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Impact of Irrigation and Nutrient Management Programs on Fruit Yields, Nitrogen Load, and Crop Value of Fresh Market Tom...

Permanent Link: http://ufdc.ufl.edu/UFE0024148/00001

Material Information

Title: Impact of Irrigation and Nutrient Management Programs on Fruit Yields, Nitrogen Load, and Crop Value of Fresh Market Tomatoes Grown with Plasticulture in the Era of Best Management Practices
Physical Description: 1 online resource (137 p.)
Language: english
Creator: Gazula, Aparna
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: break, chicken, drainage, economic, even, fertilizer, litter, lysimeter, marginal, nitrogen, poultry, price, soil
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: Because of the importance of agriculture to Florida's economy, and the federal and state water quality legislation, Florida's vegetable growers need specific guidelines to comply with these new regulations and remain competitive. Regulators also need science-based data documenting the reduction in pollution achieved by implementation of Best Management Practices. To better understand the impact of irrigation-nutrient management programs (INMP) on fresh market tomato production, simultaneous experiments were conducted to determine the effects of INMPs on 1) tomato yields, 2) tomato seasonal total-N load, and 3) economic insights into tomato production as determined with partial budget analysis (PBA). A 2-year experiment was conducted at Live Oak, Florida during springs of 2005 and 2006 with selected INMPs created by a combination of preplant fertilizer source (Chicken Litter (CL) or 13-1.8-10.8), fertilizer rate (100% or 200%), and irrigation rate (100% or 300%). The University of Florida/Institute of Food and Agricultural Sciences (UF/IFAS) recommended INMP was 100% Fertigation-100% Irrigation. CL as a preplant nutrient source increased early-yields, and did not differ significantly from the UF/IFAS INMP for nutrient loads. 300% INMP reduced total fruit yields (920 to 1242 25-lb cartons/acre), but did not differ significantly from the UF/IFAS INMP for nutrient loads. Based on the PBA, relative to the UF/IFAS INMP, 300% INMP not only increased the cost of the program ($17.18/acre), but also resulted in reduced returns ($1701 to $4112/acre). The effects of 200% fertigation rate on tomato plants varied with year. Early and total tomato yields with UF/IFAS and 200% INMP were not significantly different in both years. The high fertigation alone INMP (200% Fertigation to 100% Irrigation) resulted in highest total-N load in 2006. Though statistically not significant, it also resulted in numerical higher net returns relative to the UF/IFAS INMP ($55 to $561/acre. We can conclude that CL can be used as an alternative preplant fertilizer source. We can also conclude that growers should not use high irrigation/high fertigation-high irrigation rates to ensure adequate soil moisture levels in the crop root zone as it results in net losses relative to the UF/IFAS INMP. Instead, they should better manage irrigation water application.
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 Aparna Gazula.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Simonne, Eric H.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2010-05-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024148:00001

Permanent Link: http://ufdc.ufl.edu/UFE0024148/00001

Material Information

Title: Impact of Irrigation and Nutrient Management Programs on Fruit Yields, Nitrogen Load, and Crop Value of Fresh Market Tomatoes Grown with Plasticulture in the Era of Best Management Practices
Physical Description: 1 online resource (137 p.)
Language: english
Creator: Gazula, Aparna
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: break, chicken, drainage, economic, even, fertilizer, litter, lysimeter, marginal, nitrogen, poultry, price, soil
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: Because of the importance of agriculture to Florida's economy, and the federal and state water quality legislation, Florida's vegetable growers need specific guidelines to comply with these new regulations and remain competitive. Regulators also need science-based data documenting the reduction in pollution achieved by implementation of Best Management Practices. To better understand the impact of irrigation-nutrient management programs (INMP) on fresh market tomato production, simultaneous experiments were conducted to determine the effects of INMPs on 1) tomato yields, 2) tomato seasonal total-N load, and 3) economic insights into tomato production as determined with partial budget analysis (PBA). A 2-year experiment was conducted at Live Oak, Florida during springs of 2005 and 2006 with selected INMPs created by a combination of preplant fertilizer source (Chicken Litter (CL) or 13-1.8-10.8), fertilizer rate (100% or 200%), and irrigation rate (100% or 300%). The University of Florida/Institute of Food and Agricultural Sciences (UF/IFAS) recommended INMP was 100% Fertigation-100% Irrigation. CL as a preplant nutrient source increased early-yields, and did not differ significantly from the UF/IFAS INMP for nutrient loads. 300% INMP reduced total fruit yields (920 to 1242 25-lb cartons/acre), but did not differ significantly from the UF/IFAS INMP for nutrient loads. Based on the PBA, relative to the UF/IFAS INMP, 300% INMP not only increased the cost of the program ($17.18/acre), but also resulted in reduced returns ($1701 to $4112/acre). The effects of 200% fertigation rate on tomato plants varied with year. Early and total tomato yields with UF/IFAS and 200% INMP were not significantly different in both years. The high fertigation alone INMP (200% Fertigation to 100% Irrigation) resulted in highest total-N load in 2006. Though statistically not significant, it also resulted in numerical higher net returns relative to the UF/IFAS INMP ($55 to $561/acre. We can conclude that CL can be used as an alternative preplant fertilizer source. We can also conclude that growers should not use high irrigation/high fertigation-high irrigation rates to ensure adequate soil moisture levels in the crop root zone as it results in net losses relative to the UF/IFAS INMP. Instead, they should better manage irrigation water application.
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 Aparna Gazula.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Simonne, Eric H.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2010-05-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024148:00001


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1 IMPACT OF IRRIGATION AND NUTRIENT MANAGEMENT PROGRAMS ON FRUIT YIELDS NITROGEN LOAD, AND CROP VALUE O F FRESH MARKET TOMAT O GROWN WITH PLASTICUL TURE IN THE ERA OF B EST MANAGEMENT PRACT ICES By APARNA GAZULA A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2009

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2 2009 Aparna Gazula

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3 To my Mother

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4 ACKNOWLEDGMENTS I wish to express my sincere gratitude to Dr. Eric Simonne, chair of my graduate advisory committee, for his encouragement advice, guidance, support, and patience throughout my Ph.D. program. I would also like to express my deepest gratitude to the members of my advisory committee, Dr. Kent Cushman (deceased) Dr. Fritz Roka, Dr. George Hochmuth, Dr. Michael Dukes, and Dr. Peter Nkedi -Kizza for their assistance, technical support, and guidance. I would also like to thank David Studst ill, Michael Alligood, and Robert Hochmuth for their support and help with my work. I would like to thank my friends and colleagues Alejandra Sierra, Camille Esmel, Josh Adkins, Kate Santos, Oren Warren, Rachel Itle, Richard Tyson, Teddy McAvoy, and Valeri e McManus for their friendship and support throughout my entire program. My sincere thanks go to everyone who assisted in the setup and implementation of my research work: April Warner, Debbie Gast, Jerry Butler, Joe Bracewell, Lei Lani Davis, Randi Randel l, Scott Kerr, and Wanda Laughlin.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................................... 4 LIST OF TABLES ................................................................................................................................ 8 LIST OF FIGURES ............................................................................................................................ 10 ABSTRACT ........................................................................................................................................ 11 CHAPTER 1 INTRODUCTION ....................................................................................................................... 13 Impor tance of Fresh Market Tomato Production in Florida ..................................................... 13 Statement of the Problem, Rationale and Significance ............................................................. 13 2 REVIEW OF LITERA TURE ..................................................................................................... 16 Importance of Best Management Practices, Total Maximum Daily Load, Florida Watershed Restoration Act ..................................................................................................... 1 6 Factors Affectin g Tomato Yield ................................................................................................ 19 Nutrient Load and Tools for Determination of Nutrient Load ................................................. 20 Factors Affecting Nutrient Load ................................................................................................ 27 Conclusion and Objectives ......................................................................................................... 28 3 NUTRIENT MANAGEMENT PROGRAMS FOR FRESH MARKET TOMATOES GROWN WITH PLASTICULTURE IN THE ERA OF BEST MANAGEMENT PRACTICES. I. SOIL MOISTURE, PLANT NUTRITIONAL STATUS, AND YIELD DISTRIBUTION ......................................................................................................................... 36 Introduction ................................................................................................................................. 36 Materials and Methods ................................................................................................................ 41 Experimental Setup .............................................................................................................. 41 Data Collection .................................................................................................................... 43 Irrigation volume data .................................................................................................. 43 Soil moisture data ......................................................................................................... 43 Petiole sap data ............................................................................................................. 44 Yield data ...................................................................................................................... 44 Data Analysis ....................................................................................................................... 45 Results and Discussion ............................................................................................................... 45 Weather Conditions ............................................................................................................. 45 Raised Plant Bed Soil Moisture .......................................................................................... 46 Tomato Plant Petiole Sap NO3 N Concentration ............................................................. 47 Tomato Plant Petiole Sap K+ Concentration ...................................................................... 48 Tomato Yield and Grade Distribution ................................................................................ 50

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6 Early Fruit Yield ........................................................................................................... 50 Total Season Fruit Yields ............................................................................................ 51 Concl usion ................................................................................................................................... 54 4 NUTRIENT MANAGEMENT PROGRAMS FOR FRESH MARKET TOMATOES GROWN WITH PLASTICULTURE IN THE ERA OF BEST MANAGEMENT PRACTICES. II. DETERMINATION OF NUTRIENT LOAD ............................................. 69 Introduction ................................................................................................................................. 69 Materials and Methods ................................................................................................................ 76 Experimental Setup .............................................................................................................. 76 Drainage Lysimeters Installation ........................................................................................ 78 Drainage Lysimeters Sampling, Sample Analysis, and Load Calculation ....................... 78 Soil Sampling Sampling, Sample Analysis, and Load Calculation .................................. 79 Data Analysis ....................................................................................................................... 80 Results and Discussion ............................................................................................................... 81 Weather Conditions ............................................................................................................. 81 Season al Total N Load Estimate Based o n Drainage Lysimeter ...................................... 81 Soil profile Total N Load Estimate Based on Soil Sampling ........................................... 83 Relationship Between Seasonal Total N Load Measured wit h Drainage Lysimeters and Soil -P rofile Total N Measured with Soil Sampling ............................................... 86 Conclusion ................................................................................................................................... 87 5 NUTRIENT MANAGEMENT PROGRAMS FOR FRESH MARKET TOMATOES GROWN WITH PLASTICULTURE IN THE ERA OF BEST MANAGEMENT PRACTICES. III. ECONOMIC INSIGHTS ............................................................................. 96 Introduction ................................................................................................................................. 96 Materials and Methods ................................................................................................................ 98 Fresh Market Tomato Production System .......................................................................... 98 Fresh Market Tomato Production Model for University of Florida/Institute of Food and Agricultural Sciences (UF/IFAS) Based Recommendations ............................... 100 Methodology of Par tial Budget Analysis of Irrigation Nutrient Management Programs ......................................................................................................................... 100 Results and Discussion ............................................................................................................. 101 Fresh Market Tomato Production Co sts ........................................................................... 101 Marginal Analysis of the Value of Extra Fertilizer and Irrigation ................................. 103 Effect of Irrigation Nutrient Management Programs on Gross Returns from Fresh Market Tomato Production ........................................................................................... 105 Irrigation management ............................................................................................... 105 Fertilization management .......................................................................................... 105 Benefits from chicken litter ....................................................................................... 106 Partial Budget Analysis of Irrigation Nutrient Management Programs ......................... 107 Economic Returns versus Nutrient Loading .................................................................... 107 Conclusion ................................................................................................................................. 108 6 CONCLUSION ......................................................................................................................... 122

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7 LIST OF REFERENCES ................................................................................................................. 126 BIOGRAPHICAL SKETCH ........................................................................................................... 137

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8 LIST OF TABLES Table page 2 1 Advantages and limitations of different procedures used for measuring nutrient loads. ....................................................................................................................................... 30 2 2 Published estimates of nitrogen (nitrate, ammonium and total N) leaching in selected crops. ....................................................................................................................................... 31 3 1 Irrigation -nutrient (N -P -K) management programs for spring 20052006 Florida 47 fresh market tomato production with raised bed plasticulture system. .............................. 56 3 2 Number of sampling days when soil volumetric water content at 6 inches from the drip tape was between 0 to 13% for fresh market tomatoes grown in 2005 and 2006 on Blanton -Foxworth-Alpin Complex soil series ............................................................... 57 3 3 Effects of irrigation and nutrient management programs on Florida 47tomato fruit yields during spring of 2005 and 2006. ................................................................................ 59 4 1 Published estimates of nitrogen use efficiency (NUE) in selected crops. .......................... 89 4 2 Effects of depth of soil sampling in a Florida 47tomato field during spring of 2005 and 2006 on nitrogen loads based on mean, be d, and maximum wetted widths .............. 90 4 3 Effects of irrigation -nutrient management programs in a Florida 47tomato field during spring of 2005 and 2006 on nitrogen loads based on soil sampling with three different wetted width estimates. .......................................................................................... 91 5 1 Price of US #1 tomatoes during spring of 2005 and 2006 fresh market tomato production with raised -bed plasti culture system in North Florida. ................................... 111 5 2 Estimated costs of irrigation nu trient management programs for spring 2005 and 2006 Florida 47 fresh market tomato production with raised -bed plastic ulture system. .................................................................................................................................. 112 5 3 Estimated cost s to produce and harvest Florida 47 tomatoes with raised -bed plasticulture system using University of Florida/Institute of Food and Agricultural Sciences irrigation -nutrient management program in spring of 2005 and 2006. ............. 113 5 4 Season average prices of tomato grades for District 4 F loridas shipment and sales. ..... 115 5 5 Effects of irrigation and nutrient management programs on Florida 47tomato fruit yields, gross returns, and gross returns relative to the University of Florida/Institute of Food and Agricultural Sciences recommende d program irrigation -nutrient management program during spring of 2005 and 2006 with raisedbed plasticulture system .................................................................................................................................. 116

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9 5 6 Total negative effects, total positive effects, and net returns of the irrigation -nutrient management programs relative to the UF/IFAS recommended program for fresh market tomato production during spring of 2005 and 2006 with raised-bed plasticulture system ............................................................................................................. 118 5 7 Net returns and changes in total N load of irrigation -nutrient management programs relative to the University of Florida/ Institute of Food and Agricultural Sciences recommended program for Florida 47 fresh market tomato production during spring of 2005 and 2006 with raised-bed plasticulture system ........................................ 119

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10 LIST OF FIGURES Figure page 2 1 Fresh market tomato production in the United States .......................................................... 33 2 2 Vegetable production in Florida ............................................................................................ 34 3 1 N fertigation schedule used in the 20052006 fresh market tomato production experimen t. ............................................................................................................................. 61 3 2 Irrigation schedule for spring 20052006 Florida 47 fresh market tomato production with raised -bed plasticulture system. ................................................................. 62 3 3 Historical and 20052006 weather patterns during tomato growing season in Live Oak, FL. .................................................................................................................................. 63 3 4 Effects of irrigation and nutrient management programs on petiole sap concentrations recorded for the different programs and the sufficiency ranges recommended for the corresponding growth stages during 2005 and 2006 ....................... 65 3 5 Distribution of tomato fruit grades for the early yie lds during the 2005 and 2006 growing seasons. .................................................................................................................... 67 3 6 Distribution of tomato fruit grades for the total season yields during the 2005 and 2006 growing seasons. ........................................................................................................... 68 4 1 Schematics of the 3 -feet long lysimeter designs used in the 2005 and 2006 fresh market tomato production experiment .................................................................................. 93 4 2 Effects of irrigation -nutrient management programs on mean leachate volume (L) collected, and mean nitrate load recorded during the 2005 and 2006 growing seasons with drainage lysimeters. ....................................................................................................... 94 5 1 Effect of season average mar ket prices of tomato grades for District 4 F loridas shipment and sales of U.S. One or Better 25 lb tomato cartons and fresh market tomato yields recorded in 2005 and 2006 with the UF/IFAS irrigationnutrient management program on net profits ................................................................................... 120 5 2 Relationship between additional break -even yield and increase in nitrogen fertilizer costs due to increased nitrogen fertilizer application at different season average market prices of tomato grade s for District 4 F loridas shipment and sales of U.S. One or Better 25 lb tomato cartons. .................................................................................... 121

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11 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy IMPACT OF IRRIGATION AND NUTRIENT MANAGEMENT PROGRAMS ON FRUIT YIELDS NITROGEN LOAD, AND CROP VALUE O F FRESH MARKET TOMAT O GROWN WITH PLASTICUL TURE IN THE ERA OF B EST MANAGEMENT PRACT ICES By Ap arna Gazula May 2009 Chair: Eric H. Simonne Major: Horticultural Science Because of the importance of agriculture to Floridas economy, and the federal and state water quality legislation, Floridas vegetable growers need specific guidelines to comply wi th these new regulations and remain competitive. Regulators also need science -based data documenting the reduction in pollution achieved by implementation of B est M anagement P ractices To better understand the impact of irrigation -nutrient management progr ams (INMP) on fresh market tomato production, simultaneous experiments were conducted to determine the effects of INMPs on 1) tomato yields, 2) tomato seasonal total N load, and 3) economic insights into tomato production as determined with partial budget analysis (PBA). A 2 year experiment was conducted at Live Oak, Florida during spring s of 2005 and 2006 with selected INMPs created by a combination of preplant fertilizer source (C hicken L itter (CL) or 131.8 10.8), fertilizer rate (100% or 200%), and irri gation rat e (100% or 300%). The University of Florida/Institute of Food and Agricultural Sciences (UF/IFAS) recommended INMP was 100% Fertigation 100% Irrigation. CL as a preplant nutrient source increased early -yields and did not differ significantly fr om the UF/IFAS INMP for nutrient loads. 300% INMP reduced total fruit yields (9201242 25-

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12 lb cartons/acre), but did not differ significantly from the UF/IFAS INMP for nutrient loads. Based on the PBA, relative to the UF/IFAS INMP, 300% INMP not only increa sed the cost of the program ($17.18/acre), but also resulted in reduced returns ($1701/acre -$4112/acre). The effects of 200% fertigation rate on tomato plants varied with year Early and total tomato yields with UF/ IFAS and 200% INMP were not significantly different in both years The high fertigation alone INMP ( 200% Fertigation100% Irrigation ) resulted in highest total N load in 2006. Though statistically not significant, it also resulted in numerical higher net returns relative to the UF/IFAS INMP ($55/ acre $561/acre. We can conclude that CL can be used as an alternative preplant fertilizer source We can also conclude that growers should not use high irrigation/high fertigation high irrigation rates to ensure adequate soil moisture levels in the crop ro ot zone as it results in net losses relative to the UF/IFAS INMP. Instead, they should better manage irrigation water application.

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13 CHAPTER 1 INTRODUCTION Importance of Fresh Market Tomato Production in Florida Tomato ( Solanum lycopersicum L. ) production i n Florida accounts for approximately 39% of the national fresh market tomato production (Figure 2 1) and has an annual value of approximately $464 million (USDA NASS, 2008). Fresh market tomatoes are the number one vegetable crop in Florida (Figure 2 2) i n total harvested acres (37,80042,000 acres during 20052007) and total value ($464805 million during 20052007) In North Florida, fresh market tomatoes are typically grown as a spring crop with raised beds, black plastic mulch, drip irrigation, greenhouse -grown transplants (Olson et al., 2007), and harvested 2 4 times at the mature green stage to ensure highest quality (Sargent et al., 2005). Extensive research has been done to determine the fertilizer and irrigation requirements of drip irrigated plast ic mulched tomatoes. Placement, application scheduling, rate, and source, of N and K fertilizers are also known to affect fresh market tomato yields and quality. B ased on research, fertilizer recommendations for tomato production have been established in s everal states. The current base fertilization recommendations for tomato production in Florida on soils testing very low in Melich 1 P and K are 66 and 187 lb /acre of P and K F or nitrogen, the fertilization recommendation based on research and crop nutrie nt requirement is 200 lb /acre nitrogen (N), and includes a detailed fertigation schedule. A supplemental application of 30 and 17 lb/acre of N and K fertilizer is recommended after a leaching rain (3 inches of rainfall in 3 days or 4 inches in 7 days) even t (Olson et al., 2007). Statement of the Problem, Rational e and Significance Sand, gravel and muck soils are the major soil types in Florida. The majority of the fresh market tomato production in Florida is on sandy soils. These soils have low water holdi ng

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14 capacity ( Fares and Alva, 2000), and therefore to counteract this problem the tomato growers using drip -irrigat ion often over irrigate to maintain required soil moisture levels in the crop root zone. However, N -P -K fertilizers are highly water soluble and due to the excessive irrigation practices that the growers follow the nutrients are leached away from the crop root zone making them unavailable to the tomato plants. To counteract the loss of nutrients from the crop root zone, the growers generally t end to apply high rates of fertilizers to ensure adequate nutrient supply to the crop. This trend of excessive irrigation and fertilization has led to increased levels of nitrate and phosphate nutrient s in Floridas groundwater and fresh water bodies. Wit h the adoption of the Federal Clean Water Act (FCWA) in 1977 (US Congress, 1977), states are required to assess the impact of non point sources of pollution on surface and ground waters, and establish programs to minimize them. Section 303(d) of the FCWA a lso requires states to identify impaired water bodies and establish Total Maximum Daily Loads (TMDLs) for pollutants entering into these water bodies (FDACS, 2005; Gazula et al., 2007). One way of achieving TMDLs is through Best Management Practices (BMPs) BMPs are practices or combinations of practices determined by the coordinating agencies, based on research, field testing, and expert review, to be the most effective and practicable means, including economic and technological considerations, for improvi ng water quality in agricultural and urban discharges. As a result there has been an increased educational effort to encourage growers to follow the UF/ IFAS recommendations for fertilizer applications by improving irrigation management Because of the TMDL /BMP legislation and the importance of agriculture to the Florida economy, vegetable growers in the state need specific guidelines to comply with these new regulations and to remain competitive. Regulators also need science-based data that document the red uction in pollution achieved by BMP implementation

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15 Therefore, to better understand the impact of irrigation and nutrient management practices on fresh market tomato production, a series of experiments were conducted simultaneously with selected irrigati onnutrient management programs. The goal of these experiments was to determine the production, environment, and economic impact of selected irrigation -nutrient management programs.

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16 CHAPTER 2 REVIEW OF LITERATURE Importance of Best Management Practices, Total Maximum Daily Load, Florida Watershed Restoration Act The BMPs developed for vegetable crops grown in Florida are described in the manual titled "Water Quality/Quantity Best Management Practices for Florida Vegetable and Agronomic Crops". The manual, which is electronically accessible at http://www.floridaagwaterpolicy.com, was adopted by reference in Rule No 5M 8.004 of the Florida Administrative Code on February 8, 2006 (FDACS, 2008). The Florida Administrative Code is the official compilation of the rules and regulations of Florida regulatory agencies The purpose of this rule is to achieve pollutant reduction through the implementation of nonregulatory and incentive -based programs determined to reduce adverse impacts to Florida's water. BMPs are defined in s. 373.4595(2)(a), F.S. as "practices or combinations of practices determined by the coordinating agencies, based on research, field testing, and expert review, to be the most effective and practicable on -location means, including economical and technological considerations, for improving water quality in agricultural and urban discharges". The 5M 8 rule of the Florida Administrative Code (FDACS, 2008) includes information about the approved BMPs, presumption of compliance, notice of intent to im plement, and record keeping requirements The statutory benefits for enrolling in the BMP program are: (1) obtaining a presumption of compliance with water quality standards (s. 403.067 (7) (d) Florida Statutes.), (2) receiving a waiver of liability from t he reimbursement of cost and damages associated with the evaluation, assessment, or remediation of nutrient contamination of ground water (s. 376.307), and (3) eligibility for cost -share programs (s. 570.085 (1)). The BMP program for vegetables applies to the entire state of Florida, except for the Lake Okeechobee Priority Basin (under rule

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17 5M 3 F.A.C.) and the EAA and C 139 basin (under rule 40E 63, F.A.C.) where pre existing regulations are already in place. The BMP programs for all major agricultural com modities of Florida have been developed under the provisions of the 1999 Florida Watershed Restoration Act (FWRA .s. 403.067 F.S.). The FWRA specifically outlines the process for the Florida Department of Environmental Protection (FDEP, 2005a) to develop and implement total maximum daily loads (TMDLs) for impaired waters of the state. TMDLs are defined as the maximum amount of a pollutant that a body of water can receive and still meet the water quality standards as established by the Clean Water Act of 19 72. Section 303(d) of the Clean Water Act requires states to submit lists of surface waters that do not meet applicable water quality standards and to establish TMDLs for these waters on a prioritized schedule, "taking into account the severity of the poll ution and the uses to be made of such waters". The purpose of the FWRA was to better coordinate the numerous pollution control efforts that were implemented prior to 1999 and develop a standard to address future water quality issues. The FWRA requires tha t TMDLs be developed for all pollution sources agricultural and urban to ensure water quality standards are achieved. Once a TMDL is established for a pollutant in a watershed, a 5 -year implementation plan, also called basin management action plan (BMAP) is developed. BMAPs are the strategies for restoring impaired waters by reducing pollutant loadings to meet the allowable loadings established in a TMDL (FDEP, 2005b). The FWRA affects all Floridians; thus, in order to effectively implement the TMDL progr am, the FDEP coordinates its efforts with a variety of entities including the Florida Department of Agriculture and Consumer Services, the Water Management Districts, the local Soil and Water Conservation Districts, University of Florida Institute of Food and Agricultural Sciences

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18 (UF/IFAS), the environmental community, the agricultural community, and other concerned citizens. In theory, BMP measures are not laws and they are strictly voluntary. However, they need to be effective at improving water quality As part of the BMP implementation, growers perform an environmental assessment of their operations. This process identifies which BMPs should be considered to achieve the greatest economic and environmental benefit. The adopted BMPs may be a single pract ice or grouping of practices that, when implemented, are designed to improve water quality. The BMPs that are selected for each parcel of land with a tax ID are specified on a Notice of Intent to Implement and submitted to FDACS. If the practices are not y et implemented, the dates when they will be implemented are included on the Notice of Intent. Once enrolled in the BMP program, landowners must maintain records and provide documentation regarding the implementation of all BMPs ( e.g. fertilizer application dates and amounts or design and construction details of a water control structure). One of the most innovative elements of the FWRA and the associated agricultural BMP program is the Presumption of Compliance with water quality standards to landowners who voluntarily implement adopted BMPs that have been verified to be effective by FDEP. This component of the FWRA provides a powerful incentive to encourage landowners to enroll in BMP programs since landowners are protected from cost recovery by the state if water quality standards are not met. This unique approach to addressing water quality concerns has been well received by the environmental and agricultural communities alike and as a result is becoming the primary method for addressing water quality concerns. In addition, growers enrolled in the BMP program become eligible for cost -sharing funds to implement specific BMP practices.

