly, broccoli transplants were inhibited by velvetbean residues (Harris on et al., 2004). Crimson clover planted as living mulch in the PMSH and SSVB systems had no influence on broccoli yields. Chase and Mbuya (2008) observed inhibition of broc coli yield with living mulches even when mowed. On an average, a 41% decrease was not iced in broccoli market yield compared to total yield. There was no significant difference between cropping systems in spring 2007 in either total or marketable yields of bell pepp er. This suggests that bell pepper yield was not affected by the management practices em ployed in the different cropping systems. Sweet corn total and marketable yields were significantly higher in intermediate cropping systems (PM, SS, SH, and VB) than in the complex systems (PMSH and

PAGE 78

78 SSVB). Sweet corn average marketable yi eld was reduced by 46% compared to average total yield in spring 2008. Munoz-Carpena et al. (2008) found in their study that corn nitrogen uptake and yield were greater in sunn hemp cover crop plots compared to plots with no cover crop. Both complex systems recorded lower total and marketable yield than WF system, which suggests that bean intercropping may not influence the yield of sweet corn. In addition, crimson clov er planted in fall did not influence the yield of subsequent spring sweet corn. McVay et al. (1989) observed minimal corn yield response to nitrogenous fertilizers following crim son clover. Griffin et al. (2000) reported that a rye-hairy vetch mixt ure supplied nearly all of the nitrogen required for the subsequent sweet corn production. Experiment II: Cover Crops-Broccoli-Sweet Corn; Cover Crops-Squash-Bell Pepper Cover crop biomass was greatest with pear l millet alon e and wit h the pearl milletsunn hemp mixture and lowest in velvet bean cover crop in both 2006 and 2007. Similarly, light interception with the pear l millet-sunn hemp mixture was among the highest at both 30 and 60 DAP in both the y ears. Pearl millet plants have C4 photosythentic pathways that may help to produce la rge amount of biomass (Valenzuela and Smith, 2002; Torres et al., 2005). Sunn hemp can fix nitrogen in the soil, grow vigorously to provide good gr ound coverage, and produce a large quantity of biomass (Akanvou et al., 2001; Wang et al., 2002). In fall 2006, total and marketable yield of broccoli did not show significant differences between cropping systems. This suggests that none of the cropping systems had any influence on broccoli yield. On average, there was a decrease of 10% in marketable yield from total yield in bro ccoli. In fall 2007, squash marketable yield was

PAGE 79

79 highest in the PM system while the s quash yield with both the PMSH and SSVB complex systems were not different from t hat with the WF system. This may be due to the competition of rye-hairy vetch with the squash plants. Rye-hairy vetch living mulch fixes atmospheric nitrogen (Karpenstein -Machen and Stuelpnagel, 2000) and increases the nitrogen supply for the succeeding crop (Sai nju et al., 2005), but living mulches may interfere with the main crop and affect main crop yield through competition for light, water, and nutrients (Ammon et al., 1995). In spring 2007, total yield of sweet co rn was highest in the VB system while marketable yield was greatest in the PM sys tem. In the PMSH and SSVB systems, total and marketable yields were less than ot her cropping systems, except WF and SH systems. Sweet corn yield was also lowest in both complex systems in experiment I and highest in single planted cover crop system s. In spring 2008, the average marketable yield of bell pepper was reduced by 17% compar ed to total yield. Total and marketable yields of bell pepper were greatest in the SSVB and VB systems. This suggests that velvetbean planted as a summer cover crop im proved bell pepper yield in both these systems. Additionally, the rye-hairy vetch liv ing mulch in the preceding squash crop may have contributed to improved bell pepper yield in complex system as it was incorporated into the soil before trans planting the pepper seedlings. Rye-hairy vetch mixtures increase nitrogen supply and nitrogen uptake of the subsequent crop (Sainju et al., 2005). Isik et al. (2009a) observed that ry e and hairy vetch improve the yield of succeeding pepper with greatest pepper yield obtained from hai ry vetch planted for two consecutive years.

PAGE 80

80 Conclusion Squash marketable yield was highest in the PM system in both the experiments while marketable squash yields in the PM SH and SSVB systems were not different from that in the WF system. The ma rketable yield of sweet corn was highest in the PM and SS systems in experiment I and in the PM system in experiment II; however, both PMSH and SSVB systems resulted in marketabl e sweet corn yields that were not different from that of the WF system. In experiment II, bell pepper marketable yield was higher in the PMSH, SSVB, and VB systems t han in the WF system. There were no significant differences in brocco li yield in both the experiments.

PAGE 81

81 Table 4-1. Cropping system treatm ents used in experiments I and II a 2006-07 2007-08 Cover Crops A Fall Spring Cover Crops Fall Spring Experiment I Weedy fallow (WF) Squash Bell Pepper Weedy Fallow Broccoli Sweet Corn Pearl millet (PM) Squash Bell Pepper Sorghum Sudangrass Broccoli Sweet Corn Sorghum-sudangrass (SS) Squash Bell Pepper Pearl Millet Broccoli Sweet Corn Sunn hemp (SH) Squash Bell Pepper Velvetbean Broccoli Sweet Corn Velvetbean (VB) Squash Bell Pepper Sunn Hemp Broccoli Sweet Corn Pearl Millet-Sunn Hemp (PMSH) Squash + Rye -Hairy Vetch Bell Pepper + Bush Beans Sorghum SudangrassVelvetbean Broccoli + Crimson Clover Sweet Corn + Bush Beans Sorghum SudangrassVelvetbean (SSVB) Squash + Rye-Hairy Vetch Bell Pepper + Bush Beans Pearl Millet-Sunn Hemp Broccoli + Crimson Clover Sweet Corn + Bush Beans Experiment II Weedy fallow (WF) Broccoli Sweet Corn Weedy Fallow Squash Bell Pepper Pearl millet (PM) Broccoli Sweet Corn Sorghum Sudangrass Squash Bell Pepper Sorghum-sudangrass (SS) Broccoli Sweet Corn Pearl Millet Squash Bell Pepper Sunn hemp (SH) Broccoli Sweet Corn Velvetbean Squash Bell Pepper Velvetbean (VB) Broccoli Sweet Corn Sunn Hemp Squash Bell Pepper Pearl Millet-Sunn Hemp (PMSH) Broccoli + Crimson Clover Sweet Corn + Bush Beans Sorghum SudangrassVelvetbean Squash + Rye Hairy Vetch Bell Pepper + Bush Beans Sorghum SudangrassVelvetbean (SSVB) Broccoli + Crimson Clover Sweet Corn + Bush Beans Pearl Millet-Sunn Hemp Squash + Rye Hairy Vetch Bell Pepper + Bush Beans a For convenience, cropping system treatments are referred to in the text by the summer cover crop names of 2006-07.

PAGE 82

82 Table 4-2. Details of cover crops pl anted in this experiment at Citra, FL Cover crops Botanical Name Cultivar Source Seed-rate (kg/ha) Pearl millet Penisetum glaucum Tifleaf Production Plus, Plainview, TX 4.5 Sorghum-sudangrass Sorghum bicolor x S. bicolor var sudanense Brown Midrib Production Plus, Plainview, TX 7.2 Sunn hemp Crotalaria juncea Unknown Kaufman Seeds, Haven, KS 7.2 Velvetbean Mucuna pruriens var pruriens Georgia Bush Georgia Seed Development Commission, Athens, GA 18.0 Pearl Millet-Sunn Hemp 3.0 PM + 3.6 SH Sorghum SudangrassVelvetbean 4.8 SS + 12.0 VB

PAGE 83

83 Table 4-3. Management practices with their dates in squash and bell-pepper from 2006 to 2008 Crop management practices 2006-07 2007-08 SQUASHa NatureSafec (10-2-8 N-P2O5-K2O) fertilizer applied at 1685 kg/ha as a 30-cm band over center of the bed 9 October 2006 9 October 2007 Squash direct seeded as single row per bed with in-row plant distance of 45 cm 19 October 2006 10 October 2007 Rye-hairy vetch broadcasted between beds in mix ed cover crop plots 9 November 2006 26 October 2007 Row covers were placed to protect from frost 8 December 2006 16-19 November 2007 Squash was harvested between the following dates 14 December 2006 9 January 2007 21 November 14 December 2007 GREEN BELL PEPPERb NatureSafec (10-2-8 N-P2O5-K2O) fertilizer applied at the rate of 1116 kg/ha 7 March 2007 4 March 2008 Forty-five-day-old bell pepper seedlings transplanted in double rows per bed with 45 cm plant distance within a row. 15 March 2007 13 March 2008 Green bush bean direct seeded between bell pepper beds as intercropped in mixed cover crop plots 16 March 2007 14 March 2008 Application of NatureSafe (10-2-8 N-P2O5-K2O) fertilizer at rate of 1116 kg/ha 10 April 2007 1 April 2008 Hand weeding 2 April,18 April, and 30 May 2007 14 April and 14 May 2008 Green bush bean harvested on the following dates 16 May and 30 May 2007 13 May 2008 Bell pepper harvested between the following dates, four harvests total 21 May 20 June 2007 13 May 9 June 2008 aCucurbita pepo L. cv. Cougar F1 untreated; Harris Seeds, Rochester, NY bCapsicum annuum L. cv. Red Knight F1 untreated; Johnnys Selected Seeds, Winslow, ME cNatureSafe, Cold Springs, KY

PAGE 84

84 Table 4-4. Management practices with their dates in broccoli and sweet corn from 2006 to 2008 Crop management practices 2006-07 2007-08 BROCCOLIa NatureSafee (10-2-8 N-P2O5-K2O) fertilizer applied at 1976 kg/ha as 30-cm band over bed center. 25 October 2006 9 October 2007 Thirty-day-old broccoli seedlings transplanted in double rows per bed with 45 cm planting distance within rows 31 October 2006 16 October 2007 Crimson clover broadcast between beds in mixed cover crop plots at 28 kg/ha 9 November 2006 26 October 2007 Broccoli harvested between the following dates, 3 harvests total 4 January -16 January 2007 20 December2007 2 January 2008 SWEET CORNb Broccoli plots flail mowed and disked to 20 cm soil depth for planting sweet corn 5 March 2007 4 March 2008 NatureSafe (10-2-8 N-P2O5-K2O) fertilizer applied at the rate of 1116 kg/ha 7 March 2007 4 March 2008 Sweet corn direct-seeded at 76 cm row distance and 18 cm plant distance 12 March 2007 11 March 2008 Bush bean direct seeded in strips (4 rows/strip) arranged alternately with strips of sweet corn in mixed cover crop plots. 12 March 2007 11 March 2008 Application of NatureSafee (10-2-8 N-P2O5-K2O) fertilizer at rate of 1116 kg/ha 10 April 2007 1 April 2008 Hand weeding 2 April and 18 April 2007 14 April 2008 Biolinkc (0-0-6 N-P2O5 -K2O applied over bean plants at nozzle rate of 760 ml/min and 50 gal/ha water 29 April 2008 Sodium nitrate (Proboosterd, 10-0-0 N-P2O5 -K2O) applied at 868 kg/ha in response to nitrogen deficiency symptoms 7 May 2008 Sweet corn harvested between the following dates, 2 harvests total 31 May12 June 2007 29 May -4 June 2008 Bush beans harvested on the following dates 16 May 30 May 2007 13 May 29 May 2008 a Brassica oleracea L. cv. Marathon F1 untreated; Harris seeds, Rochester, NY b Zea mays L. cv. Montauk F1 untreated; Johnnys Selected Seeds, Winslow, ME c Westbridge Agricultural Products, Vista, CA d North Country Organics, Bradford, VT e NatureSafe, Cold Springs, KY

PAGE 85

85 Table 4-5. Cover crop height and percent light interception in 2006 and 2007 in experiment Ia 2006 2007 Height (cm) Light interceptionb (%) Height (cm) Light interceptionb (%) Cover crops 30 DAP 60 DAP 30 DAP 60 DAP Cover crops 30 DAP 60 DAP 30 DAP 60 DAP WF WF PM 40 b 87 a 93.5 a 96.0 a SS 83 a 104 a 67 ab 91 ab SS 64 a 97 a 87.3 ab 92.3 ab PM 63 b 118 a 78 a 92 ab SH 24 c 104 a 85.6 ab 86.4 b VB 25 d 24 b 49 c 78 c VB 16 c 20 b 78.8 b 72.0 c SH 51 c 118 a 62 bc 94 a PMSH 41 b 87 a 86.4 ab 94.2 a SSVB 52 c 64 b 69 ab 84 bc SSVB 64 a 102 a 85.3 ab 90.2 ab PMSH 60 b 104 a 72 ab 95 a a Data were means of four replications. Means in columns followed by the same letters were not different according to least significant difference (LSD) at P 0.05 b arc-sign transformed; mean values untransformed

PAGE 86

86 Table 4-6. Cover crop height and percent light interception in 2006 and 2007 in experiment IIa 2006 2007 Height (cm) Light interceptionb (%) Height (cm) Light interceptionb (%) Cover crops 30 DAP 60 DAP 30 DAP 60 DAP Cover crops 30 DAP 60 DAP 30 DAP 60 DAP WF WF PM 44 b 72 b 84 bc 91 abc SS 82 a 102 c 59 cd 84 b SS 52 ab 66 b 79 c 83 c PM 58 c 105 c 71 abc 84 b SH 27 c 112 a 93 ab 92 ab VB 25 d 23 d 48 d 80 b VB 16 cd 20 c 85 bc 85 bc SH 70 b 122 a 77 ab 93 a PMSH 47 b 103 a 95 a 97 a SSVB 55 c 66 cd 60 bcd 83 b SSVB 64 a 82 ab 80 c 87 bc PMSH 57 c 108 bc 81 a 94 a a Data were means of four replications. Means in columns followed by the same letters were not different according to least significant difference (LSD) at P 0.05 b arc-sign transformed; mean values untransformed Table 4-7. Total and marketable yields of bush bean inte rcropped with bell pepper and sweet corn in 2007 and 2008 Experiment I Experiment II Bell pepper 2007 Sweet corn 2008 Sweet corn 2007 Bell pepper 2008 Cropping system Total yield (kg/ha) Market yield (kg/ha) Total yield (kg/ha) Market yield (kg/ha) Total yield (kg/ha) Market yield (kg/ha) Total yield (kg/ha) Market yield (kg/ha) PMSH 3527 3206 1119 1018 3119 2906 1889 1706 SSVB 3432 3134 1991 1794 3013 2682 4440 3986

PAGE 87

87 a a bc cd a ab a b b c b b 0 1000 2000 3000 4000 5000 6000 7000PMSSSHVBPMSHSSVBCover crops Biomass (kg ha-1 ) Cover crops biomass 2006 Cover crops biomass 2007 Figure 4-1. Cover crop biomass in 2006 and 2007 in experiment I

PAGE 88

88 c bc bc ab bc a bc c bc bc ab bc a bc 0 500 1000 1500 2000 2500 3000 3500 4000 4500WFPMSSSHVBPMSHSSVBCropping systemYield (kg ha-1) Total Squash 2006 Marketable squash 2006 Figure 4-2. Total and marketable yields of squash in fa ll 2006 in different cropping systems in experiment I

PAGE 89

89 ab ab b ab a b ab a a a a a a a0 500 1000 1500 2000 2500 3000 3500 4000 4500 WF PM SS SH VBPMSHSSVBCropping systemYield (Kg ha-1) Total Broccoli 2007 Marketable broccoli 2007 Figure 4-3. Total and marketable yields of broccoli in fall 2007 in different cropping systems in experiment I

PAGE 90

90 a a a a a a a a a a a a a a 0 1000 2000 3000 4000 5000 6000 7000 8000 WFPMSSSHVBPMSHSSVB Cropping systemYield (kg ha-1) Total Pepper 2007 Marketable Pepper 2007 Figure 4-4. Total and marketable yields of bell pepper in spring 2007 in different cropping systems in experiment I

PAGE 91

91 c c a a a a b cd d ab ab a a bc0 1000 2000 3000 4000 5000 6000 7000 8000 9000WFPMSSSHVBPMSHSSVB Cropping systemYield (Kg ha-1) Total Sweet corn 2008 Marketable sweet corn 2008 Figure 4-5. Total and marketable yields of sweet corn in spring 2008 in different cropping systems in experiment I

PAGE 92

92 ab b b c a b ab c bc d a c0 1000 2000 3000 4000 5000 6000PM SS SH VBPMSHSSVB Cover cropsBiomass (kg ha-1) Cover crops biomass-2006 Cover crops biomass-2007 Figure 4-6. Cover crop biomass in summer 2006 and 2007 in experiment II

PAGE 93

93 a a a a a a a a a a a a a a0 500 1000 1500 2000 2500 3000 3500 4000 4500WFPMSSSHVBPMSHSSVB Cropping SystemYield (Kg ha-1) Total Broccoli 2006 Marketable Broccoli 2006 Figure 4-7. Total and marketable yields of broccoli in fall 2006 in different cropping systems in experiment II

PAGE 94

94 a a a a a a a b b ab ab ab a b0 1000 2000 3000 4000 5000 6000 7000WFPMSSSHVBPMSHSSVB Cropping systemCrop yield (kg ha-1) Total squash 2007 Marketable squash 2007 Figure 4-8. Total and marketable yields of squash in fall 2007 in different cropping systems in experiment II

PAGE 95

95 bc ab abc bc a c c b a ab b ab b ab0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000WFPMSSSHVBPMSHSSVB Cropping systemYield (Kg ha-1) Total sweet corn 2007 Marketable sweet corn 2007 Figure 4-9. Total and marketable yields of sweet corn in sp ring 2007 in different cropping systems in experiment II

PAGE 96

96 a ab a bc bc bc c a ab a c c bc c0 1000 2000 3000 4000 5000 6000 7000 8000WF PM SS SH VB PMSHSSVBCropping systemCrop yield (Kg ha-1) Total pepper 2008 Marketable pepper 2008 Figure 4-10. Total and marketable yields of bell pepper in spring 2008 in different cropping systems in experiment II

PAGE 97

97 CHAPTER 5 WEED COMMUNITY RESPONSE TO OR GANIC VEG ETABLE CROPPING SYSTEM COMPLEXITY IN FLORIDA Introduction Organic growers have identified weed ma nagement as a critical production constraint (Walz, 1999). Greater use of tillage and cultivation for weed suppression is typical in low external input systems, wh ich can lead to increased soil erosion and decreased soil organic matter (Liebman and Davis, 2000). Organic farmers utilize various cropping systems that may incr ease or decrease weed density and weed species variation. However, insufficient info rmation is available to farmers on the effects of cropping systems on weeds. The National Organic Program requires the use of cultural practices as a first step to manage weeds in organic crop production (Section 205.206 (Appendix C) available online at www.ecfr.gpoaccess.gov). Liebman and Davis (2000) sugg ested various cultural weed management practices for low external i nput systems that are applicable to organic production and incl ude diversifying crop sequences with multispecies rotation, cover crops, and intercrops, and amending soil with crop residues, animal manures, and compost. They indicated that diversification changes a soils physical, chemical, and biological properties, and thus affects the population dynamics of weeds. Cover crops suppress pests, improve soil and water quality, benefit nutrient cycling efficiency and cash crop productivity, particularly in irrigated systems (Snapp et al., 2005). Cover crops suppress weeds either as living plants or plant residue on or in the soil (Teasdale et al., 2007) and increase ecological complexity of the cropping system. If planted during summer fallow se ason, cover crops suppress weeds and

PAGE 98

98 nematodes, improve soil fertilit y, and improve yield in both conventional and organic cropping systems (Aguiar et al., 2001; Ngou ajio et al., 2003). Cover crops suppress weeds by competing for nutrient resources, altering environmental factors for weed germination and establishment, and releasi ng phytotoxins (Liebman and Davis, 2000). Cover crop residues can also be used as mulches to suppress weeds and provide habitat for weed seed predators. Cover crops with good canopy cover and fewer stems have the ability to suppress weeds by decreasing light transmittance through the canopy (Teasdale, 1996) and also produce enough biomass to suppress weeds (Creamer et al., 1997). The benefits of cove r crops may be optimized when mixtures of cover crops are used (Creamer et al., 1997). Mixtures that include legumes maintain a C:N ratio that is more favo rable for mineralizing nitrogen than grasses alone. Mixtures may also suppress a broader spectrum of weeds through allelopathy (Creamer et al., 1997). Crop rotation can prevent the dominance and proliferation of a particular weed by providing resource competit ion, allelopathic interfer ence, soil disturbance, and mechanical damage (Liebman and Davis 2000). Intercropping can cover the soil more effectively than a single crop and reduces weed growth by capturing a greater share of available resources than a single crop (Walters, 1971; Liebman and Dyck, 1993). Intercrops deprived weeds of light, water, and nutrients (Liebman and Dyck, 1993). Cropping systems with high levels of crop diversity through intercropping and multiple cropping practices help to reduce dependence on purchased fertilizers and pesticides while sustaining crop yields (Liebman and Staver, 2001). Diversified cropping systems include planting different types of cr ops using rotation and intercropping, and

PAGE 99

99 by planting cover crops (Liebman and Stav er, 2001). In a croppi ng system, different crops with their associated management practice s have different effects on light, water, and nutrient conditions that may affect germination and growth of weeds. Analysis of these variations increases opportunities for weed management. Integrating such cultural practices as crop rotation, living cover crops, living mulches, and intercropping in a year-round cropping system allows the producer to evaluate their effects on weed populations and biomass. This information can provide a better understanding of which system or syst ems suppress weed populations more effectively. This research may help wit h designing organic cr opping systems that suppress weeds while conserving biological resources in hortic ultural crops for the north Florida region. The objective of this study was to evaluate the effect of cropping system complexity on the population of weed comm unities. It is hypothesized that more complex cropping systems more effectivel y suppress weed density and biomass than a weedy fallow system. Materials and Methods Two experiments were established concurrently in summer 2006 on certified organic land at the Plant Science Research and Education Unit, Marion County, FL. The cropping system for each experiment cons isted of a summer cover crop and fall and spring vegetables. Before establishing the ex periment, the field site was used for the production of bahiagrass ( Paspalum notatum Flgg). The soil is Candler sand (Hyperthermic, uncoated Lamellic Quartzipsa mment; Entisol) with a soil pH of 7.1 The entire field was first planted with r oot knot nematode-susceptible White Acre southern pea or cowpea ( Vigna unguiculata Walp) in May 2006. The crop was mowed in July 2006 using a New Holland 918H flail mower (Purdy Tractor and

PAGE 100

100 Equipment, Inc., Hillsdale, MI). Finished mu shroom compost (Quincy Farms, Quincy, FL) was applied at 2500 kg/ha through a che ck drop spreader (Newton Crouch, Inc., Griffin, GA) to add organic ma tter to the soil. This was followed by incorporating and disking the field to a depth of 20 cm. Both experiments were started on 27 July 2006 with a summer fallow consisting of either su mmer cover crops or a weedy fallow. The experimental design was a randomized comp lete block with seven treatments as cropping systems and four r eplications (Table 5-1). Plots measured 12 m x 12 m and were separated by 12 m alleys. Cultivars, seed sources, and seeding rates of cover crops are summarized in Table 5-2. Pearl millet and sorghum sudangrass were planted using a seed drill (Sukup 2100, Sukup Manufacturing Company, Shefield, IA) with 17 cm between plants in the row and at 5 cm soil depth. Sunn hemp and velvetbean seeds were inoculated with Rhizobium sp. (Nitragin, cowpea type, Nitragin, Inc., Brookfield WI) before broadcasting on the plot. Later, seeds were covered us ing a roller. Overhead irrigation was used occasionally during the first three days after planting to pr omote germination and establishment of the cover crops. Aboveground biomass of summer cover crops were flail mowed on 2 October 2006 and disked to inco rporate into the soil. This was followed by the application of lime (Aglime Sales, In c., Babson Park, FL) to the entire field at 2500 kg/ha. Fall vegetables were planted in four beds (1.8 m bed-center size) per plot, each plot 12 m long x 7.2 m wide. Before plant ing fall vegetables, fertilizer,10-2-8 N-P2O5K2O (NatureSafe, Griffin Industries, Cold Spring, KY) was applied at the rate of 1685 kg/ha for squash and 1976 kg/ha for brocco li based on the conventional fertilizer

PAGE 101

101 recommendations for these crops (Olson and Simonne, 2006). It was applied as a 30cm band over the center of the b ed and incorporated bef ore planting. Squash: Yellow squash ( Cucurbita pepo L. cv. Cougar F1, untreated; Harris Seeds, Rochester, NY) was direct seeded on 19 October 2006 as a single row per bed with an in-row plant distance of 45 cm (12, 037 seeds/ha). Squash was irrigated using a drip irrigation system. A combination of rye ( Secale cereale cv Wrens Abruzzi; Alachua County Feed and Seed Store, Gai nesville, FL) and hairy vetch ( Vicia villosa, cultivar unknown; Adams Briscoe Seed Company, Jacks on, GA) was planted in between beds as living mulch in mixed cover crop plots. A rye-hairy vetch mixture improves soil organic matter and reduces nitrogen leaching as compared to hairy vetch alone (Sainju et al., 2005). The seeding rates were 48 kg/ ha for rye and 22 kg/ha for hairy vetch. Before planting, hairy vetch was inoculated with Rhizobium leguminosarum biovar viceae, ( Nitragin C, Nitragin, Inc, Brookfield, WI). Both liv ing mulch seeds were mixed and broadcasted on 9 November 2006 by hand on a shallow tilled soil and covering using a roller. Row covers were placed on squash plots on 8 December 2006 to protect from frost. Squash was harve sted six times between 14 December 2006 and 9 January 2007. Methods used for the squash crop in 200708 were similar to those of the previous year, with minor exceptions. The crop was planted on 10 October 2007 by direct seeding. Between 16 and 19 November 2007, row covers were placed on the seedlings. Squash was harvested eight time s between 21 November and 14 December 2007.

