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Soil Moisture-Based Drip Irrigation for Efficient Use of Water and Nutrients and Sustainability of Vegetables Cropped on...


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SOIL MOISTURE-BASED DRIP IRRIGATION FOR EFFICICENT USE OF WATER AND NUTRIENTS AND SUSTAINABILIT Y OF VEGETABLES CROPPED ON COARSE SOILS By JONATHAN H SCHRODER A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ENGINEERING UNIVERSITY OF FLORIDA 2006

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Copyright 2006 by Jonathan H Schroder

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This document is dedicated to the graduate students of the University of Florida.

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iv ACKNOWLEDGMENTS To achieve the opportunity of studying at a wonderful institute like the University of Florida I would like to thank my parents. They have given me the desire and platform to study and grow and look for more out of ev ery situation. I also thank Dr. Greg Kiker for his enthusiasm towards my studies. He made my passage into the USA possible, and started me out on a great academic experience from my first undergradu ate year in South Africa. For their assistance in fieldwork at the TREC I thank Tina Dispenza and Harry Trafford. For their assistance at Pine Acre s, I thank Kristen Femminella, Jason Icerman, Lincoln Zotarelli, and the Pine Acres field crew. For his continued encouragement, and help in many fields, thank you to Paul Lane. For all their support, advice and examples in academic research I thank Dr. Michael Dukes and Dr. Yuncong Li. For his continue d guidance, motivation, energy and advice, along with racquet ball games and good wine, I want to thank my chair, Dr. Rafael Muoz-Carpena. I have learned many things fr om his fine examples and standards. My experience, thanks to all thes e people and many more whom I have not listed, has been a great one, and I am grateful fo r having had this time here.

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v TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iv LIST OF TABLES............................................................................................................vii LIST OF FIGURES.........................................................................................................viii ABSTRACT......................................................................................................................x ii CHAPTER 1 INTRODUCTION........................................................................................................1 Rationale...................................................................................................................... .1 Objectives..................................................................................................................... 5 2 SOIL MOISTURE BASED DRIP IRRIGATION FOR IMPROVED WATER USE EFFICIENCY AND REDUCED LEACHING ON TOMATOES......................6 Introduction................................................................................................................... 6 Methods and M aterials..................................................................................................9 Soil Characteristics................................................................................................9 Experimental Design...........................................................................................10 Field layout...................................................................................................10 Irrigation control and da ta capture hardware...............................................14 Fertigation control and data capture hardware.............................................17 Analysis Methods................................................................................................20 Results and Discussion...............................................................................................22 Experiment 1: Calcareous gravelly soil...............................................................22 Experiment 2: Sandy Soil....................................................................................26 Comparison of results..........................................................................................31 Conclusion..................................................................................................................36 3 FERTIGATION METHODS FOR SOIL MOISTURE-BASED IRRIGATION OF VEGETABLE CROPS...............................................................................................38 Introduction.................................................................................................................38 Improved Irrigation Management........................................................................39 Fertigation............................................................................................................40

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vi Benefits of Fertigation.........................................................................................40 Fertilizer Injection........................................................................................40 Fertilizer application schedules...........................................................................41 Fertigation coupled with soil moisture-based irrigation......................................43 Methods and Materials...............................................................................................45 Experiment 1: South Florida gravelly soil..................................................46 Experiment 2: North Central Florida sandy soil.................................................49 Combining continuous methods w ith scheduled fertigation...............................52 Additional fertigation information......................................................................54 Conclusions.........................................................................................................56 4 DIELECTRIC CAPACITANCE SOIL MOISTURE PROBE CALIBRATION AND SPATIAL SOIL MOISTURE DYNAMICS STUDY......................................57 Introduction.................................................................................................................57 Methods and Materials...............................................................................................60 Presentation of Results...............................................................................................68 Discussion of results...................................................................................................77 Rainfall................................................................................................................78 Temperature.........................................................................................................79 Salinity.................................................................................................................81 Spatial distribution trends....................................................................................85 Conclusions.................................................................................................................86 5 SUMMARY AND CONCLUSIONS.........................................................................90 APPENDIX A FERTIGATION FOR SOIL MOISTURE-BASED IRRIGATION...........................99 B SOIL MOISTURE DISTRIBUTIONS WITHIN A PLASTIC MULCHED BED..107 LIST OF REFERENCES.................................................................................................113 BIOGRAPHICAL SKETCH...........................................................................................118