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19 In 2009, the Florida Legislature will assess the success of this non regulatory program by examining the participation and enrolment of agricultural operations on a regional and commodity basis. By participating in BMP programs, growers are telling the Florida Legislature that the Florida agricultur al industry has endorsed the challenge to remain in business while minimizing e nvironmental impact. By making the BMP program a success, growers are also telling the Florida legislature that there is no need for a more stringent regulatory program. Factors Affecting Tomato Yield Extensive research has been done to determine the ferti lizer and irrigation requirements of drip irrigated plastic mulched tomatoes. Placement, application scheduling, rate, and source, of N and K fertilizers are also known to affect fresh market tomato yields and quality. With plastic mulched raised -bed tomat o production, Csizinsky (1979) reported significantly higher tomato yields when fertilizer was banded than when it was broadcasted. However, the reports on effects of placement of fertilizers on tomato yields are highly variable. In a study done by Cook an d Sanders, (1990), broadcast or banded placement of fertilizers had no effect on tomato fruit size, number or total yields. In a similar study done on fine sandy soils, the placement of fertilizer had no e ffect on marketable yields at one location H owever at the second location banded placement of fertilizers resulted in significantly higher marketable yields (Persaud et al., 1976). With drip irrigation on sandy soils, it has been shown that the highest tomato yields were obtained with 50% of N -K fertiliz er applied at preplant and the remaining through fertigation (Dangler and Locascio, 1990). Further work done by Locascio et al., (1985; 1989; 1997a) on application scheduling effects on N -K fertilizer s on tomato yields showed that the response varied with the soil type. On fine sandy soils, total early market yields, and total marketable tomato yields were highest with N -K applied 40% at preplant and 60% by fertigation, while on fine sandy loam and loamy fine sand soil types split applic ation of N -K fertilizer had no e ffect on

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20 tomato fruit yields. Persaud et al. (1976) showed that m ean yield increased linearly with an increase in N K rate Optimal rate of K for maximum tomato yields with drip irrigation and preplant broadcast application was in the range of 62125 lb/acre (Persaud et al., 1976) Crop water requirements may be determined based on U.S. Weather Service Class A pan evaporation. On fine sandy soils, f resh market tomato yields were significantly higher with irrigation volumes of 0.75 and 1.0 times pan evaporation than with higher irrigation volumes of 2.0 times pan evaporation and significantly lower with irrigation volumes 0.25 and 0.50 times pan evaporation (Locascio et al., 1981; Locascio and Smajstrla, 1996). However, the effect of irrigation r ate varied with rainfall during the season and also with soil type Fruit yields were significantly higher with irrigation during extremely dry seasons, while in extremely wet seasons, irrigation had no effect on fruit yield (Locascio et al., 1996) On co arse textured soils tomato yields were higher with 0.5 than with 1.0 times pan evaporation, and maximum yields were recorded at 0.75 times pan evaporation (Locascio and Smajstrla, 1989). On the other hand, on fine textured soils, yields were the same with 0.5 and 1.0 times pan evaporation (Locascio et al., 1989; Olson and Rhoads, 1992). The rate of water application (0.5 2.0 gallons/hr water applied/emitter) had no effect on tomato plant growth and yield. Increased frequency and reduced duration of daily irr igation resulted in increased tomato yields (Csizinsky and Overman, 1979). However, under similar conditions, increasing the frequency of irrigation had no effect on total tomato yields (Locascio et al., 1985). Nutrient Load and Tools for Determination of Nutrient Load Quantifying nutrient load from vegetable production systems is the first step towards monitoring and understanding groundwater pollution in the field. Nutrient load is defined as the mass of a chemical entering or leaving an area, and is calc ulated as the product of the volume of water that the chemical is transported in and the concentration of the chemical in the water (Rice

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21 and Izuno, 2001). Nutrient load can be determined indirectly or directly. The indirect approaches of measuring load in clude nutrient flow models (Kyllmar et al., 2005) and nutrient balances (born et al., 2003; Parris, 1998). Nutrient flow models are important tools for evaluating the impact of nutrient leaching on water quality at the watershed level, and play an importa nt role in designing agricultural and environmental policies. For example, nutrient models used for determination of N leaching from agricultural land can be classified into statistical regression models, and process -based models, such as ANIMO, SOILN, and DAISY (Kyllmar et al., 2005). Nutrient balances measure the difference between nutrient inputs into and outputs from an agricultural system (Parris, 1998), and can be used as a tool for sustainable nutrient management (born et al., 2003). However, they a re only an indirect indication of nutrient losses in the agro ecosystem (Oenema et al., 2003), and seldom allow the determination of nutrient loads at the field level. Knowledge of nutrient loads at the field level will be needed in the implementation of t he Total Maximum Daily Loads legislation (Federal Clean Water Act Section 303 d. (U.S. Congress, 1977)). The direct approaches to measuring load at the field level are resin traps, leachate lysimeters, or soil sampling (Table 2 1). The essential component s of resin traps are the ion exchange resins used to create nutrient filters, and the soil core (usually PVC pipes filled with soil) inside which the resins are buried (such as A400 anion exchange resin or C100 cation exchange resin, Purolite Co., Bala Cyn wyd, Pa.; Balkcom et al., 2001). Before starting the monitoring of nutrient leaching, resin traps are buried in the soil below the crop root zone. As water flows through the soil layer and the soil cores containing the resin trap, leached nutrients are int ercepted by ion exchange. After resin trap retrieval, nutrients are extracted and quantified. This method provides nutrient quantity intercepted by the surface of the resin trap which can be

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22 extrapolated to field size. The two main types of leachate lysime ters are suction cup lysimeters and drainage lysimeters (Abdou and Flury, 2004). Suction cup lysimeters consist of a porous ceramic tip connected to an air tight buried chamber that is accessible through two sealed tubes. Suction cup lysimeters are install ed below the crop root zone, usually between the 19.7 inch and 59.1 inch depths. Lysimeter operation generally consists of two steps. First, a soil -water sample is collected by creating a 5.8 to 7.3 PSI vacuum inside the chamber with a hand-held pump. Wate r moves from the soil into the chamber through the porous cup because of the difference in pressures. After approximately 24 hrs, samples a re retrieved using a vacuum pump (Webster et al., 1993). The leachate collected from these lysimeters i s from the soi l surrounding the porous ceramic tip, but the exact volume of soil it is collected from is unknown. Hence, this technique only gives the concentration of nutrients in solution and cannot be used alone to calculate a nutrient load. Further knowledge of the actual volume of soil the water i s collected from needs to be gained. In contrast to suction cup lysimeters, drainage lysimeters collect leachate f rom macropore flow o r when the soil above the lysimeter becomes saturated or exceeds the field capacity (Zhu et al., 2002) These lysimeters consist of two main components a collection container and a storage container. The collection container is any container filled with soil, and the storage container holds the leachate water from the collection container. D rainage lysimeters are installed below the crop root zone by digging holes in the ground. The storage container is installed below the collection container such that the water collected inside the collection container flows into the storage container by gra vity (Migliaccio et al., 2006), and the leachate that is collected inside the storage container is retrieved with a pump. Drainage lysimeters allow the measurement of both concentration and volume of nutrients being leached and thus can be used for load ca lculation at the field level. For leachate samples, load is calculated by

PAGE 23

23 multiplying nutrient concentration in each sub-sample (mg/L) by the volume of leachate collected, by the collection container volume ( feet3, Width Length Depth), and by a correct ion factor for unit homogeneity. Currently, there are no standard guidelines for the dimensions of the drainage lysimeter collection container, the fill inside the collection container (which also enhance collection efficiency), and the capacity of the sto rage container. Hence, generally cultural practices and availability of materials have dictated the design of a drainage lysimeter. Consequently, it is often difficult to separate treatment effects (cultural practices) from lysimeter effects in many resear ch reports. Ideally, a drainage lysimeter should have an optimum collection area where the collection container collects leachate from the entire root zone below crop root system being tested, and should account for plant to plant and emitter to emitter v ariability (in case of drip irrigation). Leachate collection efficiency may be calculated by dividing total leachate volume collected by total water applied for that time period (Zhu et al., 2002), and factors that may improve collection efficiency are the size of the collection container, and the presence of a wick. Previous work done with large plate lysimeters has shown that collection containers with collection surfaces of 0. 1 7 0. 5 4 to 2 .16 feet2Frequency of leachate collection and storage of l eachate samples are two other factors that may affect load measurement. According to David and Gertner (1987) the leachate collected in had increased collection efficiencies from 10%, 13%, to 26%36%, respectively (Radulovitch and Sollins, 1987). In a study comparing zerotension (leachate collected by free drainage) pan lysimeters and wick lysimeters installed at a depth of 51.2 inches below the soil surface (silt loam soil type) wick lysimeters collected 2.7 times more leachate than drainage lysimeters did, thereby increasing efficiency. The higher efficiency was attributed to the breaking of soil water tension by the wick (Zhu et al., 2002).

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24 the storage container should be retrieved at frequent intervals, multiple times a week, to minimize variability in withi n site nutrient concentration measurements and prevent changes in the chemical composition of the leachate. Significant increases in NH4N concentrations were reported at 68F due to mineralization reactions, and significant increases in NO3N concentratio ns were seen at 4 F and acidic pH due to oxidation of NO2 (Clough et al., 2001). If leachate samples are being stored before analysis, the optimum storage conditions are at 39.2 F without acidification. These conditions minimize transformations of NO2 t o NO3 -, and minimize overestimation of NO3 Soil sampling is another method for direct load measurement. Typically, a soil sample used for load determination consists of a 5 -feet deep soil core divided into five subs amples, each 1 -foot long. A known amount of distilled water is added to the sample to saturate it. After thorough mixing of the sample, chemical extraction or analysis is performed. Generally, t he NH concentrations (Clough et al., 2001). 4N and NO3N concentrations in soil samples are d etermin ed using modified EPA method 350.1 and EPA method 353.2 respectively (USEPA, 1993). The chemical concentrations are then converted to original field water content basis (Ahmed et al., 2001). Nutrient load is then calculated by multiplying nutrient concentr ation in each sub -sample (mg/kg soil) by the wetted soil volume ( feet3, Width Length Depth), by soil bulk density (assumed to be homogenous), and by a correction factor for unit homogeneity. The bulk density of soils can be measured in the laboratory ( USDA, 2004), or soil bulk density estimates may be found in soil survey reports published by the Natural Resources Conservation Service (USDA -NRCS, 2008). The length (total L of mulched bed per unit area) and depth (length of the soil sub-sample) of the we tted soil volume are well know n However, width estimates of the wetted soil volume are not well known and may vary with the irrigation program and soil type. Moreover, factors which affect the

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25 volume of the wetted zone, such as soil physical properties an d their spatial variability, initial moisture content, width of raised plant bed, and irrigation length (Clark and Smajstrla, 1993; Santos et al., 2003; Simonne et al., 2005; Simonne et al., 2006) also affect the width of wetted zone. Farneselli et al. (20 08) reported estimates of mean ( 28.7, 23.6, 18.5, 13.4 and 8.3 inches for the 5.9 18.1, 29.9, 42.1 and 53.9 inch depths, respectively), and maximum ( 40.9, 33.1, 25.2, 17.3, and 9.8 inches for 1 -foot depth increments) wetted widths that can be used for c alculating mean and maximum nutrient loads from raised plant beds. However, their results were based on a single irrigation event without a crop, and depending on either the mean, bed or maximum wetted width, could result in nutrient load from 193 5 lb/acr e On the other hand, as there are no reported estimates of actual in -field wetted widths for different crop species, the mean and maximum wetted width estimates reported by Farneselli et al. (2008), and the bed width of the raised plant bed are currently the best estimates of wetted widths in Florida sandy soils. A great number of similarities exist in the methods and sampling procedures used for collecting or monitoring nutrient concentrations. Also, the construction design of lysimeters, and the methodol ogy of soil sampling procedures are explained in great detail. However, when nutrient concentrations are converted from mg/kg (for soil sampling) and mg/L (for lysimeters) to nutrient loads on a per a c re basis ( aerial or cropped), most articles do not giv e a detailed methodology of load calculation (Abad et al., 2004; Aparicio et al., 2008; Daudn and Qulez, 2004; Lecompte et al., 2008; Macaigne et al., 2008; Oikeh et al., 2003; Poudel et al., 2002; Ramos et al., 2002; Rajput and Patel, 2006; Sainju et al., 1999; Vzquez et al., 2006; Yaffa et al., 2000; Zotarelli et al., 2008; Zvomuya et al., 2003). With soil sampling as a method to monitor nutrient leaching, several reports do not convert the NO3N concentration in the soil samples to NO3N load on per a cre basis (Daudn and

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26 Qulez, 2004; Macaigne et al., 2008 ; Poudel et al., 200 2 ; Rajput and Patel, 2006; Yaffa et al., 2000). While some of the reports that measure NO3N load with soil sampling on per unit area basis mention both the NO3N analytical proce dure and the soil bulk density values ( Halvorson et al., 2002; Zvomuya et al., 2003), some mention just the NO3N analytical procedure used (Abad et al., 2004; Sainju et al., 1999), and others mention neither the NO3-N analytical procedure used nor the soi l bulk density values (Oikeh et al., 2003). For NO3N load calculated using drainage lysimeters, while Syvertsen and Jifon (2001) ga ve the dimensions of the lysimeters used, they failed to report the NO3N analytical procedure and reported their results as NO3N concentration/lysimeter rather than NO3N load on per unit area basis. For bell pepper production on plasticulture system, Romic et al. (2003) on the other hand reported NO3N load measured with drainage lysimeters on per unit area basis. However th ey failed to mention whether the NO3With suction cup lysimeters (SCL), where drainag e cannot be estimated directly assumptions are made that the volume of water retrieved by applying a vacuum i s equivalent to the drainage water volume. Aparicio et al. (2008) calculated NO N load values reported are on a cropped or aerial area basis. 3N losses with the following equation, NL = DC/100, where NL is the NO3N losses at various soil depths, D is drainage water estimated using the LEACH -W model, and C is the NO3N concentration (analytical method not mentioned) in the soil solution extracted with the SCL. Vzquez et al. (2006), Zhu et al. (2005), and Zvomuya et al. (2003) on the other hand estimated NO3N losses from each sampling interval as the product of NO3N concentration i n the soil solution and the amount of drainage. Vzquez et al. (2006) and Zvomuya et al. (2003) calculated drainage with the following equation, D = P+I -E, where D is the amount of daily drainage, P is the precipitation, I is the irrigat

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27 consecutive days, and E is the evapotranspiration. However, Zhu et al. (2005) measured drainage directly using modified lysimeters. The three publications also varied in their methodology fo r analyzing NO3N concentrations. While Vzquez et al. (2006) estimated NO3N concentration in the soil solution samples spectrophotometrically after reduction in cadmium solution (Keeney and Nelson, 1982), Zhu et al. (2005) estimated NO3N concentration i n the soil solution samples colorimetrically with the Bran and Luebbe Model TRAACS 2000 continuous -flow analyzer. On the other hand Zvomuya et al. (2003) used the diffusion-conductivity method (Carlson et al., 1990) to estimate NO3Factors Affecting Nutrient Load N concentration in the s oil solution samples. As mentioned earlier, with suction cup lysimeters drainage cannot be measured directly. Nutrient load or leaching is influenced by several natural and cultural factors. Some of the natural factors are climate, hydrology, soil characteristics, and topography, and some of the cultural factors are tillage, mulching, fertilization (type of fertilizer, rate, placement, and timing of application) and irrigation (quantity, rate, frequency, and method of applic ation) management. Factors that affect nutrient load or leaching (natural and cultural factors) also affect the variations in N leaching. Climatic conditions and fertilization affected variations in NO3N leaching by 65%, crop rotations by 20 25% (Krysa nova and Haberlandt, 2002), fertilizer inputs alone affected variations in NO3N leaching by 40% (Mertens and Huwe, 2002), and agricultural land management affected variations in N leaching by 48% (Schmidt et al., 2008). Hengsdijk and van Ittersum (2001) showed the uncertainties associated with future modeling of NO3N leaching losses as functions of crop characteristics, yield levels, and crop residue nitrogen to be 36% and +70%, 30% and +40%, and 64% and +67%, respectively. A study done by David and Gertner (1987) to identify the s ources of variation in soil solution collected by tension plate lysimeters found that the CV for volume of leachate and NO3N concentration

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28 measured during the study was 122% and 218% respectively. Moreover, they found that the variability in volume and NO3N concentration recorded within a site, soil horizon, and pit, over each period of time accounted for 18% and 15% of total variability, the variability in volume and NO3N concentration within a period of time re -measurem ent accounted for 55% and 32% of the total variability, and variation in pits within a site accounted for 50% of the total variability for NO3Conclusion and Objectives N concentration. Hansen et al. (1999) found that variability in agricultural land management resulted in CV rangi ng from 20% to 40%. Due to variability in N -load results with location, cropping system, and soil type site specific in-field load estimates are the best predictors of total N load. However, very few estimates of nutrient load from agricultural production are available in Florida (Ta ble 2 2 ). Moreover, as previously mentioned, the information on in -field nutrient load lacks consistency in method of measurement, and there is no mention of the wetted width used in conversion of nutrient concentrations from so il and leachate samples into nutrient load on a per -hectare basis. Extensive research has been done to determine the fertilizer and irrigation requirements of drip irrigated plastic mulched tomatoes and detailed methodology and research work is available for determination of nutrient load from different vegetable s However, due to variability in N l eaching results with location, cropping system, and soil type site specific in -field load estimates are the best predictors of total N l eaching Currently very few estimates of nutrient load from agricultural production are available in Florida, and the research information on in -field nutrient load lack consistency in method of measurement. Moreover, there are no research reports on the economic impact of the fertilizer and irrigation BMPs on fresh market tomato production. Therefore, to better understand the impact of irrigation and nutrient management practices on fresh market tomato production, by using an integrated fertilization/irrigation approach, a

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29 series of experiments were conducted simultaneously with selected irrigation nutrient management programs. The goal of these experiments was to determine if BMPs ( UF/ IFAS recommendations) can minimize the negative impact of vegetab le production ( fertilizer losses and inefficient irrigation) on the environment while maintaining or improving current yields and crop value of an economically important vegetable crop fresh market tomatoes ( Solanum lycopersicum L.). The specific objecti ves of this study were to Determine the effects of the irrigation and nutrient management program s on moisture levels in tomato beds, on plant nutritional status (NO3 -N and K+ Determine the combined and i ndividual effects of irrigation and nutrient management program s on tomato seasonal total N load and soil -profile total N load as measured with drainage lysimeters and with soil sampling, and determine the relationship between seasonal total -N load and soi l -profile total N load measured with soil sampling and with drainage lysimeters (Chapter 4) ), and fresh market tomato production (Chapter 3) Determine the economical impact of irrigation -nutrient management programs on tomato crop yields (Chapter 5) .

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30 Table 2 1. Advantages and limitations of different p rocedures used for measuring nutrient loads. Resin Traps Soil Sampling Suction Cup Lysimeters Drainage Lysimeters Advantages Small structures Easy to install and simple to build Require minimal labor for collecting samples Not space bound Simple procedur e Permanent structures Easy to install and simple to build Require minimal labor for collecting samples Permanent structures Simple to build Require minimal labor for collecting samples Give both concentration and volume Limitations Space bound Capture lower volumes of leachate than actual underestimate load Need to be installed every season Gives only concentration and not volume Require intensive labor for collecting samples Leaves hole in ground Space bound Gives only concentration and not volume Protracted sampling time Interfere with tillage Space bound Lack universal design Hard to install Disturb soil profile Might interfere with tillage Require constant maintenance

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31 Table 2 2. Published estimates of nitrogen (nitrate, ammonium and total N ) leaching in selected crops. Crop Soil Type Location Method z Estimate Original Unit Standardized N Load Estimate t Reference (lb/acre) Artichoke Loam Spain y SS 287 406 NO 3 kg/ha N 256 363 Ramos et al., 2002 Carrot Loamy sand California RT 0.97 NO 3 N 0.26 NH 4 mg/kg of soil N 0.87 0.23 Allaire Leung et al., 2001 Cauliflower Loam Spain y SS 168 272 NO 3 kg/ha N 150 243 Ramos et al., 2002 Corn Silt Loam Argentina SCL x 0 94 NO 3 kg/ha N 0 84 Aparicio et at., 2008 Corn Silt Loam Loam California SS 14 62 mineral N mg/kg of soil u 19 83 Poudel et al., 2002 Corn Fine loamy Nigeria SS 13 114 mineral N kg/ha 12 102 Oikeh et al., 2003 Corn Silty Clay Loam Spain SS 1 14 NO 3 mg/kg of soil N 1.3 19 Daudn & Qulez, 2004 Corn Sandy Washington M 3 28 NO 3 kg/h a N 3 25 Peralta and Stockle, 2001 Onion Clay Loam Colorado SS 25 286 NO 3 kg/ha N 2 2 255 Halvorson et al., 200 2 Onion Sandy Loam India SS 25 95 NO 3 mg/kg of soil N 34 127 Rajput and Patel, 2006 Onion Loam Spain y SS 198 474 NO 3 kg/ha N 177 423 Ramos et al. 2002 Orange Fine Sand Florida DL 174 252 mineral N g/lysimeter NE Syvertsen and Jifon, 2001 s Potato Loamy Sand Minnesota SS SCL 20 58 mineral N 4 228 NO 3 kg/ha kg/ha N 18 52 4 204 Zvomuya et al., 2003 Potato Loamy Sand Canada SS 8 120 NO 3 mg/kg N 1 1 161 Macaigne et al., 2008 Potato Loam Spain y SS 60 308 NO 3 kg/ha N 54 275 Ramos et al., 2002 Potato Sandy Washington M 3 69 NO 3 kg/ha N 3 62 Peralta and Stockle, 2001 Tomato Silt Loam Loam w California SS 26 42 mineral N mg/kg of soil 35 56 Poudel et a l., 2002 Tomato Calcareous w Spain SCL 155 421 NO 3 kg/ha N 138 376 Vzquez et al., 2006 Tomato Sandy Loam France SS 50 800 mg/L NE Lecompte et al., 2008 Tomato Sandy Loam Georgia SS 10 110 mineral N mg/kg of soil 13 147 Yaffa et al., 2000 Tomato Sandy L oam Georgia SS 7 250 NO 3 kg/ha N 6 223 Sainju et al., 1999 Tomato Sand Florida SS DL SCL 5 30 NO 3 N 5 37 NO 3N 3 4 NO3 kg/ha kg/ha kg/ha N 4.5 27 4.5 33 2.7 3.6 Zotarelli et al., 2007 Bell Pepper Gleysol hydroameliorated Croatia DL 1 16 NO 3 kg /ha N 0.9 14 Romic et al., 2003

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32 Table 2 1. Continued Crop Soil Type Location Method Estimate Original Unit Standardized N Load Estimate t Reference (lb/acre) Bell Pepper Sand Florida SS DL SCL 9 38 NO 3 N 6 37 NO 3 N 2 21 NO 3 kg/ha kg/ha kg/ha N 8 34 5 33 1.8 19 Zotarelli et al., 2007 Hot Pepper Sandy Loam China SCL 17 54 NO 3 g/m N NE 2 Zhu et al., 2005 Wheat Loam Spain SS 54 1211 NO 3 kg/ha N 48 1081 Abad et al., 2004 Zucchini Sand Florida SS DL SCL 21 34 NO 3 N 2026 NO 3 N 11 15 NO 3 kg/h a kg/ha kg/ha N 19 30 1823 10 13 Zotarelli et al., 2007 Zucchini Sand Florida SCL 2 45 NO v 3 kg/ha N 1.8 40 Zotarelli et al., 2008 z SS Soil Sampling, RT Resin Traps, SCL Suction Cup Lysimeters, M Modeling with CropSyst, DL Drainage Lysimeters y L oam, sandy loam, clayey loam x D rainage estimated with LEACH_W model w Processing tomato v W ater collected by drainage into container u Mineral nitrogen (NO3 -N+NH4 +N) t N load estimates calculated based on 2 -feet bed width and 1450 lb/feet3 soil bulk density. s NE: Not estimable based on information in original report.