PAGE 102

102 Bell pepper: Squash plots were rotated with green bell pepper ( Capsicum annuum L. cv Red Knight F1, untreated; Johnnys Selected Seeds, Winslow, ME). NatureSafe fertilizer, 10-2-8 N-P2O5-K2O (NatureSafe, Cold Spri ngs, KY) was applied at the rate of 2232 kg/ha based on synthetic fe rtilizer recommendations for these crops (Olson and Simonne, 2006). Fertilizer was applied in split applications, one on 7 March as pre-plant broadcast and 10 April 2007 as banded side-dressed. When the bell pepper seedlings were 45 days old, they were transplanted on 15 March 2007 to double row beds. There were four beds per 12 m x 7.2 m plot. The dist ance between plants within a row was 45 cm with similar distanc es between rows (24,074 plants/ha). Bush beans (Phaseolus vulgaris L. cultivar Bronco untreat ed, Seedway Elizabethtown, PA) were intercropped with pepper in mixed cover cr op plots. On 16 March 2007, they were direct-seeded between bell pepper beds using a manual push planter at a rate of 15 cm between seeds. Both bell pepper and bush beans were irrigated by drip irrigation to keep soil moisture near field capacity. H and weeding was done on 2 and 18 Apil and 30 May 2007 to control weeds. This was done throughout the crop ar ea with the help of hand hoe. The next year, hand weeding was done on 14 April and 14 May 2008. Bell pepper was harvested four times between 21 May and 20 June 2007. Bush bean was harvested on 16 and 30 May 2007. In spring 2008, bell pepper was transplanted on 13 March and bush bean on 14 March, while be ll pepper was harvested four times between 13 May and 9 June; bush bean was harvested on 13 May. Broccoli: At thirty days, broccoli ( Brassica oleracea L. cv. Marathon F1, untreated; Harris Seeds, Rochester, NY) s eedlings were transplanted on 31 October 2006 in double rows, 30 cm distance between rows, per bed at a spacing of 45 cm

PAGE 103

103 between plants in rows, and a total of eight rows per plot (24,0 74 plants/ha). It was irrigated using drip irrigation to keep soil mo isture near field capac ity. Crimson clover ( Trifolium incarnatum cv Dixie; Adams Briscoe S eed Company, Jackson, GA) was planted as living mulch between beds in mixed cover crop plots. The seeding rate was 28 kg/ha. Crimson clover was inoculated with R. leguminosarum biovar trifolii (Nitragin R/WR, Nitragin, Inc, Brookfield, WI) befor e planting. Crimson cl over was broadcasted on 9 November 2006 by hand onto a shallow t illed soil followed by covering the seeds using a roller. Broccoli was harvested th ree times between 4 January and 16 January 2007. On 5 March 2007, the field was fla il mowed and disked to a 20-cm soil depth to prepare the seedbed for planting spring vegetables. Similar methods were used to manage the broccoli crop in the second year. In 2007-08, broccoli seedlings 35 days old were transplanted on 16 October 2007. Broccoli was harvested three times betw een 20 December 2007 and 2 January 2008. Sweet corn: Broccoli plots were rotated with sweet corn ( Zea mays L. cultivar Montauk F1 untreated; Johnnys Selected Seeds, Winslow, ME). NatureSafe fertilizer (10-2-8 N-P2O5-K2O) was applied at the same rate, time, and application method as in bell pepper. Sweet corn was direct-seeded on 12 March 2007 using a Monosem planter (Monosem, Inc., Edwardsville, KS) at 76 cm bet ween rows and plant distances of 18 cm in rows, with a plot size of 144 m2 (74,444 plants/ha). Using a Monosem planter, bush beans were interplanted with sweet corn in mi xed cover crop plots. It was direct-seeded on 12 March 2007 in four strips (4 rows/strip ) arranged alternately wit h strips of sweet corn. Bush beans between row and between plant spacings were 76 cm and 13 cm, respectively. In spring 2008, sweet corn and bush beans were direct-seeded on 11

PAGE 104

104 March,. Both sweet corn and bush beans were irrigated to maintained soil moisture near field capacity. Hand weeding was done using hand hoes on 2 and 18 April 2007 to control weeds throughout the plot area. In 2008, hand weeding was done on 14 April. Sweet corn was harvested on 31 May and 12 June 2007 while bush beans were harvested on 16 May and 30 May 2007. Potassium fertilizer, 0-0-6 N-P2O5 -K2O (Biolink, Westbridge Agricultural Products, Vista, CA) was applied to t he bean plants in spring 2008 using a CO2 sprayer at a nozzle rate of 190 ml/15 second and 50 gallons/ha water. This was applied to correct potassium levels in bush bean plan ts. Sodium nitrate (Probooster, 10-0-0 NP2O5 -K2O, North Country Organics, Br adford, VT) was also applied to sweet corn plots at 868 kg/ha (less than 20% of total nitr ogen) on 7 May 2008 in response to nitrogen deficiency symptoms. Sweet corn was harvested on 29 May and 4 June and bush bean on 13 May 2008. In the second year, 2007-2008, squash plots were rotated with broccoli in the fall season while bell pepper plots we re rotated with sweet corn in the spring season. The management practices were similar to those described for the previous year. To avoid having the same cover crop in the same plot in both years, a pearl millet cover crop was rotated with sorghum-sudangrass, while sunn hemp was rotated with velvetbean and vice versa. Similarly, sorghum sudangr ass-velvetbean was rotated with pearl milletsunn hemp mixtures and vice versa. The field was mowed on 6 July 2007. To lower soil pH, elemental sulfur (Tiger 90 with 90% su lfur, Tiger-Sul Produc ts, Atmore, AL) was applied at 250 kg/ha using a drop spreader. The cover crops were planted on 31 July 2007; sorghum-sudangrass and pearl millet were direct seeded using a John Deere 450

PAGE 105

105 planter, while sunn hemp was planted using a Sukup 2100 planter at an 18-cm row distance. Before planting cove r crops, Sulpomag, 0-0-21 N-P2O5-K2O (Diamond R Fertilizer, Winter Garden, FL) was hand-applie d at 257 kg/ha. The same application rate was repeated after mowing the cover crops. Data collection and analysis Data on weed population densities and tota l weed biomass were collected for both cover crops and vegetables. In cover crop plots, weeds were counted by species at 30 and 60 days after planting cover crops, within a one m2 quadrat randomly placed in each cover crop plot. After counting weed species, above-ground weed biomass was collected from within the quadrat and dried at 60 C and weighed. For fall and spring vegetables, weeds were counted, by specie s, between beds and within vegetable rows in 0.25 m2 quadrats placed randomly one ti me per plot. Weeds were counted at 2, 4, 6, and 9 weeks after planting the vegetable crops. Above-ground weed biomass was collected after counting weed species from the same 0.25 m2 quadrats, dried at 60 C, and weighed. In fall 2006, weeds were counted between beds only. After this, weeds within crop rows were also counted. After this season, weeds were always counted within vegetable rows as well as between crop beds. Weed species were grouped into grasses, broad-leaf, and sedges. Counts were square root-transform ed (sqrt[x+1]) to normalize the data and to accommodate zero counts. In spring 2007 and 2008, the time needed to hand weed plots was determined. Time at the beginning and the end of the hand weeding was noted for each plot. The time per plot was used to calculate time per hectare and divided by the number of persons used for hoeing. In this way, data were analyzed were hoeing times per he ctare for a single person.

PAGE 106

106 Data were averages of different sampling dates because no interactions were found between cropping systems and sampling dates. Analysis of variance was performed on transformed values using the GLM procedure in Statistical Analysis System software (SAS, 2008). Means were s eparated by the least significant difference (LSD) test at the 5% leve l of significance. The data are reported as untransformed means. Results and Discussion During 2006-07 in both experiments, the major weed species were southern crabgrass ( Digitaria ciliaris (Retz.) Koel) and Florida pusley ( Richardia scabra L.) in all seasons. In addition, hairy indigo ( Indigofera hirsuta L.) in summer and wandering cudweed ( Gnaphalium pensylvanicum Willd.) in fall were al so prevalent. Major weed species present in 2006-07 persisted in 2007-08. In addition, carpet weed ( Mollugo verticillata L.) and several species of sedges were found in all the seasons. Sedge species included: Cyperus rotundus L., C. strigosus L., C. globulosus Aublet, C. compressus and C. brevifolius Experiment I: 2006 Cover Crop-Squash Pepper; 2007 Cover Crop-BroccoliSweet Corn Weeds between beds Grass w eeds. In summer 2006 only the PM syst em suppressed grass weeds to levels lower than the WF system (Table 5-3). In fall squash, only the SSVB system resulted in fewer weeds than the WF system During the spring bell pepper season of 2007, grass weed densities in cropping systems with cover crops were not significantly different from the weedy fallow (WF). Resu lts in 2007-08 changed, so that grass weed

PAGE 107

107 density was significantly greater in the WF s ystem than in the re st of the cropping systems in all seasons, except for the SH system in the fall broccoli season. Broad-leaf weeds In 2006-07, except for SH, cover crop cropping systems suppressed the broad-leaf weed populations to less than half that of WF system (Table 5-4). In squash, broad-leaf weeds were s uppressed to lower populations than the WF system only with the VB, PMSH and SSVB systems. This s uppression persisted in bell pepper in the VB and SSVB system s. In 2007-08, broad-leaf weed populations were significantly lower than the WF system with the VB and SSVB system s. In broccoli, broad-leaf weeds were suppressed by PM VB, PMSH, and SSVB systems. In sweet corn only the VB, PMSH, and SSVB system s had lower braod-leaf weed populations than the WF system. Broadleaf weed populations in the SH system were similar to or higher than those in the WF system throughout the 2-year period. Sedges: During the cover cropping period in summer 2006, sedge populations were lower in the PM and SS systems than in the WF system (Table 5-5). In squash 2006, only the PMSH system resulted in fe wer sedges than the WF system. In bell pepper in spring 2007, sedge densities were low ( 3 plants m-2) in all cropping systems except for the PMSH and SSVB systems where sedge densities were significantly higher at 11 and 15 plants m-2, respectively. In the cove r crops in summer 2007, sedge populations were significantly lower in VB and PM systems than in the WF system. In broccoli in fall 2007, only the SH system had a sedge density higher t han that of the WF system. In sweet corn in spring 2008, all cover crop cropping systems suppressed sedge populations (1-2 plants m-2) to levels lower than the WF system (58 plants m-2)..

PAGE 108

108 Overall, the SSVB system suppressed grass and broad-leaf weed populations in between beds over two years (Tables 5-3 and 5-4). SSVB mixtures produced substantial biomass (Table 5-6) that covered the so il and smothered the weeds; however only the VB system produced less biomass. A sorghum-sudangrass-cowpea mixture was reported to produc e significant above-ground biomass, a C:N ratio of 24:1 and 39:1, and significantly suppressed weeds in vegetable production systems (Creamer and Baldwin, 2000). The VB system suppressed broad-leaf weeds over the two-year period but the SH system it was not as effective. Sedge populations were suppressed in the PM and VB systems in 2-year cropping systems, but sedge populations in squash and bell pepper were not significantly different from the WF system during the first year of the experiment. This suggests that additional measures may be needed in squash and bell pepper to reduce sedges. The SH system failed to suppress sedge populations. Both rye-hairy vetch and crimson clover living mulches reduced sedges. Sedges in the spring season were less than in the previous fall season, but their populations increased in beans intercropped with spring bell pepper. Living mulch can replace weeds thr ough competition (Teas dale, 1996) and reduced light transmittance, which inactivates phyto chrome-mediated germination of weed seeds (Teasdale and Mohler, 1993). Living mulches like rye and crimson clover were effective in suppressing weeds (Nagabhushana et al., 2001). Weeds within crop rows Grass w eeds. In bell pepper in spring 2007, grass weed populations were significantly fewer in SS and SSVB systems t han in the WF system (Table 5-7). In broccoli in fall 2007, all cover crop syst ems had fewer grass weeds than in the WF system except for the SH and VB systems. In sweet corn in spring 2008, the grass

PAGE 109

109 weed populations were smaller in all the cover crop systems than in the WF system (Table 5-7). Broad-leaf weeds. There was no significant difference in broad-leaf weed populations among cover crop systems and t he WFsystem in bell pepper in spring 2007 (Table 5-8). In broccoli in fall 2007, onl y the VB, PMSH, and SSVB systems had fewer broad-leaf weeds than the WF system. In sw eet corn in spring 2008, SSVB, PMSH, and VB systems had fewer broad-leaf weed populat ions compared to the WF system. Sedges. In bell pepper in spring 2007, sedge density was highest in SH system while other cover crop systems were not signi ficantly different fr om the WF system (Table 5-9). In broccoli in fall 2007, onl y the SS system suppressed sedges to lower than the WF system. In sweet corn in spring 2008, the sedge population was significantly greater in the WF system than in all of t he other cropping systems The SS and SSVB systems suppressed grass weeds within crop rows throughout the two year cropping system. In addition, PM and PMSH systems also reduced grass weeds in the second year of the experiment. This suggests that crop growth in these systems increased with optimum crop spacing to control grass weeds. PMSH and SSVB systems suppress ed broad-leaf weeds duri ng second year of the cropping systems. Both complex systems creat ed stress on broad-leaf weeds at later stages of the cropping system. Sedge populations were greater in the SH than the WF system while the SS system had fewer sedges than the WF system except in bell pepper 2007. Sedge populations increased in broccoli in 2007, which suggests that plant and row spacing in broccoli failed to result in complete canopy closure to restrict sedge establishment.

PAGE 110

110 Generally cover crops do not reduce w eeds effectively throughout the cropping season and suppress early-season weeds (T easdale, 1996). Other reasons include management practices in bell pepper where rela tively wide row and plant spacing of 45 cm allowed weeds to germinate quickly and becom e established with little difficulty. In addition, leaf area index in pepper was less than 1.5, which provides little canopy cover and this may help these weeds to germinate and thrive. Beside this, the plant biomass of bell pepper was only 17-21 g/plant compared with that of broccoli (67-90 g/plant) and sweet corn (39-55 g/plant) (Table 5-6). This suggests that bell pepper was probably less competitive against weeds than the other crops. On the ot her hand, the SH system may have stimulated sedge populations by providi ng nitrogen to crops and weeds, while the SS system reduced sedge populations.. Allelopathy may have contributed to the effectiveness of the SS syst em. Root exudates of Sorghum species contain sorgoleone, which disrupts the growth of neighboring pl ants and helps to suppress weeds (Putnam et al., 1983, Einhelling and Souza, 1992; Nim bal et al., 1996; Duke et al., 2000). Weed biomass Betw een beds. In 2007, total weed biomass was greatest in the WF system during summer cover crop season but increased in all the cropping systems except the PMSH and SSVB systems during the fall squash season(Table 5-10). During spring bell pepper 2007, only the SS system decreased weed biomass to lower than the WF system. In 2007, total weed biomass was gr eatest in the WF system in the summer cover crop season. In fall broccoli 2007, the SS system had greatest total weed biomass while all other systems had less weed biomass than the WF system. In spring sweet corn 2008,

PAGE 111

111 total weed biomass was significantly greater in the WF than in the in SH, VB, and SSVB systems (Table 5-10). Within crop rows. In 2006-07, total weed biom ass was highest in the WF system in summer 2006 and spring bell pepper 2007 season (Table 5-11). In the summer squash season, no cropping system was significantly different from the WF system. During spring bell pepper 2007, all cover crop systems suppressed total weed biomass more effectively than the WF system. In fall broccoli 2007, only the SSVB system suppressed total weed biomass more effectively than WF system; while in spring sweet corn 2008, PM, VB, and SSVB systems had lower total weed biomass than the WF system. Overall the SSVB system suppressed total weed biomass between beds and within crop rows in most of the seasons. In addition, other cover crop systems also suppressed total weed biomass in one or tw o seasons. Isik et al. (2009b) found that grain sorghum and sudangrass cover crops reduced total weed dry biomass for subsequent vegetable production. Similarly, crimson clover as living mulch planted between beds in broccoli plots reduced to tal weed biomass in both PMSH and SSVB systems, but bush beans as an intercrop failed to reduce total weed biomass in the PMSH system in bell pepper and sweet corn. A ccumulated dry matter in crimson clover was greater with a longer growing period (den Hollander et al., 2007). Teasdale (1996) found that weed biomass is highly correlated to cover crop biomass. The SS system reduced total weed biomass in the cover crop season, but failed to reduce it in the subsequent fall and spring seasons. Grain sorghum and sudangrass have also been

PAGE 112

112 shown to lower weed density and total weed biomass in another study (Mennan et al., 2009). Experiment II: 2006 Cover Crop-Broccoli-Corn; 2007 Cover Crop-Squash-Bell Pepper Weeds between beds Grass w eeds. In 2006, grass weed populations were significantly greater in the VB system than other syst ems with cover crops during su mmer, but no cropping system was significantly different from the WF system (Table 5-12). In broccoli in fall 2007, only the SSVB system had fewer grass weeds than the other cropping systems. In sweet corn in spring 2008, no cropping system resulted in a grass weed population that was significantly different from the WF system. During the cover cropping period in summer 2007, the SS and SSVB systems resulted in lower grass weed densities than t he WF system (Table 5-12). In fall squash 2007, the best control of grass weeds occurred in the PMSH, and SSVB systems. Grass weeds were also effectively suppr essed by the PM and SS systems to lower densities than in the WF system. In spring bell pepper 2008, all cropping systems except for the SH system had fewer gr ass weeds than the WF system. Broad-leaf weeds In 2006-07, as for grasses, broad-leaf weed populations in systems with cover crops were not significantly different from that with the WF system (Table 5-13). During the fall broccoli 2006, only the SSVB system had fewer broad-leaf weeds than the WF system; however, the SS system had twice as many weeds per unit area than the WF system. In spring sweet corn 2007, no cropping system resulted in broad-leaf weed populati ons that were lower than the WF system.

PAGE 113

113 In 2007-08, in the summer cover crop seas on, broad-leaf weeds were greatest in the SH system while other croppi ng systems were not significant ly different from the WF system (Table 5-13). During fall 2007 in squash, only the PM SH and SSVB systems had lower broad-leaf weed populations than t he WF system. In spring bell pepper 2008, the broad-leaf weed population in the WF system was similar to or greater than those of the system of the other cr opping systems (Table 5-13). Sedges. In 2006-07, sedge populations were significantly lower than in the WF system with the PMSH, SSVB, and PM systems (Table 5-14). In broccoli, only the PMSH and SSVB systems had lower sedge populat ions than than the WF system. In 2007-08, the sedge populatio n was greater in the SH system than in the WF system in the summer cover crop season. In fall squash 2007, only the PMSH and SSVB systems had significantly lower sedge populations th an the WF system. In spring bell pepper 2008, no cropping system had a lower s edge population than the WF system. The SSVB complex system c ontrolled grass weeds better than the simple WF system throughout the experiment; while gr ass weeds increased in the SH system during the second year of the experiment. This suggests that velvetbean cover crop planted in the SH system during the second summer did not effectively suppress grass weeds during the second year. Germination and establishment of the cover crop was poor and some plants succumbed to disease, re sulting in an open canopy. Additionally, the residues of legume cover crops decompose and release nitrogen rapidly (Wagger, 1989). Release of nitrogenous compounds may trigger germination and stimulate emergence of specific weeds (T easdale and Pillai, 2005).

PAGE 114

114 During the two-year experiment, no croppi ng system consistently suppressed broad-leaf weed and sedge populations. Broad-leaf weeds were of different seed sizes with good food reserves. They survived better than grass weeds in the soil (Lewis, 1973) and emerged when the cover crop effects we re completed. Similarly, perennial weeds like sedges were more difficult to control with cover crops than annual weeds because of larger nutritional reserves and faster rate of establishment (Teasdale et al., 2007). Due to stored food materials in t he underground parts, perennial weeds survive in most cropping systems despite efforts to eradicate them (Rao, 2000). Whereas, living mulches in the PMSH and SSVB systems resu lted in lower broad-leaf weed and sedge densities in the fall, bean intercrops failed to effectively suppress weeds in the spring. Brberi and Mazzoncini (2001) found that rye reduced weed biomass by 54 to 99% and crimson clover reduced biomass by 22 to 46% in continuous corn systems. In vegetable production, living mulch suppressed weeds by blocking light for weed seed germination (Lanini et al., 1989, Phatak, 1992), secretion of allelochemicals (White et al., 1989), or by competing with the establishe d weed seedlings (Teasdale, 1998). Weeds within crop rows Grass w eeds. In spring sweet corn 2007, only the SSVB system suppressed grass weeds to a lower level than the WF system (Table 5-15). Grass populations in fall squash 2007 with cover crop systems were eit her not different from that of the WF system or was higher. In sp ring bell pepper 2008, all cover crop systems except the SH system resulted in fewer grass weed populati ons than WF system. The results on the suppression of grass weeds were not cons istent throughout th e experiment; however, the SSVB system appeared to be the most e ffective for grass weed suppression. Beside this, the SH system resulted in more grass weeds than other cover crop systems

PAGE 115

115 during the second year of the experiment. Sunn hemp estimated to fix 72-91% of its total nitrogen in the soil (Seneratne and Ra tnasinghe, 1995; Ladha et al., 1996). Legume cover crops released nitrogenous co mpounds that may have contributed to increased cash crop biomass (Table 5-20). Legume cover crops can provide a considerable amount of nitr ogen and essential nutrients to su cceeding crops (Fageria et al., 2005). In addition, nitrogen also trigger s germination and stim ulates grass weed emegernce (Teasdale and Pillai, 2005). Broad-leaf weeds. In spring sweet corn 2007, no di fference in broad-leaf weed populations was observed among cropping systems (Table 5-16). In 2007-08, no systems had lower broad-leaf weed populations than the WF system in fall squash and spring bell pepper seasons. Sedges. In spring sweet corn 2007, sedge densities were suppressed by SH and PMSH systems to levels lower than the WF system (Table 5-17). In 2007-08, sedge populations were significantly greater in t he WF system than in the SS, SH, and PMSH systems in fall squash 2007. Populations were significantly higher in the WF and SS systems than the VB and SSV B systems during spring bell pepper season. The cropping systems did not suppress br oad-leaf weeds and sedges were not consistently suppressed during the two-year experiment. This suggests that broad-leaf weeds were not impacted by cover crop bioma ss, crop biomass, and light interception. Sedges were not affected by the cash cr op biomass of both fall and spring seasons (Table 5-20). Similarly, no effect of cover crop biomass was noted on the sedge populations in the succeeding fall vegetables (Table 5-17 and 5-20). The differences that occurred in the experiment may be due to the resource competition with the cash

PAGE 116

116 crops as suggested by Teasdale et al. (2007) Perennial weeds like sedges and largeseeded broad-leaf weeds were difficult to cont rol due to their large nutritional reserves, (Mohler, 1996, Teasdale et al., 2007). Weed biomass Betw een beds. In 2006-07, during the summer co ver cropping period, total weed biomass was significantly greater in the WF system than the other cropping systems. This was true also in 2007-08 except fo r the SH system, whic h had even more total weed biomass than the WF system (Table 518). During the cover cropping period in 2007, the final population of velvetbean cover crop was decreased by 83% from the initial planting populati on in the SH system. Due to th is reason, weeds germinated and emerged profusely in this syst em. In fall squash 2007, tota l weed biomass was lower in the PMSH and SSVB systems than systems with sole cover crops, but not different from the WF system. In spring bell pepper, total weed biomass was greater in the SH system as compared to the SS and SSVB systems, but no cropping system was significantly different from the WF system (Table 5-18). Within crop rows In fall broccoli 2006, total weed biomass in all systems was not significantly different from the WF syst em except for the PM SH system, which had lower total weed biomass. In 2007-08, ther e was no difference in total weed biomass among systems in squash and be ll pepper (Table 5-19). Although cover crops suppressed total weed biomass during the cover cropping period, suppression did not persist into t he following fall and spring seasons. Rye-hairy vetch living mulch suppressed total weed biomass between beds in fall squash but crimson clover was ineffective in broccoli. Hence, cover crop biom ass did not impact the total weed biomass in the subsequent vegetables.