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vii LIST OF TABLES Table page 1.1 Scheduling treatments applied to two ir rigation experiments on tomato crops.......11 1.2 System specification and agronomic pa rameter summary for experiment 1...........17 1.3 Summary of system specifications fo r tomatoes grown in Experiment 2................17 1.4 Water application, yield, and irrigation water use efficiency (IWUE) averages for each treatment in Experiment 1 on calcareous gravelly soil..............................22 1.5 Nutrient leaching data obtained fr om lysimeters in Experiment 1...........................24 1.6 Water application, yield and water use efficiency (WUE) for Experiment 2..........27 1.7 Average volume leached and nitrate-nitrogen load leached per treatment for Experiment 2............................................................................................................30 1.8 Average values and the percentage cha nge from the local grower treatment for the dependant variables measured in two experiments of tomatoes........................31 2.1 Venturi injection rates and variability of inj ection rates from a calibration test conducted prior to the transplant of the tomato crop on Experiment 1....................48 2.2 IFAS suggested daily fertig ation rates for tomatoes................................................55 A.1 Mazzei injectors performan ce tables (Mazzei Injector Corp., Bakersfield, CA)...101 A.2 Example of irrigation tim er setup for decoupled con tinuous fertigation and soil moisture-based irrigation for the setup displayed in Figure 3................................102

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viii LIST OF FIGURES Figure page 1.1 Irrigation distribution sy stem and control system layout for Experiment 1.............12 1.2 Field layout and irrigation tr eatments for Experiment 2..........................................13 1.3 Bucket lysimeters used to quantify leaching loads corresponding to different irrigation treatments on gravelly loam soil in Experiment 1....................................19 1.4 Vacuum pumps extracting leachate from lysimeters positioned 60 cm under the beds of Experiment 2 on sandy soil.........................................................................20 1.5 Graph of cumulative season water applica tion for the four irrigation treatments applied to the gravely loam soils of Experiment 1...................................................23 1.6 Cumulative average leached volume record ed by the lysimeters per treatment for Experiment 1 on calcareous gravelly soil................................................................25 1.7 Cumulative load of nitrate captured in the lysimeters over the season for Experiment 1 on calcareous gravelly soil................................................................26 1.8 Cumulative water application per treatm ent applied over the season to tomatoes in Experiment 2........................................................................................................27 1.9 Cumulative volume of leachate collected in the lysimeters per treatment over the season for Experiment 2...........................................................................................29 1.10 Cumulative nitrate-nitrogen load le ached per treatment over the season for Experiment 2............................................................................................................29 2.1 A venturi injector schema tic showing flow directi ons and operating principle (adapted from Mazzei Injectors Inc.).......................................................................44 2.2 Pumphouse hardware layout for Experiment 1........................................................47 2.3 Venturi injectors placed across pressu re regulators for added pressure differential................................................................................................................47 2.4 Weekly manual injection of fertilizer solution carried out using a peristaltic pump for Experiment 2............................................................................................50

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ix 2.5 Cumulative nitrogen ra tes comparing continuous and manual fertigation treatments in Experiment 2 on sandy soil................................................................51 2.6 Fertigation system for decoupled time-b ased fertigation and soil moisture-based irrigation...................................................................................................................54 4.1 ECH2O dielectric capacitance soil moistu re probe (Deca gon Devices Inc., Pullman, WA)...........................................................................................................61 4.2 Grid of nine ECH2O probes placed between two actively growing zucchini plants to determine soil moisture distribution for probe placement.........................63 4.3 TDR nest to measure soil moisture fo r corresponding to mV irrigation threshold set point....................................................................................................................64 4.4 Nest of dielectric capacitance probes and tensiometers used to generate the drier points of the soil moisture release curve for the fine sand at PSREU......................66 4.5 Probe grid of 33 dielectric capacitance probes to determine spatial dynamics in the root zone of a mature zucch ini crop in plastic mulched bed..............................67 4.6 Dielectric capacitance probe readings fo r different spatial positions within the root zone of a plastic mulched cr op irrigated using a 475mV set-point..................68 4.7 Dielectric capacitance probe readings fo r different spatial positions within the root zone of a plastic mulched cr op irrigated using a 525mV set-point..................69 4.8 Dielectric capacitance probe readings fo r different spatial positions within the root zone of a plastic mulched cr op irrigated using a 475mV set point...................69 4.9 Bivariate plot of TDR and dielectric capacitance probes to obtain a linear relationship between soil moisture and mV.............................................................70 4.10 Soil moisture release curve obtained from in-situ measurements for the fine sand at the Plant Science Research a nd Education Unit in Citra County.........................71 4.11 Plot of soil moisture release curve ob tained from manual tensiometer readings and data obtained from nests of tensiometers and TDRs.........................................72 4.12 Soil moisture release curve and fitted model derived by ECH2O data and the calibration curve, corrected from nested tensiometer and TDR data.......................72 4.13 Average soil moisture distribution betw een two zucchini plants in a plastic mulched bed using soil moisture base d drip irrigation (threshold 475 mV)............73 4.14 Variability of soil moisture within the zone between two zucchini plants irrigated by soil moisture-based dr ip irrigation (threshold 475 mV).......................73