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33 Figure 2 1. Fresh market tomato p roduction in the United States A ) harvested area and B) value of production in $1,000,000. A Tomato Production States California Florida Other States Tomato Production in the U.S. (Harvested Acres) 0 10000 20000 30000 40000 50000 B Tomato Production States California Florida Other States Value of Tomato Production in the U.S. ($1,000,000) 0 200 400 600 800 1000 2005 2006 2007

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34 Figure 2 2. Vegetable production in Florida A ) harvested are a, and B) value of production ($1,000,000). A 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 45,000 Bell pepper Potato Snap bean Strawberry Sweet corn Tomato Watermelon Other Vegetables Vegetable Production in Florida Harvested Area (Acres ) 2005 2006 2007

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35 Figure 2 2. Continued B 0 100 200 300 400 500 600 700 800 900 Bell pepper Potato Snap beans Strawberry Sweet corn Tomato Watermelon Other Vegetables Vegetable Production in Florida Value of Production ($1,000,000) 2005 2006 2007

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36 CHAPTER 3 NUTRIENT MANAGEMENT PROGRAMS FOR FRESH M ARKET TOMATOES GROWN WITH PLASTICULTURE I N THE ERA OF BEST MA NAGEMENT PRACTICES I. SOIL MOISTURE, PLANT NUTRITIONAL STATUS, AND YIELD DI STRIBUTION Introduction Tomato ( Solanum lycopersicum L. ) production in Florida accounts for approximately 39% of the national fresh market tomato production, and has an annual value of approximately $464 million (USDA -NASS, 2008). In North Florida, fresh m arket tomatoes are typically grown as a spring crop with raised beds, black plastic mulch, drip irrigation, and greenhouse -grown transplants (Olson et al., 2007) Moreover, the fruit are harvested 2 4 times at the mature green stage to ensure highest quality (Sargent et al., 2005). Extensive research has been done to determine the fertilizer and irrigation requirements of drip irrigated plastic mulched tomatoes. Placement, application scheduling, rate, and source, of N and K fertilizers are also known to af fect fresh market tomato yields and quality. Csizinsky (1979) reported significantly higher tomato yields when placement of fertilizers was banded than broadcasted. However, the reports on effects of placement of fertilizers on tomato yields are highly var iable. In a study done by Cook and Sanders, (1990), broadcast or banded placement of fertilizers had no effect on tomato fruit size, number or total yields. In a similar study done on fine sandy soils, the placement of fertilizer had no e ffect on marketabl e yields at one location H owever at the second location banded placement of fertilizers resulted in significantly higher marketable yields (Persaud et al., 1976). With drip irrigation on sandy soils, the highest tomato yields were obtained with part of N -K fertilizer s applied at preplant and the remaining through fertigation (Dangler and Locascio, 1990; Locascio and Myers, 1975). Further work done by Locascio et al., (1985; 1989; 1997a) on application scheduling effects on N -K fertilizer s on tomato yields showed that the response varied with the soil type. On fine sandy soils, total early market yields, and total marketable

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37 tomato yields were highest with N -K applied 40% at preplant and 60% by fertigation, while on fine sandy loam and loamy fine sand soil types split application of N -K fertilizer s had no affect on tomato fruit yields. Mean yield increased linearly with an increase in N -K rate (Persaud et al., 1976).Optimal rate of K for maximum tomato yields with drip irrigation and preplant broadcast appli cation was in the range of 62.251 24.5 lb/acre. Crop water requirements may be determined based on U.S. Weather Service Class A pan evaporation. F resh market tomato yields were significantly higher with irrigation volumes of 0.75 and 1.0 times pan evaporat ion than with higher irrigation volumes of 2.0 times pan evaporation and significantly lower with irrigation volumes lower than 0.25 and 0.50 1.0 times pan evaporation (Locascio et al., 1981; Locascio and Smajstrla, 1996). However, the effect of irrigation rate varied with rainfall during the season and also with soil type Fruit yields were significantly higher with irrigation during extremely dry seasons, while in extremely wet seasons, irrigation had no effect on fruit yield (Locascio et al., 1996) On coarse textured soils tomato yields were higher with 0.5 than with 1.0 times pan evaporation, and maximum yields were recorded at 0.75 times pan evaporation (Locascio and Smajstrla, 1989). On the other hand, on fine textured soils, yields were the same wit h 0.5 and 1.0 times pan evaporation (Locascio et al., 1989; Olson and Rhoads, 1992). The rate of water application (0.5 2.0 gallons/hr water applied/emitter) had no effect on tomato plant growth and yield. Increased frequency and reduced duration of daily irrigation resulted in increased tomato yields (Csizinsky and Overman, 1979). However, under similar conditions, increasing the frequency of irrigation had no effect on total tomato yields (Locascio et al., 1985). Based on research and soil testing, fertil izer recommendations for tomato production have been established in several states in the United States. The current base fertilization

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38 recommendations for tomato production in Florida on soils testing very low in Melich 1 P and K are 66 and 187 lb /acre of P and K, and for nitrogen the fertilization recommendation based on research and crop nutrient requirement is 200 lb /acre nitrogen (N), and includes a detailed fertigation schedule. A supplemental application of 30 and 1 7 lb/acre of N and K fertilizer is recommended after a leaching rain (3 inches of rainfall in 3 days or 4 inches in 7 days) event (Olson et al., 2007). For irrigation management the it is recommended to have a target water volume (gallons/100 ft/day) to a djust irrigation water volume based on weather and plant age to f ine tune schedule by monitoring soil moisture levels, to k now how much water the root zone can store to k now the role of rain in supplying water to the vegetable crop and to k eep records (Simonne et al., 2007). The poultry industry in the U.S. has an annual value of $32 billion, and the poultry industry in Florida has an annual value of $270 million (USDA NASS, 2008). The major production areas are located in the south eastern United States (Alabama, Arkansas, Georgia, Miss issippi, North Carolina, and Virginia). The a nnual market weight of poultry production in the U.S. is approximately 58 billion pounds (USDA -NASS, 2008) which in-turn yields 29 41 billion pounds of poultry litter (Mitchell and Donald, 1999). Poultry litte r which comprises bird feces, bedding material, feathers, and remains of feed, is not only a good source of the plant macro nutrients N, P, K, calcium, magnesium, and sulfur, but is also a source of some of the micro nutrients like boron, copper, iron, man ganese, and zinc (Mitchell and Donald, 1999). The N -P -K ratios in poultry litter vary from region to region and also with the type of litter. Based on the reported N -P -K ratios, N ranged from 1.3 6%, P 1.13%, and K 1 2 % in layer litter (Mitchell and Dona ld, 1999; Nicholson et al., 1996), and N ranged from 36%, P 2 3%, and K 2 3% for broiler/turkey litter (Mitchell and Donald, 1999; Nicholson et al., 1996; Stephenson et al., 1990).

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39 Poultry litter can be transported cost effectively up to a distance of 164 miles from the production facility (Paudel et al., 2004). With the increasing cost of inorganic fertilizers, poultry litter can be used as a viable alternative fertilizer source by agricultural enterprises within the 164mile radius. Higher (20 to 36%) tomato fruit yields have been obtained with chicken litter (CL) than with inorganic fertilizers (Brown et al., 1995; Togun and Akanbi, 2003). Moreover, tomatoes grown with CL had earlier fruit set and development, and larger fruit size than those grown with inorganic fertilizers (Brown et al., 1995). Studies have also shown that CL (75%) along with inorganic fertilizers (25%) resulted in higher yields than CL or inorganic fertilizer alone (Ramadan, 2007). At the same time, work done by Ghorbani et al., (2008) showed no significant difference in tomato fruit yields when grown with CL or with inorganic fertilizers. However, they reported lower disease incidence and higher marketable yields after 6 weeks in storage with CL (14,288 lb /acre) than with inorganic fer tilizer (6,251 lb /acre ). Previous work done by Studstill et al. (2006), on the viability of CL as a preplant fertilizer in muskmelon production, found that depending on the muskmelon cultivar, total marketable yields may be increased by 15%. However, CL ha d no effect on muskmelon early marketable yields. Besides its use as a fertilizer source, studies have also shown that CL (Kaplan and Noe, 1993; Riegel et al., 1996) and CL combined with soil solarization suppress root knot nematodes ( Meloidogyne arenaria and incognita) (Kaskavalc, 2007; Stevens et al., 2003). Growers generally apply poultry litter at rates that supply the crops entire N requirement, resulting in over application of either P or K Most of the soils in Florida have high P levels and crops o ften do not respond to P application (Carrijo and Hochmuth, 2000; Hochmuth et al., 1993a, 1993b; Locascio et al., 1996; Rhoads et al., 1990; Rhue and Everett, 1987; Shuler and Hochmuth, 1995). However, for soils testing very -low, low, and medium in Melich 1 P, the current Univ. of Florida/IFAS Extension

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40 Service (IFAS) recommendations for P ferti lizat ion is broadcast application of all P in the at preplant (Olson et al., 2007). Therefore, there is considerable potential for CL as a preplant fertilizer source to supply only part of the N requirement, and no more than the 22 lb/acre of P as starter amount. G iven the low water holding capacity of Floridas coarse textured soils the dripirrigating fresh market tomato growers oftentimes over irrigate to maintain adequate moisture levels within the plant root zone N P -K fertilizers are highly water soluble, and as growers mismanage the irrigation water application, they generally tend to over -fertigate to compensate the loss of nutrients from the plant root zone With the adoption of the Federal Clean Water Act (FCWA) of 1977 (US Congress, 1977), states are required to assess the impact of non point sources of pollution on surface and ground waters, and establish programs to minimize them. Section 303(d) of the FC WA also requires states to identify impaired water bodies and establish Total Maximum Daily Loads (TMDLs) for pollutants entering into these water bodies (FDACS, 2005; Gazula et al., 2007). The TMDLs are implemented through Best Management Practices (BMPs) As a result there has been an increased educational effort to encourage growers to follow the IFAS recommendations for irrigation and fertilizer applications. Therefore, t he objectives of this study were to 1) determine the effect of irrigation rate on moisture levels in the tomato beds 2) determine the effect of the irrigation -nutrient management programs on plant nutritional status (NO3 -N and K+), 3) determine the effect of CL used as a preplant fertilizer source on fresh market tomato yield, and 4) assess the combined and individual effects of irrigation nutrient management programs on marketable fresh market tomato yield

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41 Materials and Methods A two -year experiment was conducted at the N orth F lorida Research and E ducation Center S uwannee V alley in Live Oak, Fla. on BlantonFoxwort -Alpin Complex soil series (Weatherspoon, 2006) during 2005 and 2006. Similar cultural practices were followed during both years. Drainage lysimeters were installed at 2 -feet depth in March, 2004 under the raised plant beds for all irrigation -nutrient management programs to monitor nutrient leaching from all treatments (results reported in Chapter 4 ). Preliminar y data collected from the lysimeters in 2004 had high CV therefore a modified drainage lysimeter design was added p rior to the start of the ex periment in March, 2005. Experimental Setup A winter rye ( Secale cereale L.) crop was planted in the fall of both 2004 and 2005 at the rate 50 lbs of seed/acre. The winter rye crop was rototilled two weeks before field preparati on. The field was prepared by disking and plowing the soil, after which the beds were tracked in the soil. Preplant fertilizer treatments CL and 131.8 10.8 (standard fertilizer blend) at the rate of 50 and 41.5 lbs of N -K /acre (50% of the total N in the C L is available the first year to supply 30% of the N recommended rate preplant were applied as the source preplant fertilizers at bed preparation to the respective treatments. The CL had a N -P -K analysis of 1.251.121.66 and 1.251.5 1.91 respectively in 2005 and 2006 respectively. CL was applied to the same plots each year. The field was then bedded (with 6 -ft centers), fumigated with methyl bromide, and then drip tape was laid followed by black plastic mulch. Separate drip tapes were installed for the ir rigation and nutrient management programs. The irrigation and fertigation system was installed after 14 days of field preparation. The main irrigation and fertigation line ran through the middle of the field and at the head of all plots. Each experimental plot (unit) consisted of three one hundred and fifty foot -long raised plasticulture beds formed on 6 -ft centers The large plot size

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42 was chosen for implementation of the current trial, to test for leaching of nutrients with drainage lysimeters (data report ed separately), and to represent grower field conditions. On April 8th, 2005 and April 5thThe standard flow rate used by growers in the area was used for supplying the irrigation. The 100% and 300% irrigation rate was achie ved by installing one and three drip tapes to the respective experimental plots ( 24 gph/100-ft /hr at 12 psi (12 in emitter spacing ; John Deere Water Tech nologies San Marcos, CA)). Separate drip tapes were also installed for fertigation. For the 100% and 200% fertigation rate one and two drip tapes were installed respectively. Based on the irrigationnutrient management program, the total number of drip ta p es in each program ranged from 2 to 5. Based on the volume of water applied, daily irrigation was applied either as a single application or split application (two times per day). For the 100% FertigationCL 100% Irrigation, 100% Fertigation100% Irrigation, 200% Fertigation100% Irrigation irrigation -nutrient management programs which received 100% irrigation rate, the total amount of irrigation water applied per acre was 439,085 gallons or 16.17 acre -inches. For the 100% Fertigation 300% Irrigation, 200% Fertigation 300% Irrigation, and 200% Fertigation300% Irrigation -ML irrigation -nutrient management programs which received 300% irrigation rate, the 2006 6-week old (Days After Transplanting (DAT) = 0) Florida 47 transplants w ere transplanted on to th e plasticulture system with a 18 in within row spacing, and e stablishing plant a population of 5,808 plants /acre. The irrigation -nutrient management programs were a combination of source of preplant fertilizer, fertilizer rate, and irrigation rate (Table 3 1). The current IFAS recommendation for N and K for commerci al tomato production was used as the 100% fertigation rate and twice that amount for the 200% fertigation rate. Split application of fertilizer treatments through the drip tape was done weekly throughout the growing season

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43 total amount of irrigation water applied per acre was 1,317,254 gallons or 48.51 acre inches. As fertigati on and irrigation were applied either on a weekly or daily basis, the amount of fertilizer or water to be applied at any given time tends to have very narrow differences between them with narrow differences in rate treatments. Therefore, for this experimen t we chose the standard IFAS rate and much higher rates of fertilizer and irrigation management to ensure that even with the split application of the treatments there would still be a large difference within them on a daily basis. T he detailed fertigation and irrigation s chedule for the different irrigation -nutrient management programs are shown in Figures 3 1 and 3 2. Current recommendations for commercial tomato production for pest and disease control and all other production practices were followed (Olso n et al., 2007). Data Collection Irrigation v olume d ata: Two water meters were installed on the sub -main irrigation lines which combined to form the main irrigation line running through the middle of the experimental field. Water meters were read weekly to calculate amount of water applied and to monitor the water flow rate in the main irrigation lines. Soil moisture data: Soil volumetric water content (VWC) was monitored weekly at 8:00 a m before the first daily irrigation cycle for a total of ten sampli ng times during the entire crop growth cycle, using Time Domain Reflectometry (TDR) moisture probes (Hydrosense; Campbell Scientific, Logan, UT). Readings were taken at 6 inches from the drip tape on the opposite side of the tomato plants from the three rows of each experimental unit. The sampling dates were 6, 13, 20, 28, 34, 41, 48, 55, 62, and 69 DAT in 2005, and 22, 29, 36, 44, 49, 57, 63, 71, 78, and 85 DAT in 2006. Based on the plant growth stage the sampling days were categorized as vegetative and re productive stages, which corresponded to the plant growth stage before and after flowering respectively. In 2005, four VWC readings were taken during the vegetative stage (14, 21, 28

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44 April and 6 May), and six VWC readings were taken during the reproductive stage (12, 19, 26 May and 2, 9, 16 June). In 2006, two VWC readings were taken during the vegetative stage (27 Petiole s ap data: Plant nutritional status was monitored with petiole fresh sap analysis t hr ee times for both years (4, 7, 9 WAT in 2005, and 5, 9, 11 WAT in 2006). Ten petioles from recent fully expanded leaves were collected from each plot. Petioles were then cut into 0.4 in sections, crushed with a garlic press, and two to three drops of sap w ere placed on the sensor pads of two ion specific electrode meters (Cardy, Spectrum Technologies, Plainfield, IL) for determination of NO April, 3 May), and seven VWC readings were taken during the reproductive stage (18, 23, 31 May and 6, 14, 21, 28 June). Based on soil moisture r elease curve for sandy soils, soil moisture levels were classified as very dry if the VWC readings taken were 0 4%, dry 5 8%, optimum 9 12%, and too wet when >13%. 3 -Yield data : Twenty -foot long sections located in the middle bed and representa tive of each experimental unit were marked for yield measurements. Mature green t omatoes were harvested at 66, 74, 81, and 88 DAT in 2005, and at 65, 85, and 91 DAT in 2006 and fruits were then graded as extra large, large, medium, and culls (USDA, 1991). The tomato fruits in each grade were counted and then weighed. Weight of fruits from each grade were then converted to 25 -lb carton/acre (A) by multiplying with the factor 17.44 (fruit weights from raised bed plots 20 -feet long on 5 -feet centers and with 1 3 plants each at 18 inch within row spacing were converted into fruit weights from 1 acre raised beds on 5 -feet centers and 5 808 plants at 18 inch within row N and K concentrations (Hochmuth, 1994) Both meters were calibrated at the beginning of the experiment and for ever y 20 samples using standard solutions provided with the meters (Studstill et al., 2006). The press and the meters were rinsed with deionized water and dried between each sample.

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45 spacing ) in order to compare the total yields with yields reported by growers. Total marketable y ield was calculated as the sum of extra -large, large, and medium grades. Total season yields were calculated as the sum of yields from all harvests and early season yields were calculated as the sum of first and second harvest yields (Locascio et al., 1985). Data Analysis The experimental design was a randomized complete block design with four replications. Soil VWC, petiole NO3 -N, and K+Results and Discussion concentration s, and m arketable yield responses to irrigation nutrient management programs were determined using ANOVA and treatment means were compared using Duncans multiple range test (SAS, 2008). The orthogonal contrasts Nitrogen rate (100% vs 200%), Preplant fertilizer source (CL vs Inorganic Fertilizer), and Irrigation rate (100% vs 300%) were used to test the significance of the difference between rate of fertilizer applied, source of preplant fertilizer, and irrigation rate. Weather Conditions Th e monthly average air temperatures and monthly average rainfall were different for 2005 and 2006. From April to July, 2005 t h e monthly average air temperatures were relatively lower than normal for North Florida (Figure 3 3 A ). During 2006 the monthly average air temperature for April was normal, while from May to July they were lower than normal for North Florida (Figure 3 3 A ). Cumulative weekly average maximum and minimum temperatures were relatively higher in 2006 and comparatively lower in 2005 (Figure 3 3 B). Rainfall was relatively higher than seasonal levels during April, June, July, and was lower than normal in May 2005. During 2006 rainfall was relatively lower than normal in April, May, July, and higher than normal in June (Figure 3 3 C). Rainfall events of more than 1 inch during 2005 occurred on 22, 58, 64, 65, 82, and 86 DAT recording 1. 83, 1.44, 1.66, 1.04, 2.46, and 2.35 inches, respectively,

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46 and accounted for 59% of total rainfall recorded from April 8 to July 5, 2005. During 2006 rainfall events of more than 1-inch occurred on 3, 57, 68, 69, and 81 DAT recording 1.28, 1.59, 1.6, 2.25, and 1.47 inches, respectively and accounted for 67% of total rainfall recorded from April 5 to July 5, 2006 (FAWN, 2008). Since the rainfall events mentioned above did not meet the leaching rainfall amounts of 3 inches of rainfall in three days or 4 inches in seven days (Olson et al., 2007) the plots did not require supplement al fertilizer application. Based on the above weather information, 2005 was a relatively cooler and wet year, while 2006 had normal temperatures for North Florida. However, in 2006 t he early part of the tomato growing season (April -May) was dry while the latter part was wet (June July). Raised Plant Bed Soil Moisture For soil VWC at 6 inches from the drip tape t he interaction year x treatment was significant for most of the growth s tages ( p < 0.01). Therefore the data from both years were analyzed separately. In 2005, the irrigation-nutrient management programs did not have a significant effect ( p 0.20) on soil moisture levels during the vegetative stage and the reproductive stages In 2006, though the irrigation-nutrient management programs had a significant effect ( p 0.22) on the VWC in the raised plant bed, the actual number of days that the treatments differed by were very minimal (1 day during the vegetative stage, and 1 2 da ys during the reproductive stage) (Table 3 2.). These results suggest that increasing the irrigation management from 100300% did not result in a substantial increase in soil moisture levels within the plant bed. Similar study done by Locascio et al. (1989) found higher soil moisture levels with higher irrigation levels (1.0 times pan evaporation) than with lower irrigation levels (0.5 times pan evaporation) (6 7% by weight versus 3.5 4.8% by weight). Although, the higher irrigation resulted in higher soil moisture levels, significantly higher yields were recorded with the lower irrigation treatment (Locascio et al., 1989).

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47 Tomato Plant Petiole Sap NO3 -The interaction year x treatment was significant ( p < 0.01) for all the growth stages when p etiole s ap NO -N Concentration 3 -N c oncentration s were measured. Therefore the data from both years were analyzed separately. In 2005, highest petiole sap NO3 -N concentrations were seen for 200% Fertigation 1 00% I rrigation treatment at first open flowers stage, 100% Fer tigation -CL 100% Irrigation and 200% Fertigation 100% Irrigation treatments at fruits two inch diameter stage, and 100% Fertigation -CL 1 00% I rrigation treatment at first harvest stage (Figure 3 4 A ). The orthogonal contrasts N rate (100% vs 200%) and prepla nt fertilizer source (CL vs 131.8 10.8) were not significant for all three growth stages. However the orthogonal contrast between irrigation rate (100% vs 300%) was significant for all three growth stages ( p that irrigation rate and not fertilizer rate or preplant fertilizer source affected the changes in petiole NO3 -N c oncentration s (Figure 3 4A ). Based on the calculated means for 100% and 300% irrigation, the petiole NO3 -N concentratio ns were significantly higher ( p lower irrigation rate of 100% (1558, 728, 711 mg/L NO3 -N at first open flowers, fruits two -inch diameter, and first harvest growth stages respectively) than at the higher irrigation rate of 300% (1242, 389, 347 mg/L NO3 In 2006, highest petiole sap NO N) at first open flowers, fruits two -inch diameter, and first harvest growth stages times respectively). 3 -N concentrations were seen for 100% FertigationCL, 1 00% I rrigation treatment at first open flowers stag e ( p < 0.01). At first harvest stage 100% Fertigation -CL, 1 00% I rrigation treatment and 200% Fertigation 1 00% Irrigation treatment recorded the highest petiole sap NO3 -N petiole sap concentrations ( p < 0.01). However, at the second harvest stage the treatm ents did not vary significantly in their petiole sap NO3 -N concentrations ( p = 0.30). At first open flowers and first harvest growth stages the orthogonal contrasts between preplant fertilizer source (CL vs 131.8 10.8), fertigation rate (100% vs

PAGE 48

48 300%), a nd irrigation rate (100% vs 300%) were all significant, suggesting that the changes in the petiole sap NO3 -N concentrations were affected by all three factors i.e. fertilizer rate, irrigation rate, and source of preplant fertilizer The average daily temp eratures were relatively highe r in 2006 than in 2005 (Figure 3 3 A ) which may have attributed to the difference in the plant response to the treatments during the two years. In 2005, petiole sap NO3 -N concentrations were diagnosed as insufficient (Hochm uth, 1994) 200% Fertigation300% I rrigation and 100% Fertigation300% I rrigation treatments at fruits two inch diameter stage, and for 100% Fertigation 300% I rrigation treatment at first harvest stage, which were all high -irrigation treatments. Similarly, in 2006, all three treatments with highirrigation (300%) which were 100% Fertigation300% Irrigation, 200% Fertigation300% Irrigation, and 200% Fertigation300% Irrigation -ML had petiole sap NO3 -N concentrations which were diagnosed as insufficient at first open flowers and second harvest growth stage. At first harvest growth stage both 100% Fertigation300% Irrigation and 200% Fertigation 300% Irrigation -ML treatments had petiole sap NO3 -N concentrations which were diagnosed as insufficient. These results suggest that irrigation rate, more than fertilizer rate affected the concentration of NO3 -N in tomato petiole sap and an increase in irrigation rate resulted in lower petiole sap NO3 -Tomato Plant Petiole Sap K N concentrations (Figure 3 4A ). These results also suggest that instead of managing nutrients and irrigation separately, better plant nutrition can be achieved by combining the nutrient and irrigation management. +The interaction year x treatment was significant ( p < 0.05) for all the growth stages when p etiole s ap K Concentration + c oncentrations were measured. Therefore the data from both years were analyzed separately. In 2005, the petiole sap K+ concentrations did not vary with trea tments at all three growth stages (first open flowers, fru its two inch diameter and first harvest, respectively).