PAGE 117

117 Hand weeding. Hand weeding times reflected weed density with no difference among cropping systems on 2 April or 18 April 2007 (Table 5-21). On 30 May 2007, hand weeding time in bell pepper was greater in the WF system than in the SSVB system; however, weeding time for other cropping systems did not differ significantly from that with the WF system. In spring 2008, hand weeding time in bell pepper plots did not differ between cropping systems either on 14 April or 14 May 2008. However, on sweet corn plots, the WF system took greater hand weeding time compared to other cropping systems. Conclusion In experiment I, the SSVB system result ed in fewer grasses, broad-leaf weeds and lower total weed biomass than the WF system between beds, while sedges were fewer in the second year in the SSVB system than in the WF system. Similarly within crop rows, fewer grass weeds and lower total weed biomass occurred in the SSVB system than in the WF system while no di fference was observed in sedge populations. In experiment II, the SSVB system had fe wer grass weeds than the WF system between beds; however, within rows, grass weed density increased in fall in the SSVB system. No differences were observed in between the complex syst ems and WF system in broad-leaf weeds, sedge populati ons and total weed biomass.

PAGE 118

118 Table 5-1. Cropping system treatments used in experiments a 2006-07 2007-08 Cover crop a Fall Spring Cover crops Fall Spring Experiment I Weedy fallow (WF) Squash Bell pepper Weedy Fallow Broccoli Sweet corn Pearl millet (PM) Squash Bell pepper Sorghum sudangrass Broccoli Sweet corn Sorghum-sudangrass (SS) Squash Bell pepper Pearl millet Broccoli Sweet corn Sunn hemp (SH) Squash Bell pepper Velvetbean Broccoli Sweet corn Velvetbean (VB) Squash Bell pepper Sunn hemp Broccoli Sweet corn Pearl millet + Sunn hemp (PMSH) Squash + Rye -hairy vetch Bell pepper + bush beans Sorghum sudangrassVelvetbean Broccoli + crimson clover Sweet corn + bush beans Sorghum-sudangrass + Velvetbean (SSVB) Squash + Ryehairy vetch Bell pepper + bush beans Pearl millet-sunn hemp Broccoli + crimson clover Sweet corn + bush beans Experiment II Weedy fallow (WF) Broccoli Sweet corn Weedy Fallow Squash Bell pepper Pearl millet (PM) Broccoli Sweet corn Sorghum sudangrass Squash Bell pepper Sorghum-sudangrass (SS) Broccoli Sweet corn Pearl millet Squash Bell pepper Sunn hemp (SH) Broccoli Sweet corn Velvetbean Squash Bell pepper Velvetbean (VB) Broccoli Sweet corn Sunn hemp Squash Bell pepper Pearl millet + Sunn hemp (PMSH) Broccoli + crimson clover Sweet corn + bush beans Sorghum sudangrassVelvetbean Squash + Rye -hairy vetch Bell pepper + bush beans Sorghum-sudangrass + Velvetbean (SSVB) Broccoli + crimson clover Sweet corn + bush beans Pearl millet-sunn hemp Squash + rye -hairy vetch Bell pepper + bush beans a For convenience, cropping system treatments are referr ed to in text using summer cover crop name of 2006-07.

PAGE 119

119 Table 5-2. Details of cover crops pl anted in this experiment at Citra, FL Cover crops Botanical name Cultivar Source Seed-rate (kg/ha) Pearl millet Pennisetum glaucum Tifleaf 3 Production Plus, Plainview, TX 4.5 Sorghum-sudangrass Sorghum bicolor x S. bicolor var sudanense Brown Midrib Production Plus, Plainview, TX 7.2 Sunn hemp Crotalaria juncea Unknown Kaufman Seeds, Haven, KS 7.2 Velvetbean Mucuna pruriens var pruriens Georgia Bush Georgia Seed Development Commission, Athens, GA 18.0 Pearl millet sunn hemp 3.0 PM + 3.6 SH Sorghum-sudangrass + Velvetbean 4.8 SS + 12.0 VB

PAGE 120

120 Table 5-3. Influence of cropping system on grass weed population (m-2) between beds in experiment I a Cropping system Cover crop 2006 Squash 2006 Bell pepper 2007 Cover crop 2007 Broccoli 2007 Sweet corn 2008 Weedy fallow 3 ab 6 b 7 ab 11 a 38 a 60 a Pearl millet 1 c 14 a 7 ab 4 bcd 18 bc 7 c Sorghum-sudangrass 2 bc 5 b 5 b 3 cd 14 c 10 c Sunn hemp 3 ab 10 b 6 b 7 b 31 ab 26 b Velvetbean 5 a 14 a 5 b 5 bc 15 c 8 c Pearl millet + Sunn hemp 2 bc 4 bc 10 a 4 bcd 5 d 5 c Sorghum-sudangrass + Velvetbean 2 bc 1 c 5 b 1 d 3 d 5 c a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05 based on [sqrt(x+1)] transformed values. Untransformed means are presented in tables.

PAGE 121

121 Table 5-4. Influence of cropping syst em on broad-leaf weed population (m-2) between beds in experiment I a Cropping system Cover crops 2006 Squash 2006 Bell pepper 2007 Cover crops 2007 Broccoli 2007 Sweet corn 2008 Weedy fallow 19 a 95 ab 16 a 32 b 315 a 16 a Pearl millet 9 b 77 bc 12 ab 19 bc 273 bc 24 a Sorghum-sudangrass 7 b 82 abc 11 ab 22 bc 305 ab 23 a Sunn hemp 19 a 115 a 15 a 59 a 309 a 24 a Velvetbean 8 b 59 cd 4 c 14 c 226 c 3 b Pearl millet + Sunn hemp 9 b 23 e 9 abc 25 bc 60 d 3 b Sorghum-sudangrass + Velvetbean 7 b 37 de 6 bc 12 c 31 d 4 b a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05 based on [sqrt(x+1)] transformed values. Untr ansformed means are presented in tables.

PAGE 122

122 Table 5-5. Influence of croppi ng systems on sedge population (m-2) between beds in experiment I a Cropping system Cover crops 2006 Squash 2006 Bell pepper 2007 Cover crops 2007 Broccoli 2007 Sweet corn 2008 Weedy fallow 9 b 39 bc 2 b 14 ab 75 b 58 a Pearl millet 1 c 42 b 3 b 1 c 28 c 1 b Sorghum-sudangrass 2 c 20 bcd 1 b 2 bc 30 c 2 b Sunn hemp 30 a 87 a 2 b 16 a 116 a 1 b Velvetbean 8 b 29 bc 1 b 1 c 28 c 2 b Pearl millet + Sunn hemp 5 bc 6 d 11 a 2 bc 5 d 1 b Sorghum-sudangrass + Velvetbean 4 bc 14 cd 15 a 6 bc 5 d 1 b a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05 based on [sqrt(x+1)] transformed values. Untr ansformed means are presented in tables.

PAGE 123

123 Table 5-6. Cover crop and crop biomass thr oughout 2-year cropping system in experiment I a 2006-07 2007-08 Cover crops Cover crops 2006 (kg ha-1) Bell pepper 2007 (kg ha-1) Cover crops 2007 (kg ha-1) Broccoli 2007 (kg ha-1) Sweet corn 2008 (kg ha-1) Weedy fallow 457 a 1637 a 2903 a Pearl millet 5240 a 457 a 5960 a 1613 a 3276 a Sorghum-sudangrass 5410 a 506 a 3860 b 1613 a 2978 a Sunn hemp 2530 bc 409 a 3060 b 1637 a 3722 a Velvetbean 1070 cd 409 a 310 c 1613 a 3573 a Pearl millet + Sunn hemp 5010 a 506 a 3830 b 1830 a 3797 a Sorghum-sudangrass + Velvetbean 4880 ab 481 a 3660 b 2137 a 4094 a a Data were means of four replications. Means in column followed by the same letters were not different according to least signif icant difference (LSD) at P 0.05

PAGE 124

124 Table 5-7. Influence of cropping system on grass weed population (m-2) within crop rows in experiment I ab Cropping system Bell pepper 2007 Broccoli 2007 Sweet corn 2008 Weedy fallow 10 a 19 a 54 a Pearl millet 6 ab 7 c 15 c Sorghum sudangrass 4 b 8 bc 14 c Sunn hemp 11 a 16 a 29 b Velvetbean 9 ab 12 ab 10 cd Pearl millet-sunn hemp 7 ab 8 bc 13 c Sorghum-sudangrass + Velvetbean 4 b 8 bc 6 d a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05 based on [sqrt(x+1)] transformed values. Untransformed means are presented in tables. b No weed counts were done in fall squash 2006.

PAGE 125

125 Table 5-8. Influence of cropping syst em on broad-leaf weed population (m-2) within crop rows in experiment I ab Cropping system Bell pepper 2007 Broccoli 2007 Sweet corn 2008 Weedy fallow 16 ab 218 a 35 a Pearl millet 9 b 181 ab 28 ab Sorghum-sudangrass 13 ab 211 ab 30 a Sunn hemp 22 a 170 b 37 a Velvetbean 11 b 207 ab 16 bc Pearl millet + Sunn hemp 11 b 139 c 15 bc Sorghum sudangrassvelvetbean 13 ab 119 c 13 c a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05 based on [sqrt(x+1)] transformed values. Untransformed means are presented in tables. b No weed counts were done in fall squash 2006.

PAGE 126

126 Table 5-9. Influence of cropping system on sedge population (m-2) within crop rows in experiment I ab Cropping system Bell pepper 2007 Broccoli 2007 Sweet corn 2008 Weedy fallow 6 b 42 abc 34 a Pearl millet 3 b 28 bcd 4 b Sorghum-sudangrass 7 b 21 d 3 b Sunn hemp 24 a 51 a 2 b Velvetbean 6 b 25 cd 3 b Pearl millet +Sunn hemp 10 b 38 bcd 3 b Sorghum-sudangrass + Velvetbean 12 b 62 a 4 b a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05 based on [sqrt(x+1)] transformed values. Untransformed means are presented in tables. b No weed counts were done in fall squash 2006.

PAGE 127

127 Table 5-10. Influence of cropping system on total weed biomass (g m-2) between beds in experiment I a Cropping system Cover crop 2006 Squash 2006 Bell pepper 2007 Cover crop 2007 Broccoli 2007 Sweet corn 2008 Weedy fallow 162.8 a 31.0 ab 36.9 ab 134.7 a 36.9 b 52.6 a Pearl millet 1.3 c 31.0 ab 53.0 a 8.0 c 24.0 c 24.0 ab Sorghum-sudangrass 0.6 c 43.0 ab 25.8 bc 4.2 c 49.4 a 25.7 ab Sunn hemp 56.6 b 70.0 a 34.7 ab 77.7 b 22.3 c 18.0 b Velvetbean 43.7 bc 29.0 ab 15.4 bc 7.0 c 27.0 c 8.9 b Pearl millet + Sunn hemp 0.8 c 9.0 b 15.5 bc 20.2 c 8.7 d 36.8 ab Sorghum-sudangrass + Velvetbean 1.6 c 7.0 b 5.5 c 2.8 c 1.6 d 14.2 b a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05.

PAGE 128

128 Table 5-11. Influence of cropping system on total weed biomass (g m-2) within crop rows in experiment I ab Cropping system Squash 2006 Bell pepper 2007 Broccoli 2007 Sweet corn 2008 Weedy fallow 15.8 a 51.9 a 14.6 a 57.0 a Pearl millet 24.0 a 23.0 bc 10.0 ab 7.8 b Sorghum-sudangrass 24.9 a 29.4 b 12.0 ab 28.9 ab Sunn hemp 18.6 a 26.3 b 11.1 ab 27.9 ab Velvetbean 28.1 a 29.1 b 10.0 ab 11.9 b Pearl millet + Sunn hemp 23.5 a 14.1 bc 12.5 ab 29.1 ab Sorghum-sudangrass + Velvetbean 27.4 a 7.7 c 7.3 b 25.7 b a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05. b Cover crop biomass was same in both between beds and within crop rows, presented in Table 5-10

PAGE 129

129 Table 5-12. Influence of cropping system on grass weed population (m-2) between beds in experiment II a Cropping system Cover crop 2006 Broccoli 2006 Sweet corn 2007 Cover crop 2007 Squash 2007 Bell pepper 2008 Weedy fallow 4 ab 9 ab 2 ab 6 b 17 b 97 a Pearl millet 1 b 11 ab 2 ab 4 bc 10 c 30 b Sorghum sudangrass 3 b 8 b 4 a 2 c 8 c 22 b Sunn hemp 2 b 7 b 2 ab 12 a 41 a 75 a Velvetbean 6 a 13 a 3 ab 5 bc 17 b 22 b Pearl millet + Sunn hemp 2 b 7 b 3 ab 5 bc 1 d 27 b Sorghum-sudangrass + Velvetbean 1 b 3 c 1 b 2 c 1 d 20 b a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05 based on [sqrt(x+1)] transformed values. Untr ansformed means are presented in tables.

PAGE 130

130 Table 5-13. Influence of cropping syst em on broad-leaf weed population (m-2) between beds in experiment IIa Cropping system Cover crop 2006 Broccoli 2006 Sweet corn 2007 Cover crop 2007 Squash 2007 Bell pepper 2008 Weedy fallow 12 bc 62 bc 4 b 21 b 154 ab 30 c Pearl millet 5 c 89 ab 5 b 13 b 128 b 17 c Sorghum sudangrass 18 ab 131 a 9 ab 19 b 178 a 31 bc Sunn hemp 27 a 101 ab 36 a 45 a 184 a 33 bc Velvetbean 11 bc 97 ab 5 b 11 b 175 a 14 c Pearl millet-sunn hemp 14 bc 30 cd 7 ab 22 b 38 c 63 a Sorghum-sudangrass + Velvetbean 13 bc 16 d 6 b 21 b 48 c 54 ab a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05 based on [sqrt(x+1)] transformed values. Untr ansformed means are presented in tables.

PAGE 131

131 Table 5-14. Influence of croppi ng system on sedge population (m-2) between beds in experiment IIa Cropping system Cover crop 2006 Broccoli 2006 Sweet corn 2007 Cover crop 2007 Squash 2007 Bell pepper 2008 Weedy fallow 30 a 55 ab 9 a 3 b 53 ab 3 bc Pearl millet 3 b 67 ab 1 a 6 ab 46 ab 1 c Sorghum sudangrass 10 ab 39 ab 2 a 2 b 30 b 3 bc Sunn hemp 9 ab 25 bc 3 a 8 a 18 b 5 abc Velvetbean 38 a 83 a 2 a 3 b 56 a 3 bc Pearl millet + Sunn hemp 1 b 6 d 2 a 5 ab 0 c 9 a Sorghum-sudangrass + Velvetbean 3 b 7 cd 1 a 2 b 1 c 6 ab a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05 based on [sqrt(x+1)] transformed values. Untr ansformed means are presented in tables.

PAGE 132

132 Table 5-15. Influence of cropping system on grass weed population (m-2) within crop rows in experiment II ab Cropping system Sweet corn 2007 Squash 2007 Bell pepper 2008 Weedy fallow 3 abc 9 b 55 a Pearl millet 2 bcd 8 b 24 b Sorghum sudangrass 6 a 9 b 18 bc Sunn hemp 1 cd 25 a 51 a Velvetbean 3 abc 12 b 15 bc Pearl millet + Sunn hemp 4 ab 8 b 19 bc Sorghum-sudangrass + Velvetbean 0 d 9 b 13 c a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05 based on [sqrt(x+1)] transformed values. Untransformed means are presented in tables. b No weed counts were done in fall broccoli 2006.

PAGE 133

133 Table 5-16. Influence of cropping syst em on broad-leaf weed population (m-2) within crop rows in experiment II ab Cropping system Sweet corn 2007 Squash 2007 Bell pepper 2008 Weedy fallow 8 a 142 ab 48 ab Pearl millet 7 a 111 b 44 ab Sorghum-sudangrass 11 a 152 a 45 ab Sunn hemp 18 a 153 a 40 ab Velvetbean 6 a 134 ab 28 b Pearl millet +Sunn hemp 7 a 127 ab 56 a Sorghum-sudangrass + Velvetbean 9 a 154 a 41 ab a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05 based on [sqrt(x+1)] transformed values. Untransformed means are presented in tables. b No weed counts were done in fall broccoli 2006

PAGE 134

134 Table 5-17. Influence of croppi ng systems on sedge population (m-2) within crop rows in experiment II ab Cropping system Sweet corn 2007 Squash 2007 Bell pepper 2008 Weedy fallow 8 a 40 a 11 a Pearl millet 3 ab 23 abc 9 ab Sorghum sudangrass 5 a 18 bc 10 a Sunn hemp 1 b 17 bc 7 ab Velvetbean 3 ab 32 ab 5 b Pearl millet + Sunn hemp 1 b 14 c 9 ab Sorghum-sudangrass + Velvetbean 2 ab 35 ab 5 b a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05 based on [sqrt(x+1)] transformed values. Untransformed means are presented in tables. b No weed counts were done in fall broccoli 2006

PAGE 135

135 Table 5-18. Influence of cropping system on total weed biomass (g m-2) between beds in experiment II a Cropping system Cover crop 2006 Broccoli 2006 Sweet corn 2007 Cover crop 2007 Squash 2007 Bell pepper 2008 Weedy fallow 151.4 a 14.0 a 2.6 a 79.6 b 17.0 b 29.6 ab Pearl millet 2.1 c 11.8 a 11.0 a 3.2 c 34.6 ab 20.2 ab Sorghum sudangrass 4.5 c 22.6 a 8.3 a 3.8 c 27.9 b 15.4 b Sunn hemp 41.5 bc 25.5 a 3.1 a 114.8 a 29.2 b 32.3 a Velvetbean 75.6 b 27.3 a 5.6 a 6.0 c 47.8 a 25.4 ab Pearl millet +Sunn hemp 0.7 c 17.5 a 6.2 a 23.3 c 1.0 c 22.2 ab Sorghum-sudangrass + Velvetbean 3.1 c 20.8 a 6.2 a 5.0 c 3.3 c 15.9 b a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05.

PAGE 136

136 Table 5-19. Influence of cropping system on total weed biomass (g m-2) within crop rows in experiment II ab Cropping system Cover crop 2006b Broccoli 2006 Sweet corn 2007 Cover crop 2007b Squash 2007 Bell pepper 2008 Weedy fallow 151.4 a 14.6 a 2.9 a 79.6 b 15.8 a 30.6 a Pearl millet 2.1 c 12.0 ab 5.1 a 3.2 c 24.9 a 25.2 a Sorghum sudangrass 4.5 c 10.0 ab 4.2 a 3.8 c 24.0 a 18.6 a Sunn hemp 41.5 bc 10.0 ab 4.7 a 114.8 a 28.1 a 27.7 a Velvetbean 75.6 b 11.1 ab 5.7 a 6.0 c 18.6 a 20.3 a Pearl millet + Sunn hemp 0.7 c 7.3 b 7.7 a 23.3 c 27.4 a 31.0 a Sorghum Sudangrass + Velvetbean 3.1 c 12.5 ab 4.4 a 5.0 c 23.5 a 17.2 a a Data were the average of different sampling dates as no interaction was found between cropping systems and observation dates. Means within columns with different letters are statistically different according to least significant difference (LSD) at =0.05. b Cover crop biomass was same in both between beds and within crop rows, presented in table 5-18

PAGE 137

137 Table 5-20. Cover crop and crop biomass throughout the 2-year cropping system in Experiment II a 2006-07 2007-08 Cropping system Cover crop 2006 (kg ha-1) Sweet corn 2007 (kg ha-1) Cover crops 2007 (kg ha-1) Squash 2007 (kg ha-1) Bell pepper 2008 (kg ha-1) Weedy fallow 2360 ab 469 bc 270 b Pearl millet 3860 ab 2620 ab 4140 ab 590 ab 494 a Sorghum-sudangrass 2830 b 2799 a 3070 c 578 ab 402 ab Sunn hemp 3160 b 2799 a 3170 bc 638 a 525 a Velvetbean 720 c 2591 ab 120 d 530 ab 364 ab Pearl millet + Sunn hemp 5100 a 2978 a 4610 a 469 bc 467 a Sorghum-sudangrass + Velvetbean 3360 b 1846 b 3040 c 397 c 445 a a Data were means of four replications. Means in column followed by the same letters were not different according to least significant difference (LSD) at P 0.05

PAGE 138

138 Table 5-21. Hand weeding time (man-hours/ha) at di fferent time intervals in spring 2007 and 2008a Spring 2007 (hours/ha) Spring 2008 (hours/ha) 2 April 2 April 18 April 18 April 30 May 14 April 14 April 14 May Cropping system Sweet corn Bell pepper Sweet corn Bell pepper Bell pepper Sweet corn Bell pepper Bell pepper Weedy fallow 50.9 a a 54.0 a 24.3 a 42.0 a 400.0 a 227.1 a 195.3 a 392.6 a Pearl millet 46.3 a 51.4 a 22.6 a 34.7 a 284.0 ab 96.9 b 152.4 a 396.9 a Sorghum-sudangrass 63.7 a 28.3 a 21.7 a 39.0 a 368.4 ab 103.8 b 125.9 a 200.6 a Sunn hemp 69.4 a 43.7 a 26.0 a 49.2 a 278.3 ab 120.3 b 222.3 a 407.0 a Velvetbean 54.4 a 36.0 a 23.4 a 42.0 a 374.2 ab 101.2 b 128.8 a 394.5 a Pearl millet + Sunn hemp 79.9 a 36.0 a 33.9 a 43.4 a 255.6 ab 102.4 b 164.5 a 378.1 a Sorghum-sudangrass + Velvetbean 49.8 a 36.0 a 25.2 a 31.8 a 242.1 b 67.4 b 178.0 a 286.0 a a Values with the same letters were not different from one another at the 5% level of significance of LSD test

PAGE 139

139 CHAPTER 6 IMPACT OF MULTIPLE CROPPING SYSTEM S ON WEED FLORA SHIFTS AT DIFFERENT SOIL DEPTHS Introduction During the transition from conventional to organic production, farmers are concerned about increases in weed abundance that can lead to a larger seedbank, both of which can reduce yields in the coming ye ars (Albrecht, 2005; Maxwell et al., 2007). A weed seedbank is the product of the past and represents the potential future of the aboveground weed community (S wanton and Booth, 2004). It is the source of future weed infestations in agricultural fields so managing a weed seedbank is a possible alternative to applying herbicides to suppr ess weeds (Bellinder et al., 2004). Greater weed seeds in a seedbank results in great er weed densities, which often requires several years of intensive management to minimize the problem (Kegode et al., 1999; Ekeleme et al., 2003). If not controlled, this may impact the efficacy of weed seedling management (Taylor and Hartzlor, 2000). Becaus e the main source of weed propagules is the weed seedbank, crop yields are a ffected (Cavers and Benoit et al., 1989). Therefore, strategies are needed to manage the weed seedbank to control aboveground weed infestation (Bellinder et al., 2004) because lack of knowledge can result in weeds escaping and producing abundant seeds to replenished the seedbank in the soil (Hanson et al., 2004; Maxwell et al., 2007). Maxwell et al. (2007) described two sali ent features of a weed seedbank: the reservoir of weed seeds already in the so il and the increase in the weed seedbank due to increases in corresponding weed density. If aboveground weed density can be suppressed, weed control will be less of a problem in future crop management. In organic agriculture, growers must use management practices that include crop rotation,

PAGE 140

140 sanitation measures, and cultural practices to prevent weeds (Section 205.206 available at ( www.ecfr.gpoaccess.gov)). Brberi (2002) stresses the need to develop a systemic (holistic) approach to tackle weed problems in organic agriculture. Cropping systems can affect the weed seedbank de nsity and diversity (Menalled et al., 2001; Harbuck et al., 2009) by using div erse crop rotation and introducing cover crops. Cover crops suppress weeds either as living plants or plant residue in the soil (Teasdale et al., 2007) by competing for nutrient resources, alte ring environmental factors for weed germination and establishment, and releasing phytotoxins (Liebman and Davis, 2000). Diverse crop rotations also reduced total weed densit y and increased weed diversity better than simple rotations (Liebman and Dyck, 1993; Liebman and Staver, 2001) While increases in weed species diversity may cause weed infestation problems (Becker and Hurle, 1998), Liebman and Dyck (1993) found that diverse crop ro tations increased evenness in weed species because weeds face greater st ress in diverse rotations due to different management practices. The research reported in this chapter wa s part of larger project focused on an integrated program for suppressing pests in organic vegetable production. Cultural practices such as crop rotation, living cover crops, living mulches, and intercropping were integrated in year-round cropping systems to assess their effects on the weed seedbank at different soil depths. The inform ation will be generated on which system or systems can most effectively reduce weed se ed populations in the soil. The objective was to study the impact of multiple croppi ng systems on different weed species, their richness, diversity, and evenness at different soil depth, and also the systems influence on weed flora shifts at different time intervals in their vert ical distribution in the soil.