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x 4.15 Average soil moisture distribution betw een too zucchini plants in a plastic mulched bed using soil moisture base d drip irrigation (threshold 525 mV)............74 4.16 Variability of soil moisture within the zone between two zucchini plants irrigated by soil moisture-based dr ip irrigation (threshold 525 mV).......................74 4.17 Average soil moisture distribution for th e root zone of a ma ture zucchini plant irrigated by soil moisture-based scheduling (threshold 475 mV)............................75 4.18 Soil moisture variability for the root z one of a mature zucchini plant irrigated by soil moisture-based scheduling (threshold 475 mV)................................................75 4.19 Average soil moisture tension for the r oot zone of a mature zucchini plant irrigated by soil moisture-based scheduling (threshold 475 mV)............................76 4.20 Average cross-section profile of soil moisture across the bed with varying distance from drip tape fo r a mature zucchini crop..................................................77 4.21 Soil moisture time series showing how soil moisture spikes during rainfall events are limited to probes on exterior of bed........................................................78 4.22 Temperature fluxes within three plastic mulched beds in the fall season of 2005. Thermocouples were buried approx imately 15 mm beneath the surface.................80 4.23 Time series of soil moisture in bed I1 to show limited effects of temperature on outer probes that receiv e little irrigation water........................................................81 4.24 Water applications for the three soil mois ture-based drip irrigation treatments I1, I2 and I3 on a plastic mulched zucchini crop...........................................................83 4.25 Soil moisture time series showing soil moisture determined by TDR and calculated by dielectric capacitance for soil moisture treatment I1.........................83 4.26 Soil moisture time series showing soil moisture determined by TDR and calculated by dielectric capacitance for soil moisture treatment I2.........................84 4.27 Soil moisture time series showing soil moisture determined by TDR and calculated by dielectric capacitanc e for soil moisture treatment I3.........................84 A.1 Bypass venturi assembly for fertigation using either a pressure regulator or a control valve.............................................................................................................99 A.2 Bypass assembly with a booster pump for venturi injection fertigation................100 A.3 Bypass assembly with venturi inject or installed across an irrigation pump..........100 A.4 Automated soil moisture-based irriga tion scheduling hardware developed by the University of Florida..............................................................................................102

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xi A.5 Cumulative water use for ETc and the estimate for soil moisture-based scheduling using the QIC and dielectric probe set to 25 cbar soil moisture..........104 A.6 Required 4-0-8 liquid fertilizer diluti on to achieve IFAS rates when driven by estimated soil moisture-based water application....................................................105 A.7 Step-wise estimated eva potranspiration functions vs. likely actual functions.......106 B.1 Probe layout and numbering, used to dete rmine soil moisture distribution within the root zone of a mature zucchini pl ant grown in plastic mulched beds..............107 B.2 ECH2O probes placed next to drip line, mV output..............................................108 B.3 ECH2O probes placed perpendicular to drip tape to drip, line mV output............108 B.4 ECH2O probes parallel to and 30 cm from the drip line, mV output....................109 B.5 ECH2O probes parallel to and 15 cm from the drip line, mV output. ..................109 B.6 ECH2O probes parallel to and cm from the drip line, mV output..................110 B.7 ECH2O probes parallel to and cm from the drip line, mV output..................110 B.8 ECH2O probes perpendicular to and 30 cm from the drip line, mV output..........111 B.9 ECH2O probes perpendicular to and 15 cm from the drip line, mV output..........111 B.10 ECH2O probes perpendicular to and 15 cm from the drip line, mV output.........112

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xii Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Engineering SOIL MOISTURE-BASED IRRIGATI ON: A SCHEDULING METHOD TO IMPROVE FUTURE RESORCE USE EFFICIENCIES AND PROMOTE AGRICULTURE SUSTAINABILITY By Jonathan Schroder May 2006 Chair: Rafael Munoz-Carpena Cochair: Michael Dukes Major Department: Agricultur al and Biological Engineering To improve water and nutrient use effici ency, growers need to maintain the soil water in the crop root zone at optimal le vels for plant growth and minimal nutrient leaching. An automated drip irrigation syst em has been developed that interfaces a dielectric capacitance probe to evaluate soil moisture and control irrigation accordingly. If the soil moisture is below a user-set threshold the scheduled irrigation event is initiated. If soil moisture is above the threshold, the event is bypassed and water is conserved. Multiple small volume events are scheduled per day. The aims of this threeseason project were to quantify the water app lications and the leached loads of nutrients for soil moisture-based irrigation and traditional time-based irrigation; to develop a fertigation methodology that could be integrated with soil mo isture-based irrigation; and to calibrate the soil moisture probe for sandy soils common in Florida, and gain knowledge on the spatial dynamics of soil mois ture within the plastic mulched beds.