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49 In 2006, highest K+ concentrations in the plant were seen with 100% FertigationCL 1 00% I rrigation treatment at all three growth stages ( p <0.03 respectively). The orthogonal contrasts between prepl ant fertilizer sources (CL vs 131.8 10.8) were significant for all three growth stages ( p <0.01). Moreover, the calculated means for CL (4800, 4425, 5200 mg/L of K+) were higher than the means for 131.8 10.8 (4125, 3750, 3155 mg/L of K+) for all these gr owth stages, suggesting that the high K+ concentrations recorded in the petiole with the 100% Fertigation -CL, 100% I rrigation treatment were a result of the preplant fertilizer source treatment. At first harvest stage the orthogonal contrasts for all three comparisons fertigation rate (100% vs 300%), preplant fertilizer source (CL vs 13 1.8 10.8), and irrigation rate (100% vs 300%) were significant (Figure 3 4 B) In 2005, the K+ concentrations recorded in the plant at first open flowers growth stage were d iagnosed as insufficient for all treatments (Hochmuth, 1994). At fruits twoinch diameter growth stage except for the 200% Fertigation100% Irrigation treatment all the other treatments had K+ concentrations higher than the sufficiency range. At first ha rvest growth stage all the treatments had K+ concentrations higher than the sufficiency range. In 2006, all the treatments at all the three growth stages had K+ concentrations higher than the sufficiency ranges (Figure 3 4B ). The results varied with year, depending on the growing conditions the changes in the petiole sap K+ In 2006, CL as a p replant fertilizer source resulted in significantly higher K concentrations were affected either by irrigation treatments or by all three factors i.e. fertilizer rate, irrigation rate, and source of preplant fertilizer source. + concentrations in the plant. In both 2005 and 2006, the calculation of the amount of CL applied to the respective treatment plots was based on the amount of N present in it. However, as the CL u sed in the experiment had higher levels of K ( CL N -K analysis for 2005 and 2006 was 1.25 2.0

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50 and 1.66 1.91 respectively) than N, higher amount of K was applied with the CL than with the other five irrigation -nutrient management program ( 24.9 and 34.86 lb h igher in 2005 and 2006 respectively). Although the effects of this higher amount of K from the CL were not seen in 2005 (a relatively cool and wet year), the higher K in the CL irrigation -nutrient management program resulted in significantly higher levels of K+ concentration in the tomato plants in 2006 (a relatively hot and dry year). In 2006, a cumulative effect of increased fertigation (200%) was seen by the first harvest stage, higher petiole K+ concentrations were recorded with the higher (200%) than w ith the lower (100%) fertigation management program. This increase in petiole sap concentration with increase in fertilizer corresponds to similar results reported by Locascio et al., (1997b) where significant linear increase in leaf K+Tomato Yield and Grade Distribution concentration with increase in K rates were seen. As th e interaction year x treatment was significant for most of the harvests and grade distributions ( p < 0.05), data were analyzed separately by year. Total marketable tomato yields rec or ded in 2005 ranged from 1,2421,883 25lb cartons /acre, and in 2006, the total marketable tomato yields ranged from 9201,424 25lb cartons /acre. Total marketable tomato yields recorded in 2005 were relatively higher than the yields recorded in 2006. Early Fruit Yield: Early marketable fruit yields were influenced by treatme nt during 2005 and 2006 (Table 3 3). In 2005, highest early marketable fruit yields were obtained with 100% Fertigation -CL, 1 00% Irrigation treatment (1,127 25lb carton /acre), and no si gnificant differences were found between the remaining five irrigation nutrient management programs. Based on orthogonal contrasts, in 2005, early marketable fruit yields were not significantly affected by fertigation rate ( p = 0.89) (100% and 200%) and ir rigation rate ( p = 0.21) (100% and 300%). Further, there were no significant differences between the IFAS irrigation-fertigation

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51 program (100% Fertigation100% Irrigation) and increased fertigation program ( 200% Fertigation 100% Irrigation) for early yield s. However, early marketable fruit yields varied significantly ( p = 0.03) with preplant fertilizer source, fruit yields higher by 211 25lb cartons were recorded with CL than with inorganic fertilizer source 13 1.8 10.8. As previously discussed, the CL pre plant program supplied higher amount of P and K. These higher amounts of nutrients might have resulted in significantly higher early marketable yields. In 2006, highest early marketable fruit yields were obtained with 200% Fertigation 100% Irrigation tre atment (1,219 25lb carton /acre ), and lowest yields were recorded with100% Fertigation -CL, 1 00% Irrigation treatment (826 25lb carton /acre). Based on the orthogonal contrasts, early marketable fruit yields were not significantly influenced by irrigation ra te ( p = 0.31) (100% and 300%). However, preplant fertilizer source had a significant effect on early marketable fruit yields ( p = 0.02). Yields were higher by 276 25lb cartons with inorganic fertilizer source 13 1.8 10.8 than with CL. Moreover, fertigatio n rate also had a significant effect on early marketable fruit yields ( p = 0.04), yields were higher by 169 25lb cartons with 200% rather than with the 100% fertigation rate. However, similar to 2005, there were no significant differences between the IFAS irrigation -fertigation program (100% Fertigation 100% Irrigation) and increased fertigation program ( 200% Fertigation 100% Irrigation ) for early yields. Total Season Fruit Yields: In 2005 and 2006, treatment had a significant effect ( p < 0.01) on the tota l marketab le yield (all harvests) (Table 3 3). In 2005, highest total marketable yields were seen with 1 00% Fertigation -CL, 100% Irrigation (1,883 25lb carton /acre) and the lowest with 1 00% Fertigation 300% Irrigation treatment (1,242 25lb carton /acre). Based on the orthogonal contrasts, preplant fertilizer source (CL and 13 1.8 10.8) and fertigation rate (100% and 200%) did not have a significant effect on total marketable yields ( p = 0.49 and 0.09 respectively).

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52 Similar to the early yield results, there were no significant differences between the IFAS irrigation -fertigation program (100% Fertigation 100% Irrigation) and increased fertigation program ( 200% Fertigation 100% Irrigation ) for total yields. However, irrigation rate (100% vs 300% ) had significant effect on total marketable yields ( p <0.01), yields were higher by 337 25lb cartons with 100% rather than with the 300% irrigation rate. In 2006, highest total marketable yields were seen with 200% Fertigation 100% Irrigation treatment (1,424 25lb ca rtons ) and lowest yields were recorded with 100% Fertigation 300% Irrigation treatment (920 25lb cartons ). Based on the orthogonal contrasts, preplant fertilizer source (CL and 131.8 10.8) did not have a significant effect on total marketable yields ( p = 0.86). However, fertigation rate (100% and 200%) and irrigation rate (100% and 300% ) had a significant effect on total marketable yields ( p = 0.0 3 and p <0.01 respectively). Yields were higher by 197 25lb cartons with 200% rather than with the 100% ferti gation rate, and higher yields (by 280 25lb cartons) were recorded with lower irrigation rate of 100% than with the higher rate of 300%. However, there were no significant differences between the IFAS irrigation -fertigation program (100% Fertigation 100% Irrigation) and increased fertigation program ( 200% Fertigation 100% Irrigation ) for total yields. I n 2006, t he tomato transplants in CL treatment plots showed symptoms of burn damage during the 1st and 2nd week after transplanting The CL used in 2005 and 2006 had very similar nutrient analysis. However, as the electrical conductivity information was not reported for both the sample s it was found later that the CL was aged in 2005 while the CL used in 2006 was unaged. This burn damage might have affected the early tomato yields in 2006, resulting in a significant reduction in total early marketable tomato yields when compared to the same preplant programs results in 2005.

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53 Based on the results from both years, preplant fertilizer source did not have a si gnificant effect on total marketable tomato yields, which was contrary to Studstill et al.s (2006) findings with CL as a preplant fertilizer source in muskmelon. Moreover, with fresh market tomatoes, depending on the age of the CL used as a preplant ferti lizer source, early marketable yields may be increased by +18%. Although irrigation rate (100% and 300%) did not have a significant effect on early yields, based on the results from both years, the total marketable yields were significantly lower (by 280337 25lb cartons /acre) with the higher irrigation of 300%. The percentage of early marketable fruits in 2006 were significantly higher ( p = 0.03) with 100% than with 300% irrigation rate, and the percentage of total marketable fruit in 2005 were signifi cantly higher with 100% than with 300% irrigation rate ( p < 0.01). These results suggest that the higher irrigation rate may have resulted in higher number of defective fruits (Table 3 3). These results also suggest that in a relatively cool and wet year ( 2005) the higher irrigation rate (300%) results in a significant reduction in the total season percentage of marketable fruits, and in a relatively hot and dry year (2006) the higher irrigation rate (300%) results in a significant reduction in the total ea rly percentage of marketable fruits. As a consequence of the loss in marketable fruits, the total season yields from both years were lower with the high irrigation rate of 300%. These results were similar to previous research on fine sandy soils where higher season yields were reported with irrigation at 0.5 rather than with 1.0 times pan evaporation (Kafkafi and Bar Yosef, 1980; Locascio et al., 1981; Locascio et al., 1989). Fresh market tomato yield response to fertilizer rate varied with year. In 2005, a relatively cool and wet year, there were no significant differences between the 100% and 200% fertilizer rates for early and total season yield response. Moreover, there were no significant

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54 differences between the IFAS irrigation -fertigation program (100 % Fertigation 100% Irrigation) and the increased fertigation program ( 200% Fertigation 100% Irrigation ) for early and total fruit yields. However in 2006, a relatively warm and dry year, significantly higher yields were recorded with the 200% than the 100% fertilizer rate for both early and total season yields. These results suggest that the response of fresh market tomato yield to fertilizer rates varies with the climatic conditions from one year to the next. Similar variability in yield responses to ferti lizer rates with climatic conditions has also been reported by other research (Rhoads et al., 1999). Conclusion The effects of irrigation -nutrient management programs were evaluated on raised plant bed soil moisture levels, tomato plant petiole NO3N and K+ concentrations, and yield and grade distribution of fresh market tomatoes grown with plasticulture. The results from this study suggest that CL resulted in highest early -yields T herefore CL can be used as an alternative fertilizer source at preplant. T he study also looked at the effects o f increased irrigation management program on tomato production. Applying higher irrigation (300%) reduced water stress in the plant bed for only for 1 2 days during the cropping cycle. However, it also resulted in insu fficient NO3 -N and K+ petiole concentrations, which further result ed in lower total fruit yields. Therefore, i f increased irrigation water application is needed, approaches that increase the irrigation time (such as lower flow rate or lower drip tape ope rating pressure or more cycles throughout the day) should be used. The effects of fertigation rates on tomato plants varied with year. The higher fertigation rate (200%) did not have any significant effect on plant nutrient levels and tomato yields. Furthe r, early and total tomato yield responses to the IFAS irrigation fertigation program (100% Fertigation 100% Irrigation) and the increased fertigation program (200% Fertigation 100% Irrigation) were not significantly different in both years However, in a relatively hot -dry year, the higher fertigation rate significantly increased early and total

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55 marketable tomato fruit yields. We can conclude that over irrigating has a negative impact on tomato production and tomato plant response to fertilizer rates varies with growing conditions.

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56 Table 3 1. Irrigation -nutrient (N -P -K) management programs for spring 20052006 Florida 47 fresh market tomato production with raised bed plasticulture system. Irrigation Nutrient Management PrePlant Fertilization Injected Fer tigation Total Number Programs Source Amount (lb /acre ) Source Amount (lb /acre ) Amount (lb /acre ) Rate (%) z 2005 1 100% Fertigation CL y CL ,100% Irrigation 50 44.7 66.4 8 0 6.6 x 186 0 154 236 44.7 242 100 x 2 100% Fertigation, 100% Irrigation 13 1.7 10 .7 50 6.8 41.5 8 0 6.6 186 0 154 236 6.8 195.5 100 3 100% Fertigation, 300% Irrigation 13 1.7 10.7 50 6.8 41.5 8 0 6.6 186 0 154 236 6.8 195.5 100 4 200% Fertigation, 100% Irrigation 13 1.7 10.7 50 6.8 41.5 8 0 6.6 371 0 307 421 6.8 348.5 200 5 200% Fer tigation, 300% Irrigation 13 1.7 10.7 50 6.8 41.5 8 0 6.6 371 0 307 421 6.8 348.5 200 6 200% Fertigation, 300% Irrigation ML 13 1.7 10.7 w 50 6.8 41.5 8 0 6.6 371 0 307 421 6.8 348.5 200 2006 1 100% Fertigation CL, 100% Irrigation CL 50 59.8 92 8 0 6.6 186 0 154 236 59.8 217 100 2 100% Fertigation 100% Irrigation 13 1.7 10.7 50 6.8 41.5 8 0 6.6 186 0 154 236 6.8 195.5 100 3 100% Fertigation 300% Irrigation 13 1.7 10.7 50 6.8 41.5 8 0 6.6 186 0 154 236 6.8 195.5 100 4 200% Fertigation 100% Irrigation 1 3 1.7 10.7 50 6.8 41.5 8 0 6.6 371 0 307 421 6.8 348.5 200 5 200% Fertigation 300% Irrigation 13 1.7 10.7 50 6.8 41.5 8 0 6.6 371 0 307 421 6.8 348.5 200 6 200% Fertigation 300% Irrigation ML 13 1.7 10.7 50 6.8 41.5 8 0 6.6 371 0 307 421 6.8 348.5 200 z Because the treatments were only applied to the injected portion of the N -K nutrient management program, the program rates were labeled as 100% and 200% although they were 100% and 175% of the total N -K applied. y For program 1 00% Fertigation CL, 100% Irri gation the source of the preplant fertilizer was chicken litter. The other programs had 131.7 10.7 as the source of preplant fertilizer. x The N P -K analysis of the CL was different in 2005 and 2006 (1.251.121.66 and 1.25 1.5 1.91 respectively). Therefo re, the total N -P -K applied at preplant with the CL varied from 2005 and 2006. In 2005 the N P -K amount was 50 44.766.4 lb, while in 2006 it was 50 59.892 lb. w An additional program for estimating nitrate load using drainage lysimeters installed in the ground was carried out at the same time as the current study. The lysimeters installed under programs 100% Fertigation-CL, 100% Irrigation 100% Fertigation 100% Irrigation 100% Fertigation300% Irrigation 200% Fertigation 100% Irrigation and 200% Ferti gation 3 00% Irrigation were of the same design, and the lysimeters installed under the program 200% Fertigation 3 00% Irrigation ML were modified (ML) in design and varied from the above lysimeters. To maintain the integrity of the predetermined programs da ta from 200% Fertigation 3 00% Irrigation and 200% Fertigation 3 00% Irrigation -ML (which received the same above ground programs) were not combined.

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57 Table 3 2. N umber of sampling days when soil volumetric water content ( % ) at 6 inches from the drip tape w as between 0 4, 5 8, 9 12, and > 13% for fresh market tomatoes grown in 2005 and 2006 on BlantonFoxworth-Alpin Complex soil series z The vegetative stage corresponds to the plant stage before flowering. During 2005 there were four VWC readings rec orded during the vegetative stage (14, 21, 28 April and 6 May), and during 2006 there were two VWC readings recorded during the vegetative stage (27 April, 3 May). y The reproductive stage corresponds to the plant stage after flowering. During 2005 there w ere six VWC readings recorded during the reproductive stage (12, 19, 26 May and 2, 9, 16 June), and during 2006 there were seven VWC readings recorded during the reproductive stage (18, 23, 31 May and 6, 14, 21, 28 June). No of Sampling Days Vegetative Stage Reproductive Stage z y Irrigation Nutrient Management Programs 0 4 % 5 8 % 9 12 % >13 % 0 4 % 5 8 % 9 12 % >13 % 2005 x 100% Fertigation w CL v 1 ,100% Irrigation 3 1 0 2 4 0 0 100% Fertigation, 100% Irrigation 1 3 1 0 2 4 0 0 100% Fertigation, 300% Irrigation 1 3 1 0 1 4 0 0 200% Fertigation, 100% Irrigation 1 3 1 0 2 4 0 0 200% Fertigation, 3 00% Irrigation 1 3 1 0 1 5 0 0 200% Fertigation, 300% Irrigation ML 1 u 3 1 0 2 4 0 0 p values: Program 1.00 0.25 0.25 0.00 0.3 1 0. 37 0. 20 0 00 2006 100% Fertigation CL,100% Irrigation 1 .2 c 1 .3 b 1 .4 ab 1 .2 a 2 .1 b 3 .3 ab 0.5 bc 0 100% Fertigation, 1 00% Irrigation 2 .3 a 2 .4 a 0 .3 c 0 .0 b 1.8 bc 4 .3 a 0 .0 c 0 100% Fertigation, 300% Irrigation 1 .3 bc 2.8 a 0.8 bc 0 .1 b 0.5 d 4 .4 a 1 .0 ab 0 200% Fertigation, 100% Irrigation 2 .8 b 2.9 a 0 .3 c 0 .0 b 3 .3 a 2 .4 b 0 .3 bc 0 200% Fertigation, 300% Irrigation 1 .4 bc 2 .3 a 1 .3 ab 0 .0 b 0.6 d 3.7 a 1.7 a 0 200% Fertigation, 300% Irrigation ML 1 .2 c 2 .1 a 1.8 a 0 .0 b 0.8 d 3.7 a 1.5 a 0 p values: Program 0.38 < 0. 01 0.02 <0.01 <0.01 0. 06 0.04 0. 22 Irrigation Contrast Means 1 00% 0.06 1.28 0.39 0.28 3. 39 4.03 0.47 0.11 3 00% 0.06 1.22 0.72 0 .00 0.92 5.08 1.94 0.06 p value s: Irrigation Contrast 1.00 0. 74 0.02 < 0.0 1 <0.01 0. 03 <0.01 0.5 2

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58 x The interaction term for year x treatment was significant for the effect of treatment on n umber of sampling days when soil volumetric water content ( VWC ) at 6 inches from the drip tape was between 0 4, 5 8, 912, and greater than 13% (p Therefore the data from both years were analyzed separately. w Fertigation : Nitrogen Potassium rate v For program 100% Fertigation CL,1 00% Irrigation the source of the preplant fertilizer was chicken litter, while the rest of the programs had 131.8 10.8 as the source of preplant fertilizer. u An additional program for estimating nitrate load using drainage lysimeters installed in the ground was carried out at the sa me time as the current study. The lysimeters installed under programs 100% Fertig ation -CL, 100% Irrigation 100% Fertigation 100% Irrigation 100% Fertigation300% Irrigation 200% Fertigation 100% Irrigation and 200% Fertigation 3 00% Irrigation were of the same design, and the lysimeters installed under the program 200% Fertigation 3 0 0% Irrigation ML were modified (ML) in design and varied from the above lysimeters. To maintain the integrity of the predetermined programs data from 200% Fertigation 3 00% Irrigation and 200% Fertigation 3 00% Irrigation -ML (which received the same above gr ound programs) were not combined.

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59 Table 3 3 Effects of irrigation and nutrient management programs on Florida 47tomato fruit yield s ( 25-lb carton /acre) during spring of 2005 and 2006zIrrigation Nutrient Management Program Early Marketable 25lb carto n /acre Percent Early Marketable (%) y Total Marketable 25lb carton /acre Percent Total Marketable (%) x 2005 100% Fertigation w CL v 1,127 a ,1 00% Irrigation 92 a 1,883 a 84 ab 100% Fertigation 100% Irrigation 916 b 92 a 1,783 ab 84 a 100% Fertigation 3 0 0% Irrigation 800 b 87 b 1,242 c 78 c 200% Fertigation 1 00% Irrigation 831 b 89 ab 1,820 ab 82 abc 200% Fertigation 3 00% Irrigation 904 b 92 a 1,556 b 80 bc 200% Fertigation 3 00% Irrigation ML 959 ab u 92 a 1,677 ab 81 abc p values: Program 0.02 0.03 <0 .01 0.02 Contrast Preplant source (CL vs 131.8 10.8) 0.03 0.87 0.49 0.88 Contrast Fertigation rate (100% vs 200%) 0.89 0.62 0.09 0.82 Contrast Irrigation Rate (100% vs 300%) 0.21 0.43 <0.01 <0.01 2006 100% Fertigation -CL 1 00% Irrig ation 826 c 80 ab 1,291 ab 64 100% Fertigation 100% Irrigation 1,102 ab 76 bc 1,271 ab 64 100% Fertigation 3 00% Irrigation 866 bc 72 c 920 c 63 200% Fertigation 1 00% Irrigation 1,219 a 83 a 1,424 a 67 200% Fertigation 3 00% Irrigation 1,086 abc 78 abc 1,161 abc 71 200% Fertigation 3 00% Irrigation ML 1,000 abc 77 abc 1,064 bc 68 p values: Program <0.01 0.02 <0.01 0.12 Contrast Preplant source (CL vs 13 1.8 10.8 ) 0.02 0.26 0.86 0.97 Contrast Fertigation rate (100% vs 200% ) 0.04 <0.01 0.03 0. 03 Contrast Irrigation Rate (1 00% vs 3 00% ) 0.31 0.03 <0.01 0.12

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60 z The interaction term for year x irrigation and nutrient management program was significant for fruit yields ( p data from both years were analyzed separately. y Means followed by different letters within each column are significantly different at the 0.05 level, according to Duncans multiple range test. x Percent early and total marketable y ields were calculated by dividing the early and total marketable yields by total early (early marketable + early culls) and total total yields (total marketable + total culls). w Fertigation : Nitrogen Potassium rate v For program 100% Fertigation CL,1 00% Irrigation the source of the preplant fertilizer was chicken litter, while the rest of the programs had 131.8 10.8 as the source of preplant fertilizer. u An additional program for estimating nitrate load using drainage lysimeters installed in the ground was carried out at the same time as the current study. The lysimeters installed under programs 100% Fertigation-CL, 100% Irrigation 100% Fertigation 100% Irrigation 100% Fertigation300% Irrigation 200% Fertigation 100% Irrigation and 200% Fertigation 3 00% Irrigation were of the same design, and the lysimeters installed under the program 200% Fertigation 3 00% Irrigation ML were modified (ML) in design and varied from the above lysimeters. To maintain the integrity of the predetermined programs data from 200% Fertigation 3 00% Irrigation and 200% Fertigation 3 00% Irrigation -ML (which received the same above ground programs) were not combined.