PAGE 141

141 Knowledge of weed seed distribution at differ ent soil depths was found to be important for successfully controlling weed seedling emergence (Grundy et al., 1996), as the depth at which weed seeds were buried had an impact on the rates of germination and emergence of weed seeds (Grundy and Mead, 1998). Materials and Methods Two concurrent experiments were established in summer 2006 on certified organic land at the Plant Science Research and Education Unit, Marion County, FL. The field site had been used for the production of bahiagrass ( Paspalum notatum Fluegg) before establishing the experiment. The soil is Candler sand (Hyperthermic, uncoated Lamellic Quartzipsamment; Entisol) with a soil pH of 7.1. The experimental design was a randomized complete block with seven treatments as cropping systems with four replications (Table 6-1). Plots measured 12 m x 12 m and were separated by 12 m alleys. The entire field was first planted with root-knot-nematode-susceptible White Acre southern pea (cowpea; Vigna unguiculata (L.) Walp ) in May 2006 and mowed in July 2006. Finished mushroom compost (Q uincy Farms, Quincy, FL) was applied at 2500 kg/ha through a check drop spreader (Newt on Crouch, Inc., Griffin, GA) followed by incorporating and disking the field to a depth of about 20 cm. Two experiments consisting of summer cover crops and a weedy fallow were started on 27 July 2006. Pearl millet (PM; Pennisetum glaucum (L.) R. Br ) and sorghum-sudangrass (SS; Sorghum bicolor (L.) Moench x S. bicolor (L.) Moench var. sudanense ) were planted at a 17 cm spacing between plants in the ro w and 5 cm soil depth. Sunn hemp (SH; Crotalaria juncea L.) and velvetbean (VB; Mucuna pruriens (L.) DC. var. pruriens ) seeds were broadcast and then covered using a ro ller. Pearl millet-sunn hemp (PMSH) and

PAGE 142

142 sorghum-sudangrass-velvetbean ( SSVB) mixtures were also planted in mixed cover crop plots (Table 6-2). Overhead irrigation wa s used occasionally during the first three days after planting to prom ote germination and establishm ent of the cover crops. Summer cover crops were flail mowed on 2 October 2006 and disked to incorporate into the soil. This was followed by the application of lime (Aglime Sales, Inc., Babson Park, FL) to the entire field at 2500 kg/ha. Fall vegetables were planted in four beds (1.8 m bed-center size) per 12 m long x 7.2 m wide plot. Squash was planted in one experiment while broccoli was transplanted in the other. Rye (Secale cereale L. cv. Wrens Abruzzi; Alachua County Feed and Seed Store, Gainesville, FL) and hairy vetch ( Vicia villosa Roth, cultivar unknown; Adams Briscoe Seed Company, Jackson, GA) were planted between bed-cent er in mixed cover crop squash plots at 48 kg/ha rye and 22 kg/ha hairy vetch. In broccoli, crimson clover ( Trifolium incarnatum L. cv. Dixie; Adams Briscoe Seed Company, Jackson, GA) was planted as a living mulch in between bed-center s in mixed cover crop plots. During the spring season, bush beans (Phaseolus vulgaris L. cv. Bronco untreated, Seedway, Elizabethtown, PA) were intercropped with pepper and strip intercropped with sweet corn in mixed cover crop plots. Before planting the spring vegetables, the field was flailmowed and disked to a depth of 20 cm on 5 March 2007. The details of management practices with respective dates relevant to both fall and spring vegetables are given in Table 6-3. In the second year (2007-08), squash pl ots were rotated with broccoli and bell pepper with sweet corn. Similarly, broccoli plots were rotated with squash and sweet corn with bell pepper. The field was mowed on 6 July 2007 followed by an application of

PAGE 143

143 elemental sulfur (Tiger 90 wit h 90% sulfur, Tiger-Sul Products, Atmore, AL) at 250 kg/ha on 10 July 2007 to lower soil pH. The cover crops were planted on 31 July 2007. Before planting the cover crops, Sulpomag, 0-0-21 N-P2O5-K2O (Diamond R Fertilizer, Winter Garden, FL) was hand applied at 257 kg/ha. The same application rate was repeated after mowing the cover crops. Soil Sample Collection: Seven cover crop-based cropping system s were imposed on various plots and their soil seedbank were monitored before and after completing the experiments. A soil sampler (AMS, Inc., American Falls, ID) with a 5 cm core diameter and 15 cm length was used for this purpose. The length was divi ded into three layers (0-5, 5-10 and, 1015 cm soil depth from the soil surface). Soil samples were collected along both diagonals of each plot (Colbach et al., 2000; Forcella et al., 2003). Seven samples were drawn from one diagonal and six from the other diagonal cove ring a total surface area per plot of 255 cm2. Forcella (1984) used a cumulatively sampled soil surface area of 250 cm2 to estimate seed-banks of i ndividual research plots. In the present work, each 15 cm sample was divided into layers (upper-5 cm, middle-10 cm, and lower-15 cm) and each was stored in a paper bag. Later, these samples were pooled by layers and kept in three 15 cm x 15 cm plastic bedding containers in a greenhouse and surfaced wate red daily. Emerged weed seedlings were identified and counted. When emergence ceased, samples were dried, stirred, and rewatered (Forcella, 1992). Before last stirring samples were chilled at 3-4 C for about 30 days to break dormancy. After chilling, they again were kept in a greenhouse for subsequent emerged weed counting.

PAGE 144

144 Data Analysis: Soil temperatures at a depth of 20 cm were monitored throughout each year using a Watchdog datalogger, Model 100 8k (Spectrum Technologies, Inc. East Plainfield, IL) at 30-minute time intervals. Emerged weeds were identified and count ed on a bi-weekly basis (number per 254.8 cm2) for both experiments. Each experim ent was analyzed separately using a randomized complete block design. Later, annual data were summed, condensed for better interpretation, and divided into th ree groups: grasses, broad-leaf weeds, and sedges. Total weed flora was cataloged by w eed species richness, which consists of the number of weed species per container. T he Shannon diversity index (H) measures diversity in a given area by applying the formula H = pi ln (pi), where pi = the fraction of the total number of individual s in the sample that belongs to species i (Pielou, 1975; Magurran, 1988). Its value usually is found to fall between 1.5 and 3.5 and rarely surpasses 4.5 (Margalef, 1972). Maximum dive rsity (Hmax) can occur in a situation where all species are equally abundant, and the ratio of observed diversity (H) to maximum diversity (Pielou, 1969) can be measured as evenness (E) = H/Hmax. E is constrained between 0 and 1.0, with 1.0 representi ng a situation in which all species were equally abundant (Magurran, 1988). Data were analyzed using GLM (SAS, 2008). Means were separated using least significant difference (LSD) at the 5% level of significance. Interactions between cropping systems, depth, and time were also assessed in both experiments. Means for depth were compared within each experiment by year using least square means (LSMEANS) and PDIFF statements in GLM (SAS, 2008).

PAGE 145

145 Results Soil temperatures under cover crops ranged from < 23 C in September 2006 to > 37 C in August 2007 (Table 6-4). Temper atures under vegetable crops ranged from a low of 9.1 C in winter to a high of 38.7 C in bell pepper in June (Table 6-5). In summer 2006, five weed species a ccounted for more than 50% of the seedbank in both experiments (Table 6-6) ; however, in summer 2009, major weed species presence was less than 50%. This may suggest an increase in the number of weed species in these cropping systems. Digitaria ciliaris (Retz.) Koeler was more prominent in the upper layer (0-5 cm). Chenopodium ambrosioides L., prominent in all layers in summer 2006, became the least represented in summer 2008. Conversely, Linaria canadensis (L.) Chaz., prominent in middle and lower layers in summer 2006, became widespread in all the layers in summer 2008. In 2006, there was no significant difference in weed species distribution in the upper layer in both the experiments (Tables 6-7 and 6-9). Neither were there differences in weed species richness, diversity, or evenness in the upper layer (Tables 6-8 and 610). Similar results were obtained in the middl e layer, except for the sedge population, which increased more in the SH system than in other systems in Experiment I; while weed species richness increased more in the SH than the WF system. In Experiment II, broad-leaf weed density was significantly greater in the SS than the SH system in the middle layer, while diversity and evenness increased more in the WF than the SH system. In the same year, the lowest laye r in Experiment I showed an increase in broad-leaf weeds in the SSVB system and s edges in the SH and WF systems. In the same layer, the SH system showed significa ntly greater weed species richness than the PM and SS systems, while the SSVB system showed greater diversity than the PM

PAGE 146

146 system. In Experiment II, the lowest layer showed no significant difference in weed species distribution, richness, diversit y, or evenness among all cropping systems in summer 2006. In the upper layer in Experiment I, t here was no significant difference among cropping systems in the grass weeds or sedges in summer 2008, but the SS system was associated with a greater increase in broad-leaf weed dens ity than the PMSH system (Table 6-7). Similarly, Shannons ev enness was significantly greater in the WF system than the VB system in the upper layer (Table 6-8). In Experiment II, no significant difference among cropping systems in weed species richness, diversity, or evenness was found in the upper layer (Tables 6-9 and 6-10). In the middle layer in Experiment I, grass weeds were significant ly greater in the VB and PMSH systems than the SS and SSVB systems, while sedge populations significant ly increased in the SH system. In the same layer, no differ ence among cropping systems in weed species richness, diversity, or evenness was found. In Experiment II in the middle layer, no significant difference among weed specie s distribution was found in summer 2008; neither were there differences in weed specie s richness, diversity, or evenness. In the lowest layer in Experiment I, broad-leaf weed density was si gnificantly greater in the SS system than the SSVB system in summer 2008, but no significant difference was found in weed species richness, diversity, or ev enness. In the same layer in Experiment II, broad-leaf weed density was significantly greater in the SH than t he WF system or the PMSH systems in summer 2008. Similarly, Shannons diversity indices and evenness was less in the WF system compared to ot her cropping systems, wit h the exception of the PMSH system.

PAGE 147

147 Discussion Managing a weed seedbank is one approach to weed control (Bellinder et al., 2004). Seedbank depletion is hastened by soil cu ltivation, seed mort ality, and predation (Moonen and Brberi, 2004). Soil cultivation stimulates s eed emergence, which results in more seedbank depletion in tilled soil (Mulugeta and Stoltenberg, 1997). Under tilled conditions, long-term studies show that planting cover crops decreased the weed seedbank density (Moonen and Brber i, 2004). Diversified crop rotation also can alter the weed seedbank community, thus improving weed management results (Bellinder et al., 2004). In our study, the different cropping systems did not result in significant variations in weed seed populations, but interactions bet ween depth and time indicated significant differences in both experiments (Table 6-11). Sedges are perennials and their populations were observed to be markedly greater at the lowest depth (10-15 cm) compared to the upper 5 cm (T able 6-11). This indicates that perennial weeds were more prominent at deeper depths, but differe nces attributable to the presence of multiple cropping systems were not significant for the period from 2006 to 2008 in either experiment (Tables 6-7 and 6-9) Perennial weeds are difficult to control by cover crops because of larger nutritional reserves (T easdale et al., 2007; Akobundu et al., 2000). Due to this, they survive in the early season after cover crop harvesting and incorporating in the field and emerge at later stages of vegetable planting irrespective of the cover crop systems. A good approach fo r controlling perennial weeds is by fragmenting roots or rhizomes by soil cult ivation followed by deep ploughing. This was further followed by planting cover crops (Hkansson, 2003).

PAGE 148

148 In the same study, grass weeds, consi dered annuals, were nearer to the soil surface than the lowest 10-15 cm, which may be due to their small size. There was a significant increase in grass weeds from 2006 to 2008 in the upper layer in all cropping systems, but no significant increase in the middl e or lower layers in either experiment, except for the SS and SSVB system s in the lower layer. This may be due to the small size of grass weeds that have insufficient ener gy to germinate if located more than 5 cm below the soil surface (Mohler and Teasdale, 1993; Teasdale and Abdul-Baki, 1998). In experiment I of year 2008, the results suggest that grass weeds were fewer in the SS and SSVB systems in the middle la yer. Root exudates of Sorghum species may inhibit the growth of annual weeds like Digitaria sanguinalis (L.) Scop. through allelopathy (Einhelling and Souza, 1992; Nimbal,. et al. 1996). Presumably because of their different seed sizes, broad-leaf weed species were observed at all soil depths. Their seedling density increas ed in all cropping systems from 2006 to 2008 at all soil depths in both experiments. The depth at which weed seeds were buried has been found to have an impact on weed seed germination and emergence (Roberts and Feast, 1972; Grundy and Mead, 1998). Broad-leaf weeds survive better in the soil than grass weeds (Lewis 1973) and persi st better than grass when the soil is plowed (Mohler, 1993). In addition, the percent age of seeds that actually germinate and establish depends on other factors, including crop management practices and macroand micro-climate vari ables (Roberts and Ricketts, 1979; Forcella et al., 1997). Also, the presence of germinated weed seeds, if not competitive, may not have an economic affect (Moonen and Brberi, 2004).

PAGE 149

149 Weed species richness, diversity, and ev enness increased significantly in both experiments from 2006 to 2008 (Tables 6-8 and 6-10), except for the SSVB system in Experiment I, which indicated no increase in weed evenness at any soil depth. An increase in weed species diversity and ev enness showed that weed species were distributed evenly, as shown by a decline in the dominant weed species. The SSVB system, despite crop rotation, did not show improved weed species evenness, reflecting the presence of dominant weed species in its plots. Ngouajio and McGiffen (2002) observed an increase in weed species richness in organic farms with lower weed density and biomass. Conclusion We conclude that different cover crops along with crop rotations in multiple cropping systems over a two-year period could not create sufficient pressure to change the weed or weed seed populations, although some differences were observed and reported in the results.

PAGE 150

150 Table 6-1. Cropping system treatments used in experiments a 2006-07 2007-08 Cover crop a Fall Spring Cover crop Fall Spring Experiment I Weedy fallow (WF) Squash Bell pepper Weedy fallow Broccoli Sweet corn Pearl millet (PM) Squash Bell pepper Sorghum-sudangrass Broccoli Sweet corn Sorghum-sudangrass (SS) Squash Bell pepper Pearl millet Broccoli Sweet corn Sunn hemp (SH) Squash Bell pepper Velvetbean Broccoli Sweet corn Velvetbean (VB) Squash Bell pepper Sunn hemp Broccoli Sweet corn Pearl millet + Sunn hemp (PMSH) Squash + ryehairy vetch Bell pepper + bush beans Sorghum-sudangrass + Velvetbean Broccoli + crimson clover Sweet corn + bush beans Sorghum+sudangrass + Velvetbean (SSVB) Squash + ryehairy vetch Bell pepper + bush beans Pearl millet + Sunn hemp Broccoli + crimson clover Sweet corn + bush beans Experiment II Weedy fallow (WF) Broccoli Sweet corn Weedy Fallow Squash Bell pepper Pearl millet (PM) Broccoli Sweet corn Sorghum sudangrass Squash Bell pepper Sorghum-sudangrass (SS) Broccoli Sweet corn Pearl millet Squash Bell pepper Sunn hemp (SH) Broccoli Sweet corn Velvetbean Squash Bell pepper Velvetbean (VB) Broccoli Sweet corn Sunn hemp Squash Bell pepper Pearl millet +Sunn hemp (PMSH) Broccoli + crimson clover Sweet corn + bush beans Sorghum-sudangrass + Velvetbean Squash + rye-hairy vetch Bell pepper + bush beans Sorghum-sudangrass + Velvetbean (SSVB) Broccoli + crimson clover Sweet corn + bush beans Pearl millet + Sunn hemp Squash + rye-hairy vetch Bell pepper + bush beans a For convenience, cropping system treatments are referr ed to in text using summer cover crop name of 2006-07.

PAGE 151

151 Table 6-2. Details of cover crops planted in this experiment at Marion County, FL Cover crops Botanical name Cultivar Source Seed-rate (kg/ha) Pearl millet Pennisetum glaucum Tifleaf 3 Production Plus, Plainview, TX 4.5 Sorghum-sudangrass Sorghum bicolor x S. bicolor var sudanense Brown Midrib Production Plus, Plainview, TX 7.2 Sunn hemp Crotalaria juncea Unknown Kaufman seeds, Haven, KS 7.2 Velvetbean Mucuna pruriens var pruriens Georgia Bush Georgia Seed Development Commission, Athens, GA 18.0 Pearl millet + Sunn hemp 3.0 PM + 3.6 SH Sorghum-sudangrass + Velvetbean 4.8 SS + 12.0 VB

PAGE 152

152 Table 6-3. Management practices with their dates of fall and spring vegetables Crop and crop management 2006-07 2007-08 Squasha NatureSafee (10-2-8 N-P-K) fertilizer applied at 1685 kg/ha as 30-cm band over beds 9 October 2006 9 October 2007 Squash direct seeded as single row per bed with an in-row plant distance of 45 cm 19 October 2006 10 October 2007 Rye-hairy vetch broadcast between beds in mixed cover crop plots 9 November 2006 26 October 2007 Row covers placed to protect from frost 8 December 2006 16-19 November 2007 Broccolib NatureSafee (10-2-8 N-P-K) fertilizer applied at 1976 kg/ha as 30-cm band over beds 25 October 2006 9 October 2007 30-day-old broccoli seedlings were transplanted in double rows per bed with 45 cm planting distance within rows 31 October 2006 16 October 2007 Crimson clover broadcast between beds in mixed cover crop plots at 28 kg/ha 9 November 2006 26 October 2007 Bell Pepperc NatureSafee (10-2-8 N-P-K) fertilizer applied at the rate of 1116 kg/ha 7 March 2007 4 March 2008 45-day-old seedlings transplanted in double rows per bed, 45 cm plant distance in-row. 15 March 2007 13 March 2008 Planting of bush beans in mixed cover crop plots 16 March 2007 14 March 2008 Application of NatureSafe (10-2-8 N-P-K) fertilizer at rate of 1116 kg/ha 10 April 2007 1 April 2008 Hand weeding 2,18 April, 30 May 2007 14 April and 14 May 2008 Sweet Cornd NatureSafee (10-2-8 N-P-K) fertilizer applied at rate of 1116 kg/ha 7 March 2007 4 March 2008 Sweet corn direct-seeded at 76 cm row distance and 18 cm plant distance 12 March 2007 11 March 2008 Bush beans planted in strips (4 rows/strip) arranged alternately with sweet corn 12 March 2007 11 March 2008 Hand weeding 2 and 18 April 2007 14 April 2008 Application of NatureSafe (10-2-8, N-P-K) fertilizer at rate of 1116 kg/ha 10 April 2007 1 April 2008 Biolinkf (0-0-6 N-P-K) applied to bean plants at nozzle rate of 760 ml/min, 50 gal/ha water 29 April 2008 Sodium nitrate (Proboosterg, 10-0-0 N-P-K) applied at 868 kg/ha in response to nitrogen deficiency symptoms. 7 May 2008 a Cucurbita pepo L. cv. Cougar F1 untreated; Harris Seeds, Rochester, NY b Brassica oleracea L. cv. Marathon F1 untreated; Harris Seeds, Rochester, NY c Capsicum annuum L. cv. Red Knight F1 untreated; Johnnys Selected Seeds, Winslow, ME d Zea mays L. cv. Montauk F1 untreated; Johnnys Selected Seeds, Winslow, ME e NatureSafe 10-2-8, N-P2O5-K2O (NatureSafe, Cold Spring, KY) f Potassium fertilizer (Biolink, Westbridge Agricultural Products, CA) g Probooster, North Country Organics, Bradford, VT)

PAGE 153

153 Table 6-4. Maximum and minimum soil temperature (20 cm dept h) during cover crop growing season, 2006 and 2007, at experimental field, Marion County, FL September 2006 August 2007 September 2007 Cover crop Maximum ( C) Minimum ( C) Maximum ( C) Minimum ( C) Maximum ( C) Minimum ( C) Weedy fallow 33.1 22.6 38.7 26.7 36.2 24.2 Pearl millet 27.3 22.7 37.6 26.7 31.1 24.2 Sorghum-sudangrass 29.2 22.7 37.6 27.1 31.1 24.1 Sunn hemp 28.7 22.7 37.2 26.7 33.2 24.2 Velvetbean 33.7 22.7 38.6 25.7 34.7 23.7 Pearl millet + sunn hemp 27.7 22.2 37.1 27.2 30.7 23.7 Sorghum-sudangrass + velvetbean 28.7 21.7 37.1 27.2 32.7 24.2

PAGE 154

154 Table 6-5. Maximum and minimum soil temperature (20 cm depth) during growing season of both fall vegetable crops for both years in experimental field, Marion County, FL 2006-07 2007-08 Experiment I Experiment II Experiment I Experiment II Month Maximum ( C) Minimum ( C) Maximum ( C) Minimum ( C) Maximum ( C) Minimum ( C) Maximum ( C) Minimum ( C) Squash Broccoli Broccoli Squash October 29.7 20.2 29.2 20.7 November 23.7 10.6 24.2 10.6 24.7 13.2 24.7 15.7 December 23.2 10.1 23.2 9.1 23.2 10.6 22.7 11.6 January 24.2 10.6 23.7 11.7 19.7 9.1 20.2 10.1 Bell pepper Sweet corn Sweet corn Bell pepper March 28.7 20.7 27.7 19.7 25.2 15.7 25.2 16.2 April 33.2 14.2 29.7 13.7 30.2 17.2 29.7 17.2 May 34.7 23.2 30.2 13.7 32.2 22.7 33.7 20.7 June 38.7 22.7 35.2 13.7 32.7 26.2 34.7 25.7