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xiii Two experiments were conducted on tomato crops, one on Krome, a calcareous gravely loam soil in South Florida, and another on a fine sandy soil in North Central Florida. Replicates of soil moisture-based scheduli ng and time-based scheduling were applied. Soil moisture-based scheduling applied 55 to 80% less irrigati on water and yielded Irrigation Water Use Efficiencies (IWUEs) of 200% to 415% higher than time-based scheduling. Leachate volumes were 68% lo wer, a 90% reduction of leached NH4-N, a 75-89% reduction in NO3-N, and an 85% re duction in dissolved and total phosphorous loads leached, and were obtained by soil moistu re-based treatments compared to the time based treatments. To further improve the systems nutrient management an automated fertigation system to be integrated within a soil moisture-based irrigation system was developed and tested. The system used a venturi injector and provided sufficiently accurate fertilizer applications to meet the crop nutrient needs throughout the season. The system is easy to manage and relatively inexpensive. An experiment on a plastic mulched zucchini crop was conducted to be tter understand spatial soil moisture dynamics. This is critical, as the informa tion from the soil moisture probe drives the irrigation. Soil moisture in a narrow zone of up to 15 cm away from the drip line was influenced by irrigation events in the fast draining sand soil. Soil moisture tensions were found to increase rapidly beyond 8% soil moistu re by volume. Temperature, and rainfall showed very little effect on output readings of the diel ectric capacitance probe, but salinity effects could be signifi cant and need to be calculated. The system has proved to be successful at improving water and nutrient use efficiencies, and shows potential for improved coexistence of vegetable production agriculture with environmental systems.

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1 CHAPTER 1 INTRODUCTION For the purpose of motivation of research this first chapter will briefly introduce water management issues pertaining particularly to agriculture in Florida. Focus will be given to areas where water management challe nges have prompted ag riculture to advance its systems and become more competitive and sustainable. Rationale The Everglades and associated costal ecosystems of South Florida are unique and highly valued ecosystems. One of the worl ds largest water management systems has been developed in South Florida over the pa st 50 years to provide flood control, urban and agricultural water supply, and drainage of land for development. However this system has inadvertently cause d extensive degradation of the South Florida ecosystems and elimination of whole classes of ecosyst ems. The hydrodynamics and water quality in Everglades National Park and adjacent lands ar e now being restored in accordance with the Comprehensive Everglades Restoration Plan (CERP). CERP authorizes modifications of the existing surf ace water management system, so as to reestablish historic freshwater flows that restore more natura l hydro-patterns in the Park and contribute to ecosystem restoration. Part of CERPs mission is also to protect the water resources in Central and Southern Florida by balancing and improving water quality and supply. Lack of knowledge about the hydrological syst em and its effects on crops, local and regional flow, and chemical transport patterns are all major concerns for all stakeholders in the area (Muoz-Carpena, 2004). As such, farmers in the area have

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2 taken a key role in promoting the need for scientific investigation into the possible impact of CERP on the sustainability of agriculture in South Florida. To understand the scale of the industry th at is being impacted by the need for environmental compatibility one needs to look at the extent of agriculture in Florida. Florida ranks second among the states in fr esh market vegetable production on the basis of area cultivated (9.6%) and in value ( 13%) of the crops grown. Tomato production accounted for over 30% of the states total production in value in 2001-2002. According to the National Resources Conservation Se rvice (1995), Dade County produces roughly a quarter of the states tomatoes Higher yields than more northern growing areas, and the ability to produce a crop during the winter season when othe r regions are inactive, have helped establish this region s importance in the tomato market. The Miami-Dade County vegetable crops industry also employs ove r 6000 people, and has a $491 million impact on the state economy. Florida tomato growers are at a comp etitive disadvantage due to off-shore competition from countries where labor is consid erably cheaper than in the United States. This disadvantage is even greater with the phase out of methyl-bromide in the U.S, but not in other developing countri es. Apart from environmen tal benefits, the vegetable industry in Florida is hugely in need of methodologies th at improve resource use and decrease operating costs. Water is a vital resource and is a driving force for much of crop production. With its large contribution to industry in Florida, agricultural self-supply accounts for 35% of fresh ground water withdrawals, and 60% of fresh surface water withdrawals, which makes it the largest component of freshwater use in Florida (Marella, 1999). Overall,