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61 Figure 3 1. N fertigation (lb/acre) schedule used in the 20052006 fresh market tomato pro duction experiment A) w eekly, and B) cumulative. (Note: the i rrigation and nutrient management programs we re 1) 100% Fertigation-CL, 100% Irrigation 2) 100% Fertigation 100% Irrigation 3) 100% Fertigation 300% Irrigation, 4) 200% Fertigation 100% Irrigati on, 5) 200% Fertigation300% Irrigation and 6) 200% Fertigation 300% Irrigation -ML ) A Days After Transplanting 0 7 14 21 28 35 42 49 56 63 70 77 84 Weekly N Fertigation (lb/A) 0 10 20 30 40 Programs 1,2,3 Programs 4,5,6 B Days After Transplanting 0 7 14 21 28 35 42 49 56 63 70 77 84 Cumulative N Fertigation (lb/A) 0 100 200 300 400 500 Programs 1,2,3 Programs 4,5,6

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62 Figure 3 2. Irrigation (1000 gallons/acre) schedule for spring 20052006 Florida 47 fresh market tomato production with raisedbed plasticulture system. A) Weekly, an d B) cumulative. (Note: the irrigation and nutrient management programs were 1) 100% Fertigation -CL, 100% Irrigation, 2) 100% Fertigation100% Irrigation, 3) 100% Fertigation 300% Irrigation, 4) 200% Fertigation100% Irrigation, 5) 200% Fertigation 300% Irr igation, and 6) 200% Fertigation300% Irrigation-ML). 2D Graph 2 Days After Transplanting 0 7 14 21 28 35 42 49 56 63 70 77 84 Cumulative Irrigation Schedule (1000 gallons/A) 0 200 400 600 800 1000 1200 1400 Programs 1,2,3 Programs 4,5,6 B A Days After Transplanting 0 7 14 21 28 35 42 49 56 63 70 77 84 Weekly Irrigation Schedule (1000 gallons/A) 0 50 100 150 200 Programs 1,2,3 Programs 4,5,6

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63 Figure 3 3. Historical and 20052006 weather patterns during tomato growing season in Live Oak, FL (April July) A) monthly average temperatures (F). B) cumulative w eekly temperatures (F), and C) monthly average rainfall (inches) (Note: the weather information was obtained from The Southeast Regional Climate and the Florida Automated Weather Network). B Weeks After Transplanting 0 2 4 6 8 10 12 14 16 Cumulative Degrees (F) 0 2000 4000 6000 8000 10000 Cumulative Minimum 2005 Cumulative Minimum 2006 Cumulative Minimum 1971-2000 Cumulative Maximum 2005 Cumulative Maximum 2006 Cumulative Maximum 1971-2000 A North Florida Tomato Production Months April May June July Monthly Average Temperatures (F) 0 20 40 60 80 100 1971-2000 2005 2006

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64 Figure 3 3 Continued North Florida Tomato Production Months April May June July Average Monthly Rainfall (inches) 0 2 4 6 8 10 12 1971-2000 2005 2006 C

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65 Figure 3 4 Effects of irrigation and nutr ient management programs on petiole sap concentrations recorded for the different program s and the sufficiency ranges recommended for the corresponding growth stages during 2005 and 2006 A) NO3 -N and B) K+ (Note: the irrigation and nutrient management programs were 1) 100% Fertigation -CL 100% Irrigation 2) 100% Fertigation 100% Irrigation 3) 100% Fertigation 300% Irrigation 4) 200% Fertigation 100% Irrigation 5) 200% Fertigation 300% Irrigation 6) 200% Fertigation300% Irrigation -ML, and 7) Sufficie ncy Range). 2005 Crop Stage 1st Open Flowers Fruits 2-in. Diameter 1st Harvest Petiole NO3 --N Concentration (mg/L) 0 200 400 600 800 1000 1200 1400 1600 1800 2000 1 2 3 4 5 6 7 2006 1st Open Flowers 1st Harvest 2nd Harvest A a ab b b b b a a ab ab ab b a ab bc cd cd d a b d b c d a b c a c c a a a a a a

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66 Figure 3 4. Continued 2005Crop Stage 1st Open Flowers Fruits 2-in. Diameter 1st Harvest Petiole K + Concentration (mg/L) 0 1000 2000 3000 4000 5000 6000 1st Open Flowers 1st Harvest 2nd Harvest 1 2 3 4 5 6 7 2006B a b b b b b a b bc bcd cd d a b b b b b

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67 Figure 3 5. Distribution of tomato fruit grades for the early yields during the 2005 and 2006 growing seasons. (Note: the irrigation a nd nutrient management programs were 1) 100% Fertigation -CL 100% Irrigation, 2) 100% Fertigation 100% Irrigation, 3) 100% Fertigation 300% Irrigation, 4) 200% Fertigation100% Irrigation, 5) 200% Fertigation300% Irrigation, and 6) 200% Fertigation 300% Irrigation -ML). 2005 Irrigation-Nutrient Management Programs 1 2 3 4 5 6 Early Yield (25-lbs carton/acre) 0 200 400 600 800 1000 1200 1400 1600 2006 1 2 3 4 5 6 Total Marketable X-Large Large Medium a b b b b ab a c ab bc abc abc a a b b ab ab a b b b b ab b c b b a ab b ab c a bc bc

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68 Figure 3 6 Distribution of tomato fruit grades f or the total s eason yields during the 2005 and 2006 growing seasons. (Note: the irrigation and nutrient management programs were 1) 100% Fertigation CL 100% Irrigation 2) 100% Fertigation100% Irrigation 3) 100% Fertigation300% Irrigation 4) 200% Fertigation 100% Ir rigation 5) 200% Fertigation300% Irrigation and 6) 200% Fertigation 300% Irrigation -ML). 2005Irrigation-Nutrient Management Scenarios 1 2 3 4 5 6 Season Yield (25-lbs carton/acre) 0 500 1000 1500 2000 2006 1 2 3 4 5 6 Total Marketable X-Large Large Medium a abcab b ab a bc a b c ab ab a abc bc ab bcc aa c bc bc a c ab abc ab a c ab bc bc c ab ab c a abc ab a a c c

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69 CHAPTER 4 NUTRIENT MANAGEMENT PROGRAMS FOR FRESH MARKET TOM ATOES GROWN WITH PLASTICULTURE I N THE ERA OF BEST MANAGEMENT P RACTICES II. DETERMINATION OF NUT RIENT L OAD Introduction Quantifying nutrient load from vegetable production systems is the first step towards monitoring and understanding groundwater pollution in the field. Nutrient load is defined as the mass of a chemical entering or leaving an area, and is c alculated as the product of the volume of water that the chemical is transported in and the concentration of the chemical in the water (Rice and Izuno, 2001). Fresh market tomatoes are grown with intensive fertilization and irrigation practices, and given the low water holding capacity of Floridas sandy soils, there is an increased risk of contaminating the groundwater with plant nutrients. In 2007, Florida accounted for 39% of the national fresh market tomato ( Solanum lycopersicum L. ) production with a value of $464 million (USDA NASS, 2008). Fresh market tomatoes are the number one vegetable crop in Florida in total harvested acres (37,80042,000 acres during 20052007) and total value ($464805 million during 20052007) Nutrient load can be determined indirectly or directly. The indirect approaches of measuring load include nutrient flow models (Kyllmar et al., 2005) and nutrient balances (born et al., 2003; Parris, 1998) The direct approaches to measuring load at the field level are resin traps (Balk com et al., 2001), leachate lysimeters, or soil sampling (Ahmed et al., 2001). The two main types of leachate lysimeters are suction cup lysimeters and drainage lysimeters (Abdou and Flury, 2004). Drainage lysimeters collect leachate f rom macropore flow o r when the soil above the lysimeter becomes saturated or exceeds the field capacity (Zhu et al., 2002) These lysimeters consist of two main components a collection container and a storage container. The collection container is any container filled with so il, and the storage container hold s the leachate water from

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70 the collection container. D rainage lysimeters are installed below crop root zones The storage container is installed below the collection container such that the water collected inside the collection container flows into the storage container by gravity (Migliaccio et al., 2006) and the leachate that is collected inside the storage container is retrieved with a pump. Drainage lysimeters allow the measurement of both concentration and volume of nu trients being leached and thus can be used for load calculation at the field level. For leachate samples, load is calculated by multiplying nutrient concentration in each sub-sample (mg/L) by the volume of leachate collected, by th e collection container vo lume (feet3Ideally, a drainage lysimeter should have an optimum collection area where the collection container collects leachate from the entire root zone below crop root system being teste d, and should account for plant to plant and emitter to emitter variability (in the case of drip irrigation). Leachate collection efficiency may be calculated by dividing total leachate volume collected by total water applied for that time period (Zhu et al., 2002), and f actor s that may improve collection efficiency are the size of the collection container, and the presence of a wick. Previous work done with large plate lysimeters has shown that collection container s with collection surfaces of 162, 500 to 2005 cm Width Length Depth), and by a correction factor for unit homogeneity. Currently, t here are no standard guidelines for the dimensions of the drainage lysimeter collection container, the collection container fill (which also enhance collect ion efficiency ) a nd the capacity of the storage container Hence, g enerally cultural practices and availability of materials have dictate d the design of a drainage lysimeter. Consequently it is often difficult to separate treatment effects (cultural practices) from lysimeter effect s in many research reports 2 ha d increased collection efficiencies from 10%, 13%, to 26%36%, respectively (Radulovitch and Sollins, 1987). In a study comparing zerotension (leachate

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71 collected by free drainage) pan lysimeters and wick lysimeters installed at a depth of 4.3 feet below the soil su rface, wick lysimeters collected 2.7 times more leachate than drainage lysimeters did, thereby increasing efficiency. The higher efficiency was attributed to the breaking of soil water tension by the wick (Zhu et al., 2002). Frequency of leachate collecti on and storage of leachate samples are two other factor s that may affect load measurement. According to David and Gertner (1987) t he leachate collected in the storage container should be retrieved at frequent intervals multiple times a week, to minimize v ariability in within -site nutrient concentration measurements and prevent changes in the chemical composition of the leachate. Significant increases in NH4N concentrations were reported at 68 F due to mineralization reactions, and significant increases in NO3N concentrations were seen at 4 F and acidic pH due to oxidation of NO2 (Clough et al., 2001). If leachate samples are being stored before analysis, the optimum storage conditions are at 39.2F without acidification. These conditions minimize transf ormations of NO2 to NO3 -, and minimize overestimation of NO3 Soil sampling is another method for direct load measurement. Typically, a soil sample used for load determination consists of a 5 -foot deep soil core divided in to five subsamples, each 1 -foot long. A known amount of extractant is added to the sample to saturate it. After thorough mixing of the sample, chemical extraction or analysis is performed. Generally, t he NH concentrations (Clough et al., 2001) 4N and NO3N concentrations in soil sample s are d etermined using modified EPA method 350.1 and EPA method 353.2 respectively (USEPA, 1993). The chemical concentrations are then converted to original field water content basis (Ahmed et al., 2001). Nutrient load is then calculated by multiplying nut rient concentration in each sub-sample (mg/kg soil) by the wetted soil volume (feet3, Width Length Depth), by soil bulk density (assumed to be homogenous) and by a

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72 correction factor for unit homogeneity. The bulk density of soils can be measured in th e laboratory (USDA, 2004) or soil bulk density estimates may be found in soil survey reports published of the Natural Resources Conservation Service ( USDA NRCS 2008 ). The length (total L of mulched bed per unit area) and depth (length of the soil subs ample) of the wetted soil volume are well known. H owever width estimates of the wetted soil volume are not well known and may vary with the irrigation program and soil type Moreover, factors which affect the volume of the wetted zone, such as soil physic al properties and their spatial variability, initial moisture content, width of raised plant bed, and irrigation length (Clark and Smajstrla, 1993; Santos et al., 2003; Simonne et al., 2005; Simonne et al., 2006) also affect the width of wetted zone Farne selli et al. (2008) reported estimates of mean (28.7, 23.6, 18.5, 13.4, and 8.3 inches for the 5.9 18.1, 29.9, 42.1 and 53.9 inch depths, respectively) and maximum (40.9, 33.1, 25.2, 17.3, and 9.8 inches for every 1 -foot depth increment ) wetted widths th at can be used for calculating mean and maximum nutrient loads from raised plant beds on Blanton Foxworth -Alpin soil series (fine sand) However, t heir results were based on a single irrigation event without a crop, and depending on either the mean bed or maximum wetted width, could result in nutrient load from 18.9 34.9 lb / acre. On the other hand, as there are no reported estimates of actual in -field wetted wi dths for different crop species, the mean and maximum wetted width estimates reported by Farnesel li et al. (2008), and the bed width of the raised plant bed are currently the best estimates of wetted widths in Florida sandy soils A great number of similarities exist in the methods and sampling procedures used for collecting or monitoring nutrient con centrations Also, the construction design of lysimeters, and the methodology of soil sampling procedures are explained in great detail in the literature H owever, when nutrient concentrations are converted from mg/kg (for soil sampling) and mg/L

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73 (for lysi meters) to nutrient loads on a per unit area basis most articles do not give a detailed methodology of load calculation and there are no similarities in published literature ( Abad et al., 2004; Aparicio et al., 2008; Daudn and Qulez, 2004; Lecompte et a l., 2008; Macaigne et al., 2008; Oikeh et al., 2003; Poudel et al., 2002; Ramos et al., 2002 ; Rajput and Patel, 2006; Sainju et al., 1999; Vzquez et al., 2006; Yaffa et al., 2000; Zotarelli et al., 2008; Zvomuya et al., 200 3 ). With soil sampling as a met hod to monitor nutrient leaching, few of the reports do not convert the NO3N concentration in the soil samples to NO3-N load on per -hectare basis (Daudn and Qulez, 2004; Macaigne et al., 2008; Poudel et al., 2002; Rajput and Patel, 2006 ; Yaffa et al., 2 000). While some of the reports that measure NO3N load with soil sampling on per hectare basis mention both the NO3N analytical procedure and the soil bulk density values (Halvorson et al., 2002 ; Zvomuya et al., 2003), some mention just the NO3-N analyti cal procedure used ( Abad et al., 2004; Sainju et al., 1999), and others mention neither the NO3N analytical procedure used nor the soil bulk density values (Oikeh et al., 2003). Syvertsen and Jifon (2001) provide the dimensions of the ir drainage lysimeter s however, they fail ed to report the NO3N analytical procedure and report ed their results as NO3N concentration/lysimeter rather than NO3N load on per hectare basis. For bell pepper production on plasticulture system, Romic et al. (2003) on the other h and report ed NO3N load measured with drainage lysimeters on per -hectare basis T hey however, fail ed to mention whether the NO3With suction type lysimeters (SCL), where draina ge cannot be estimated directly, Aparicio et al. (2008) calculated NO N load values reported are on a cropped hectare basis or on a unit area basis. 3N losses with the following equation NL = DC/100, where NL is the NO3N losses at various soil depths, D is drainage water estimated using the LEACH -W model, and C is the NO3N concent ration (analytical method not mentioned) in the soil solution

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74 extracted with the SCL. Vzquez et al. (2006), Zhu et al. (2005), and Zvomuya et al (2003) on the other hand estimated NO3N losses from each sampling interval as the product of NO3N concentra tion is the soil solution and the amount of drainage. Vzquez et al. (2006) and Zvomuya et al. (2003) calculated drainage with the following equation, D = P+I -E, where D change in soil water storage between consecutive days, and E is the evapotranspiration. However, Zhu et al. (2005) measured drainage directly using modified lysimeters. The three publications also varied in their methodology for analyzing NO3-N concentrations. While Vzquez et al. (2006) estimated NO3N concentration in the soil solution samples spectrophot ometrically after reduction in cadmium solution (Keeney and Nelson, 1982) Zhu et al. estimated NO3N concentration in the soil solution samples colorimetrically with the Bran and Luebbe Model TRAACS 2000 continuous -flow analyzer O n the other hand Zvomuya et al. (2003) used the diffusion-conductivity method (Carlson et al., 1990) to estimate NO3Nutrient load or leaching is influenced by several natural and cultural factors. Some of the natural factors are cli mate, hydrology, soil characteristics, and topography, and some of the cultural factors are tillage, mulching, fertilization (type of fertilizer, rate, placement, and timing of application) nitrogen use efficiency of the plant (NUE) and irrigation (quanti ty, rate, frequency, and method of application) management. Factors that affect n utrient load or leaching (natural and cultural fa ctors ) also affe ct the variations in N leaching Climatic conditions and fertilization affected variations in NO N concentration in the soil solution samples 3N leaching b y 65%, crop rotations by 20 25% (Krysanova and Haberlandt, 2002), fertilizer inputs alone affected variations in NO3N leaching by 40% ( Mertens and Huwe, 2002), and agricultural land management affected variations in N

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75 leaching by 48% (Schmidt et al., 2008). Hengsdijk and van Ittersum (2001) showed the uncertainties associated with future modeling of NO3N leaching losses as functions of crop characteristics, yield levels, and crop residue -nitrogen to be 36 % and +70%, 30% and +40%, and 64 % and +67%, respectively. The potential for leaching might also be influenced by the NUE of the crop Crops with low NUE could potentially result in high leaching losses. The reported NUE of crops are highly variable (Table 4 1), and for tomato depending on the soil t ype the NUE ranged from 27% (silt loam (Hills et al., 1983)) to 82% (sand (Scholberg et al., 2000)). A study done by David and Gertner (1987), found that the CV for volume of leachate and NO3N concentration measured during the study was 122% and 218% respectively. Moreover, they found that the variability in volume and NO3N concentration recorded within a site, soil horizon, and pit, over each period of time accounted for 18 % and 15% of total variability, the variability in volume and NO3N concentration within a period of time re -measurement accounted for 55 % and 32% of the total variability, and variation in pits within a site accounted for 50% of the total variability for NO3-N concentration. Hansen et al. (1999) found that variability in agricultural land management resulted in CV ranging from 20 % to 40%. Due to variability in N load results with location, cropping system, and soil type site specific in -field load estimates are the best predictors of total N load. Zotarelli et al. (2007, 2008) conducted several experiments to compare different methods of monitoring nitrate leaching in sandy soils, and for determining nitrogen and water use efficiency of zucchini squash They reported that in sandy soils depending on the method used to monitor nitrate le aching, nitrate N load range d from 1.79 33.93 lb/acre in bell pepper, 2.6833.04 lb/acre in tomatoes and 1.7940.19 lb/acre in zucchini While the CV was relatively lower than the previous studies it ranged from 26.3 35.9% for bell peppers, 15.831.5% for tomatoes, and 19.6 30.0 for zucchini. Moreover, with the

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76 drainage lysimeter method of estimating nitrate N leaching, Zotarelli et al. (2007) applied a partial vacuum of 5.1 5.8 PSI which may have affected the overall nitrate N solution flow and/or drainag e. A s previously mentioned, quantifying in -field nutrient load lacks consistency in method of measurement, and there is no mention of the wetted width used in conversion of nutrient concentrations from soil and leachate samples into nutrient load on a per unit area basis. Therefore, t he goal of this project was to determine the effects of different irrigation nutrient management programs on tomato seasonal nutrient load. The specific objectives of this study were to 1) d etermine the effects of a combination of irrigation -nutrient management programs on tomato seasonal total -N load as measured with drainage lysimeters, 2) d etermine the effects of lysimeter design on tomato seasonal total N load measured, 3) determine the effect of depth of sampling on NO3N, NH4N and total soil -profile N using soil samples and three different estimates of bed widths ( mean wetted width, maximum wetted width, and raised bed width), 4) d etermine the effects of a combination of irrigation -nutrient management programs on soil prof ile NO3N, NH4Materials and Methods N and total N using soil samples and three different estimates of bed widths (mean wetted width, maximum wetted width, and raised bed width), and 5) determine the relationship between total N load measured with drainage lysimeters and soil -p rofile total N measured with soil sampling Experimental Setup The experiment was conducted at the N orth F lorida Research and E ducation Center S uwannee V alley at Live Oak, Fla. on Blanton-Foxwort -Alpin Complex soil series ( 20-feet dee p fine sand). Field preparation and layout of treatments was done as described in Chapter 1. On April 8th, 2005 and April 5th, 2006 6-week old (Days After Transplanting (DAT) = 0) Florida

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77 47 transplants w ere transplanted on to th e plasticulture system wit h a 18 inch within row spacing, on 6 -foot center raised plant beds, and establishing plant a population of 4,840 plants/ a cre The irrigation -nutrient management programs were a combination of preplant fertilizer source fertilizer rate, and irrigation rate (Table 3 1 ). The current IFAS recommendation for N and K for commercial tomato production was used as the 100% fertigation rate and twice that amount for the 200% fertigation rate. Split application of fertilizer treatments through the drip tape was done weekly throughout the growing season and in both years (Figure 3 1) A medium flow rate drip -tape was used for supplying the irrigation. The 100% and 300% irrigation rate was achieved by installing one drip tape three drip tapes to the respective experime ntal plots ( 24 gallons/100 ft/h flow rate at 12 PSI operating pressure, 12 inch emitter spacing ; John Deere Water Technologies San Marcos, CA). Separate drip tapes were also installed for fertigation. For the 100% and 200% fertigation rate one and two dri p tapes were installed respectively. Based on the irrigation -nutrient management program, the total number of drip tapes in each program ranged from 2 to 5. Irrigation was applied as described in Chapter 1 (Figure 3 2 ) respectively. As fertigation and irr igation are applied either on a weekly and daily basis, the weekly and daily amounts of fertilizer and irrigation to be applied tend to have very narrow differences between them which then tends to result in narrow differences in fertilizer and irrigation rate treatments. Therefore, for this experiment we chose the standard IFAS rate and much higher rates of fertilizer and irrigation management as an attempt to have large treatment difference s on a daily basis even with the split application of the treatme nts Current recommendations for commercial tomato production for pest and disease control and all other production practices were followed (Olson et al., 2007).

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78 Drainage Lysimeters : Installation In March 200 5 two type s of d rainage lysimeters designs were installed under ground at 2 feet depth to monitor different irrigation -nutrient management programs for nutrient leaching (Table 3 1 ). The lysimeters were installed at this depth to be below the crop root zone and to avoid damage by tillage operations Th e collection containers of the lysimeters were constructed out of 55-gallon drums cut in half lengthwise. The collection containers wer e 3 -feet long, 2 -feet wide, 1 -foot deep, and filled with either s oil only (Soil Only Design) or soil and gravel (Soil & G ravel Design) (Figure 4 1 ). The Soil Only lysimeters were installed under program s 1 5 and the Soil & Gravel lysimeters were installed under program 6. The leachate storage containers, 55 gallon plastic barrels, were installed under the collection containe rs. Prior to installation of the lysimeters, the field was tracked to form the outline of the raised plant bed treatment rows. Both the lysimeter designs were installed lengthwise within the treatment rows and the collection containers were installed wit h 2% lengthwise slope to facilitate water movement into the storage container and to reduce the risk of a perched water table. A 2 inch diameter PVC -pipe (sample retrieval spout) running from the top of the soil and through a hole in the lid of the storage container, and connected to the bottom was installed to facilitate the retrieval of leachate water inside the storage container The top 18inch detachable part of the sample retrieval spout was removed for tillage purposes and reinstalled a minimum of 7 DAT. Drainage Lysimeters : Sampling Sample Analysis and Load Calculation As the sample retrieval spouts were not accessible until all tillage operations and transplant establishment were completed, the leachate was not retrieved from drainage lysimeters until 13 DAT in 2005 and 30 DAT in 2006. After ward t he storage containers were probed once in every two weeks with a 10 -foot long dipstick, and leachate was retrieved from the lysimeters

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79 with leachate inside them. L eachate was retrieved 13, 31, 48, 66, 77, and 98 DAT in 2005, and 30, 43, 57, 70, 85, 110, 148 DAT in 2006. F or lysimeters without leachate inside them, the volume and nitrate ( NO3N ) concentration were recorded as Leachate was retriev ed with a silicone tube attached to a pump (B/T Rapid L oad Variable Occlusion Peristaltic Pump, Cole Parmer Instrument Co, Vernon Hills, IL) that was placed into the 2 -inch di a meter PVC -pipe. On each sample retrieval date leachate was pumped out and volume immediately measured and recorded Aliquots of 0.8 oz volume were collected, treated with 2 -drops of hydrochloric acid to stop nitrate loss, and rapidly frozen at 18 C until analysis. The leachate samples were analyzed by the University of Florida (UF) Analytical Research Laboratory (ARL) in Gainesville Fl a. for NO3N concentration using EPA method 353.2. In addition to the ARL laboratory quality assurance/quality control, set standards of NO3N in nitric acid concentrations were randomly included in the sample set. NO3Soil Sampling : Sampling, Sample Analysis, and Load Calculation N concentrations in the leachate samp les were converted to N -load on a croppedacre basis ( lb/acre ) by multiplying the nutrient concentration in each sub-sample (mg/L) by the volume ( gallons ) of leachate collected, and by the length of the collection container ( feet ). Cu mulative N load at the end of the tomato growing season was calculated as the sum of the N -load of each collection event Similar to Abad et al. (2004), s oil sampling was done at the end of the tomato production se ason on 104 and 92 DAT in 2005 and 2006, respectively using 5 -foot long, 2.5 -inch internal diameter steel tube s (Forestry Supplies, Inc., Jackson, MS) O ne of the assumptions of the soil sampling procedure was that the rate of vertical movement of water is 0. 0 7 inches / gallon /100ft or up to 7 inch depth for a 4 -hr irrigation duration per day. A second assumption was that nutrient concentration was uniformly distributed in wetted zone (Simonne et al., 2006) Therefore, s amples were taken at the center of the raised -bed from each experiment plot, and

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80 w ithin each plot, each sample was the composite of two cores taken approximately 5 -feet apart. These soil cores were subdivided into five 1 -foot long sections representing 0 1 1 2 2 3 3 4 4 5 foot depths, and e ach section was bagged separately. T he s ample bags were frozen at 18 C until analys i s. The soil samples were analyzed by the UF ARL in Gainesville Fla. for NO3N and NH4N concentrations with Me h lich 1 extractant (0.0125 M H2SO4 and 0.05 M HCl). The NH4N w as determined using modified EPA method 350.1 and NO3N was determined using EPA method 353.2 (USEPA, 1993) Nitrogen (NO3N and NH4N) concentrations in the soil samples were converted to NO3N NH4N, and total N -load (sum of NO3N and NH4N load) o n a cropped-acre basis (lb/acre) by multiplying N concentration in each sub -sample (mg/kgsoil), by the wetted zone volume ( feet3, W x L x D ), and by soil bulk density ( 90.6 lb / feet3Data Analysis USDA, 1961). As there are no reported estimates of actual wetted widths in the crop root zone, w etted zone width was calculated based on mean, maximum and bed width at the five sampling depth sections (Farneselli et al., 2008) The above ground irrigation -nutrient management programs were organized in a randomize d complete block design with four replications. As the drainage lysimeters were buried in the ground and could not be re -installed every year, except for 200% Fertigation, 300% Irrigation -ML irrigation -nutrient management program, the remaining irrigation -nutrient management programs were randomized in both years. Soil and d ra inage lysimeter leachate sample responses to irrigation -nutrient management programs were determined using ANOVA and treatment means were compared using Duncans multiple range test (S AS, 2008). The orthogonal contrasts Nitrogen rate (100% vs 200%), Preplant fertilizer source (CL vs Inorganic Fertilizer), and Irrigation rate (100% vs 300%) were used to test the significance of the difference between rate of fertilizer applied, sou rce of preplant fertilizer, and irrigation rate.