PAGE 155

155 Table. 6-6. Major weed species at different soil depths, May 2006 and July 2008 a Cyperus spp. comprised of C. globulosus, and C. strigosus b Gnaphalium spp. comprised of G. pensylvanicum and G. falcatum Season Upper (0-5 cm) % Middle (5-10 cm) % Lower (10-15 cm) % Experiment I: Cover crop-Squash-Bell pepper; Cover crop-Broccoli-Sweet corn Cyperus spp a 27 Cyperus spp a 29 Cyperus spp a 29 Gnaphalium spp b 19 Chenopodium ambrosioides 15 Linaria canadensis 14 Chenopodium ambrosioides 11 Linaria canadensis 12 Chenopodium ambrosioides 13 Digitaria ciliaris 9 Gnaphalium spp b 8 Gnaphalium spp b 12 Summer 2006 Indigofera hirsuta 8 Indigofera hirsuta 8 Cyperus spp a 9 Cyperus spp a 9 Cyperus spp a 9 Gnaphalium pensylvanicum 8 Gnaphalium pensylvanicum 7 Gnaphalium pensylvanicum 8 Digitaria ciliaris 8 Digitaria ciliaris 7 Gnaphalium falcatum 8 Mollugo verticillata 8 Mollugo verticillata 7 Mollugo verticillata 8 Summer 2008 Linaria canadensis 8 Linaria canadensis 7 Linaria canadensis 7 Experiment II: Cover crop-Broccoli-Sweet corn; Cover crop-Squash-Bell pepper Cyperus spp a 23 Cyperus spp a 24 Cyperus spp a 26 Gnaphalium spp b 15 Chenopodium ambrosioides 16 Richardia scabra 13 Chenopodium ambrosioides 13 Linaria canadensis 13 Chenopodium ambrosioides 12 Digitaria ciliaris 13 Indigofera hirsuta 8 Linaria canadensis 11 Summer 2006 Richardia scabra 13 Rumex acetosella 5 Gnaphalium spp b 11 Cyperus spp a 9 Cyperus spp a 10 Cyperus spp a 9 Gnaphalium pensylvanicum 8 Gnaphalium pensylvanicum 7 Gnaphalium pensylvanicum 8 Digitaria ciliaris 8 Gnaphalium falcatum 7 Gnaphalium falcatum 8 Mollugo verticillata 8 Mollugo verticillata 7 Mollugo verticillata 7 Summer 2008 Linaria canadensis 7 Linaria canadensis 7 Linaria canadensis 7

PAGE 156

156 Table 6-7. Weed species populations/255 cm2 at different soil depths in Experim ent I (cover crop-squash-pepper; cover crop-broccoli-sweet corn) Upper (0-5 cm)/ 255 cm2 Middle (5-10 cm) /255 cm2 Lower (10-15 cm) /255 cm2 Cropping system 2006 2008 P-value a 2006 2008 P-value 2006 2008 P-value Grass weeds WF 0.5 a 76.0 a b < 0.0001 0.0 a 5.0 ab 0.6890 1.0 a 3.0 a 0.8728 PM 0.3 a 55.0 a < 0.0001 0.3 a 3.0 ab 0.8257 0.0 a 2.0 a 0.8728 SS 0.3 a 62.3 a < 0.0001 0.0 a 1.0 b 0.9362 0.3 a 2.0 a < 0.0001 SH 0.5 a 62.3 a < 0.0001 0.3 a 4.3 ab 0.7488 0.5 a 2.5 a 0.8728 VB 0.8 a 80.5 a < 0.0001 0.8 a 7.5 a 0.5890 0.3 a 4.5 a 0.7337 PMSH 0.3 a 93.3 a < 0.0001 0.0 a 8.3 a 0.5091 1.0 a 3.0 a 0.8728 SSVB 0.3 a 69.3 a < 0.0001 1.3 a 1.5 b 0.9840 1.3 a 2.8 a < 0.0001 Broad-leaf weeds WF 1.0 a 83.8 ab < 0.0001 1.3 a 63.8 a 0.0006 3.5 ab 58.8 ab 0.0025 PM 1.5 a 92.5 ab < 0.0001 2.0 a 65.8 a 0.0005 1.5 b 34.0 ab 0.0725 SS 2.8 a 121.0 a < 0.0001 5.5 a 80.3 a < 0.0001 1.3 b 65.0 a < 0.0001 SH 3.0 a 81.3 ab < 0.0001 5.3 a 68.8 a 0.0005 7.3 ab 54.3 ab 0.0097 VB 1.3 a 82.8 ab < 0.0001 2.5 a 69.5 a 0.0003 1.5 b 58.3 ab 0.0019 PMSH 1.0 a 53.5 b 0.004 3.0 a 57.5 a 0.0028 1.3 b 49.5 ab 0.0080 SSVB 4.0 a 79.5 ab < 0.0001 5.5 a 45.5 a 0.0274 10.0 a 29.8 b 0.0002 Sedges WF 1.5 a 5.8 a 0.5269 3.3 b 11.3 ab 0.2343 17.5 ab 8.5 a 0.1811 PM 0.8 a 5.0 a 0.5269 4.0 b 6.5 b 0.7096 5.3 bc 6.3 a 0.8816 SS 0.8 a 4.3 a 0.6023 4.0 b 8.8 ab 0.4795 4.8 c 9.5 a 0.9406 SH 2.3 a 5.8 a 0.6023 13.3 a 22.8 a 0.1582 19.3 a 18.3 a 0.8816 VB 3.0 a 2.3 a 0.9110 4.0 b 7.3 b 0.6284 4.8 c 7.0 a 0.7375 PMSH 0.8 a 6.8 a 0.3720 1.8 b 9.0 ab 0.2809 6.8 bc 10.8 a 0.5515 SSVB 2.8 a 7.3 a 0.5029 4.5 b 14.0 ab 0.1582 5.3 bc 17.0 a 0.7658 a P-values are for comparison between years b Means within columns with same letters are not significantly different using LSD test at 5% probability level.

PAGE 157

157 Table 6-8. Weed species richness, diversity, and evenness at different soil depths in Experi ment I (cover crop-squashpepper; cover crop-broccoli-sweet corn) Upper (0-5 cm)/ 255 cm2 Middle (5-10 cm) /255 cm2 Lower (10-15 cm) /255 cm2 Cropping system 2006 2008 P-value a 2006 2008 P-value 2006 2008 P-value Weed species richness WF 1.8 a 13.3 a b < 0.0001 1.8 b 13.0 a < 0.0001 3.0 ab 11.0 a < 0.0001 PM 1.8 a 13.3 a < 0.0001 2.8 ab 12.3 a < 0.0001 1.8 b 10.3 a < 0.0001 SS 2.5 a 13.8 a < 0.0001 3.3 ab 15.5 a < 0.0001 2.0 b 13.0 a < 0.0001 SH 2.0 a 12.5 a < 0.0001 4.5 a 13.0 a < 0.0001 4.8 a 12.5 a < 0.0001 VB 2.0 a 10.8 a < 0.0001 3.0 ab 12.8 a < 0.0001 2.5 ab 10.5 a < 0.0001 PMSH 2.0 a 12.0 a < 0.0001 2.3 ab 13.0 a < 0.0001 2.8 ab 12.3 a < 0.0001 SSVB 3.5 a 10.5 a < 0.0001 3.3 ab 11.5 a < 0.0001 4.3 ab 12.0 a < 0.0001 Shannons diversity index WF 0.27 a 1.82 a < 0.0001 0.49 a 2.15 a < 0.0001 0.40 ab 1.93 a < 0.0001 PM 0.56 a 1.79 a < 0.0001 0.72 a 2.07 a < 0.0001 0.35 b 1.95 a < 0.0001 SS 0.66 a 1.72 a 0.0001 0.74 a 2.09 a < 0.0001 0.48 ab 2.10 a < 0.0001 SH 0.52 a 1.59 a < 0.0001 0.88 a 2.03 a < 0.0001 0.81 ab 2.01 a < 0.0001 VB 0.56 a 1.52 a 0.0004 0.89 a 2.09 a < 0.0001 0.41 ab 1.75 a < 0.0001 PMSH 0.62 a 1.56 a 0.0006 0.64 a 2.13 a < 0.0001 0.58 ab 2.14 a < 0.0001 SSVB 1.15 a 1.68 a 0.0493 1.00 a 1.97 a 0.0004 1.04 a 1.97 a 0.0006 Shannons evenness WF 0.15 a 0.48 a < 0.0001 0.16 a 0.56 a < 0.0001 0.13 a 0.50 a < 0.0001 PM 0.18 a 0.47 ab 0.0003 0.22 a 0.54 a < 0.0001 0.11 a 0.51 a < 0.0001 SS 0.21 a 0.45 ab 0.002 0.23 a 0.55 a < 0.0001 0.15 a 0.55 a < 0.0001 SH 0.16 a 0.41 ab 0.0016 0.27 a 0.53 a 0.0014 0.25 a 0.52 a 0.0008 VB 0.18 a 0.39 b 0.0053 0.28 a 0.55 a 0.0007 0.13 a 0.46 a < 0.0001 PMSH 0.19 a 0.41 ab 0.007 0.20 a 0.55 a < 0.0001 0.18 a 0.56 a < 0.0001 SSVB 0.36 a 0.44 ab 0.3114 0.31 a 0.52 a 0.01 0.32 a 0.52 a 0.0155 a P-values for comparison between years b Means within columns with same letters not significant ly different using LSD test at 5% probability level.

PAGE 158

158 Table 6-9. Weed spec ies populations/254.8 cm2 at different soil depth in Experiment II (cover crop-Br occoli-sweet corncover crop-squash-pepper) Upper (0-5 cm)/ 255 cm2 Middle (5-10 cm) /255 cm2 Lower (10-15 cm) /255 cm2 Cropping system 2006 2008 P-value a 2006 2008 P-value 2006 2008 P-value Grass weeds WF 0.25 a 17.0 a b 0.004 0.25 a 7.3 a 0.2294 0.5 a 5.0 a 0.4392 PM 0.00 a 25.0 a < 0.0001 0.25 a 2.3 a 0.7309 0.25 a 5.0 a 0.4143 SS 0.25 a 16.8 a 0.005 0.50 a 2.8 a 0.6988 0.25 a 3.0 a 0.005 SH 0.25 a 22.0 a 0.0002 0.00 a 9.3 a 0.1128 0.5 a 1.0 a 0.9315 VB 0.00 a 40.3 a < 0.0001 0.00 a 3.0 a 0.6059 0.25 a 1.3 a 0.8634 PMSH 0.50 a 35.5 a < 0.0001 0.75 a 9.3 a 0.1448 0.25 a 5.3 a 0.3902 SSVB 0.50 a 20.0 a 0.0009 0.00 a 2.3 a 0.6988 0.25 a 3.3 a 0.0008 Broad-leaf weeds WF 1.00 a 71.3 a 0.0001 5.50 ab 55.8 a 0.0057 4.25 a 39.8 b 0.0496 PM 1.50 a 69.0 a 0.0002 3.00 ab 56.8 a 0.0031 5.75 a 47.5 ab 0.0212 SS 3.50 a 55.8 a 0.0041 7.00 a 69.8 a 0.0006 3.75 a 62.0 ab 0.0042 SH 0.75 a 87.3 a <0.0001 1.00 b 85.5 a < 0.0001 4.25 a 84.0 a < 0.0001 VB 1.75 a 69.3 a 0.0002 5.75 ab 59.0 a 0.0034 5.50 a 64.0 ab 0.0013 PMSH 2.00 a 69.5 a 0.0002 3.25 ab 49.3 a 0.0112 4.25 a 40.8 b 0.0436 SSVB 0.25 a 54.0 a 0.0031 2.75 ab 48.3 a 0.0121 2.75 a 53.3 ab 0.0048 Sedges WF 0.25 a 5.8 a 0.3779 6.5 a 7.8 a 0.8702 21.25 a 8.5 a 0.9219 PM 0.50 a 5.0 a 0.6473 3.5 a 11.3 a 0.3115 8.00 a 6.3 a 0.0510 SS 0.00 a 4.3 a 0.3958 2.25 a 10.5 a 0.2814 10.00 a 9.5 a 0.6473 SH 1.00 a 5.8 a 0.5564 2.00 a 2.8 a 0.9219 7.00 a 18.3 a 0.7192 VB 0.75 a 2.3 a 0.5785 7.00 a 13.5 a 0.3958 13.5 a 7.0 a 0.7686 PMSH 0.75 a 6.8 a 0.0592 2.75 a 12.3 a 0.2151 3.5 a 10.8 a 0.1609 SSVB 0.75 a 7.3 a 0.6949 3.25 a 12.0 a 0.2534 7.25 a 17.0 a 0.6473 a P-values for comparison between years b Means within columns with same letters not significant ly different using LSD test at 5% probability level.

PAGE 159

159 Table 6-10. Weed species richness, diversity, and evenness at different soil depths in Experiment II (cover crop-broccolisweet corn; cover crop-squash-pepper) Upper (0-5 cm)/255 cm2 Middle (5-10 cm) /255 cm2 Lower (10-15 cm) /255 cm2 Cropping system 2006 2008 P-value a 2006 2008 P-value 2006 2008 P-value Weed species richness WF 1.5 a 13.3 a b < 0.0001 3.8 a 12.8 a < 0.0001 3.5 a 11.2 a < 0.0001 PM 1.0 a 12.3 a < 0.0001 3.5 a 11.8 a < 0.0001 4.0 a 14.3 a < 0.0001 SS 1.8 a 11.8 a < 0.0001 3.5 a 10.5 a < 0.0001 2.8 a 13.3 a < 0.0001 SH 1.3 a 12.5 a < 0.0001 1.3 a 13.8 a < 0.0001 4.0 a 13.8 a < 0.0001 VB 1.8 a 12.0 a < 0.0001 3.8 a 13.2 a < 0.0001 3.0 a 13.5 a < 0.0001 PMSH 1.8 a 12.8 a < 0.0001 4.0 a 12.3 a < 0.0001 3.8 a 12.5 a < 0.0001 SSVB 1.0 a 12.8 a < 0.0001 2.8 a 12.5 a < 0.0001 2.5 a 12.8 a < 0.0001 Shannons diversity index WF 0.35 a 2.02 a < 0.0001 1.15 a 2.04 a 0.0017 0.49 a 1.85 b < 0.0001 PM 0.17 a 1.92 a < 0.0001 0.91 ab 2.00 a < 0.0001 1.03 a 2.10 a 0.0002 SS 0.42 a 1.96 a < 0.0001 0.85 ab 1.87 a 0.0003 0.69 a 2.20 a < 0.0001 SH 0.32 a 1.80 a < 0.0001 0.29 b 2.06 a < 0.0001 0.91 a 2.15 a < 0.0001 VB 0.52 a 1.79 a < 0.0001 0.87 ab 2.06 a < 0.0001 0.45 a 2.15 a < 0.0001 PMSH 0.59 a 1.94 a < 0.0001 1.04 ab 1.98 a 0.0009 1.00 a 2.00 ab 0.0005 SSVB 0.14 a 2.05 a < 0.0001 0.77 ab 2.09 a < 0.0001 0.43 a 2.14 a < 0.0001 Shannons evenness WF 0.11 a 0.53 a < 0.0001 0.36 a 0.53 a 0.0338 0.15 a 0.48 b 0.0001 PM 0.05 a 0.50 a < 0.0001 0.29 ab 0.52 a 0.0052 0.32 a 0.55 a 0.0067 SS 0.13 a 0.51 a < 0.0001 0.27 ab 0.49 a 0.008 0.21 a 0.57 a < 0.0001 SH 0.10 a 0.47 a < 0.0001 0.10 b 0.54 a < 0.0001 0.29 a 0.57 a 0.001 VB 0.16 a 0.47 a 0.0003 0.27 ab 0.54 a 0.0014 0.14 a 0.56 a < 0.0001 PMSH 0.18 a 0.51 a 0.0001 0.32 ab 0.52 a 0.0215 0.31 a 0.52 ab 0.0123 SSVB 0.04 a 0.54 a < 0.0001 0.24 ab 0.55 a 0.0003 0.13 a 0.56 a < 0.0001 a P-values are for comparison between years b Means within columns with same letters are not significantly different using LSD test at 5% probability level.

PAGE 160

160 Table 6-11. Comparison of weed species density/255 cm2 in summer 2006 and summer 2008, in both experiments a Upper (0-5 cm) Middle (5-10 cm) Lower (10-15 cm) Weed Species 2006 2008 P-value b 2006 2008 P-value b 2006 2008 P-value b Experiment I Grasses 1 71 < 0.0001 1 4 0.3972 1 3 0.6391 BLW 2 85 < 0.0001 4 64 < 0.0001 4 50 < 0.0001 Sedges 2 5 0.1563 5 11 0.0125 9 11 0.4392 Experiment II Grasses 1 25 < 0.0001 1 5 0.027 1 3 0.1633 BLW 2 68 < 0.0001 4 60 < 0.0001 4 56 < 0.0001 Sedges 1 7 0.0346 4 10 0.2513 10 16 0.0346 a Significant interaction between depth and time of weed species noted in both experiments b P-value for comparison between weed species counts in 2006 and 2008

PAGE 161

161 CHAPTER 7 IMPACT OF CROPPING SYSTEM COMPLEXITY ON THE POPULATION DYNAMICS OF SOUTHERN CRABGRA SS AND FLORID A PUSLEY IN ORGANIC VEGETABLE PRODUCTION UNDER NORTH FLORIDA CONDITIONS Introduction Weeds have been recognized as a major c onstraint for suppressing yield in organic production (Penfold et al., 1995; Walz 1999). In crop fields, increases in weed abundance may lead to increases in the weed seedbank, which ultimately affect the quality and productivity of subsequent crops. The availability of herbicides is limited in organic vegetable production; however, weed control in vegetables is an essential practice to sustain crop yield (Grundy et al., 1999). A systemic or holistic approach to weed management is needed in organic agricul ture (Brberi, 2002), but requires a thorough understanding of the dynamics of t he weed populations. The National Organic Program advoc ates a systems approach to pest management and requires the use of cultural practices to manage pests and diseases (CFR 205.206, USDA, 2009 available at (www.ec fr.gpoaccess.gov)). Cultural practices such as crop rotation with diverse crops, cover crops during fallow periods, living mulches and intercropping can be used in cropping systems for managing weeds. Diverse crop rotation with different planting dates, crop growth habits, and cultivation equipment can cause stress and increase we ed mortality (Liebman and Dyck, 1993). Cover crops can reduce the weed seedbank dire ctly by occupying space and resources otherwise used by weeds; while killing cover crops terminates weed growth before mature seeds are set (Gallandt, 2006). Cove r crops also suppress weeds by crop-weed competition, allelopathy, and alteration in soil environment (Creamer and Baldwin, 2000). Intercropping can also increase ecologic al diversity and crop competitive ability

PAGE 162

162 against weeds, thereby depriving weeds by light, water, and nutrients (Liebman and Dyck, 1993). The study of the population dynamics of weeds may facilitate the prediction of their populations, which will be helpful for planning future managem ent strategies. The regulation of weed populations could become an important ob jective for future weed management programs using cover crops (Teasdale et al., 2007). However, the analysis of a weed population is complex as the weed of in terest competes with other weed species at different functional stages of the cropping systems under different management practices and weather condi tions (Fernandez-Quintanilla, 1988). This chapter explores the population dynamics of southern crabgrass ( Digitaria ciliaris (Retz.) Koel) and Florida pusley ( Richardia scabra L). Both weeds were prominent in the field and the seedbank studies These weeds were also identified as the most common weeds in Florida, and s outhern crabgrass is also considered one of the most troublesome weeds of Florida (Dowler, 1999). Florida pusley is a summer annual propagated by seeds and is found abundantly in cultivated fields throughout the southern United States (Biswas et al., 1975). Seeds failed to germinate under dark conditions or a constant temperature of less than 15 C and greater than 40 C; however germination improves if ex posed for more than two hours of light every day (Biswas et al., 1975) Florida pusley seedlings failed to emerge if seeds were located at soil depths gr eater than 1.5 cm (Biswas et al., 1975). Southern crabgrass is summer annual and is propagated by seeds (Holm et al., 1977). It is a prolific seed producer and a single plant may produce up to 188,000 seeds (Peters and Dunn, 1971). Crabgrass have the abili ty to tolerate mowing (Kin et al.,

PAGE 163

163 2002), and physical disturbance associated with cropping system s favors invasion of crabgrass species due to a light requirement for germination (Toole and Toole, 1941). Crabgrass can tolerate hot, dry conditions in summer due to C4 photosynthetic pathway (Danneberger, 1993). Due to its physiology, crabgrass occurs in almost every cropping system throughout the United States (Danneberger, 1993). The objective of the study was to ev aluate the effect of cropping system complexity on the population dynamics of southern crabgrass and Florida pusley in organic vegetable cropping systems. The corresponding hypothesis was that cropping system complexity will affe ct the population dynamics of the southern crabgrass and Florida pusley. Materials and Methods A field experiment was established in summer 2006 on certified organic land at the University of Florida-Plant Science Research and Education Unit, Marion County, Florida. The field site was dominated by bahiagrass ( Paspalum notatum Flgge.) before establishing the experiment. The soil type c onsists of Candler sand (Hyperthermic, uncoated Lamellic Quartzipsamments; entisol) with a pH of 7.1. The field was first planted with White Acre southern pea ( Vigna unguiculata (L.) Walp) in May 2006 and mowed in July 2006. The experiment was st arted on 27 July 2006 with the planting of summer cover crops or a summer weedy fallow. Treatments consisted of seven cropping systems that were arranged in a randomized complete block design with 4 replications (Table 7-1). The plot size was 12 m x 12 m while distance between the plots was 12 m. Pearl millet (PM) and sor ghum sudangrass (SS) were planted in rows spaced 17 cm apart and at 5 cm soil depth. Sunn hemp (SH) was planted using an18-cm row

PAGE 164

164 spacing and velvetbean (VB) seeds were broadcasted followed by covering with soil. A mixture of pearl millet-sunn hemp (PMSH) and sorghum sudangra ss-velveteban (SSVB) were also planted in mixed cover crop plots. Their seed rates, cultivar, and sources are provided in Table 7-2. Overhead irrigation wa s used occasionally during the first three days after planting to promot e germination and establishment of the cover crops. Fall vegetables were planted on four beds (1.8 m wide) per plot (12 m length x 7.2 m width plot size). Before planting sp ring bell pepper, the field was flail-mowed and disked to a depth of 20 cm on March 05, 2007. The details of management practices with respective dates for both fall and spring v egetables are given in Table 7-3. In the second year (2007-08), broccoli was used as the fall vegetable with sweet corn as the spring vegetable (Fig.7-1). Collection of Soil Samples Soil samples were collected before the beginning of the experiment, one year after, and at the end of the experiment using a sampler 5 cm in diameter and 15 cm in length (AMS, Inc., American Fall s ID). Samples were divided into 3 layers (0-5 cm as upper, 5-10 cm as middle, and 10 -15 cm as lower layer fr om the soil surface). Soil samples were collected along both diagonal of each plot (Colbach et al., 2000; Forcella et al., 2003) resulting in a total surface area of 255 cm2 per plot. Greenhouse Weed Seedbank Study Collected soil samples for each plot were pooled by layers and placed in a 15by 15-cm plastic bedding containers in a gr eenhouse and surfaced water daily. Emerged weed seedlings were identified and count ed on every 2 weeks. Following weed identification and density data colle ction, samples were allowed to air-dry. Soil was then stirred, and moistened as described above. This pattern was repeated until no more

PAGE 165

165 weeds emerged. Samples were then chill ed at 3-4 C for about 30 days to break dormancy. After chilling, they were kept again in the greenhouse to allow emergence of weeds released from dormancy. Field Weed Density Study Weed dens ity data were collected for both co ver crops and vegetables. In cover crop plots, weeds were counted and sampl ed at 30 and 60 days after planting cover crops, using 1 m2 quadrats randomly placed in the co ver crop plots. For fall and spring vegetables, weeds were counted in 0.25 m2 quadrats placed randomly in two locations per plot. In vegetables, weeds were counted at 2, 4, 6, and 9 weeks after planting the vegetable crops. Data Analysis The number of emerged weed seedlings and seed bank populations from all blocks were added together since there wa s no significant block effect. The relationships between rainfall and air tem perature and the emergence rate and the mortality rate of weed seedlings were det ermined to assess the environmental effects. They were done using the REG procedure of St atistical Analysis System software (SAS, 2008). The models of both weed species were generated using Python software version 2.3.5 available at www.python.org (Python Software Foundation, Hampton, New Hampshire). Using these data, population trends, emergence rate, and mortality rate were determined for the various cropping sy stems. Climate Maximum and minim um air temperatures were monitored at 30 cm above the soil surface using a Watchdog datalogger, Model 100 8k (Spectrum Technologies, Inc., East

PAGE 166

166 Plainfield, IL) at 30-minute time intervals while rainfall data were obtained from the Florida Automated Weather Network ( www.fawn.ifas.ufl.edu). Seedbank The seedbank was divided into three soil layers of 5 cm each from the soil surface because it was anticipated that s eed movement would occ ur as a result of tillage. Weed seeds that came from outside of the experiment plot with tillage equipment were also included in the model. Tillage Any field operation that dist urbs the soil can be included in the model as a factor that kills seedlings or stimulate germinati on (Debaek e and Sebillotte, 1988; Holst et al., 2007). Soil tillage is a field operation that redistributes seeds d among soil layers according to depth and type of cultivation (Aarts, 1986; Holst et al., 2007). The main impact of tillage is to move soil and seeds, wh ich affects vertical seed distribution in the soil profile (Colbach et al., 2005). In this experiment, tillage operations were performed at 2, 11, 24, 45, 58, 70, and 115 weeks after beginning the experiment with soil movement occurring within t he top 20-25 cm of soil. Tillage factor The tillag e factor was calc ulated as the mean percent difference of the proportion of weed seeds in the upper and lower layers. Seed mortality Mortality rate includes the disappearanc e of weeds due to age, competition, diseases, and predators within a specified time. Mortality rate was calculated by: Mortality = (Nt-Nt+1)/Nt, where Nt = Number of weeds at time t.