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3 82% of the farms in the Miami-Dade County have irrigation systems. The primary use of this water is irrigation to supplement rainfa ll during dry crop periods (Muoz-Carpena et al., 2004). The high yields of the Biscayne A quifer were originally attractive for growers and have lead to the general perception among growers that water is not a limiting factor. But as urban pressure in the Miami-Dade County area increases, water could become a more scarce resource (Muoz-C arpena et al., 2002). Despit e the potential shortages, over-irrigation is a problem in the area and may be explained by th e low water holding capacity and high permeability of Floridas sand y soils, and especially the gravelly soils found in the south Miami-Dade County agricultur al area. Analysis shows that irrigation efficiency is highly sensitive to both soil texture and irriga tion volume. Over irrigation can also be attributed to inadequate irriga tion scheduling (Muoz-Car pena et al., 2004). Traditional irrigation based on low freque ncy and high volumes usually results in inefficient water use. With this type of irrigation, a substantia l volume of the applied water percolates quickly to the shallow groundwater potentially carryi ng with it nutrients and other agrochemicals applied to th e soil (Muoz-Carpena et al., 2003a). For some important reasons, drip irrigati on of raised beds covered with plastic mulch is the most suited form of micro irri gation for high value ve getable production. Its slower more precise application of water is su itable to easily drained soils and one of the major benefits of drip irrigation is the capaci ty to conserve water and fertilizer compared to overhead sprinklers and subirrigation. Drip irrigation also helps reduce foliar disease incidence compared to overhead sprinkler systems, which wet the plant foliage. By maintaining drier plants drip irrigation reduces susceptibility to out breaks of bacteria and fungal diseases, and reduces the need for bactericides and fungicides (Hochmuth and

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4 Smajstrla, 1998). Drip irrigation provides fo r precise timing and application of nutrients and certain pesticides in ve getable production. Fertilizers can be prescription-applied during the season in amounts that the crop n eeds and at particular times when those nutrients are needed. These small, controlled applications of fer tilizer under plastic mulch not only save fertilizer, but also have the potential to redu ce groundwater pollution due to fertilizer leaching from heavy rainstorms or irrigation. Drip irrigation however has become the st andard for plastic mulched raised bed vegetable production, and no longer gives any be nefits over competitors. Furthermore, the design and implementation of a good irri gation system requires good scheduling for it to operate efficiently. The University of Floridas Institute of Food and Agricultural Sciences, a leader in deve loping best management pract ices, recommends scheduling according to crop evapotranspiration requirements combined with soil moisture monitoring. A methodology of scheduling has re cently been developed to automatically schedule water according to soil moisture st atus. Preliminary tests have shown the system has potential for large savings in wa ter application from tr aditional methods of irrigation scheduling. More and more, water conservation appear s on top priority lists for projecting, planning and managing future water needs, not just in South Florida, but statewide and globally as well (Anon, 2003). The following Chapters will introduce and discuss an automated drip irrigation system and management practices that have been developed and test ed by the University of Florida. Different aspects of the system will be analyzed, namely the system configuration and hardware, the systems ab ility to conserve water and reduce leaching

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5 with results from field trials, and the pot ential of integrating soil moisture based scheduling with continuous fertigation. Although these studies have focused on a specific hardware technology, it must be str ongly emphasized that it is not the specific technology that is of highest importance, but the methodologies pres ented here within. The potential of the system lies within th e methodology; the technologies are important for optimization of the method. Objectives Chapter 2 1. To test and mange water and fertilize r application with the automated soil moisture based irrigation system 2. To quantify the load of nutrients bein g leached from the root zone of the crop for different irrigation sche duling methods to determine the effectiveness of the proposed sy stem in reducing leaching loses 3. To demonstrate that with proper manage ment that yields can be maintained while reducing water and nut rient application from local grower standards Chapter 3 4. To evaluate the potential and effectiv eness of integrating soil moisture based irrigation scheduling and au tomatic continuous fertigation Chapter 4 5. To better understand soil moisture dist ribution within plastic mulched beds and its effects on probe placement fo r soil moisture based irrigation 6. To calibrate the soil moisture probe used with the UF developed automated soil moisture based system for the fine sand soils at local research site Chapter 5 7. To hi-light potential issues for future research within this field.