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81 Pearsons correlation coefficient analysis was performed with PROC CORR (SAS, 2008) to correlate seasonal total -N load for the different monitoring methods. Results and Discussion Weather Conditions Rainfal l was relatively higher than seasonal levels during April, June, July, and was lower than normal in May 2005. During 2006 rainfall was relatively lower than normal in April, May, July, and higher than normal in June (Figure 3 3 C). Rainfall events of more t han 1 -inch during 2005 occurred on 22, 58, 64, 65, 82, and 86 DAT recording 1.83, 1.44, 1.66, 1.04, 2.46, and 2.35 inches, respectively, and accounted for 59% of total rainfall recorded from April 8 to July 5, 2005. During 2006 rainfall events of more than 1 inch occurred on 3, 57, 68, 69, and 81 DAT recording 1.28, 1.59, 1.6, 2.25, and 1.47 inches, respectively and accounted for 67% of total rainfall recorded from April 5 to July 5, 2006 (FAWN, 2008). Based on the above weather information, 2005 was a rela tively cooler and wet year, while 2006 had normal temperatures for North Florida. However, in 2006 the early part of the tomato growing season (April -May) was dry while the latter part was wet (June July). Seasonal Total N Load Estimate Based o n Drainage Lysimeter For tomato seasonal total N load calculated from drainage lysimeters, t he interaction year x treatment was significant for both the volume of leachate ( gallons ) recorded and the total N load (lb/acre ) estimates ( p < 0.01). Therefore data from b oth years were analyzed separately. In 2005, there were no significant differences between the leachate volume s recorded for the irrigation -nutrient management programs. In 200 6 there were significant differences between the leachate volume s recorded for the irrigation -nutrient management programs. Highest total leachate volume ( 87.2 gallons ) was recorded with 200% Fertigation, 300% IrrigationML irrigation -nutrient management program and the lowest with 100% Fertigation -CL, 1 00%

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82 Irrigation, In 2006, highest total N load (18.75 lb/acre ) was recorded wi th 200% Fertigation, 300% Irrigation -ML irrigation -nutrient management program and the lowest total -N load was recorded with 100% FertigationCL,100% Irrigation, 100% Fertigation, 100% Irrigation, 100% Fertigation, 300% Irrigation, and 200% Fertigation, 100% Irrigation. Similar to the 2005 results, the CV was very high and ranged from 68 % 208% Based on the orthogonal contrasts, the differences in the total N load were due to the irrigation management program ( p ) and the lysimeter design ( p ) and were not due to the nutrient management program. Higher total N load (p was recorded with the Sand & Gravel lysimeter design ( 15.27 lb/acre ) than with the Soil Only lysimeter design ( 7.05 lb/acre ), a nd higher total N load was recorded with 100% Fertigation, 100% Irrigation, and 100% Fertigation, 300% Irrigation irrigation nutrient management program (Figure 4 2 A ). In 2005 and 2006, irrigation -nutrient management program had a significant effect on total N load. In 2005, the highest total N load (8.93 lb/ac re ) was recorded with 200% Fertigation, 300% IrrigationML irrigation -nutrient management program ( p = 0.02) and there were no significant differences between the remaining five irrigation -nutrient management programs (Figure 4 2 B). The total N load was re latively higher with the higher N nutrient management programs (200% Fertigation 100% Irrigation, 200% Fertigation 300% Irrigation, 200% Fertigation300% Irrigation -ML) than with the lower N management programs (100% Fertigation -CL, 100% Irrigation, 100% Fe rtigation 100% Irrigation, 100% Fertigation300% Irrigation) (Figure 4 2 ). How ever, the CV was high and ranged from 8 7 % 1 76% Based on the orthogonal contrast s, the differences in the totalN load were due to the lysimeter design and were not due to the ir rigation -nutrient management program. Higher total N load (p was recorded with the Sand & Gravel lysimeter design (7.14 lb/acre ) than with the Soil Only lysimeter design (0. 7 9 lb/acre )

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83 200% irrigation management program ( 8.17 lb/acre ) than with 100% irrigation management program (0.3 1 lb/acre). Therefore, the Soil & Gravel drainage lysimeter design should be used for monitoring total N load. A stu dy done by David and Gertner (1987), found that the CV for volume of leachate and NO3N concentration measured during the study was 122% and 218%, respectively. Moreover, they found that the variability in volume and NO3N concentration recorded within a s ite, soil horizon, and pit, over each period of time accounted for 18 % and 15% of total variability, the variability in volume and NO3N concentration within a period of time re -measurement accounted for 55 and 32% of the total variability, and variation i n pits within a site accounted for 50% of the total variability for NO3Soil -profile Total -N Load Esti mate Based o n Soil Sampling N concentration. For tomato soil profile total N calculated from soil sampling, t he interaction year x treatment was signific ant for most of the load estimates ( p < 0.01). Therefore the data from both years were analyzed separately. In 2005, the NH4N load estimate based on bed wetted width did not vary with depth ( p = 0.22). For the remaining NH4N, NO3N and total -N load esti mates, i rrespective of method of estimating the wetted width, load estimates were highest in t he first 1 foot depth of soil, and did not vary for the 2 5 foot soil depth (Table 4 2 ). All NH4N, NO3N and total N load estimates (based on mean, bed, and maximum wetted width, and except for bed NH4In 2006, all NH N) followed the pattern 1 > 2 = 3 = 4 = 5 foot depth (Table 4 2 ). 4N, NO3N and total N load estimates ( based on mean, bed, and maximum wetted width ) var ied significantly with depth ( p 0. 01) Mor eover, irrespective of method of estimating the width, NH4N NO3N and total N load estimates were highest in the first 30.5-cm depth of soil (Table 4 2 ). These results were contrary to those reported by Sainju et al. (1999) who observed an increase in N O3-N load with an increase in soil depth. The NH4-N

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84 load estimates based on mean and maximum wetted width estimates increased with an increase in the soil depth and followed the following pattern 1 > 2 > 3 > 4 > 5 foot depth, while the NH4N load estimates based on bed wetted width followed the pattern 1 = 2 > 3 = 4 = 5 foot depth. All t he NO3Soil sampling load was calculated based on mean, maximum and bed wetted width (Farneselli et al., 2008). Depending on the method of estimating wetted width and the irrigationnutrient management program, the total -N load ranged from 0. 1 3 1.54 lb/acre in 2005, and from 1.5 4.3 lb/acre in 2006. In 2005, t he irrigation -nutrient manageme nt programs did not have a significant effect ( p 0. 054 ) on NH N load estimates followed the pattern 1 > 2 = 3 = 4 = 5 foot depth. T otal -N load based on mean and maximum wetted width followed the following pattern 1 > 2 > 3 = 4 > 5 foot depth, while the total N load based on bed wetted width followed the following pattern 1 > 2 > 3 = 4 = 5 foot depth (Table 4 2 ) These results suggest that the soil samples from the top 1 -foot depth may have quantified the most recent fertilizer ap plication (high total N load in top 1 -foot soil depth), and the N -load from the previous fertilizer applications may be beyond the highest soil depth monitored ( 5 foot depth). 4N, NO3N, and total -N load. Moreover, the CV was high and ranged from 83 % 135% (Table 4 2 ). In 2006, except for NH4N load estimates based on mean and maximum bed width, NH4N load based on b ed width ( p = 0.02), NO3 -N load (based on mean, bed a nd maximum wetted widths), and t otal -N load (based on mean, bed and maximum wetted widths) varied significantly with irrigation nutrient management program ( p < 0.01). A l though the irrigation -nutrient m anagement programs had a significant effect on the nutrient load estimates in 2006, the coefficient s of variation were high and ranged from 38 % 97% (Table 4 3 ). Highest and lowest NH4N load based on bed width were seen with 200% Fertigation, 300% Irrigati on-ML and 100% Fertigation -CL,100% Irrigation irrigation nutrient management

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85 programs respectively (1.6 and 1.07 lb/acre respectively). Significantly higher (p < 0.01) NO3N load estimates (2.09 3. 1 lb/acre) were recorded with 200% Fertigation, 100% Irriga tion irrigation -nutrient management program for all three methods of estimating wetted width ( Table 4 3 ). Similarly, significantly higher ( p < 0.01) t otal N load estimates (3. 18 4.32 lb/acre ) were recorded with 200% Fertigation, 100% Irrigation irrigation-nutrient management program for all three methods of e stimating wetted width (Table 4 3 ). These results suggest that based on soil sampling, increasing fertilizer rate from 100% to 200% result ed in a significant increase in NO3N load and total N load in t he soil. However increasing both the fertilizer and irrigation rates (200% Fertigation, 300% Irrigation, 200% Fertigation, 300% Irrigation-ML irrigation -nut rient management programs) tended to dilute nutrient concentration which reduced NO3N load and tota l N load measured. The inorganic N concentrations measured in the tomato field from the different treatments within 1 -foot depth (0.648.31 mg/kg of soil) were lower than th ose reported in literature fo r soil samples (sandy loam) collected at similar depth and tomato production stage (1 5 45 mg/kg of soil ; Yaffa et al., 1994). Also the totalN load values measured (0 1 8.75 lb/acre ) were lower than those reported in literature for soil samples collected from similar depths (2 3.2 192.9 lb/acre Sainju et al., 1999) However, the studies done by Sainju et al. (1999) and Yaffa et al. (1994) were conducted on Norfolk sandy loam soils (65% sand, 25% silt, and 10% clay) with a high er anion exchange capacity than the fine sand soils of the current study. Moreover, fo r plasticulture raised bed s or row crops, depending o n whether nutrient concentration is converted to nutrient load on per -cropped hectare or per real estate hectare, nutrient load may be overestimated 3 -fold (when raised bed or rows are on 6 -foot centers) In a similar study done by Zotarelli et al. (2007) on sandy soils the N load measured with soil samples ranged from 4.6 3 2.51 lb/acre T he total N load measured in the current study was much lower and ranged from

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86 1. 494. 32 lb/acre In the current study soil samples were collected at the end of the tomato season, Zotarelli et al. (2007) on the other hand collected soil samples bi -weekly. One of the assumptions of the study was that the rate of vertical movement of water i s 0. 0 7 inches / gallon/100ft or up t o 7 -inch depth for a 4 hr irrigation duration per day. Moreover the maximum possible depth of the wetted zone ( 46.5 46.9 inches ; Farnaselli et al., 2008) was well within the depth to which the soil samples were taken ( 60 inches ). H owever based on the nutr ient load measured the rate of vertical movement of water was probably greater than our assumption. Another assum p tion of the study was that nutrient concentration is uniformly distributed in wetted zone (Simon n e et al., 2006) Based on the low nutrient l oads that we recorded within the wetted zone however, the nutrient concentration distribution could possibly be nonuniform and soil sampling at the drip tape may be a zone of highest leaching rate. Moreover, Simonne et al.s (2006) results are based on a single irrigation event and do not reflect the actual water and fertilizer movement during the cropping cycle. However, except for modeling and soil column studies (Chen et al., 1996; Mansell et al., 1988; Mansell et al., 1992; Mansell et al., 1993; Ouyan g et al., 2004; Shinde et al., 1996), there are no in-field reports on water and solute movement in acidic sandy soils. In the current study soil samples were collected at the end of the growing season and sampling at the end of the cropping cycle m ay not give a complete estimate of N losses from the crop root zone and more frequent soil sampling might be required. Relationship b etween Seasonal Total -N Load Measured with Drainage Lysimeters and Soil -P rofile Total -N Measured with Soil Sampling Although Pears ons correlation comparative analysis was performed on seasonal total N load monitored with drainage lysimeters and soil profile total N measured with soil sampling there was no significant relationship (p > 0.70) between the two measures (r = 0.052 drain age

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87 lysimeter x soil samplingbed width, r = 0.069 drainage lysimeter x soil samplingmean width, r = 0.07 drainage lysimeter x soil samplingmaximum widthConclusion ). The effect of irrigation -nutrient management programs on tomato seasonal total N load var ied with year. In both 2005 and 2006, higher total -N load was recorded with Soil & Gravel lysimeter design than with Soil Only lysimeter design. With soil sampling, irrespective of treatment, tomato soil profile total N was highest in the first 1 -foot dept h of soil, and tended to decrease with an increase in depth. Tomato soil -profile total N varied with year depending on the method of estimating wetted width and the irrigation nutrient management program, t he soil profile total -N load ranged from 0.391. 5 4 lb/acre in 2005, and from 1. 494. 32 lb/acre in 2006. The soil -profile total N load measured in 2005 was much lower than that measured in 2006, and the results within each year showed high variability. There were no significant differences between the irr igation -nutrient management programs in 2005. While, in 2006 the highest soil profile total -N load was recorded with 200% Fertigation100% Irrigation program and lowest soil -profile total N load was recorded with the high irrigation programs (100% Fertigat ion 300% Irrigation, 200% Fertigation300% Irrigation, 200% Fertigation300% Irrigation-ML). However, based on the relatively low soil profile total N loads recorded, the rate of movement of the water front in this study might have been higher than expecte d from past research conducted under similar conditions of soil and irrigation. Moreove r within the wetted zone the nutrient concentration distribution could possibly be nonuniform and soil sampling at the drip tape possibly the zone of highest leachin g rate might not have been the best option. Therefore, b oth the drainage lysimeters and the soil samples might have underestimated the tomato seasonal total N load and the soil -profile total N from the different irrigation -nutrient management programs. A comparison of the seasonal total -N load monitored with drainage lysimeters and

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88 soil -profile total N measured with soil sampling showed a lack of relationship between the two measures. Further, due to the lack of consistency in methodology of reported nutri ent loads, a true comparison of total N load across studies was not possible, and given the inherent variability associated with nutrient load measurements from site to site and within site, a comparison of total N load across studies might not be a valid comparison

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89 Table 4 1. Published estimates of nitrogen use efficiency (NUE) in selected crops. Crop Soil Type Location NUE (%) Reference Cauliflower Sandy Loam Denmark 60 84 Srensen, 1996 Canola Loam Canada z 35 42 Gan et al., 2008 Corn Coarse Fine Lo amy N. Dakota 50 Wienhold et al., 1995 Corn Silt Loam California 52 57 Hills et al., 1983 Corn Silt Loam Kansas 46 48 Olson, 1980 Leeks Sandy Loam Denmark 58 87 Srensen, 1996 Mustard Coarse Sandy Clay India 53 93 Ahmad et al., 2008 Onion Silt Loam Ut ah 59 99 Drost et al., 2002 Onion Silty Clay Colorado 11 19 Halvorson et al., 2002 Onion Sandy Loam Denmark 102 182 Srensen, 1996 Hot pepper Sandy Loam China 11 Zhu et al., 2005 Rice Silt Loam Louisiana 17 23 Patrick et al., 1974 Rice Silt Loam Louis iana 33 61 Reddy & Patrick, 1976 Ryegrass Sandy Loam Silty Clay Alabama 90 85 Terman & Brown, 1968 Sugarbeet Silt Loam California 27 37 Hills et al., 1983 Sugarbeet Loam California 47 Hills et al., 1978 Tomato Sandy Egypt 51 68 Badr, 2007 Tomato Cl ay Loam California 40 50 Miller et al., 1981 Tomato Silt Loam California 27 Hills et al., 1983 Tomato Sand Florida 36 82 Scholberg et al., 2000 Tomato Clay Sandy Clay Turkey 72 76 Topcu et al., 2007 Wheat Silt Loam Kansas 77 81 Olson et al., 1979 Zucc hini Sand Florida 43 63 Zotarelli et al., 2008 z The experiment was conducted at four Saskatchewan locations: Melfort, Saskatoon, Scott, and Swift Current. The soil types at these locations were loam, clay loam, silt clay loam, abd silt loam respectively.

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90 Table 4 2 Effects of depth of soil sampling in a Florida 47tomato field during spring of 2005 and 2006z Depth on nitrogen loads ( lb/acre ) based on mean, bed, and maximum wetted widths (WW) NH 4 + N Load ( lb/acre ) NO y 3 Total N ( lb/ac re ) N Load ( lb/acre ) x (feet) Mean WW Bed WW Max WW Mean WW Bed WW Max WW Mean WW Bed WW Max WW 2005 0 1 0.48 a 0.41 0.69 a 2.02 a 1.79 3.00 a 2.59 a 2.21 a 1.02 a 1 2 0.25 b 0.26 0.35 b 0.45 b 0.46 0.63 b 0.70 b 0.72 b 0.97 b 2 3 0.20 b 0.26 0.27 b 0.17 b 0.22 0.23 b 0.52 b 0.48 b 0.50 b 3 4 0.16 b 0.3 0.21 b 0.35 b 0.64 0.46 b 0.37 b 0.94 b 0.67 b 4 5 0.11 b 0.31 0.13 b 0.18 b 0.54 0.21 b 0.29 b 0.84 b 0.34 b p values < 0.01 0.22 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 CV (%) 122 83 127 133 122 135 125 1 04 128 2006 0 1 2.21 a 1.88 a 3.14 a 2.39 a 2.04 a 3.41 a 4.60 a 3.90 a 6.55 a 1 2 1.79 b 1.86 a 2.52 b 1.13 b 1.16 b 1.58 b 2.93 b 3.03 b 4.10 b 2 3 1.02 c 1.35 b 1.38 c 0.56 c 0.74 b 0.82 c 1.58 c 2.08 c 2.15 c 3 4 0.49 d 0.90 c 0.64 d 0.63 bc 1.16 b 0.76 c 1.13 cd 2.06 c 1.46 cd 4 5 0.23 e 0.68 c 0.28 e 0.45 c 1.33 ab 0.54 c 0.68 d 2.01 c 0.81 d p values < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 CV (%) 38 39 39 85 97 84 4 5 52 44 z The interaction term for year x irrigation and nutrient management program was significant for nutrient loads ( p the data from both years were analyzed separately. y Means followed by different letters within each column are significantly different at the 0.05 level, according to Duncans multiple range test. x Total N load ( lb/acre ) based on bed, mean and maximum wetted widths was calculated by adding the NO3 --N and the NH4 + N loads (lb/acre ) from the respective wetted widths.

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91 Table 4 3 Effects of irrigation -nutrient manageme nt programs in a Florida 47tomato field during spring of 2005 and 2006z on nitrogen loads ( lb/acre) based on soil sampling with three different wetted width ( W W) estimates NH 4 + N Load ( lb/acre ) NO y 3 Total N ( lb/acre ) N Load ( lb/acre ) Irrigation Nut rient Management Programs Mean WW x Bed WW Max WW Mean WW Bed WW Max WW Mean WW Bed WW Max WW 2005 100% Fertigation -CL 1 00% Irrigation 0.23 w 0.31 0.31 0.70 0.79 0.96 0.93 1.11 1.28 100% Fertigation 100% Irrigation 0.22 0.30 0.31 0.57 0.71 0.78 0.79 1.02 1.09 100% Fertigation 3 00% Irrigation 0.33 0.38 0.46 0.88 0.81 1.24 1.21 1.19 1.71 200% Fertigation 1 00% Irrigation 0.22 0.30 0.30 0.91 1.22 1.24 1.13 1.53 1.54 200% Fertigation 3 00% Irrigation 0.22 0.30 0.30 0.42 0.41 0.59 0.64 0.71 0.89 200% Fertiga tion 3 00% Irrigation ML 0.20 v 0.26 0.27 0.44 0.42 0.62 0.63 0.68 0.88 p values 0.75 0.84 0.74 0.31 0.05 4 0.35 0.44 0.14 0.46 CV (%) 122 83 127 133 122 135 125 104 128 2006 100% Fertigation CL 1 00% Irrigation 1.79 1.79 c 1.31 1.52 b 1.91 b 2.09 ab 2.46 b 2.98 b 3.39 b 100% Fertigation 100% Irrigation 2.68 2.68 ab 1.74 1.16 bc 1.07 c 1.40 bc 2.26 bc 2.51 bc 3.14 bc 100% Fertigation 3 00% Irrigation 3.57 3.57 ab 1.68 0.56 c 0.56 c 0.79 cd 1.77 cd 2.00 c 2.46 cd 200% Fertigation 1 00% Irrigation 4.47 4.47 bc 1.54 2.09 a 3.10 a 2.79 a 3.18 a 4.31 a 4.32 a 200% Fertigation 3 00% Irrigation 5.36 5.36 bc 1.48 0.42 c 0.42 c 0.59 d 1.49 d 1.63 c 2.07 d 200% Fertigation 3 00% Irrigation ML 6.25 6.25 a 1.79 0.63 c 0.64 c 0.88 cd 1.93 bcd 2.25 bc 2.68 bcd p values 0.11 0.02 0.13 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 CV (%) 38 39 39 85 97 84 45 52 44 Contrast Preplant source (CL vs 13 1.8 10.8 ) 0.95 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 Contrast Fertigation rate (100% vs 200% ) 0.06 0.0 2 < 0.01 0.0 3 0.15 0.02 0.19 Irrigation Rate (1 00% vs 3 00% ) 0.06 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 < 0.01 z The interaction term for year x irrigation and nutrient management program was significant for nutrient loads (p th e data from both years were analyzed separately. y Means followed by different letters within each column are significantly different at the 0.05 level, according to Duncans multiple range test.

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92 x Fertigation : Nitrogen Potassium rate. w For program 100% F ertigation CL,1 00% Irrigation the source of the preplant fertilizer was chicken litter, while the rest of the programs had 131.8 10.8 as the source of preplant fertilizer. v An additional program for estimating nitrate load using drainage lysimeters insta lled in the ground was carried out at the same time as the current study. The lysimeters installed under programs 100% Fertigation-CL 100% Irrigation 100% Fertigation 100% Irrigation 100% Fertigation300% Irrigation 200% Fertigation 100% Irrigation and 200% Fertigation 3 00% Irrigation were of the same design, and the lysimeters installed under the program 200% Fertigation 3 00% Irrigation ML were modified (ML) in design and varied from the above lysimeters. To maintain the integrity of the predetermined programs data from 200% Fertigation 3 00% Irrigation and 200% Fertigation 3 00% Irrigation -ML (which received the same above ground programs) were not combined. w Total N load ( lb/acre ) based on bed, mean and maximum wetted widths was calculated by adding th e NO3 -N and the NH4 +N loads (lb/acre ) from the respective wetted widths.

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93 Figure 4 1 Schematics of the 3 -feet long lysimeter designs used in the 2005 and 2006 fresh market tomato production experiment are as follows A ) Soil Only and B) Soil & Gravel lysimeter. (Note: t he dotted line in the figure represents the soil level prior to bed formation). Soil Depth ( inches ) Gravel 1 2 inches 24 inches Soil Only 24 inches 1 2 inches (a) Soil Depth ( inches ) ( b ) 24 inches 24 inches Soil

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94 Figure 4 2. Effect s of irrigation -nutrient management program s on A) mean leachate volume (L) collected, and B) mean nitrate load recorded during the 2005 and 2006 growing seasons 2005 Days After Transplanting 0 20 40 60 80 100 120 Leachate Volume (gallons) 0 10 20 30 40 50 60 70 80 90 1 2 3 4 5 6 2006 Days After Transplanting 0 20 40 60 80 100 120 2005 A with drainage lysimeters. (Note: the irrigation and nutrient management programs were 1) 100% Fertigation -CL 100% Irrigation 2) 100% Fertigation100% Irrigation 3) 100% Fertigation 300% Irrigation 4) 200% Fertigation 100% Irrigation 5) 200% Fertigation 300% Irrigation and 6) 200% Fertigation 300% Irrigation -ML. The arrows indicate rainfall events greater than 1 -inch Means followed by different letters within each tom ato fruit grade are significantly different at the 0.05 level, according to Duncans multiple range test and m eans within each tomato fruit grade without mean separation were not significantly affected by irrigation -nutrient management program. The mean s eparation was done in descending order of the means).