PAGE 167

167 Emergence rate The emergence rate (proportion of seeds germinated during a two week period) was calculated based on observed numbers of new seedlings, and estimated numbers of seeds in the upper soil. The emergence ra te increased with daily temperature and was delayed with increasing seed depth in Abutilon theophrasti Medicus (Forcella, 1993). In the field, seed germination was tr iggered by several events, which include tillage under moist conditions and sufficient rain to leach all existing water-soluble germination-inhibiting substances within t he seeds (Colbach et al., 2005). Seedling emergence rates were linked to soil tillage, without using environmental conditions (Colbach et al., 2005). Southern Crabgrass Model To study the population dynamics of southern crabgrass, a model has been developed into three equations. Figure 7-2 shows the diagrammatic representation of the model. In the first equati on, weed seedlings that germi nated in the field with cover crops and vegetables were selected as: X1 = [X1 + (emergence rate. X2) (mortality rate. X1)] where X1 is the weed seedlings germinat ed in the field; and X2 denotes weed seedlings that emerged from the 0-5 cm soil layer (Fig. 2). In the second equation, weed seed from upper (0-5 cm) seedbank was calculated as X2=[X2 (emergence rate. X2) + (till age factor. X3) + seeds from outside through tillage] where X3 represents weed seedlings emerged from the 1015 cm soil depth. This equation is adjusted for additional seeds brought into the treated plots through

PAGE 168

168 tillage. The third equation comprised of w eed seedlings emerged from the 10-15 cm soil depth and were represented by the equation, X3=[X3 (tillage factor. X3)] Tillage factor was analyzed by compari ng weed seedling proportions at lower and upper depths. Florida Pusley Model For Florida pusley, the model was changed d ue to increases in the seeds in both upper and lower layers over time (Fig. 7-2). Ti llage factor of both upper and lower layers were included in the equations. The first equati on is similar to that of southern crabgrass model equation. In the second equation, Flor ida pusley seeds from the upper layer of the seedbank were calculated as: X2=((X2. tillage factor )-emergence rate. X2) X2=X2 (emergence rate. X2). Similarly, equation three was also modified as: X3 = (tillage factor in lower layer. X3) Results and Discussion Maximum and minimum air temperatures and rainfall were measured in all of the cropping seasons. Maximum temperatures r anged from 26.9 to 39.6 C while minimum temperature ranged from -2.4 to 18.6 C (Figure 7-3). Rain fall was greatest at the end of the cover cropping period in late summer as well as in during fall. Less rainfall occurred during spring in both the year s. These environmental parameters (temperature, moisture) were found to be important for w eed seed growth and development (Holst et al., 2007). Weather conditions can pl ay a pivotal role in the validity of a model (Mo rtimer et al., 1989).

PAGE 169

169 In southern crabgrass, there was no re lationship between emergence rate and maximum and minimum temperature (P>0. 2003; P>0.0696), and rainfall (P>0.3761). Similarly, no relationship was observed between mortality rate and maximum and minimum temperature (P>0.2932; P> 0.1270) and rainfall (P>0.7576). Therefore, both temperature and rainfall were removed from the model equations. In Florida pusley, there was no relationship between em ergence rate and maximum and minimum temperature (P>0.06; P>0.0648) and rainfall (P>0.356). Sim ilarly, no relationship was observed between mortality rate and maxi mum and minimum temperature (P>0.5632; P>0.3165) and rainfall (P>0.5448). The model was evaluated with the help of field emergence and mortality pattern Holst et al. (2007) indicated that models can help to provide guidelines for practical weed management and predictions in specific scenarios. They can be useful tools for making weed management decisions (Jordan et al., 1995). However, models are difficult to validate because of the scarcity of long-term data seri es (Mortimer et al., 1989; Freckleton and Stephens, 2009). Model par ameters were estimated through the experimental data and simulat ed in the Python software. Simulations Southern crabgrass Seven simulations representing sev en cropping systems were ru n on southern crabgrass model in the Python software (Appendix A). It started with the values obtained from seedbank as well as field experi ment. The simulation runs for 128 weeks. The effect of tillage was noticed on soil laye rs and plant population in the field. From simulation results, X1 increased considerably in all of the cropping systems. Similarly, X2 also increased in the predicted populatio n dynamics while X3 decreased in all the

PAGE 170

170 cropping systems (Figures 7-4; 7-5; 7-6; 7-7; 78; 7-9; 7-10). These simulated results predict that the effect of va rious cultural practices were not sufficient to decrease southern crabgrass seedlings and seeds in the upper layer in all of the cropping systems; however, germinated seedlings were destroyed by tillage. Tillage should be done with an aim to bury the majority of weed seeds t oo deeply for emergence under dry conditions to avoid stimulating germi nation (Colbach et al., 2005). These results suggest that complex systems did not differ from the simple system in suppressing seedlings of southern crabgrass and there is a need to include other management tactics to increase seedling mortality in these organic vegetable systems. Florida pusley There were no Florida pusley seeds in the weed seedbank prior to the beginning of the experiment. Therefore, data of the second year (200708) were used to predict population dynamics of this weed (Append ix B). Tillage factor of both upper and lower layers were included in the model equations. The simulation predicts that Florida pusley seeds in the lower layer will decrease one year after completing the experiment in SH and WF systems (Fig. 7-12 and 7-17). Seedling emergence rate was linked to soil tillage, without using environmental conditions (Colbach et al., 2005). Tilling operations can move weed seeds from one soil layer to another burying the weed seeds or by transferring seeds from the lower layers back to the surface. Seeds in the lower layer in both complex systems increased as compared to the simple WF system (Fig. 7-15 and 7-16). Germinated seedlings and seed bank populations in the upper layer decreased with cultural management practices in all of the cropping systems; however, reduction in PM and SH systems (Fig. 7-11 and 7-12) were lower (> 128 weeks) than other cropping systems (90-100 weeks) (Fig. 713; 7-14). This suggests t hat Florida pusley population

PAGE 171

171 may decrease in all the cropping systems and t here is no difference between simple WF and complex systems. Several studies found higher densities of grass weeds in reduced tillage systems while broad-leaf weeds were higher with conventional tillage (Froud-Williams et al., 1983). Since broad-leaf weeds tend to survive better in the soil than grass weeds (Lewis 1973), they may be able to persist better than grasses when the soil is plowed (Mohler, 1993). Model description Sensitiv ity of the model was measured by the resulting change in model output as it helps in identifying the most influentia l parameter used in the model (Holst et al., 2007). To explore the sensitivity of the mode l, the parameter values were reduced by 50% and also increased by 50%. A large val ue of sensitivity indicates that a small variation in the parameters will result in large modification in the model output. Southern crabgrass A 50 % increase in the emergence rate increased southern crabgrass seedlings in the field by 26% and reduced seed population by 40% at 5 cm from the soi l surface (Table 7-4). Similarly, a decrease in the emergence rate by 50% reduced emerged seedlings in the field by 36% but increas ed the seed population by 93% in the upper 5 cm of soil. An increase in the mortality rate by 50% reduced marginally both emerged seedlings and southern crabgra ss seed populations in the upper 5 cm soil layer (Table 7-4). There was no effect on seedling and seed populations with a decrease of the mortality rate. This may suggest that increas ed mortality rates improve weed control in these types of systems. Hence, there is a need to improve management tactics to increase mortality rate for controlling souther n crabgrass. Roush et al. (1989) suggested

PAGE 172

172 minimizing emergence rate to decrease seedbank size by the use of management practices such as planting cover crops. In addition, deeper plowing also buries weed seeds too deeply to reduce their successful germination (Aldrich, 1984). Effect of cover crop syst ems relative to WF system suggests that emerged southern crabgrass seedlings were fewer in num bers (< 1) in all cover crop systems as compared to the WF system (Table 7-5). However, southern crabgrass seed populations in the upper 5 cm soil layer were higher in all cover crop systems than in the WF system, except in the SH system where seed populations lower by 5% than in the WF system. The results suggest that living cover crops may suppress seedling populations of southern crabgrass in the field; however, southern crabgrass seed populations increase in the upper 5 cm soil layer in all systems except for the SH system. Florida pusley A 50% increase in the emergence rate decreased the Florida pus ley seed populations by 72% in the upper 5 cm so il layer (Table 7-6). This may be due to intraspecific competition between Florida pu sley plants. Increase or decrease of mortality rate may not effect the Florida pusley seedlings or seed populations in the soil. Increase or decrease of tillage factor may reduce the numbers of Florida pusley seeds in the upper 5 cm soil layer. Effect of simulated cover crop systems rela tive to WF system indicated that the numbers of Florida pusley seeds in the upper 5 cm soil layer were fewer in all cover crop systems as compared to the WF system except for the PM and SH systems (Table 7-7). In the PM and SH systems, seed numbers increased, respectively, to 29% and 14% more than that of the WF system, (T able 7-7). Similarly, seed populations in

PAGE 173

173 the lower 10-15 cm soil layer were higher in all cover crop systems than in the WF system. The results suggest that Florida pusle y seed populations were not affected by the mortality rate or decrease of emergence rate. However, tillage factor affected their numbers in both upper 0-5 cm and lower 10-15 cm soil layers. Cultural management practices increased Florida pusley seed populati ons in the lower 10-15 cm soil layer but reduced seed numbers in the upper 5 cm soil, except in the PM and SH systems. Conclusion No difference was observed between complex and simple systems for suppressing the populations of both sout hern crabgrass and Florida pusley; however, long-term data may improve the simulated re sults of the populati on dynamics of these weed species.

PAGE 174

174 Table 7-1. Cropping system treatments used in experiments a 2006-07 2007-08 Cover crops a Fall Spring Cover crops Fall Spring Experiment I Weedy Fallow (WF) Squash Bell pepper Weedy Fallow Broccoli Sweet corn Pearl millet (PM) Squash Bell pepper Sorghum sudangrass Broccoli Sweet corn Sorghum sudangrass (SS) Squash Bell pepper Pearl millet Broccoli Sweet corn Sunn hemp (SH) Squash Bell pepper Velvetbean Broccoli Sweet corn Velvetbean (VB) Squash Bell pepper Sunn hemp Broccoli Sweet corn Pearl millet-sunn hemp (PMSH) Squash + Rye -hairy vetch Bell pepper + bush beans Sorghum sudangrassvelvetbean Broccoli + crimson clover Sweet corn + bush beans Sorghum sudangrassvelvetbean (SSVB) Squash + Rye -hairy vetch Bell pepper + bush beans Pearl millet-sunn hemp Broccoli + crimson clover Sweet corn + bush beans a For convenience, cropping system treatments are referr ed to in text using summer cover crop name of 2006-07.

PAGE 175

175 Table 7-2. Cover crop treatments planted in this experiment at Citra, Florida Cover crops Botanical name Cultivar Source Seed-rate (kg/ha) Weedy Fallow Pearl millet Pennisetum glaucum Tifleaf 3 Production Plus, Plainview, TX 4.5 Sorghum sudangrass Sorghum bicolor x S. bicolor var sudanense Brown Midrib Production Plus, Plainview, TX 7.2 Sunn hemp Crotalaria juncea Unknown Kaufman Seeds, Haven, KS 7.2 Velvetbean Mucuna pruriens var pruriens Georgia Bush Georgia Seed Development Commission, Athens, GA 18.0 Pearl millet sunn hemp 3.0 PM + 3.6 SH Sorghum sudangrass velvetbean 4.8 SS + 12.0 VB

PAGE 176

176 Table 7-3. Management practices with their dates of the cropping system from 2006 to 2008 at Citra, FL Management practices including tilling operations Dates Soil samples were collected from the plots at 3 different soil depths 2-4 May 2006 Field was tilled to a depth of 25 cm for planting southern pea 17 May 2006 Finished mushroom compost a applied at 2500 kg/ha followed by discing to a depth of about 20 cm. 13 July 2006 Planting summer cover crops 27 July 2006 Mowing cover crops followed by incorporating into the soil to a depth of 25 cm 2 October 2006 NatureSafe b (10-2-8 N-P2O5 -K2O) fertilizer applied at 1685 kg/ha as 30-cm band over beds 9 October 2006 Squash direct seeded as single row per bed with an in-row plant distance of 45 cm 19 October 2006 Ryed-hairy vetche broadcast in between beds in mixed cover crop plots at the rate of 48 kg and 22 kg /ha 9 November 2006 Row covers placed to protect from frost 8 December 2006 Squashc was harvested between the following dates 14 December 2006 9 January 2007 Field was mowed and field were disced with a depth of 25 cm soil depth. 5 March 2007 NatureSafe (10-2-8 N-P2O5 -K2O) fertilizer applied at the rate of 1116 kg/ha 7 March 2007 45-day-old bell pepper seedlings transplanted in double rows per bed, 45 cm plant distance within row. 15 March 2007 Planting of bush beansg in mixed cover crop plots 16 March 2007 Application of NatureSafe (10-2-8 N-P2O5 -K2O) fertilizer at rate of 1116 kg/ha 10 April 2007 Hand weeding 2,18 April, 30 May 2007 Bell pepperf harvested between the following dates, four harvests total 21 May 20 June 2007 Soil samples were collected again from the plots at 3 different soil depths 3 July 2007 Field was tilled at 20 cm soil depth along with the applications of elemental sulfuri at 250 kg/ha and sulpomagj at the rate of 257 kg/ha. This was followed by application of finished mushroom compost at 2500 kg/ha 10-25 July 2007 Cover crops were planted again 31 July 2007 Mowing of cover crops followed by applying sulpomag at 257 kg/ha 3-9 October 2007 NatureSafe (10-2-8 N-P2O5-K2O) fertilizer applied at 1976 kg/ha as 30-cm band over beds. 9 October 2007 Thirty-day-old broccoli seedlings transplanted in double rows per bed with 45 cm planting distance within rows 16 October 2007 Crimson cloverh broadcast in between beds in mixed cover crop plots at 28 kg/ha 26 October 2007 Broccoli harvested between the following dates, 3 harvests total 20 December2007 -2 January 2008 Broccoli plots were mowed, discing, and tilling the plots at a depth of 25 cm 4 March 2008 NatureSafe (10-2-8 N-P2O5-K2O) fertilizer applied at the rate of 1116 kg/ha 4 March 2008 Sweet cornl direct-seeded at 76 cm row distance and 18 cm plant distance 11 March 2008 Bush bean direct seeded in strips (4 rows/strip) arranged alternately with strips of sweet corn in mixed cover crop plots. 11 March 2008

PAGE 177

177 Table 7-3. Continued Application of NatureSafe (10-2-8 N-P2O5-K2O) fertilizer at rate of 1116 kg/ha 1 April 2008 Hand weeding 14 April 2008 Biolinkm (0-0-6 N-P2O5 -K2O applied over bean plants at nozzle rate of 760 ml/min and 50 gal/ha water 29 April 2008 Sodium nitrate (Probooster n, 10-0-0 N-P2O5 -K2O) applied at 868 kg/ha in response to nitrogen deficiency symptoms 7 May 2008 Sweet corn harvested between the following dates, 2 harvests total 29 May -4 June 2008 Soil samples collected at 3 different soil depths after completing the experiments 23 June 2008 a Quincy Farms, Quincy, FL b Griffin Industries, Cold Spring, KY c Cucurbita pepo L. cv. Cougar F1 untreated; Harris Seeds, Rochester, NY d Secale cereale cv Wrens Abruzzi; Alachua County Feed and Seeds, Gainesville, FL e Vicia villosa, cultivar unknown; Adams Briscoe Seed Company, Jackson, GA f Capsicum annuum L. cv. Red Knight F1 untreated; Johnnys Selected Seeds, Winslow, ME g Phaseolus vulgaris cultivar Bronco untreated, Seedway Elizabethtown, PA h Trifolium incarnatum cv Dixie; Adams Briscoe Seed Company, Jackson, GA i Tiger 90 with 90% sulfur, Tiger-Sul Products, Atmore, AL j N-P2O5-K2O (0-0-21), Diamond R Fertilizer, Winter Garden, FL k Brassica oleracea L. cv. Marathon F1 untreated; Harris Seeds, Rochester, NY l Zea mays L. cv. Montauk F1 untreated; Johnnys Selected Seeds, Winslow, ME m Westbridge Agricultural Products, Vista, CA n North Country Organics, Bradford, VT

PAGE 178

178 Figure 7-1. Multiple cropping systems in organic vegetable production in Experiment Squash Bell pepper Single legume or grass covercrops Broccoli Sweet corn Grass-Legume cover cropsmixtures Bell pepper + Bush bean Squash+ Rye-hairy vetch Sweet corn + Bush bean Broccoli + crimson clover No cover crop Sweet corn Broccoli No cover crop Bell pepper Squash SIMPLE Single Grass or legume cover crops INTERMEDIATE Grass-Legume cover crops mixtures COMPLEX Summer 2006 Fall 2006 Spring 2007 Soil sample collection for weed seedbank studies Summer 2007 Spring 2008 Fall 2007

PAGE 179

179 Figure 7-2. Diagrammatic model showing weed seedbank and seedling levels of sout hern crabgrass and Florida pusley Weed Seedlings or germinated seeds X1 Seeds from 0-5cm layer below soil surface X2 Seeds from 10-15 cm layer below soil surface X3 Tillage Seeds from outside the plots through crop management Seedling emergence Seedling mortality Environmental factors Temperature Rainfall

PAGE 180

180 -5.0 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 CC06Fall06Spring07CC07Fall07Spring08Cropping season and yearsTemperature (0C)-2 0 2 4 6 8 10 12 14 16Rainfall (cm) Max Temp Min Temp Rainfall Figure 7-3. Maximum and minimum air temperatures and rainfa ll in the experiment field during the cropping season (CC=Cover crops)

PAGE 181

181 Figure 7-4. Simulation of germinated seedlings and seed bank populations of southern crabgrass dynamics in the PM cropping system (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) layer)

PAGE 182

182 Figure 7-5. Simulation of germinated seedlings and seed bank populations of southern crabgrass dynamics in the SH cropping system (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) layer)

PAGE 183

183 Figure 7-6. Simulation of germinated seedlings and seed bank populations of southern crabgrass dynamics in the SS cropping system (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) layer. Number of seedlings was in 10000 /m2 on Y-axis)

PAGE 184

184 Figure 7-7. Simulation of germinated seedlings and seed bank populations of southern crabgrass dynamics in the SSVB cropping system (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) layer. Number of seedlings was in 10000 /m2 on Y-axis)

PAGE 185

185 Figure 7-8. Simulation of germinated seedlings and seed bank populations of southern crabgrass dynamics in the VB cropping system (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) laye r. Number of seedlings was in 10000 /m2 on Y-axis)

PAGE 186

186 Figure 7-9. Simulation of germinated seedlings and seed bank populations of southern crabgrass dynamics in the PMSH croppi ng system (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) layer. Number of seedlings was in 10000 /m2 on Y-axis

PAGE 187

187 Figure 7-10. Simulation of germinated seedl ings and seed bank popul ations of southern crabgrass dynamics in the WF cropping system (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) layer)

PAGE 188

188 Figure 7-11. Simulation of germinated seedlings and seed bank populations of Florida Pusley dynamics in the PM cropping system (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) layer)

PAGE 189

189 Figure 7-12. Simulation of germinated seedlings and seed bank populations of Florida Pusley dynamics in the SH cropping system (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) layer)

PAGE 190

190 Figure 7-13. Simulation of germinated seedlings and seed bank populations of Florida Pusley dynamics in the SS cropping system (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) layer)

PAGE 191

191 Figure 7-14. Simulation of germinated seedlings and seed bank populations of Florida Pusley dynamics in the VB cropping system (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) layer)

PAGE 192

192 Figure 7-15. Simulation of germinated seedlings and seed bank populations of Florida Pusley dynamics in the PMSH cropping system (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) layer)

PAGE 193

193 Figure 7-16. Simulation of germinated seedlings and seed bank populations of Florida Pusley dynamics in the SSVB cropping system (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) layer)

PAGE 194

194 Figure 7-17. Simulation of germinated seedlings and seed bank populations of Florida Pusley dynamics in the WF cropping system (X1= Weed seedlings in the field; X2= Seed bank population in the upper (0-5 cm) layer; X3= Seed bank population in the lower (10-15 cm) layer)

PAGE 195

195 Table 7-4. Effect of increasing or decreasing model parameters on t he ratio of final state variable numbers relative to unaltered state variable of southern crabgrass after 128 weeks Ratio relative to unaltered parameters Parameters X1 X2 X3 50% increase Emergence rate 1.269 0.608 NA Mortality rate 0.992 0.999 NA Tillage factor 1.00 0.999 NA 50% decrease Emergence rate 0.639 1.933 NA Mortality rate 1.00 1.00 NA Tillage factor 1.00 1.00 NA X1 = Seedling emerged in the field X2 = Seed population in upper soil layer (0-5 cm) X3 = Seed population in lower soil layer (10-15 cm) NA = Not applicable Table 7-5. Simulated cover crop systems effe ct on numbers relative to the WF system of germinated seedlings of sout hern crabgrass after 128 weeks Ratio relative of cover crop systems by WF system Variables PM SS SH VB PMSH SSVB X1 0.471 0.301 0.598 0.482 0.507 0.607 X2 1.109 1.907 0.949 2.217 2.901 1.702 X3 NA NA NA NA NA NA X1 = Seedling emerged in the field X2 = Seed population in upper soil layer (0-5 cm) X3 = Seed population in lower soil layer (10-15 cm) NA = Not applicable