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6 CHAPTER 2 SOIL MOISTURE BASED DRIP IRRIGATION FOR IMPROVED WATER USE EFFICIENCY AND REDUCED LEACHING ON TOMATOES Introduction Florida tomato growers are at a comp etitive disadvantage due to off-shore competition from countries where labor is cheaper than in the United states (MunozCarpena et.al., 2005). Improving irrigation efficiency can cont ribute to reducing production costs of vegetables and make the i ndustry more competitive and sustainable. Through proper irrigation, average yields can be maintained or increased (Shae, et al., 1999) while minimizing environmental impact s caused by excess wa ter application and subsequent agrichemical leac hing. Tomatoes are typically grown in raised beds with plastic mulch and drip irrigation. Although th is method has the potential to be very efficient, over-irrigation is a common occurr ence in Florida due to inadequate irrigation scheduling and low soil water holding capacity of soils commonly used for agriculture. Traditional irrigation of applyi ng large volumes of water at low frequencies (a few times per week) results in a large portion of the ir rigated water percolating quickly through the root zone to the shallow gr oundwater, potentially carrying with it nutrients and other agrochemicals in the soil. In addition, exce ss water in the root zone can reduce tomato yields (Wang et al., 2004). Recent technological advances have made lo w-cost soil water sensors available for efficient and automatic operation of irri gation systems (Dukes and Muoz-Carpena, 2005). Automation of irrigation systems base d on soil moisture sensors may improve

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7 water use efficiency by maintaining soil moisture at optimum levels in coarse soils (sands and gravels) rather than a cycle of very wet to very dry as a result of typical low frequency high volume irrigation. This is partic ularly critical in Floridas sand and gravel soils where available soil moisture is typi cally 6-8% by volume or less (Dukes et al., 2003). Soil moisture probes can be installed at repr esentative points in an agricultural field to provide repeated moisture readings over time for irrigation scheduling and management. The target soil water status is us ually set in terms of soil tension (or matric potential expressed in kPa or cbar), or volumetric moisture content. Care needs to be taken when using these soil moisture sensor devices in coarse soils, as most devices require good contact with the soil matrix, which is difficult coarse soils (Dukes and Munoz-Carpena, 2005). In addition soil moisture sensing devices need to be able to capture fast soil water changes typical to coar se soils. Tensiometers have been widely used in soil moisture based scheduling in va rious applications such as tomato production (Clark et al, 1994; Smajstrla and Locasc io, 1994), blackcurrent production (Hoppula and Salo, 2005), and rice (Kukal, et al., 2005). Due to their di rect reading of soil matrix potential and thus plant water stress, tensiometers provide good scheduling a pplications. Tensiometers however need to be carefully maintained (e.g. refilled) and the ceramic cup has the potential to loose contact with coarse soils, requiring reinst allation. Dielectric probes however need little maintenance a nd can be accurate without soil specific calibrations, although soil-specific calibration increases accuracy, and is recommended on certain soils (Munoz-Carpena, 2004). A dr awback of some dielectric probes is the cost due to the complex electronics.

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8 Soil moisture based scheduling has resulted in water savings on coarse soils in Florida. Smajstrla and Locascio (1996) re ported reductions of irrigation of 40 to 50% compared to local practices without affec ting yield using switching tensiometers to irrigate tomatoes on fine sands in Florida. Scheduling according to soil matric potential measuring devices achieved a 70% reduction in water applications against time based practices for tomato grown on a calcareous soil in South Florida compared to local grower practices was reported by Muoz-Car pena et al., (2005). The methodology of using soil moisture based scheduling has been used successfully on other crops and applications such as citrus (Fares and Alva, 2000), potatoes (Shae et al., 1999) and (Shock et al., 1998), onions (Shock et al., 2000), and for the automatic irrigation of urban landscapes (Qualls et al., 2001). Corresponding reductions in nutrient leaching loads due to reduced water applications are expected. He bbar et al. (2003) found improved fertilizer use efficiencies with all drip irrigated and fertigated treatme nts over furrow irrigation, as well as reduced NO3-N leaching from soil analysis at varyi ng depths. Drip irrigation and fertilizer applied through fertigation, combined with soil moisture based scheduling has high potential for reducing leaching of nutrients, bu t little quantification of the loads leached have be reported. The objective of this project were to determine the effect of the soil moisture-based irrigation scheduling applied to plastic mu lched tomatoes grown on two soil types and seasons. The soil moisture based-irriga tion scheduling was compared to traditional time-based scheduling. Different dependant variables were studied to determine the effect of the independent vari able (irrigation scheduling met hod). The different variables