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95 2005 Days After Planting 0 20 40 60 80 100 120 Nitrate-Nitrogen Load (lb/acre) 0 5 10 15 20 1 2 3 4 5 6 a Days After Planting 0 20 40 60 80 100 120 2006 a b b b b b b c c c c B Figure 4 2 Continued

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96 CHAPTER 5 NUTRIENT MANAGEMENT PROGRAMS FOR FRESH MARKET TOM ATOES GROWN WITH PLASTICULTURE I N THE ERA OF BEST MANAGEMENT P RACTICES III. ECONOM IC INSIGHTS Introduction Florida is the second largest producer of fresh market tomatoes ( Solanum lycopersicum L. ), for harvested acres and value of production, in the US. Tomato production in Florida accounts for approximately 39% of the national fresh ma rket tomato production, and has an annual value of approximately $464 million (USDA NASS, 2008). In North Florida, fresh market tomatoes are typically grown as a spring crop with raised beds, black plastic mulch, drip irrigation, greenhouse -grown transplan ts (Olson et al., 2007), and harvested 2 4 times at the mature green stage to ensure highest quality (Sargent et al., 2005). Quantity, rate, and scheduling of irrigation (Locascio, 2005) rate, sources, placement, and timing of fertilizer application are t he main factors that affect fresh market tomato yield and quality ( Hochmuth, 2003). Extensive research has been done to determine the fertilizer and irrigation requirements of dripirrigated plastic mulched tomatoes. The current base fertilization recommen dations for tomato production in Florida on soils testing very low in Melich 1 phosphorus (P) and potassium (K) are 66 and 187 lb /acre of P and K F or nitrogen (N) the fertilization recommendation based on research and crop nutrient requirement is 200 lb /a cre N, and includes a detailed fertigation schedule (Olson et al., 2007). Production of fresh market tomatoes requires a significant financial investment in plasticulture, drip irrigation, hybrid seeds and transplants, and manual labor. Achieving high mark etable crop yields has been a fundamental goal of tomato producers to assure economic viability. Growers perceive fertilizer s as having a direct and positive impact on crop yields. Further, fertilizer as a crop input has been relatively cheap, representing less than 5% (University of Florida Center for Agribusiness, 200 6 ) of the total production cost Consequently, growers

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97 tend to apply fertilizer in excess of the University of Florida/Institute of Food and Agricultural Sciences (UF/IFAS) recommended rates as a strategy to prevent nutrient shortages and maintain productivity (Cantliffe et al., 2006). Growers are also hesitant in reducing their irrigation amounts because of low water holding capacity of the sandy soils and because water movement below the roo t zone is a rather abstract concept to them With the adoption of the Federal Clean Water Act (FCWA) of 1977 (US Congress, 1977), states are required to assess the impact of non point sources of pollution on surface and ground waters, and establish progra ms to minimize them. Section 303(d) of the FCWA also requires states to identify impaired water bodies and establish Total Maximum Daily Loads (TMDLs) for pollutants entering these water bodies (FDACS, 2005; Gazula et al., 2007). As a result there has been an increased educational effort to encourage growers to follow the UF/ IFAS recommendations for irrigation and fertilizer application. Environment friendly crop production pract ices may reduce farm income are very hard to sell to farmers and tend not to be adopted (Kelly et al., 1995) Comprehensive crop budget analysis and partial budget analysis help growers with their decision making process, and can be used to calculate potential profits from a change in specific farm ing operations (Muraro et al., 2005; Sydorovych et al., 2008). If growers are shown that under some circumstances, fertilizer/irrigation reductions are unlikely to reduce profitability, they may be more willing to follow UF/IFAS recommendations. Partial budget analysis is a standard economic analysis tool used to determine the cost and return effects of change in a part of the production practices on production economics (Kay and Edwards. 1994; Sydorovych et al., 2008) and has in the past been used to test the economic impact of BMPs aimed a t reducing N levels in river basin, or farms (Wossink and Osmond, 2002). Presently, few current research reports are available on the econom i c impact of the

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98 fertilizer and irrigation BMPs on fresh market tomato pr ofitability Therefore, to better understan d the impact of irrigation and nutrient management practices on fresh market tomato production, a series of experiments were conducted simultaneously with selected irrigation nutrient management programs. The goal of these experiments was to determine if p ossible BMPs (UF/IFAS recommendations) could lessen the negative impact of vegetable production (high fertilizer and irrigation rates) on the environment while maintaining or improving current yields and crop value of an economically important vegetable cr op fresh market tomatoes. The specific objective of this study w as to d etermine the economic impact of irrigation nutrient management programs on fresh market tomato returns. The approach was to first assess the costs and returns associated with growing, harvesting, and marketing fresh market tomatoes grown with different irrigation -nutrient management program s and establish a fresh market tomato production model and second through partial budget analysis assess the economic impact of changes in the irri gation -nutrient management programs on gross returns, gross returns relative to UF/IFAS recommended irrigation -nutrient management program net returns, and net returns relative UF/IFAS recommended irrigation nutrient management program. Materials and Meth ods Fresh Market Tomato Production System A two -year experiment was conducted at the N orth F lorida Research and E ducation Center S uwannee V alley at Live Oak, Fla. on BlantonFoxwort -Alpin Complex soil series (fine sand) during 2005 and 2006. Similar cultur al practices were followed for both years. On April 8th, 2005 and April 5th, 2006 6-week old (Days After Transplanting (DAT) = 0) Florida 47 transplants w ere transplanted on to th e plasticulture system with a 18 in within row spacing, and establishing pla nt a population of 5,808 plants /acre (1 acre = 7,260 linear bed feet) The plants were trained using the standard California/Flor i da stake and weave system. The irrigation -

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99 nutrient management programs were a combination of source of preplant fertilizer s f ertilizer ra te s and irrigation rate s (Table 3 1). The current IFAS recommendation for N -K for commercial tomato production was used as the 100% fertigation rate and twice that amount for the 200% fertigation rate. Split application of fertilizer treatment s through the drip tape was done weekly throughout the growing season and in both years. The standard medium flow rate used by growers in the area (24 gph/100-ft /hr at 12 psi (12 in emitter spacing ; John Deere Water Technologies San Marcos, CA)) was use d for supplying the irrigation. The 100% and 300% irrigation rate was achieved by installing one drip tape and three drip tapes to the respective experimental plots For the 100% and 200% fertigation rate additional one and two drip tapes were installed re spectively. Based on the irrigationnutrient management program, the total number of drip tapes in each program ranged from 2 to 5. Twenty -foot long sections located in the middle bed and representative of each experimental unit were marked for yield meas urements. Mature green t omatoes were harvested at 66, 74, 81, and 88 DAT in 2005, and at 65, 85, and 91 DAT in 2006 and fruits were then graded as extra large, large, medium, and culls (USDA, 1991). The tomato fruits in each grade were counted and then wei ghed. Weight of fruits from each grade were then converted to 25-lb carton/acre (A) by multiplying with the factor 17.44 (fruit weights from raised bed plots 20 -feet long on 5 -feet centers and with 13 plants each at 18 inch within row spacing were converte d into fruit weights from 1 acre raised beds on 5 -feet centers and 5808 plants at 18inch within row spacing ) in order to compare the total yields with yields reported by growers. Total marketable yield was calculated as the sum of extra -large, large, and medium grades. Total season yields were calculated as the sum of yields from all harvests and early season yields were calculated as the sum of first and second harvest yields (Locascio et al., 1985). Market prices for US #1 fresh

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100 market 25 -lb tomato carto ns during s pring of 2005 and 2006 are presented in Table 5 1 (USDA, 2007) Fresh Market Tomato Production Model for University of Florida/Institute of Food and Agricultural Sciences (UF/IFAS) B ased Recommendations The estimated cost to produce and harvest fresh market tomatoes with raised bed plasticulture system consist primarily of the following costs: fertilizer and irrigation costs (Table 5 2 ), operating costs, miscellaneous costs, fixed costs, and harves t and marketing costs (Table 5 3 ). Th e e stimated cost s per acre needed to produce and harvest fresh market tomatoes in Florida using raised -bed plasticulture system were based on the tomato crop budget developed by the University of Florida Center for Agribusiness (200 6 ). Variable c ost s of irrigation (Ta ble 5 2 ) w ere based on information provided by Pitts et al. (2002) and the f ertilizer input prices from 2005 and 2006 (Table 5 2 ) were obtained from local dealers. A harvest and marketing charge of $3.64/25 lb carton was used to estimate the harvest and ma rketing costs for total marketable tomato yields in 2005 and 2006. It included cost of containers, selling cost, packing cost, harvesting cost hauling cost and organization fees (Table 5 3 ). Methodology of Partial Budget Analysis of Irrigation -Nutrient M anagement Programs Partial budget analysis was performed to determine economic effects of the irrigationnutrient management programs on fresh market tomato production. Typically, partial budget analysis has the following components (Dalsted and Gutierrez, 2007; Eleveld, 1989): 1 Additions to income/Pos itive effects include a A dded returns due to new management program b Re duced costs due to new management program c Total Additions sum of additions to income 2 Subtractions from income/Negative effects include a A dded costs due to new management program b Reduced returns due to new management program

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101 c Total subtractions : sum of subtractions from income 3 Total effects/Net change in revenue : calculated as the difference between total additions/ positive effects and tota l subtractions/negative effects. Added or reduced costs of the irrigation -nutrient management programs relative to the UF/IFAS recommended program were calculated by using the es timated program costs (Table 5 2 ) and harvest costs (Table 5 5 ). Added returns were incurred if the irrigation nutrient management program resulted in higher yields and thereby higher gross returns relative to the UF/IFAS recommended program, while reduced returns were seen with lower yields and thereby lower gross returns relative to the UF/IFAS recommended program. Added costs were incurred if the irrigation -nutrient management program resulted in higher fertilizer, irrigation, or harvest costs relative to the UF/IFAS recommended program. While reduced costs were incurred if the i rrigation -nutrient management program resulted in lower fertilizer, irrigation, or harvest costs relative to the UF/IFAS recommended program. Added or reduced returns relative to the UF/IFAS recommended program were based on measured yield values of the di fferent irrigation nutrient management programs (Table 5 6 ). Results and Discussion Fresh Market Tomato Production Costs The market prices that the growers received for the 25 lb tomato car tons varied with year (Table 5 1 ). However, in 2005 and 2005, the price variations within grades and within season were minimal. Because t he fresh market tomato yields varied significantly with year results from both years were analyzed separately. Estimated cost of irrigation -nutrient management programs varied with y ear and program (Table 5 2 ). The estimated irrigation nutrient management costs associated with the UF/IFAS program were $ 402.93/acre and $418.37/acre in 2005 and 2006, respectively. The CL preplant

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102 irrigation -nutrient management program resulted in decrea sed treatment costs ( $25.39/acre and $19.23/acre in 2005 and 2006, respectively) relative to the UF/IFAS recommended program The higher irrigation and fertigation programs resulted in increased treatment costs. The cost difference between these programs a nd the UF/IFAS recommended irrigation nutrient management program ranged from an addition al $17.18/acre $214.84/acre and $17.18/acre $195.90/acre in 2005 and 2006, respectively (Table 5 2 ). Total production costs, including fixed costs, harvest and market ing costs, were $13,820/acre in 2005 and $11,972/acre in 2006 (Table 5 3 ). T he irrigation variable cost was $128.86/acre in both years, and represented 0.9%1.1% of the total production cost. The cost of the fertilizer program ranged from $274/acre $ 290/ac re in 2005 and 2006, respectively. The cost of fertilizer inputs represented 1.98% to 2.42% of the total production cost. In contrast consider a crop like field corn where per acre production costs are considerably lower than fresh market tomatoes, but whe re fertilizer inputs represent 17.73%19.89% of the total production costs (D uffy and Smith 2008) with fresh market tomatoes fertilizer inputs represent ed a minor 1.98% 2.42% of the total production cost. A break even (B -E) price is defined as the marke t price threshold, or price needed, to recoup all production costs. Break -even price for a 25 -lb tomato carton is a fun ction of total marketable yield, and therefore varie s by season The total marketable yield in 2005 and 2006 were 1,783 and 1,271 25lb c artons /acre, respectively. The break -even price in 2005 was $7.75 per 25-lb carton ($13,820/ 1,783 25lb cartons ). Lower total marketable yields in 2006 increased the break -even price by nearly $2 per 25 lb carton to $9.42 per 25-lb carton. Season average prices of tomato grades ($/25 lb carton) for District 4 F loridas shipment and sales were obtained for 19982008 from Annual Reports of the Florida Tomato Committee (Table 5 4 ). U sing the

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103 fresh market tomato yields recorded in 2005 and 2006, and the UF/IFA S irrigation -nutrient management program a net profit ($/25lb carton) analysis was conducted between 1998 and 2008 (Figure 5 1 ). With a break -even price of $7.75, net profits would have been realized six out of eleven years between 1998 and 2009. At a hi gher break even price of $9.42, net profits would have been realized only in three Growers generally make production decisions such as rate of fertilizer input at the beginning of the season As commodity prices vary with season and year, current fertiliz er prices, and break even price analysis influence grower decisions on production practices. Marginal Analysis of the Value of Extra Fertilizer and Irrigation Marginal analysis is the p rocess of identifying the benefits and costs of alternative farm manag ement practices by examining the incremental or additional effect s on total revenue and total cost caused by a unit change in the output or input. Marginal analysis supports decisionmaking based on marginal or incremental changes to resources A relations hip (Equation 5 1) was developed to determine the break -even yield necessary to cover an increase in fertilizer (nitrogen) costs, for a range of market prices. Y = F c P H W here, Y = break -even yield (25 lb cartons/acre) FcIn 2005, the cost of a 32% urea ammonium nitrate solution (32 0 0, N P -K) was $229/2000 lbs (USDA NASS, 2008) or $ 0.32/lb of N Therefore, the cost of UF/IFAS irrigation nutrient management program is $72/acre. Increasing the N fertilizer application by 200% increases appli ed N from 200 to 400 pounds per acre. Nitrogen costs increase correspondingly from $72 to = change in fertilizer cost ($/acre) P = market price of 25 -lb tomato carton ($/25 lb carton) H = unit harvest cost ($/25 lb carton)

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104 $144 per acre, or by $72. (Figure 5 2). The additional yield required to cover the increased fertilizer cost depends on the unit price of 25lb tomato carton. With tw ice the UF/IFAS recommended fertilizer rate and with market price of $ 5 per /25 lb tomato carton, grower s would need to realize an additional 5 3 25lb carton /acre to pay for the increased fertilizer costs. Alternatively, if market prices approached $20 pe r 25 lb carton, the additional increase in marketable yield would be 4 25lb carton/acre In 2005 and 2006, the tomato yields were numerically higher with the 2 00% Fertigation program and yield differences among these programs ranged from 37 to 153 25lb cartons/acre. This difference is above the addi ti onal yield required to cover the increased fertilizer costs. Therefore, the additional yield required to cover the increased fertilizer costs is minimal for a high input crop like fresh market tomato. Growe rs generally make production decisions regarding rate of fertilizer input at the beginning of the season. Therefore, marginal analysis helps identify the benefits and costs of alternative farm management practices by examining the incremental or additional effect s on total revenue and total cost caused by a unit change in the output or input As mentioned earlier, because of the high capital investment in plasticulture, drip irrigation, hybrid seeds and transplants, and because fertilizer as a crop input re presents only 1.98%2.42% of the total production cost, fertilizer rates in excess of the University of Florida/Institute of Food and Agricultural Sciences (UF/IFAS) recommended rates have been used by growers as a strategy to prevent nutrient shortages an d maintain productivity. Based on the break -even yield analysis, the se results give an insight into the growers practice of high fertilization rates.

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105 Effect of Irrigation -Nutrient Management Programs on Gross Returns from Fresh Market Tomato Production As th e interaction year x treatment was significant for most of the harvests and grade distributions ( p < 0.05), data were analyzed separately by year. Total marketable tomato yields rec orded in 2005 ranged from 1,2421,883 25lb cartons /acre, and in 2006, t he total marketable tomato yields ranged from 9201,424 25lb cartons /acre. Overall, t otal marketable tomato yields recorded in 2005 were higher than th os e recorded in 2006. In 2005, highest total marketable yields occurred with 1 00% Fertigation CL,100% Irrigation (1,883 25lb carton/acre) and the lowest with 1 00% Fertigation 300% Irrigation treatment (1,242 25lb carton/acre). In 2006, highest total marketable yields for were seen with 200% Fertigation 100% Irrigation treatment (1,424 25lb cartons ) and lo west yields were recorded with 100% Fertigation300% Irrigation treatment (920 25lb cartons ). Irrigation management In both 2005 and 2006, relative to the UF/IFAS recommended irrigationnutrient management program ( 100% Fertigation 100% Irrigation) the h igh irrigation alone program (100% Fertigation 3 00% Irrigation ) resulted in significantly lowest t otal marketable tomato yields, and therefore lowest gross returns (Table 5 5 ). Fertilization management In both 2005 and 2006, there were no significant diff erences between the UF/IFAS recommended irrigation -nutrient management program and the high fertigation alone program (2 00% Fertigation 1 00% Irrigation ) for t otal marketable tomato yields, and gross returns. However, in both 2005 and 2006, the 200% Fertiga tion 1 00% Irrigation irrigation -nutrient management program resulted in numerically higher t otal marketable tomato yields ( 1,820 and 1,424 25lbs cartons/acre in 2005 and 2006, respectively ), and gross returns ($20,379/acre and

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106 $12,035/acre, in 2005 and 2006, respectively) relative to the UF/IFAS irrigation -nutrient management program (total marketable tomato yields: 1,783 and 1,271 25lbs cartons/acre in 2005 and 2006, respectively; gross returns: $19,972/acre and $10,736/acre in 2005 and 2006, respective ly). In 2005, with a high fertigation and irrigation management program (200% Fertigation 3 00% Irrigation ) there were no significant differences between the UF/IFAS recommended irrigation -nutrient management program and the 200% Fertigation3 00% Irrigation irrigation nutrient management programs for t otal marketable tomato yields, and gross returns (Table 5 5 ). However, in 2006, the 200% Fertigation3 00% Irrigation resulted in significantly lower total marketable tomato yields, and gross returns (Table 5 5 ). These results suggest in 2005, a relatively cool and wet year, the higher fertigation rate of the 200% Fertigation3 00% Irrigation irrigation -nutrient management program helped offset the lower yields recorded with the high irrigation alone 100% Fertigat ion 3 00% Irrigation program While, in 2006, a relatively warm and dry year, the higher fertigation rate of the 200% Fertigation 3 00% Irrigation irrigation nutrient management program lacked a similar ameliorative effect. Benefits from chicken litter In both 2005 and 2006, there were no significant differences between the UF/IFAS recommended irrigation -nutrient management program (100% Fertigation 1 00% Irrigation) and the 100% Fertigation -CL,100% Irrigation program for t otal marketable tomato yiel ds, and g ross returns (Table 5 5 ). However, in both 2005 and 2006, the CL preplant nutrient management program resulted in numerically higher t otal marketable tomato yiel ds, and gross returns (Table 5 5 ).

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107 Partial Budget Analysis of Irrigation -Nutrient Management Pr ograms Partial budget analysis was performed on the 100% Fertigation 100% Irrigation (UF/IFAS recommended irrigation -nutrient management program), 100% Fertigation-300% Irrigation, 200% Fertigation 100% Irrigation, and 200% Fertigation300% Irrigation irri gation nutrient management programs. In both 2005 and 2006, there were no significant differences between the 100% Fertigation 100% Irrigation and 200% Fertigation100% Irrigation programs. However, in both years the 200% Fertigation100% Irrigation progra m resulted in numerically higher yields and the partial budget analysis was conducted to analyze the numerical differences between the different irrigation -nutrient management programs. As the UF/IFAS recommended program was used as the reference program for comparing the remaining five programs with, it did not have any added costs or reduced returns, and therefore the total effects were zero (Table 5 6 ). In both years, the 200% Fertigation 100% Irrigation program had higher positive effects relative to th e UF/IFAS program (+$54.5/acre, and +$561.3/acre, in 2005 and 2006 respectively). In both years, relative to the UF/IFAS recommended program, the 100% Fertigation300% Irrigation program resulted in the highest total negative effects ( $ 4,112.2/acre). Simi larly, in both 2005 and 2006, relative to the UF/IFAS recommended irrigation-nutrient management program, the 200% Fertigation 300% Irrigation program also resulted in negative effects ( $1,932.8/acre, and $722.9/acre, in 2005 and 2006 respectively). Eco nomic R eturns versus N utrient Loading In both 2005 and 2006, relative to the UF/IFAS recommended program the 200% Fertigation 100% Irrigation program resulted in numerically higher net returns ranging from $54. 5 /acre $561.3 /acre However, relative to the UF/IFAS recommended program, the 200% Fertigation 100% Irrigation program also resulted in higher total N load (2.42 lb/acre ) (Table 5 7 ). Therefore, although the 200% Fertigation100% Irrigation irrigation -nutrient management

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108 program resulted in numerical ly higher net returns relative to the UF/IFAS program (an advantage to growers), it also results in increased total N load (disadvantage to environment ). Currently, there are no established monetary penalties for nutrient pollution in the watershed. Howeve r, with the adoption of House Bill 547 which amends s. 403.067, F.S. (FDEP, 2008) the current law governing water quality credit trading Florida Legislation authorizes the Florida Department of Environmental Protection (FDEP, 2008) to adopt rules to impl ement a water quality credit trading program specifically in the Lower St. Johns River Basin as a pilot program If the pilot program is a success, water quality credit trading program could potentially be expanded to other water management districts in F lorida, and thus allocating a monetary value on increased total N load or nutrient pollution. In both 2005 and 2006, relative to the UF/IFAS recommended program, the 100% Fertigation 300% Irrigation program resulted in the highest total net negative returns ( $ 4,112.2/acre, and $1,701.2/acre, in 2005 and 2006 respectively). Similarly, in both 2005 and 2006, relative to the UF/IFAS recommended irrigation-nutrient management program, the 200% Fertigation 300% Irrigation program also resulted in net negative returns ( $1,932.8/acre, and $722.9/acre, in 2005 and 2006 respectively). When comparing the high irrigation programs (100% Fertigation 300% Irrigation 200% Fertigation 300% Irrigation) alone, the 200% Fertigation 300% Irrigation resulted in significantl y lower net negative returns than the 100% Fertigation 300% Irrigation program. These results suggest that in a high irrigation scenario higher fertilizer rates may ameliorate the negative effects of the high irrigation program. However, both high irrigati on programs could also result in higher total N l oad (Table 5 7 ). Conclusion G iven the low water holding capacity of Floridas coarse textured soils the dripirrigating fresh market tomato growers oftentimes over irrigate to maintain adequate moisture leve ls within

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109 the plant root zone. N P -K fertilizers are highly water soluble, and as growers mismanage the irrigation water application, they generally tend to over -fertigate to compensate the loss of nutrients from the plant root zone. Moreover, because of t he high capital investment in plasticulture, drip irrigation, hybrid seeds and transplants, and because fertilizer as a crop input in this instance represents only 0.9% to 1.1% of the total production cost, fertilizer rates in excess of the University of F lorida/Institute of Food and Agricultural Sciences (UF/IFAS) recommended rates have been used by growers as a strategy to prevent nutrient shortages and maintain productivity (Cantliffe et al., 2006). Based on our results the high irrigation management pro gram (100% Fertigation 300% Irrigation) not only increase d the cost of the irrigation -nutrient manage ment program but it also resulted in lower returns relative to the UF/IFAS recommended irrigation nutrient management program Moreover, it could also resu lt in higher total N load relative to the UF/IFAS program Therefore w e can conclude that growers should not use higher irrigation rates to ensure adequate soil moisture levels in the crop root zone as it results in net losses. Instead, they should better manage irrigation water application either by splitting irrigation application, and/or by using low -flow drip irrigation. T he high fertigation alone irrigation -nutrient management program did not differ statistically from the UF/IFAS irrigation -nutrient m anagement program. Although, it resulted in numerically higher net returns relative to the UF/IFAS recommended ir rigation -nutrient management program in both 2005 and 2006, it also resulted in higher total -N load than the UF/IFAS recommended program. Given the adoption of legislation to establish a monetary value on increased total N load or nutrient pollution in select regions of state of Florida, there is an added negative impact to high fertilizer application. Ther e fore, w e can conclude that with better

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110 management of irrigation water application there is n o economic benefit in applying fertilizer rates in excess of the UF/IFAS recommended nutrient management program .