PAGE 196

196 Table 7-6. Effect of increasing or decreasing model parameters on t he ratio of final state variable numbers relative to unaltered state variable of Florida pusley after 128 weeks Ratio relative to unaltered parameters Parameters X1 X2 X3 50% increase Emergence rate NA 0.285 1.0 Mortality rate NA 1.0 1.0 Tillage factor-Upper layer NA 0.428 1.0 Tillage factor-lower layer NA 1.0 3.5 50 % decrease Emergence rate NA NA 1.0 Mortality rate NA 1.0 1.0 Tillage factor-Upper layer NA 0.571 1.0 Tillage factor-lower layer NA 1.0 0.125 X1 = Seedling emerged in the field X2 = Seed population in upper soil layer (0-5 cm) X3 = Seed population in lower soil layer (10-15 cm) NA = Not applicable Table 7-7. Simulated cover crop systems effe ct on numbers relative to WF system of germinated seedlings of Florida pusley after 128 weeks Ratio relative of cover crop systems by WF system Variables PM SS SH VB PMSH SSVB X1 NA NA NA NA NA NA X2 1.285 0.286 1.143 0.0 0.857 0.714 X3 10.87 60.37 8.312 3.625 27.81 12.75 X1 = Seedling emerged in the field X2 = Seed population in upper soil layer (0-5 cm) X3 = Seed population in lower soil layer (10-15 cm) NA = Not applicable

PAGE 197

197 APPENDIX A SOUTHERN CRABGRASS PROGRAM from pylab import mr=0.0058 # mortality rate er=0.023 # emergence rate tr=0.65 # tillage factor ot=2903 # no. of outsi de seeds x1=0 # initial values x2=10 x3=30 tillflag=0 time_tillage =[2, 11,24,45,58,70,115] fintime=128#weeks x1t=[] x2t=[] x3t=[] for t in range(fintime): try: if t == time_tillage[tillflag]: print t tillflag=tillflag+1 x2=(tr*x3)+x2+ot x3=x3-(tr*x3) x1=x1+(er*x2)-(mr*x1) except: pass x2=x2-(er*x2) x1t.append(x1) x2t.append(x2) x3t.append(x3) plot(x1t, linewidth=3) plot(x2t, linewidth=3) plot(x3t, linewidth=3) print 'x1t', x1t print 'x2t', x2t print 'x3t', x3t legend(('x1', 'x2', 'x3')) xlabel('weeks', fontsize=16) ax = axes() xlabels = ax.get_xticklabels() ylabels = ax.get_yticklabels() for xl in xlabels:

PAGE 198

198 xl.get_fontsize() xl.set_fontsize(14) for yl in ylabels: yl.get_fontsize() yl.set_fontsize(14) ylabel(r'$\rm {Number\ of\ seedlings \ (m}\ ^-^2)$', fontsize=16) title ('Crabgrass in WF system', fontsize=16) show()

PAGE 199

199 APPENDIX B FLORIDA PUSLEY PROGRAM from pylab import mr=0.13 # mortality ra te er=0.27 # emergence rate tf=1.38 # tillage factor tf3 = 0.57 # tf1 ot=87 # no. of outside s eeds as add upper+lower x1=12 # initial values AFTER 58 WEEKS x2=20 x3=89 tillflag=0 time_tillage =[58,70,115] # weeks fintime=128#weeks x1t=[] x2t=[] x3t=[] tim = [] print time_tillage print time_tillage[0] for t in range(58,fintime): if tillflag < len(time_till age) and t == time_tillage[tillflag]: print t tillf lag=tillflag+1 x2=((x2*tf)-er*x2) x3=tf3*x3 x1=x1+(er*x2)-(mr*x1) x1 = x1 + er*x2 mr*x1 x2 = x2 er*x2 x1t.append(x1) x2t.append(x2) x3t.append(x3) tim.append(t) plot(tim,x1t, 'k', linewidth=2) plot(tim,x2t, '--k', linewidth=2) plot(tim,x3t, 'k', linewidth=3) print 'x1t', x1t print 'x2t', x2t print 'x3t', x3t legend(('x1', 'x2', 'x3'))

PAGE 200

200 xlabel('weeks', fontsize=16) ax = axes() xlabels = ax.get_xticklabels() ylabels = ax.get_yticklabels() for xl in xlabels: xl.get_fontsize() xl.set_fontsize(14) for yl in ylabels: yl.get_fontsize() yl.set_fontsize(14) ylabel(r'$\rm {Number\ of\ seedlings \ (m}\ ^-^2)$', fontsize=16) title ('Florida Pusley in WF system', fontsize=16) show()

PAGE 201

201 APPENDIX C NATIONAL ORGANIC PROGRAM Sections of Final rule referred to i n the dissertation. Available at: www.ecfr.gpoaccess.gov. 205.206 Crop pest, weed, and dis ease management practice standard. (a) The producer must use management prac tices to prevent crop pests, weeds, and diseases including but not limited to: (1) Crop rotation and soil and crop nutrient management practices, as provided for in .203 and 205.205; (2) Sanitation measures to remove dis ease vectors, weed seeds, and habitat for pest organisms; and (3) Cultural practices that enhance crop health, including selection of plant species and varieties with regard to suit ability to site-specific conditions and resistance to prevalent pests, weeds, and diseases. (b) Pest problems may be controlled through mechanical or physical methods including but not limited to: (1) Augmentation or introduction of predator s or parasites of the pest species; (2) Development of habitat fo r natural enemies of pests; (3) Nonsynthetic controls such as lures, traps, and repellents. (c) Weed problems may be controlled through: (1) Mulching with fully biodegradable materials; (2) Mowing; (3) Livestock grazing; (4) Hand weeding and mechanical cultivation;

PAGE 202

202 (5) Flame, heat, or electrical means; or (6) Plastic or other synthetic mulches: Pr ovided, That, they are removed from the field at the end of the gr owing or harvest season. (d) Disease problems may be controlled through: (1) Management practices which suppress the spread of disease organisms; or (2) Application of nonsynthetic biologi cal, botanical, or mineral inputs. (e) When the practices provided for in paragraphs (a) through (d) of this section are insufficient to prevent or control crop pests, weeds, and diseases, a biological or botanical substance or a substance includ ed on the National List of synthetic substances allowed for use in organic crop production may be applied to prevent, suppress, or control pests, weeds, or diseas es: Provided, That, the conditions for using the substance are documented in the organic system plan. (f) The producer must not use lumber treated with arsenate or other prohibited materials for new installations or replacement pur poses in contact with soil or livestock.

PAGE 203

203 LIST OF REFERENCES Aarts, H.F.M. 1986. A com puterized model for predicting changes in a populat ion of Galium aparine. Pages 277-284 in Proceedings of European Weed Research Society Symposium. Economic weed control, Stuttgart, Germany. Aguiar, J.L., W.A. Williams, W. L. Graves, M. McGiffen, J.V. Samons, J.D. Ehlers, and W.C. Mathews Jr. 2001. Fact ors for estimating nitrogen contribution of cowpea as a cover crop. Journal of Ag ronomy and Crop Science 186: 145-149. Akanvou, R., L. Bastiaans, M.J. Kroprr, J. Goudriaan, and M. Becker. 2001. Characterization of growth, nitrogen accumu lation and competitive ability of six tropical legumes for potential use in intercropping systems. Journal of Agronomy and Crop Sciences 187:111-120. Akobundu, I.O., U.E. Udensi, and D. Chikoye. 2000. Velvetbean suppresses speargrass and increases maize yield. Internati onal Journal of Pest Management. 46:103108. Albrecht, H. 2005. Development of arable weed seedbanks during the 6 years after the change from conventional to organic fa rming. Weed Research 45: 339-350. Aldrich, R.J. 1984. Weed Crop Ecol ogy. Breton, North Scituate, MA. Altieri, M.A., and D. K. Letourneau. 1982. Vegetati on management and biological control in agroecosystems. Crop Protection 1: 405-430. Altieri, M.A. 1994. Biodiversity and pest management in agroecosystems. Haworth Press Binghamton, NY. Altieri, M.A. 1995. Toward sustainable agric ulture. Pages 367-379 in M.A. Altieri, ed. Agroecology-The Science of Sustainable Agriculture, Boulder, CO, Westview Press. Amankwa, G.A., A.D. White, T.W. McDowell, and D.L. Van Hooren. 2006. Pearl millet as a rotation crop with flue cured tobacco for control of root-lesion nematodes in Ontario. Canadian Journal of Plant Science 86:1265-1271. Ammon, H.U., S. Garibay, and C. Bohren. 1995. The use of dead or living mulch in maize and its suppression with herbicides. In 9th EWRS Symposium Challenges for weed science in a changing Europe, Budapest, pp. 527-534. Angonin, C. J.P., Caussanel, and J.M. Meynard. 1996. Compet ition between winter wheat and Veronica hederifolia : Influence of weed density and the amount and timing of nitrogen application. Weed Research 36:175-187.

PAGE 204

204 Ball-Coelho, B., A.J. Brui n, R.C. Roy, and E. Riga. 2003. Forage pearl millet and marigold as rotation crops for biological control of root-lesion nematodes in potato. Agronomy J ournal 95:282-292. Brberi, P.2002. Weed m anagement in organic agriculture : are we addressing the right issue? Weed Research 42:177-193. Brberi, P., and M. Mazzoncin i. 2001. Changes in weed community composition as influenced by cover crop and management system in continuous corn. Weed Science 49:491-499. Barlow, C.A., P.A. Randolph, and J.C. Randolph. 1977. Effect of pea aphids (Homoptera: Aphididae) on growth and productivity of pea plants. Canadian Entomologist 109:1491-1502. Baumann, D.T, M.J. Kropff, and L. Basti aans. 2000. Intercropping leeks to suppress weeds. Weed Research 40:359 -374. Beaudoin, A.L.P, N.D. Kahn, and G.G. K ennedy. 2009. Bell and banana pepper exhibit mature-plant resistance to tomato spotted wilt tospovirus transmitted by Frankliniella fusca (Thysanoptera: Thripidae). Jour nal of Economic Entomology 102:30-35. Becker, B., and K. Hurle. 1998. Unkrautflor a auf Feldern mit unt erschiedlich langer kologischer Bewirtschaftung. Zeit schrift fr Pflanzenkrankheiten und Pflanzenschutz (Sonderheft) 16: 155-161. Belair, G., N. Dauphinais, Y. Fournier, O.P Dangi, and M. Ciotola. 2006. Effect of 3year rotation sequences and pearl millet on population densities of Pratylenchus penetrans and subsequent potato yield. Canadi an Journal of Plant Pathology 28:230-235. Bellinder, R.R., H.R. Dillard, and D.A. Shah. 2004. Weed seedbank community responses to crop rotation schemes. Crop Protection 23:95-101. Benbrook, C.M. 1996. Pest management at the crossroads. Consumers Union, Yonkers, NY, USA. Biswas, P.K., P.D. Bell, J.L. Crayton, and K.B. Paul. 1975. Germination behavior of Florida pusley seeds I. Effects of storage, light, temperature, and planting depths on germination. Weed Science 23:400-403. Blumenthal, M. 2007. Presi dent of Global Organic. Glob al Organic, Sarasota, FL. Available at [ http://www.global-organi cs.com/about/whats.html] Brown, J.K., D.R. Frohlich, and R.C. Rosell. 1995. The sweetpotato or silverleaf whiteflies :biotypes of Bemisia tabaci or a species complex? Annual Review of Entomology 40:511-534.

PAGE 205

205 Bugg, R.L., F.L. Wckers, K.E. Brunson, J. D. Dutcher, and S.C. Phatak. 1991. Coolseason cover crops relay intercropped wit h cantaloupe: influence on a general predator, Geocoris punctipes (Hemiptera: Lygaeidae). Journal of Economic Entomology 84:408-416. Bugg, R.L., and C. Waddington. 1994. Using cover crops to manage arthropod pests of orchards: A review. Agriculture, Ecosystems and Enviro nment 50:11-28. Buhler, D.D., M. Liebman, and J.J. Obrycki. 2000. Theoretical and practical challenges to an IPM approach to weed man agement. Weed Science 48:274. Buntin, G.D., D.A. Gilbertz and R.D. Oetting. 1993. Chlo rophyll loss and gas exchange in tomato leaves after feeding injury by Bemisia tabaci (Homoptera: Aleyrodidae). Journal of Economic Entomology 86:517-522. Byrne, D.N., and T.S. Bellows, Jr. 1991. Whitefly biology. Annual Review of Entomology 36:431-457. Byrne, D.N., and W. B. Miller. 1990. Car bohydrate and amino acid composition of phloem sap and honeydew produced by Bemisia tabaci. Journal of Insect Physiology 36:433-439. Carmona, D.M., and D.A. Landis. 1999. Influence of refuge habitats and cover crops on seasonal activity-density of ground beetle s (Coleoptera: Carabidae) in field crops. Biological C ontrol 28:1145-1153. Carter, W.W. 1982. Influence of soil temperature on Meloidogyne incognita resistant and susceptible cotton, Gossypium hirsutum Journal of Nematology 14:343-346. Cavers, P.B., and D.L. Benoit. 1989. Seed banks in arable land. Pp. 309-328 in: Ecology of Soil Seedbanks, V.T.P.M.A. Leck and R.L. Simpson (eds.). San Diego, CA: Academic Press. Chamberlin, J.R., J.W. Todd, R.J. Beshear, A.K. Culbreath, and J.W. Demski. 1992. Overwintering hosts and wingform of thrips, Frankliniella spp in Georgia (Thysanoptera, Thripidae) Implications for management of spotted wilt disease. Environmental Entomology 21:121-128. Chancellor, R.J. 1964. The dept h of weed seed germination in the field. Pages 607-613 in Proceedings Seventh British Weed C ontrol Conference, Brighton, UK. Chapman, A.V., T.P. Kuhar, P.B. Schultz, T.W. Leslie, S.J. Eleischer, G.P. Dively, and J. Whalen. 2009. Integrati ng chemical and biological control of European corn borer in bell pepper. Journal of Ec onomic Entomology 102: 287-295. Chase, C.A., and O.S. Mbuya. 2008. Greater interference from living mulches than weeds in organic broccoli production. Weed Technology 22:280-285.

PAGE 206

206 Cherr, C.M., J.M.S. Schol berg, and R. McSorley. 2006. Green manure approaches to crop production: a synthesis. Agronomy Journal 98:302-319. Clark, A. 2007. Managing cover crop profitably, Third edition, Sustainable Agriculture Network handbook series book 9, Beltsville, MD, Page 106. Colbach, N., F. Dessaint, and F. Forcella. 2000. Evaluating field-scale sampling methods for the estimation of mean plant densities of weeds. Weed Research 40:411-430. Colbach, N., C. Drr, J. Roger-Estrade, and J. Caneill. 2005. How to model the effects of farming practices on weed emer gence. Weed Research 45: 2-17. Collard, A. 2003. Modelling of the long-term effects of cropping systems on the population dynamics of weeds. Page 20 in : Crop-weed interactions in Proceedings of the fourth workshop of European Weed Research Society working group. April 10-12, 2003, Viterbo, Italy. Collins, A.S. 2004. Leguminous cover crops fallows for the suppression of weeds. University of Florida, Gainesville, MS Thesis. Available at: www.etd.fcla.edu/UF/UFE0007018/collins_a.pdf. Costello, M.J., and M.A. Altieri. 1995. A bundance, growth rate and parasitism of Brevicoryne brassicae and Myzus persicae (Homoptera:Aphididae) on broccoli grown in living mulches. Agricultur e Ecosystem and Environment 52:187-196. Coombe, P.E. 1982. Visual behav ior of the greenhouse whitefly, Trialeurodes vaporariorum Physiological Entomology 7:243-51. Cousens, R. 1987. Theory and reality of w eed control thresholds. Plant Protection Quarterly 2, 13-20. Cousens, R. and M. Mortimer.1995. Dy namics of weed populations. Cambridge University Press, UK. Creamer, N.G., M.A. Bennett, B. R. Stinner, and J. Cardina. 1996. A comparison of four processing tomato production systems differing in cover crop and chemical inputs. Journal of American Society fo r Horticultural Science 121:559-568. Creamer, N.G., M.A. Bennett, and B.R. Stinner. 1997. Evaluati on of cover crop mixtures for use in vegetable production systems. HortScience 32:866-870. Creamer, N.G., and K.R. Baldwin. 2000. An evaluation of summer cover crops for use in vegetable production systems in North Carolina. HortScience 35:600-603. Crow, W.T., D.P. Weingartner, D.W. Dickson, and R. McSorley 2001. Effect of sorghum sudangrass and velvetbean cover crops on plant-parasitic nematodes associated with potato production in Fl orida. Journal of Nematology 33:285-288.

PAGE 207

207 Danneberger, T.K. 1993. Turfgrass ecology and management. Cleveland, Ohio: G.I.E. Publishers. PP. 201. Dauphinais, N., G. Belair, Y. Fournier, and O. P. Dangi. 2005. Effect of crop rotation with grain pearl millet on Pratylenchus penetrans and subsequent potato yields in Quebec. Phytoprotection 86:195-199. Debaeke, P. and M. Sebillotte. 1988. Modelin g the long-term evolution of the weed flora. I. Evolution of the seed bank in the cultivated layer. Agronomie 8:393-403. den Hollander, N,G., L. Basti aans, and M.J. Kropff. 2007. Clover as a cover crop for weed suppression in an intercropping design I. Characteristics of several clover species. European Journal of Agronomy 26:92-103. Dowler, C. 1999. Weed survey-southern st ates. Proceedings of the Southern Weed Science Society 52: 280. Duke, S.O., F.E. Dayan, J. G. Romagni, and A.M. Rimando. 2000. Natural products as a sources of herbicides: cu rrent status and future tr ends. Weed Research 40:99111. Einhellig, F.A. and I.F. Souza. 1992. Phytotoxicity of sorgoleone found in grain sorghum root exudates. Journal of Chemical Ecology 18:1-11. Ekeleme, F., I.O. Akobundu, A.O. Isichei, and D. Chikoye. 2003. Cover crops reduce weed seedbanks in maize-cassava system s in southwestern Nigeria. Weed Science 51:774-780. Fageria, N.K., V.C. Baligar, and B.A. Bailey. 2005. Role of cover crops in improving soil and low crop productivity. Communications in Soil Science and Plant Analysis 36: 2733-2757. Fernandez-Quintanilla, C. 1988. Studying the population dynamics of weeds. Weed Research 28:443-447. Finn, E. 2003. Developing in tegrated pest management (IPM) techniques for managing key insect pests of blueberries in s outheastern United States. MS Thesis, Department of Entomology and Nematology, University of Florida, Gainesville, FL. Florida Agriculture Statistical Directory. 2008. Florida Departmen t of Agriculture and Consumer Services. Available at: http://www.nass.usda.gov/fl/. Forcella, F. 1984. A species-area curve for buried viable seeds. Australian Journal of Agricultural Research 35: 645-652. Forcella, F. 1992. Prediction of weed seedl ing densities from bur ied seed reserves Weed Research 32:29-38.

PAGE 208

208 Forcella, F. 1993. Seedling emergence model for velvetleaf. Agronomy Journal 85:929933. Forcella, F., R.G. Wilson, and J. Dekke r. 1997. Weed seedbank emergence across the corn belt. Weed Science 45:67-76. Forcella, F., T. Webster, and J. Card ina. 2003. Protocols for weed seed bank determination in agro-ecosystems. Weed Management for Developing Countries, Addendum 1, Chapter 1, R. Labrada, ed. Rome: F.A.O. Forney, D.R., C.L. Foy, and D.D. Wol f. 1985. Weed suppression in no-till alfalfa ( Medicago sativa ) by prior cropping of summer annual forage grasses. Weed Science 33:490-497. Frank, D.L., and O.E. Liburd. 2005. Effects of living and synthetic mulch on the population dynamics of whit eflies and aphids, their asso ciated natural enemies, and insect-transmitted plant diseases in zucchini. Environmental Entomology 34: 857-865. Frantz, G and H.C. Melli nger. 2009. Shifts in western flower thrips, Frankliniella occidentalis (Thysanoptera: Thripidae) population abundance and crop damage. Florida Entomologist 92: 29-34. Freckleton, R.P. and P.A. Stephens. 2009. Predictive models of weed population dynamics. Weed Research 49:225-232. Froud-Williams, R.J., D.S.H. Drennan, and R.J. Chancellor. 1983. Influence of cultivation regime on weed floras of ar able cropping systems. Journal of Applied Ecology 20:187-197. Fuchsberg, J.R., T.H. Yong, J.E. Losey, M.E. Carter, and M.P. Hoffmann. 2007. Evaluation of corn leaf aphid ( Rhopalosiphum maidis ; Homoptera:Aphididae) honeydew as a food source for the egg parasitoid Trichogramma ostriniae (Hymenoptea:Trichogrammatidae). Biol ogical control 40: 230-236. Gallandt, E.R. 2006. How can we target weed seedbank? Weed Science 54:588-596. Gaskell,M., and R. Smith. 2007. Nitrogen so urces for organic vegetable crops. HortTechnology 17:431-441. Geier, B. 1998. The organic market-oppor tunities and challenges. ILEIA Newsletter 14:6-7. Gold, C.S., M.A. Altieri, and A.C. Bellotti. 1989. Effects of intercrop competition and differential herbivore numbers on cassa va growth and yields. Agriculture Ecosystem and Environment 26:131-146.

PAGE 209

209 Greene, C., and A. Kremen. 2003. U.S. Organic Farming in 2000-2001: Adoption of Certified Systems. Agri culture Information Bulletin No. 780, USDA, Economic Research Service, April. Griffin, T., M. Liebman, and J. Jemison Jr. 2000. Cover crop (rye, hairy vetch and alfalfa) as alternate source of nitr ogen for subsequent sweet corn. Agronomy Journal 92: 144-151. Gross, H.R., and J.E. Carpent er. 1991. Role of fall army worm (Lepidoptera:Noctuidae) and other factors in the capture of bumblebees (Hymenoptera:Apidae) by Universal moth traps. Environm ental Entomology 20:377-381. Grundy, A.C., A. Mead, and W. Bond. 1996 Modelling the effect of weed-seed distribution in the soil profile on s eedling emergence. Weed Research 36:375384. Grundy, A.C., and A. Mead. 1998. Modelling the effects of seed depth on weed seedling emergence. Aspects of Applied Biology 51: 71-82. Grundy, A.C., A. Mead, and S. Bu rston. 1999. Modelling the effect of cultivation on seed movement with application to the prediction of w eed seedling emergence. Journal of Applied Ecology 36: 663-678. Hkansson, S. 2003. Weeds and weed m anagement on arable land: An ecological approach. CABI Publishing, Wal lingford, Oxon, UK, Pp. 274. Hall, D.O., and K.K. Rao. 1995. Photosynthesis (5th ed.), Cambridge: Cambridge University Press, UK. Halbrendt, J.M. 1996. Allelopathy in the management of plant-parasitic nematodes. Journal of Nematology 28:8-14. Hallmann, J., A. Frankenberg, A. Paffr ath, and H. Schmidt. 2007. Occurrence and importance of plant-parasitic nematodes in organic farming in Germany. Nematology 9:869-879. Hanson, J., R. Dismukes, W. Chambers, C. Greene, and A. Kremen. 2004. Risk and risk management in organic agriculture: Views of organic farmers. Renewable Agriculture and Food S ystems 19: 218-227. Harbuck, K.S.B., F. D. Menalled, and F. W. Pollnac. 2009. Impact of cropping systems on the weed seedbanks in the northern Gr eat Plains, USA. Weed Biology and Management 9:160-168. Harrison, H.F., D.M. Jackson, A.P. Keinath, P.C. Marino, and T. Pullaro. 2004. Broccoli production in cowpea, soybean, and velvetbean cover crop mulches. HortTechnology 14:484-487.