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9 that were studied were 1) water applica tion by treatment, 2) yield and water use efficiency for each treatment, 3) volume of leachate passing through the root zone as a result of different treatment water applications, and 4) the load of nutri ents in the leachate lost from the root zone corresponding to each treatment. Methods and Materials Two field trials were conducted on plas tic mulched tomato crops using the soil moisture based drip irrigation system. Th e first experiment was conducted during the 2004/2005 winter cropping season on gravelly loam soil in Homestead, Miami-Dade County in South Florida. The second e xperiment was conducted during the 2005 spring cropping season on sandy soils in Marion County, North Central Florida. Soil Characteristics The field site of the first experiment wa s at the Tropical Research and Education Center (TREC) in Homestead, Miami-Dade County. The region is dominated by three calcareous soils, namely Krome, Chekika, and Marl (Munoz-Carpena et al., 2002). The soil at TREC is Krome, a calcareous soil ar tificially made by rock-ploughing the top layer of the limestone coral bedrock. It is a bimodal soil and has 51% gravel particles and the remainder is loam texture. The highly permeable gravel component the soil presents soil water management challenges to growers in the area. A large portion of the soil water (approx. 50%) can easily be leached during regular water applications, due to the low water holding potential of the gravel component of the soil. The second field site was at the Plant Research and Education Unit (PSREU) in Marion County, on sandy soils. Buster (1979) classified the soil at the PSREU research site as a Candler sand and Tavares sand. These soil types contain 97% sand-sized particles and have a field capacity of 5.0% to 7.5% by volume in the upper 100 cm of the

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10 soil profile (Carlise et al., 1978). Like the Kr ome soil in South Florida, the sandy soils of this region are highly permeable and also have a low water holding capacity and high potential for leaching. Experimental Design Tomatoes were grown according to local agronomic practices in each region. The field in Experiment 1 had sorghum sudangr ass grown as cover crops prior to the cultivation and the tomato-cropping season. The tomato seedlings of the cultivar, FL 47, were transplanted on the 15th of October 2004 (Experiment 1), and the 5th of April 2005 (Experiment 2) into raised black plastic mulched beds. The beds were spaced 1.83 m apart, center-to-center, and seedlings were planted in one row per bed with plants spaced 0.46 m apart. Dual drip lines under the plastic mulch were used to supply irrigation water to the crop on the gravelly loam soil (Experiment 1), and single lines were used for the sandy soil (Experiment 2). Dual lines were employed on Experiment 1 as the gravelly loam soil was only 35-45 cm deep and the wider wetting area would provide a larger soil water storage volume, which is common horticultural practice. Field layout For Experiment 1 the field was divided into two areas, an experimental plot, and a demonstration plot (Figure 1.1). All experime ntal data was obtained from the experiment plot, and the demonstration plot was used as an extension se rvice and provided visitors with an example of the system working as it would in commercial practice. Four irrigation-scheduling treatments were applied to the experi mental plot. Two of these treatments were soil moisture based schedulin g (I11 and I12), and tw o of the treatments were time based scheduling (I13 and I14). Each treatment consisted of three replications of 50 m long beds, individua lly controlled by a separate sensor.

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11 To reduce wiring treatments were not spat ially randomized and control points could be kept close together in the field and supplied by a single multiple station cable. The demonstration plot consisted of two treatments, a soil mois ture based treatment I12, and the local grower time based treatment I14. Figure 1.1, shows the field layout. For Experiment 2 on the gravelly loam so il, a randomized complete block design was used. Three irrigation treatments cons isted of two soil moisture-based schedules, and the third treatment was a time-based lo cal grower schedule. Each treatment was replicated four times (four 15 m beds) a nd a common valve and soil moisture probe controlled all four replicat es. Treatments I21 and I22 were soil moisture-based treatments and I23 was a time-based treatment, similar to grower practices (Table 1.1). Table 1.1. Scheduling treatments applied to two irrigation experiments on tomato crops. The field layout and treatments can be seen in Figure 2. A single drip tape supplied the irrigation water and a second line supplied the fertilizer. For tr eatments I22 and I23 these two lines were placed ne xt to each other in the middle of the bed at the surface under the plastic mulch. For treatment I21, th e irrigation line was buried 15 cm beneath the surface and 15 cm offset from the fertiga tion line, which was at the surface. Plats were transplanted 10 cm away from the drip lines. In treatment I21 this was 10cm from the fertilizer line at the surface. Experiment TreatmentScheduling MethodDevice/practice I11Soil moisture-basedSwitching tensiometers I12Soil moisture-based ECH2O dielectric probe I13time-basedETc based on historical weather data I14time-basedLocal grower practice I21Soil moisture-based ECH2O dielectric probe I22Soil moisture-based ECH2O dielectric probe I23Time-basedLocal grower practice 1 2

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12 Figure 1.1. Irrigation distributi on system and control system layout for Experiment 1.