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111 Table 5 1 Price of US #1 tomat oes during spring of 2005 and 2006 fresh market tomato pro duction with raised -bed plasticulture system in North Floridaz Price of US #1 tomatoes $/25 lb carton Harvest Date XLarge Large Medium 2005 6/13/2005 13.20 13.20 13.20 6/21/2005 9.20 9.20 9.20 6/28/2005 11.20 11.20 11.20 7/5/2005 11.20 11.20 11.20 2006 6/9/2006 8.45 8.45 8.45 6/29/2006 8.45 8.45 8.45 7/5/2006 8.45 8.45 8.45 z Prices of US #1 tomatoes during spring of 2005 and 2006 fresh market tomato production were based on information from USDA Agriculltural Marketing Service

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112 Table 5 2 Estimated costs of irrigation -nutrient management programs for spring 2005 and 2006 Florida 47 fresh market tomato production with raised -bed plasticulture system. Irrigation Nutrient Management Program Costs ($ /acre z ) Irrigation Nutrient Management P rogram Preplant Fertilizer Cost Injected Fertilizer Cost y Irrigation Tubing Cost x Irrigation Pumping Cost Irrigation System Labor Cost Total Program Cost Cost of Program Relative to UF/IFAS 2005 100% Fertigation CL w 40.00 ,100% Irrigation 208.69 107.5 8. 59 12.77 377.55 25.39 100% Fertigation, 100% Irrigation 65.39 208.69 107.5 8.59 12.77 402.93 0.00 100% Fertigation, 300% Irrigation 65.39 208.69 107.5 25.77 12.77 420.11 17.18 200% Fertigation, 100% Irrigation 65.39 417.38 107.5 8.59 12.77 611.62 208.6 9 200% Fertigation, 300% Irrigation 65.39 417.38 107.5 25.77 12.77 628.80 225.87 200% Fertigation, 300% Irrigation ML 65.39 v 417.38 107.5 25.77 12.77 628.80 225.87 2006 100% Fertigation CL, 100% Irrigation 50.00 220.28 107.5 8.59 12.77 399.14 19.23 1 00% Fertigation 100% Irrigation 69.23 220.28 107.5 8.59 12.77 418.37 0.00 100% Fertigation 300% Irrigation 69.23 220.28 107.5 25.77 12.77 435.55 17.18 200% Fertigation 100% Irrigation 69.23 440.56 107.5 8.59 12.77 638.65 220.28 200% Fertigation 300% Irr igation 69.23 440.56 107.5 25.77 12.77 655.83 237.46 200% Fertigation 300% Irrigation ML 69.23 440.56 107.5 25.77 12.77 655.83 237.46 z The raised plant beds were on 6 -ft centers. Therefore, there was a total of 7,260 linear bed feet of raised plastic be ds. y The cost of preplant fertilizer chicken litter was $20 and $25 per 2000 lbs in 2005 and 2006, respectively. The cost of prepl ant fertilizer 13 1.7 10.7 was $330 and $350 per 2000 lbs in 2005 and 2006, respectively. x The cost of 80 6.6 injected fertilizer was $180 and $190 per 2000 lbs in 2005 and 2006, respectively. w For program 1 00%Fertigation -CL, 100% Irrigation the source of the preplant fertilizer was chicken litter. The other programs had 13 1.7 10.7 as the source of preplant fertilizer. v An a dditional program for estimating nitrate load using drainage lysimeters installed in the ground was carried out at the same time as the current study. The lysimeters installed under programs 100% Fertigation-CL, 100% Irrigation 100% Fertigation 100% Irrig ation 100% Fertigation300% Irrigation 200% Fertigation 100% Irrigation and 200% Fertigation 3 00% Irrigation were of the same design, and the lysimeters installed under the program 200% Fertigation 3 00% Irrigation -ML were modified (ML) in design and varie d from the above lysimeters. To maintain the integrity of the predetermined programs data from 200% Fertigation 3 00% Irrigation and 200% Fertigation 3 00% Irrigation -ML (which received the same above ground programs) were not combined.

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113 Table 5 3 Estimated costz to produce and harvesty Category Florida 47 tomato es with raised bed plasticulture system using University of Florida/Institute of Food and Agricultural Sciences irrigation -nutrient management program in spring of 2005 and 2006. 2005 2006 2005 200 6 Fertilizer and Irrigation Costs $ /acre $/25 lb Carton Fertilizer 274.07 289.51 Irrigation Tubing 107.50 107.50 Pumping Costs 8.59 8.59 Labor Cost 12.77 12.77 Total Fertilizer and Irrigation Costs 402.93 418.37 Operating Costs Transp lants 450.00 450.00 Fumigant 843.75 843.75 Fungicide 243.52 243.52 Herbicide 44.51 44.51 Insecticide 514.75 514.75 General Farm Labor 186.62 186.62 Machinery Variable Cost 677.81 677.81 Tractor Driver Labor 311.58 311.58 Miscellaneo us Costs Tie Plants 145.20 145.20 Scouting 45.00 45.00 Plastic Mulch 345.00 345.00 Stakes 96.00 96.00 Plastic String 110.00 110.00 Farm Vehicles 32.00 32.00 Stake and String Disposal 199.00 199.00 Plastic Mulch Disposal 140.00 140 .00 Interest on Operating Capital 237.72 237.72 Total Operating Cost 4622.46 4622.46 Fixed Costs Land Rent 300.00 300.00 Machinery Fixed Cost 235.94 235.94 Farm Management 663.20 663.20 Overhead 1105.33 1105.33 Total Fixed Cost 23 04.47 2304.47 Total Pre harvest Cost 7329.86 7345.30 Harvest and Marketing Costs Containers 1337.25 953.25 0.75 0.75 Sell 267.45 190.65 0.15 0.15 Pack 3209.40 2287.80 1.8 1.8 Harvest and Haul 1515.55 1080.35 0.85 0.85 Organization Fees 160.4 7 114.39 0.09 0.09 Total Harvest and Marketing Cost 6490.12 4626.44 3.64 3.64 Total Cost 13819.98 11971.74 7.75 9.42 y y

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114 z Cost of fertilizer, irrigation, preharvest production costs for a 1 acre tomato field for the different treatments were calculated b ased on information provided by local fertilizer dealers, Pitts et al., (2002), and e stimated production costs in the Manatee/Ruskin area, 2005 2006, University of Florida Center for Agribusiness website. y Measured tomato yield of 1,783 and 1,271 25lb ca rtons /acre in spring of 2005 and 2006 respectively

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115 Table 5 4 Season average prices of tomato grades ($/ 25 lb carton ) for District 4 F loridas shipment and salesz Season Average Tomato Price ($/25 lb carton) Year U.S. One or Better U.S. Combination U. S. Two 1998 10.17 8.96 8.47 1999 7.65 7.43 9.05 2000 7.33 6.46 6.69 2001 10.12 9.07 8.40 2002 8.24 7.40 6.75 2003 9.43 8.99 8.28 2004 8.51 7.37 7.04 2005 14.43 13.40 11.73 2006 10.69 10.90 10.80 2007 7.88 7.34 6.86 2008 14.76 13.33 12.44 z Sea son average prices of tomato grades for District 4 Floridas shipment and sales were based on information available in the Annual Reports of the Florida Tomato Committee, Orlando, FL.

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116 Table 5 5 Effects of irrigation and nutrient management programs on Fl orida 47tomato fruit yield s ( 25-lb carton/acre), gross returns ($/acre ), and gross returns relative to the University of Florida/Institute of Food and Agricultural Sciences recommended irrigation -nutrient management programz during spring of 2005 and 2006y Irrigation Nutrient Management Program with raised -bed plasticulture system. Total Marketable 25 lb cartons/acre x Harvest Cost ($/acre ) w Harvest Cost Relative to UF/IFAS Program ($/acre ) Gross Returns ($/ acre ) Gross Returns Relative to UF/IFAS Program ($/acre) 2005 100% Fertigation CL v 1,883 a ,100% Irrigation 6,853 +362 21,087 a +608 100% Fertigation 100% Irrigation 1,783 ab 6,491 0 19,972 ab 0 100% Fertigation 300% Irrigation 1,242 c 4,519 1,972 13,905 c 6,084 200% Fertigation 100% Irrigation 1 ,820 ab 6,623 +132 20,379 ab +325 200% Fertigation 300% Irrigation 1,556 b 5,663 828 17,426 b 2,490 200% Fertigation 300% Irrigation ML 1,677 ab u 6,103 388 18,778 ab 1,339 p value < 0.01 < 0.01 2006 100% Fertigation CL, 100% Irrigation 1,291 ab 4,700 +75 10,912 ab +176 100% Fertigation 100% Irrigation 1,271 ab 4,625 0 10,736 ab 0 100% Fertigation 300% Irrigation 920 c 3,349 1,276 7,776 c 2,960 200% Fertigation 100% Irrigation 1,424 a 5,184 +559 12,035 a +1,299 200% Fertigation 300% Irrigat ion 1,161 abc 4,226 399 9,810 abc 926 200% Fertigation 300% Irrigation ML 1,064 bc 3,875 750 8,995 bc 1,741 p value < 0.01 < 0.01 z The University of Florida/Institute of Food and Agricultural Sciences recommended irrigation-nutrient management program was 100% Fertigation 100% Irrigation y The interaction term for year x irrigation and nutrient management program was significant for fruit yields ( p data from both years were analyzed separately. x Fertigation : Nitrogen Potas sium rate w Means followed by different letters within each column are significantly different at the 0.05 level, according to Duncans multiple range test. v For program 100% Fertigation CL,1 00% Irrigation the source of the preplant fertilizer was chicke n litter, while the rest of the programs had 131.8 10.8 as the source of preplant fertilizer. u An additional program for estimating nitrate load using drainage lysimeters installed in the ground was carried out at the sa me time as the current study. The lysimeters installed under programs 100% Fertigation -CL, 100% Irrigation 100% Fertigation 100%

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117 Irrigation 100% Fertigation300% Irrigation 200% Fertigation 100% Irrigation and 200% Fertigation 3 00% Irrigation were of the same design, and the lysimeters installed under the program 200% Fertigation 3 00% Irrigation ML were modified (ML) in design and varied from the above lysimeters. To maintain the integrity of the predetermined programs data from 200% Fertigation 3 00% Irrigation and 200% Fertigation 3 00% Irrigation -ML (which received the same above ground programs) were not combined.

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118 Table 5 6 Total negative effects (added costs and reduced returns), total positive effects (reduced costs and added returns), and net returns of the irrigation-nutrient mana gement programs relative to the UF/IFAS recommended programz for fresh market tomato production during spring of 2005 and 2006y Irrigation Nutrient Management Program with raised bed plasticulture system. Added Costs of Alternative Program ($/ acre ) x Reduced Ret urns of Alternative Program ($/acre ) Total Negative Eff ects of Alternative Program ($/acre ) Reduced Costs of Alternative Program ($/acre ) Added Returns of Alternative Program ($/acre ) Total Positive Effe cts of Alternative Program ($/ac re ) Total Effects of Alternative Program Relative to UF/IFAS Program ($/acre ) 2005 100% Fertigation 100% Irrigation 0 0 0 0 0 0 0.0 100% Fertigation 300% Irrigation 17 6,067 6,084 1,972 0 1,972 4,112.2 200% Fertigation 100% Irrigation 132 221 353 0 407 407 +54.5 200% Fertigation 300% Irrigation 215 2,546 2,761 828 0 828 1,932.8 2006 100% Fertigation 100% Irrigation 0 0 0 0 0 0 0.0 100% Fertigation 300% Irrigation 17 2,960 2,977 1,276 0 1,276 1,701.2 200% Fertigation 100% Irrigation 179 559 73 8 0 1,299 1,299 +561.3 200% Fertigation 300% Irrigation 196 926 1,122 399 0 399 722.9 z The University of Florida/Institute of Food and Agricultural Sciences recommended irrigation-nutrient management program was 100% Fertigation 100% Irrigation y The i nteraction term for year x irrigation and nutrient management program was significant for fruit yields ( p data from both years were analyzed separately. x Fertigation : Nitrogen Potassium rate .

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11 9 Table 5 7 Net return s and changes in total N load of irrigation nutrient management program s relative to the University of Florida/ Institute of Food and Agricultural Sciences recommended programz for Florida 47 fresh market tomato production during spring of 2005 and 2006y Irrigation Nutrient Management Program with raised -bed pl asticulture system. Net Returns Relative to UF/IFAS Program ($/acre) x Changes in Total N Load Relative to UF/IFAS Program ( lb/acre ) 2005 100% Fertigation 100% Irrigation 0.0 0.00 100% Fertigation 300% Irrigati on 4,112.2 1.40 200% Fertigation 100% Irrigation +54.5 2.42 200% Fertigation 300% Irrigation 1,932.8 0.02 2006 100% Fertigation 100% Irrigation 0.0 0.00 100% Fertigation 300% Irrigation 1,701.2 1.64 200% Fertigation 100% Irrigation +561.3 0.16 200% Fertigation 300% Irrigation 722.9 6.53 z The University of Florida/Institute of Food and Agricultural Sciences recommended irrigationnutrient management program was 100% Fertigation 100% Irrigation y The interaction term for year x irrigation and nutrient management program was significant for fruit yields (p x Fertigation: Nitrogen Potassium rate

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120 Figure 5 1 Effect of season average market prices of tomato grades ($/25 lb ca rton) for District 4 F loridas shipment and sales of U.S. One or Better 25 lb tomato cartons and fresh market tomato yields recorded in 2005 and 2006 with the UF/IFAS irrigation nutrient management program (25 -lb tomato cartons) on net profits ($/25 lb car ton). Year of Production 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Net Profit ($/25-lb tomato carton) -4 -2 0 2 4 6 8 2005 2006

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121 Figure 5 2 Relationship between additional break -even yield ( yield) and increase in nitrogen fertilizer costs ( F ) due to increased nitrogen fertilizer application at different season average market prices of tomato grades ($/25-lb carton) for District 4 F loridas shipment and sales of U.S. One or Better 25 lb tom ato cartons Market Price of Tomatoes ($/25 lb-carton) 0 2 4 6 8 10 12 14 16 18 20 22 Yield Required to Cover Nitrogen (25 lb-cartons/acre) 0 5 10 15 20 25 30 35 40 45 50 55 60 F $72/acre

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122 CHAPTER 6 CONCLUSION To better understand the impact of irrigation and nutrient management practices on fresh market tomato production, by using an integrated fertilization/irrigation approach, a series of experiments were conducted simultaneo usly with selected irrigation -nutrient management programs. The goal of these experiments was to determine if possible BMPs (UF/IFAS recommendations) can minimize the negative impact of vegetable production (high fertilizer and irrigation rates) on the env ironment while maintaining or improving current yields and crop value of an economically important vegetable crop fresh market tomatoes ( Solanum lycopersicum L.). The results from these experiments suggest that CL did not differ significantly from the U F/IFAS recommended irrigationnutrient management program for total marketable yields (1 2911 883 25lb carton /acre 1 2711 291 25lb carton/acre, respectively) and soil profile total N load measured with soil sampling (2. 4 6 3. 39 lb/acre, 2.26 3. 14 lb/ac re respectively) and seasonal total -N load measured with drainage lysimeters (0.0040 1.04 lb/acre 0.54 0.8 1 lb/acre respectively) Based on the economic analysis, not only did CL used as a preplant fertilizer source decrease the cost of the irrigationnutrient management program ($19.23/acre $25.39/acre), but it also resulted in higher net returns ($1 20/acre $777/acre) relative to the UF/IFAS recommended irrigation nutrient management program. T herefore CL can be used as an alternative preplant fertilizer source if transported within 164-miles from the production facility Applying higher irrigation ( 100% Fertigation300% Irrigation ) reduced water stress in the plant bed for only for 1 2 days during the cropping cycle, but resulted in insufficient NO3 -N and K+ petiole concentrations, which further result ed in lowest total fruit yields in both 2005 and

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123 2006 (9201 242 25lb carton /acre) The soil -profile total N load with the 100% Fertigation300% Irrigation did not differ significantly from the UF/IFA S recommended irrigation -nutrient management program in both 2005 and 2006 and (2. 192.21 lb/acre 2.26 3. 14 lb/acre respectively) and neither did the seasonal total N load measured with drainage lysimeters (0.0040 1.04 lb/acre 0.540.8 1 lb/acre, respec tively ). The partial budget economic analysis suggests that a high irrigation management program (100% Fertigation300% Irrigation ) not only increased the cost of the irrigation -nutrient management program ($17.18/acre ), but it also resulted in lowe st net returns ( $1,702/acre $ 4,113/acre) relative to the UF/IFAS recommended irrigation -nutrient management program. Hence, growers should not use higher irrigation rates to ensure adequate soil moisture levels in the crop root zone. Instead they should bett er manage irrigation water application either by splitting irrigation application, and/or by using low -flow drip irrigation. In the current study the high fertigation rate (200% Fertigation100% Irrigation ) was twice the UF/IFAS recommended nutrient manag ement rate. Even with a considerably higher fertigation rate there were no significant differences between the 200% Fertigation100% Irrigation and the UF/IFAS recommended irrigation -nutrient management program for total marketable yield in both 2005 and 2006 (1,4241,820 25lb carton /acre, 1,271 1,783 25lb carton /acre, respectively) In 2006, with soil sampling the highest soil -profile total -N load was recorded with 200% Fertigation100% Irrigation program (3. 184. 32 lb/acre ). However with drainage lysi meters the seasonal total N load with the 200% Fertigation 100% Irrigation did not differ significantly from the UF/IFAS recommended irrigation -nutrient management program in both 2005 and 2006 (0. 383.24 lb/acre 0. 540.8 1 lb/acre respectively). Although it resulted in numerically higher net returns relative to the UF/IFAS recommended irrigation-nutrient

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124 management program in both 2005 and 2006, it also resulted in higher total -N load than the UF/IFAS recommended program. Given the adoption of legislation to establish a monetary value on increased total N load or nutrient pollution in select regions of the state of Florida, there is an added negative impact to high fertilizer application. The high fertigation and high irrigation nutrient management progra m (200% Fertigation 3 00% Irrigation ) did not differ significantly from the UF/IFAS recommended irrigation -nutrient management program for total marketable yields (1,161 1,556 25lb carton /acre 1,2711,783 25lb carton /acre respectively). The seasonal tot al N load recorded with the 200% Fertigation 3 00% Irrigation varied highly with year. I n 2005, the 200% Fertigation 3 00% Irrigation did not differ significantly from the UF/IFAS recommended irrigation -nutrient manageme nt program for total N load (0.7 9 lb/a cre, 3. 24 lb/acre ). However, in 2006 200% Fertigation 3 00% Irrigation had significantly higher seasonal total N load (7. 07 lb/acre ) than the UF/IFAS recommended irrigation -nutrient management program (0. 54 lb/acre ). Moreover, based on the partial budget an alysis the 200% Fertigation 3 00% Irrigation not only increased the cost of the irrigationnutrient management program ($225.87/acre $237/a cre ), but it also resulted negative net returns ($722/acre $1,934/acre) relative to the UF/IFAS recommended irrigation -nutrient management program. Therefore, the growers should not follow a high irrigation and a high fertigation program as it results in net losses when compared to the UF/IFAS recommended irrigation -nutrient management program. Soil profile total N lo ad of selected programs was estimated using soil sampling. Irrespective of treatment, tomato soil -profile total N load was highest in the first 30.5 -cm depth of soil, and tended to decrease with an increase in depth. Tomato soil -profile total N load varied with year, depending on the method of estimating wetted width and the irrigationnutrient

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125 management program, the total -N load ranged from 0. 1 3 1.54 lb/acre in 2005, and from 1. 494. 32 lb/acre in 2006. The soil profile total N load measured in 2005 was much lower than that measured in 2006, and the results within each year showed high variability. However, based on the relatively low soil profile total N loads recorded, the rate of movement of the water front in this study might have been higher than expec ted from past research conducted under similar conditions of soil and irrigation. Therefore, b oth the seasonal and soil -profile load monitoring methods might have underestimated the total N load from the different irrigatio n nutrient management programs. F urther work needs to be done to improve the soil sampling and drainage lysimeter based nutrient load monitoring procedures. Based on the results from these studies we can conclude that CL can be used as an alternative preplant fertilizer source if transported within 164-miles from the production facility. We can also conclude that growers should not use higher irrigation rates to ensure adequate soil moisture levels in the crop root zone as it results in net losses. Instead, they should better manage irriga tion water application either by splitting irrigation application, and/or by using low -flow drip irrigation. We can also conclude that growers should not follow a high irrigation and high fertigation program as it results in net losses when compared to the UF/IFAS recommended irrigation -nutrient management program.

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126 LIST OF REFERENCES Abad, A., J. Lloveras, and A. Michelena. 2004. Nitrogen fertilization and foliar urea effects on durum wheat yield and quality and on residual soil nitrate in irrigated Medit erranean conditions. Field Crops Res. 87(2 3)257269. Abdou, H. M. and M. Flury. 2004. Simulation of water flow and solute transport in free -drainage lysimeters and field soils with heterogenous structures. Europ. J. Soil Sci. 55:229241. Ahmad, A., I. K han, Y P Abrol, and M Iqbal 2008. Genotypic variation of nitrogen use efficiency in Indian mustard Environ. Pollution 154(3):462466. Ahmed, M., M.L. Sharma, Q.D. Richards, and M.S. Al -Kalbani. 2001. Sampling soil water in sandy soils: Comparative ana lysis of some common methods. Commun. Soil Sci. Plant Anal. 32:16771686. Allaire Leung, S.E., L. Wu, J.P. Mitchell, and B.L. Sanden. 2001. Nitrate leaching and soil nitrate content as affected by irrigation uniformity in a carrot field. Agr. Water Mgt. 4 8(1):3750. Aparicio, V., J.L. Costa, M. Zamora. 2008. Nitrate leaching assessment in a long-term experiment under supplementary irrigation in humid Argentina. Agr. Water Mgt. (In Press). 17 Sept. 2008. < http://www.sciencedirect.com/science?_ob=ArticleUR L&_udi=B6T3X 4SY6YD7 1&_user=2139813&_coverDate=07%2F09%2F2008&_alid=791552523&_rdoc=1&_fmt=high& _orig=search&_cdi=4958&_st=13&_docanchor=&_ct=53&_acct=C000054276&_version=1&_ urlVersion=0&_userid=2139813&md5=9fa266e10929183ae2aefe3c8d81eefa> Badr, M.A. 20 07. Response of drip-irrigated tomatoes to nitrogen supply under different fertigation strategies. Amer Eurasian J. Agri. Environ. Sci. 2(6):702710. Balkcom, K.S., J.F. Adams, D.L. Hartzog, and C.W. Wood. 2001. Mineralization of composted municipal sludge under field conditions. Commun. Soil Sci. Plant Anal. 32:15891605. Brown, J.E., C.H. Gilliam, R.L. Shumack, D.W. Porch, and J.O. Donald. 1995. Comparison of broiler litter and commercial fertilizer on production of tomato, Lycopersicon esculentum J. V eg. Crop Prod. 1:5362. Cantliffe, D., P. Gilreath, D. Haman, C. Hutchinson, Y. Li, G. McAvoy, K. Migliaccio, T. Olczyk, S. Olson, D. Parmenter, B. Santos, S. Shukla, E. Simonne, C. Stanley, and A. Whidden. 2006. Review of nutrient management systems for Florida vegetable producers: A white paper from the UF/IFAS vegetable fertilizer task force. Proc. Fla. State Hort. Soc. 119:240248. Carlson, R.M., R.I. Cabrera, J.L. Paul, J. Quick, and R.Y. Evans. 1990. Rapid direct determination of ammonium and nitra te in soil and plant tissue extracts. Commun. Soil Sci. Plant Anal. 21:15191529.

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137 BIOG RAPHICAL SKETCH Aparna Gazula was born on September 1, 1977 in Visakhapatnam, India and she is the oldest of three children. She graduated from the Acharya N.G. Ranga Agricultural University in 2000 with a BS in A gricultural S ciences. In 2004, Aparna rece ived a Master of Science degree in h orticultural and c rop s ciences from The Ohio State University. Aparna began her work towards a doctor of philosophy in the Horticultural Sciences department at the University of Florida under the guidance of Dr. Eric Sim onne. She passed her qualifying exam and w as admitted to candidacy in spring 2008, with a successful defense of the dissertation i n November 2008. She was awarded the Ph D in horticultural s ciences in May 2009.