PAGE 210

210 Hoelmer, K.A., W.J. Roltsch, C.C. Chu, and T.J. Henneberry. 1998. Selectivity of whitefly traps in cotton for Eretmocerus eremicus (Hymenoptera: Aphelinidae), a native parasitoid of Bemisia argentifolli (Homoptera: Aleyrodidae). Environmental Entomology 27:1039-1044. Holm, L.G., D.L. Plucknett, J.V. Pancho, and J.P. Herberger. 1977. The Worlds Worst Weeds-Distribution and Biol ogy. Honolulu, HI: The Ea st-West Food Institute. Holst, N., I.A. Rasmussen, and L. Basti aans. 2007. Field weed population dynamics: a review of model approaches and applic ations. Weed Research 47:1-14. Hooks, C.R.R., H.R. Valenzuela, and J. De frank. 1998. Incidence of pest and arthropod natural enemies in zucchini grown in liv ing mulches. Agriculture Ecosystem and Environment 69:217. Irrizarry, H., W.R. Jenkins, and N.F. Childers. 1971. Interaction of soil temperature and Meloidogyne spp. on resistance of the common bean, Phaseolus vulgaris L. to the root-knot disease. Nematropica 1:41-42. Isik, D., E. Kaya, M. Ngouajio, and H. Mennan. 2009a. Weed suppression in organic pepper ( Capsicum annum L.) with winter cover crops. Crop Protection 28:356363. Isik, D., E. Kaya, M. Ngouajio, and H. Mennan. 2009b. Summer cover crops for weed management and yield improvement in organic lettuce ( Lactuca sativa ) production. Phytoparasitica 37: 193-203. Jenkins, W.R. 1964. A rapid centrifugal-floatation techni que for separating nematodes from soil. Plant Disease Reporter 48:692. Jordan, N., D.A. Mortensen, D.M. Prenzlow, and K. C. Cox. 1995. Simulation analysis of crop rotation effects on weed seedbanks. American Journal of Botany 82: 390398. Kagezi, G.H., D.J. Voegtlin, and R.A. We inzierl. 1999. The aphids (Homoptera: Aphididae) associated wit h bell peppers and surrounding vegetation in southern Illinois. Great Lakes Entomologist 32:161-173. Karpenstein-Machen, M., and R. Stuelpnagel. 2000. Biomass yield and nitrogen fixation of legumes monocropped and intercropped with rye and rotation effects on a subsequent maize crop. Plant and Soil 218:215-232. Kegode, G.O., F. Forcella, and S. Clay. 1999. Influence of crop rotation, tillage, and management inputs on weed seed production. Weed Science 47:175-183. Kin, T.J., J.C. Neal, J.M. Ditomaso, and F. S. Rossi. 2002. A survey of Weed Scientists perceptions on the significance of crabgrasses ( Digitaria spp.) in the United States. Weed Techno logy 16:239-242.

PAGE 211

211 Kloepper, J.W., R. Rodrguez-K bana, J.A. McInroy, and D.J. Collins. 1991. Analysis of populations and physiological characterization of microorganisms in rhizospheres of plants with antagonistic properties to phytopathogenic nematodes. Plant and Soil 136:95-102. Ladha, J.K., D.K. Kundu, M.G. Angelo-Van Coppenolle, M.B. Peoples V.R. Caranagel, and P.J. Dart.1996. Legume productivity and soil nitrogen dynamics in lowland rice-based cropping systems. Soil Scienc e Society of America Journal 60:183192. Landis, D.A., F.D. Menalled, A.C. Costam agna, and T.K. Wilkinso n. 2005. Manipulating plant resources to enhance beneficial arthropods in agricultural landscapes. Weed Science 53:902-908. Lanini, W.T., D.R. Pi ttenger, W.L. Graves, F. Munoz and H.S. Agamalien. 1989. Subclovers as living mulches for m anaging weeds in vegetables. California Agriculture 43:25-27. Lewis, J. 1973. Longevity of crop and weed seeds: survival after 20 years in soil. Weed Research 13:179-191. Li, Y., E. Hanlon, W. Klassen, Q. Wang, T. Olczyk, and I.V. Ezenwa. 2006. Cover crop benefits for South Florida commercial v egetable producers. EDIS publication SL242. Available at:[ http://edis.ifas.ufl.edu/SS461]. Liebman, M. and E. Dyck. 1993. Crop rota ti on and intercropping strategies for weed management. Ecological Applications 3: 92-122. Liebman, M. and A.S. Davis. 2000. Integrati on of soil, crop, and weed management in low-external-input farming systems. Weed Research 40:2747. Liebman, M. and E.R. Gallandt. 1997 Many li ttle hammers: ecological approaches for management of cropweed interactions. P ages 291 in L. E. Jackson (ed.). Ecology in Agriculture. Academic Press, San Diego, CA. Liebman, M., and Y. Ohno. 1998. Crop rotation and legume residue effects on weed emergence and growth: applications for weed management. Pages 181-221 in J.L. Hatfield, D.D. Buhler and B.A. Stewart (ed.). Inte grated Soil and Weed management, Chelsea, MI: Ann Arbor Press. Liebman, M., and C.P. Staver 2001. Crop diversificati on for weed management. Pages 322-374 in M. Liebman, C. L. Mohler, and C.P. St aver(ed.). Ecological Management of Agricultural Weeds. Cambridge University Press, NY. Lu,Y., B. Watkins, J.R. Teasdale, and A.A. Abdul-Baki. 2000. Cover crops in sustainable food production. Food Re views International 16:121-157.

PAGE 212

212 Magurran, A.E. 1988. Ec ological Diversity and Its Meas urement, Chapter 2: Diversity indices and species abundance models, Prin ceton University Press, Princeton, NJ. Manandhar, R., C.R.R. Hooks, and M.G. Wright. 2009. Influence of cover crop and intercrop systems on Bemisia argentifolli (Hemiptera:Aleyrodidae) infestation and associated squash silverleaf disorder in zucchini. Environmental Entomology 38:442-449. Mansoer, Z., D.W. Reeves, and C.W. Wood. 1997. Suitability of sunn hemp as an alternative late-summer legume cover cr op. Soil Science Society of America Journal 61: 246-253. Maxwell, B.D., R.G. Smith, and M. Brelsford. 2007. Wild oat ( Avena fatua ) seed bank dynamics in transition to organic wheat production systems. Weed Science 55: 212-217. McSorley, R., and R.N. Gallaher.1991. Managing plant-parasitic nematodes in crop sequences. Proceedings of the Soil Crop Sc ience Society of Florida 51:42-45. McSorley, R., D.W.Dickson, J.A. de Brito, T.E. Hewlett, and J.J. Frederick.1994a. Effects of tropical rotation crops on Meloidogyne arenaria population densities and vegetable yields in microplots. Journal of Nematology 26:175-181. McSorley, R., D.W. Dickson, J.A. de Brito, and R.C. Hochmuth.1994b. Tropical rotation crops influence nematode densities and veget able yields. Journal of Nematology 26:308-314. McSorley, R.1998. Alternative practice s for managing plantparasitic nematodes. American Journal of Alter native Agriculture 13:98-104. McSorley, R., and D.L. Porazinska. 2001. Elements of sustai nable agriculture. Nematropica 31:1-9. McVay, K.A., D.E. Radcliffe, and W.L. Ha rgrove. 1989. Winter legume effects on soil properties and nitrogen fertilizer requirements. Soil Science Society of America Journal 53:1856-1862. Meagher, R.L., and E.R. Mitchell. 1999. Nontarget hymenoptera collected in pheromoneand synthetic floral volatilebaited traps. Environmental Entomology 28:367-371. Mennan, H., M. Ngouajio, E. Kaya, and D. Isik. 2009. Weed management in organically grown kale using alternative cover cropping systems. Weed Technology 23:8188.

PAGE 213

213 Menalled, F.D., K.L. Gross, and M. Hammond. 2001. Weed aboveground and seedbank community responses to agricultu ral management systems. Ecological Applications 11:1586-1601. Mohler, C.L. 1993. A model of the effect s of tillage on emergence of weed seedlings. Ecological Applications 3:55-73. Mohler, C.L. and J.R. Teas dale. 1993. Response of w eed emergence to rate of Vicia villosa Roth and Secale cereale L. residue. Weed Re search 33:487-499. Moonen, A.C., and P. Brberi. 2004. Size and composition of the weed seedbank after 7 years of different cover-crop-maiz e management systems. Weed Research 44:163-177. Mortensen, D.A., L. Bastiaans, and M. Satt in. 2000. The role of ecology in the development of weed management systems: an outlook. Weed Research 49:4962. Mortimer, A.M., J.J. Sutt on, and P. Gould. 1989. On robust weed population models. Weed Research 29:229-238. Mulugeta, D., and D.E. Stoltenberg. 1997. Increased weed emergence and seed bank depletion by soil disturbance in a no-t illage system. Weed Science 45:234-241. Munoz-Carpena, R. A. Ritter, D.D. Bosch, B. Schaffer, and T.L. Potter. 2008. Summer cover crop impacts on soil percolation and nitrogen leaching from a winter corn field. Agricultural Water Management 95:633-644. Nault, B.A., and G.G. Kennedy. 2000. Seaso nal changes in habitat preference by Coleomegilla maculate : implications for Color ado potato beetle management in potato. Biological Control 17:164-173. Nagabhushana, G.G., A.D. Wo rsham, and J.P. Yenish. 2001. Allelopathic cover crops to reduce herbicide use in sustainable agr icultural systems. Allelopathy Journal 8:133-146. Nagoshi, R.N., and R.L. Meagher. 2004. Seasonal distribution of fall armyworm (Lepidoptera: Noctuidae) host strains in agricultural and turf grass habitats. Environmental Entomology 33: 881-889. Nelson, W.A., B.A. Kahn, and B.W. Roberts 1991. Screening cover crops for use in conservation tillage systems for vegetables following spring plow ing. HortScience 26:860-862. Ngouajio, M., M.E. McGiffen, and C.M. Hutchinson. 2003. Effect of cover crop and management system on weed population in le ttuce. Crop Protection 22: 57-64.

PAGE 214

214 Nguyen, Thu-Vi, A. Wysocki, and D.D. Trea dwell. 2008. Economics of the organic food industry in Florida. Gainesville: University of Florida, IFAS Extension, publication no. FE732. NOSB [National Organic Standard Board] .2001. Policy and procedures manual. Section VII. Page. 28. Available at http://www.ams.usda.gov/AMSv1.0/getfile?dDocName=STELDEV3013893. Nguyen, T-V, A. Wysocki, and D.D. Treadwe ll. 2008. Economics of the organic food industry in Florida. University of Flori da, IFAS Extension, FE732, Gainesville, FL. Nimbal, C.I., J.F. Pedersen, C.N. Yerkes L.A. Weston, and S.C. Weller. 1996. Phytotoxicity and distribution of sorgoleon e in grain sorghum germplasm. Journal of Agricultural and Food Chemistry 44:1343-1347. Noe, J.P. 1988. Theory and practice of the cropping systems approach to reducing nematode problems in the tropics. Jour nal of Nematology 20:204-213. Noe, J.P., J.N. Sasser, and J.L. Imbriani. 1991. Maximizi ng the potential of cropping systems for nematode management. Journal of Nematology 23:353-361. Nuessly, G.S., and S.E. Webb 2007. Insect m anagement for sweet corn. University of Florida, IFAS Extensi on, ENY-472 (IG158). Nutrition Business Journal. 2004. The NBJ / SPINS Organic Foods Report 2004, Penton Media, Inc., Boulder, CO. Nyoike, T.W., O.E. Liburd, and S.E. W ebb. 2008. Suppression of whiteflies, Bemisia tabaci (Hemiptera:Aleyrodidae) and incidence of cucurbit leaf crumple virus a whitefly-transmitted virus of zucchini squash new to Florida, with mulches and imidacloprid. Florida Entomologist 91:460-465. Oerke, E.-C. 2006. Crop losses to pests. Jo urnal of Agricultural Science 144:31-43. Offner, J. 2000. Organic foods niche gro wing into big business. The Packer, 25 December, 2000, Page A6. Ofori, C.F., and W.R. Stern. 1987. Cereal-legume intercro pping systems. Advances in Agronomy 26:177-204. OFRF (Organic Farming Research Foundation). 1998. Third biennial national organic farmers survey. Organic Farming Res earch Foundation. Santa Cruz, CA. Olson, S.M., and E.H. Si monne. 2006. Vegetable production handbook for Florida (2005-06), University of Florida, IF AS Extension, Gainesville, FL. Opperman, C.H., J.R. Rich, and R.A. Dunn. 1988. Reproduc tion of three root-knot nematodes on winter small grain cr ops. Plant Disease 72:869-871.

PAGE 215

215 Pathak, S.C. 1992. An integrated sustainab le vegetable production system. HortScience 27:738-741. Palumbo, J.C., N.C. Toscano, M.J. Bl ua, and H.A. Yoshida. 2000. Impact of Bemisia whiteflies (Homoptera: Aley rodidae) on alfalfa growth forage yield, and quality. Journal of Economic Entomology 93:1688-1694. Pappu, H.R. 1997. Managing tospovirus through biotechnology: progress and prospects. Biotechnology and De velopment Monitor 32:1417-1421. Parajulee, M.N, and J.E. Slosser. 1999. Ev aluation of potential relay strip crops for predator enhancement in Texas cotton. International Journal of Pest Management 45:275-286. Penfold, C.M., M.S. Miyan, T.G. Reeves, and I.T. Grierson. 1995. Bi ological farming for sustainable agriculture production. Austra lian Journal of Exper imental Agriculture 35:849-856. Perring,T.M., A.D. Cooper, R.J. Rodriguez C.A. Farrar and T.S. Bellows. 1993. Identification of a whitef ly species by genomic and behavioral studies. Science 259:74-77. Peters, R.A., and S. Dunn. 1971. Life history st udies as related to weed control in the northeast. 6. Large and small crabgrass. Northeast Regional Weed Control Technical Committee (NE 42). Storrs, CT : Connecticut Agricultural Research Station. Pielou, E.C. 1969. An Introduction to Mat hematical Ecology, New York: John Wiley. Pielou, E.C. 1975. Ecological Diver sity, New York: John Wiley. Pimentel, D., H.B. Acquay, M. Rice, M. Silv a, J. Nelson, V. Lipner, S. Giordano, A. Horowitz, and M. Damore. 1992. Environmen tal and economic cost of pesticide use. BioScience 42:750. Putnam, A.R., J. DeFrank, and J.P. Barnes. 1983. Exploitation of allelopathy for weed control in annual and perennial cropping systems. Journal of Chemical Ecology 8:1001-1010. Qunherv, P., P. Topart, and B. Martiny. 1998. Mucuna pruriens and other rotational crops for control of Meloidogyne incognita and Rotylenchulus reniformis in vegetables in polytunnels in Mart inique. Nematropica 28:19-30. Rafie, A., J. Diaz, and P. McLeod. 1999. E ffects of forage groundnut in reducing the sweet-potato whitefly and associated Gemini virus disease in bell pepper in Honduras. Tropical Ag riculture 76:208-211.

PAGE 216

216 Ranganathan, R. 1993. Anal ysis of yield advantage in mixed cropping. PhD dissertation, Wageningen Agricultural Univ ersity, Wageningen, The Netherlands. Roush, M.L., N.R. Jordan, and J.S. Holt. 1989. Ecological basis of weed biology in IPM. Pages 136-157 in: National IPM Coordinat ing Committee(eds.). Proceedings of the National Integrated Pest Managem ent Symposium, Geneva, NY. Roberts, H.A., and P.M. Feast. 1972. Fate of seeds of some annual weeds in different depths of cultivated and undisturb ed soil. Weed Research 12:316-324. Roberts, H.A., and M.E. Rickets. 1979. Quant itative relationships between the weed flora after cultivation and the seed populat ion in the soil. Weed Research 19:269275. Rodrguez-Kbana, R., N. Kokalis-Burelle, D.G. Robertson, P.S. King, and L.W. Wells. 1994. Rotations with coastal berm udagrass, cotton, and bahiagrass for management of Meloidogyne arenaria and southern blight in peanut. Journal of Nematology 26:665-668. Rosen, C.J., and D.L. Allan. 2007. Exploring the benefits of or ganic nutrient sources for crop production and soil quality. HortTechnology 17: 422-430. Rotar, P.P. and R.J. Joy. 1983. Tropic Sunn sunn hemp Crotalaria juncea L. Research Extension Series 036. Honolulu: Coll ege of Tropical Agriculture and Human Resources, University of Hawaii. SAS Institute. 2008. SAS software, Version 9.1. Cary, NC: Statistical Analysis Systems Institute, Inc. Sainju, U.M., W.F. Whitehead, and B.P. Singh. 2005. Bicu lture legume-cereal cover crops for enhanced biomass yield and ca rbon and nitrogen. Agronomy Journal 97:1403-1412. Sasser, J.N., and D.W. Freckman. 1986. A worl d perspective on nematology: the role of the Society. Pp. 7-14 in J.A. Veec h and D.W. Dickson (eds). Vistas on Nematology. Society of Nema tologists, Hyattsville, MD. Seneratne, R,and D.S. Ratnasinghe. 1995. Nitrogen fixation and beneficial effects of some grain legumes and green manure cr ops on rice. Biology and Fertility of Soils 19:49-54. Scott, C.A. 2008. Leguminous and graminaceous cover crops for the control of insect pests in organic squash. M.S. thesis. Univ ersity of Florida, Gainesville, FL. Simmons, A.M., S. Abd-Rabou, and G.S. McCutcheon. 2002. Incidence of parasitoids and parasitism of Bemisia tabaci (Homoptera:Aleyrodidae) in numerous crops. Environmental Entomology 31:1030-1036.

PAGE 217

217 Smith, H.A., and R. McSorley. 2000. Potent ial of field corn as a barrier crop and eggplant as a trap crop for management of Bemisia argentifolii (Homoptera: Aleyrodidae) on common bean in North Florida. Florida Entomologist 83: 145158. Snapp, S.S., S.M. Swinton, R. Labarta, D. Mutch, J.R. Black, R. Leep, J. Nyiraneza, and K. ONeil. 2005. Evaluating cover cr ops for benefits, cost and performance within cropping system niches. Agronomy Journal 97:322-332. Sooby, J. 2003. State of the States. Organic farming systems research at land grant institutions 2001~2003. 2nd ed. A publication of Or ganic Farming Research Foundation (OFRF), Santa Cruz, CA. Sullivan, P.2003. Overview of cove r crops and green manures. Page 16 in Fundamentals of sustainable agriculture Appropriate Technology Transfer for Rural Areas (ATTRA) Publication IP107. Summers, C.G., J.P. Mitchell, T.S. Prather, and J.J. Stapleton. 2009. Sudex cover crops can kill and stunt subsequent tomato, lettuce, and broccoli transplants through allelopathy. California Agriculture 63:35-40. Swanton, C.J., and B.D. Boot h. 2004. Management of weed s eedbanks in the context of populations and communities. W eed Technology 18:1496-1502. Taylor, K.L., and R.G. Hartzler. 2000. Effect of seed bank augmentation on herbicide efficacy. Weed Technology 14:261-267. Teasdale, J.R. 1993. Interaction of ligh t, soil moisture and temperature with weed suppression by hairy vetch residue. Weed Science 41, 46-51. Teasdale, J.R. 1996. Contribut ion of cover crops to weed management in sustainable agricultural systems. Journal in Production Agriculture 9:475-479. Teasdale, J.R. 1998. Influence of corn ( Zea mays) population and row spacing on corn and velvetleaf ( Abutilon theophrasti ) yield. Weed Science 46:447-453. Teasdale, J.R., and C.L. Mohl er. 1993. Light transmittance, soil temperature, and soil moisture under residue of hairy vetch and rye. Agronomy Journal 85:673-680. Teasdale, J.R. and C.S.T. Daughtry. 1993. Weed suppre ssion by live and desiccated hairy vetch ( Vicia villosa ), Weed Science 41: 207-212. Teasdale, J.R. and A.A. Abdul-Baki. 1998. Com parison of mixtures vs. monocultures of cover crops for fresh-market tomato production with and without herbicide. HortScience 33:1163-1166.

PAGE 218

218 Teasdale, J.R., L.O. Brandsaeter, A. Cale gari, and F. Skora Neto. 2007. Cover crops and weed management. Chapter 4 in Non-chemical Weed Management, M.K. Upadhyaya and R.E. Blackshaw (eds), Oxfo rdshire, UK: CAB International. Theunissen, J. 1997. Application of interc ropping in organic agriculture. Biological Agriculture and Horticulture 15:251-259. Tommasini, M.G., and S. Maini.1995. Frankliniella occidentlis and other thrips harmful to vegetable and ornamental crops in Europe. Wageningen University Papers 95:1-42. Toole, E.H., and V.K. T oole. 1941. Progress of germination of seed of Digitaria as influenced by germination temperature and other factors. Journal of Agricultural Research 63:65-90. Torres, J.L.R., M.G. Pereira, I. Andrioli, J.C. Polidoro, and A.J. Fabian. 2005. Cover crops residue decomposition and nitrogen re lease in a cerrado soil. Revista Brasileira de Ciencia do Solo 29:609-618. Trivedi, P.C., and K.R. Barker. 1986. Management of nematodes by cultural practices. Nematropica 16:213-236. USDA-AMS. 2009. Agriculture Marketing Serv ice. Fresh vegetable market programs. Available online at: [ http://www.ams.usda.gov /AMSv1.0/ ams.fetch TemplateData.do?template=TemplateN& page=FreshMarketVegetableStanda rds] USDA-ERS. 2005. United States Department of Agriculture, Economic Research Service. Data sets of organic production. Table 4. Certified organic pasture and cropland. Available online at: [ http://www.ers.usda.gov/data/organic/]. Valenzuela, H., and J. Sm ith. 2002. Sorghum-sudangrass hybrids. Manoa, H I: Cooperative Extension Service, Coll ege of Tropical Agriculture and Human Resources, University of Hawaii, SA-GM-10. Vandermeer, J.H. 1989. The ecology of in tercropping. Cambridge, UK: Cambridge University Press. Walters, R.F. 1971. Shifting cultivation in Latin America. Report No. 17. Rome: United Nations Food and Agricultural Organization (FAO). Walz, E. 1999. Final results of the Third Biennial National Organic Farmers Survey. Santa Cruz, CA: Organic Farming Research Foundation. Wang, K.-H., B.S. Sipes, and D.P. Schmitt. 2002. Crotolaria as a cover crop for nematode management: A review Nematropica 32:35-57. Wang, K.-H., R. McSorley, and R.N. Gallaher .2004. Effect of winter cover crops on nematode population levels in No rth Florida. Journal of Ne matology 36:517-523.

PAGE 219

219 Webb, S. 2006. Insect management for cucurbits (Cucumber, Squash, Cantaloupe and Watermelon), IFAS Extnesion ENy-460. Univer sity of Florida, Gainesville, FL. White, R.H., A.D. Worsham, and U. Blum. 1989. A llelopatic potential of legume debris and aqueous extracts. W eed Science 37:674-679. White, A.J., S.D. Wratten, N.A. Berry, and U. Weigmann 1995. Habitat management to enhance biological control of Brassica pests by hoverflies (Diptera:Syrphidae). Journal of Economic Entomology 88: 1171-1176 Wubs, A.M., L. Bastiaans, and P.S. Bindrab an. 2005. Input levels and intercropping productivity: exploration by simulation. In: Plant Research International B.V., Wageningen, Netherlands, p. 7.

PAGE 220

220 BIOGRAPHICAL SKETCH Manish Bhan was born in Gw alio r, India. He receiv ed a Bachelor of Science degree in Agricultural Sciences and Mast er of Science degree in agronomy from Jawaharlal Nehru Agricultural University in Jabalpur, India. Subsequently, he was awarded a senior research fellowship for two years at the Directorate of Weed Science Research, Jabalpur, India and worked on the biology and management of dodder in field crops. After completing hi s fellowship, Manish joined Monsanto India as trainee in Technology Development working on the development of maize and bollgard cotton hybrids. He started his PhD program in the Horticultural Sciences Department at the University of Florida in fall 2005. After co mpleting his degree requi rements, Manish will continue to work on pest ecology in sustainable agriculture.