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13 Figure 1.2. Field layout and irrigation treatments for Experiment 2.

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14 Irrigation control and data capture hardware The soil moisture-based treatments applie d water during preset events depending on soil moisture status. An irrigation timer was used to preset sub-daily irrigation events. When it was time for an event to occur the soil moisture sensor was queried. If soil moisture was below a set threshold the soil moisture sensor would allow a set event to occur. If soil moisture was above the thre shold set point, the event would be bypassed. For Experiment 1 treatments I11 and I12 used switching tensiometers (LT-RA, Irrometer Co., Inc., CA), and dielectric capacitance probes (ECH2O, Decagon Devices Inc., Pullman, WA) respectively. The switching tens iometer irrigation set point was set at a soil matric potential of 25 cbar. The ECH2O probes were interfaced with an irrigation timer by a quantified irrigation controller (QIC ) developed by the University of Florida Agricultural and Biological Engineering De partment (Dukes and Munoz-Carpena, 2005). The irrigation threshold for the QIC was se t to 400mV, which corresponded to a soil matric potential of approximately 25 cbar fo r the gravelly soil and dielectric probe. Treatments I13 and I14 were time based with I13 derived from histor ic weather data and IFAS recommended crop coefficients (Simonne et al., 2004), and I14 following local grower practices, which corresponded to 1 hour of irrigation per day for the system (4 mm/day). For Experiment 2 treatments I21 and I 22 used dielectric, capacitance probes (ECH2O, Decagon Devices Inc., Pullman, WA) inte rfaced with an irrigation timer using QICs (Munoz-Carpena and Dukes, 2005). The irrigation threshold for the QICs was 500 mV, which corresponds to soil moisture c ontent by volume of roughly 10-13 % for the sandy soil using dielectric capacitance probes. Treatment I21 had its irrigation drip-tape buried in the soil 15 cm beneath the surface of the bed, and its fertigation line on the

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15 surface. Treatment I23 was the local grower practice time based treatment, and irrigated once a day for 1 hour (2.1 mm/day) for the fi rst 45 days after tr ansplanting, and 2 hours (4.2 mm/day) for the remaining 40 days in the season. Soil moisture based scheduling with an au tomated system can apply water in two different procedures. The soil moisture pr obes can continuously read the soil moisture status and initiate irrigation whenever the level gets below a threshold, and switch the irrigation off when once the profile has been sufficiently wetted whic h is an on-demand technique (Dukes and Muoz-Carpena, 2005). This technique has negative design complications. The maximum flow rate of th e system is not known, as the time at which irrigation events occur during a day is dynami c, and there could be many valves open at once or none. To accommodate the possibility that all the soil moistu re treatment valves could be open at once the system pipe networ k would have use large diameter pipes. This would be particularly impractical in commercial systems where larger areas are irrigated. As such, a fixed schedule of s ub-daily events was employed where the soil moisture sensor control system could bypass these timed events if soil moisture was adequate (Dukes and Muoz-Carpena, 2005). For Experiment 1 four events of 12 minutes per event were employed per day. This corresponded to maximum daily needs fo r the season (2.5 mm/day) calculated from historical weather data (ETo = 2.79 mm/day) and crop coefficients (Kcmax = 0.9). Experiment 2 was conducted during the follo wing spring-summer season when warmer temperatures increase crop water needs. As such five events per day were chosen. For the beginning of the season each event was 12 minutes long. After 48 days the event length was extended to 24 minutes (4.1 mm /day), which corresponded to the maximum

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16 daily water requirement for a tomato crop in the area, and was derived from historical weather data (ETo = 4.57mm/day) and cr op evapotranspiration coefficients (Kcmax = 0.9). Crop coefficients and historical weather data were obtained fr om (Simonne et al., 2004). A schedule was programmed into an irrigati on timer. The schedule consisted of 4 events per day (Experiment 1), and five even ts per day (Experiment 2). Each of the 4 events in Experiment 1 was 12 minutes long, an d the 5 events in Experiment 2 were 12 minutes long for the first 45 days after transplant and 24 minutes long for the remaining 40 days. The soil moisture probes then eith er allowed or bypassed a prescheduled event according to in-field soil moisture status, a nd a set threshold. The sub-daily events were staggered and spread out through the day so that only one treatment was irrigated, if needed, at a time. As a result of this scheduling set up, water is still delivered to the crop as determined by the soil moisture probes, but the maximum flow rates are explicit and reduced. The system specifications for Expe riments 1 and 2 are presented in Table 1.2 and 1.3. Water applications per treatment for Expe riment 2, and per replication (individual beds) within treatments for Experiment 1 were manually recorded from positive displacement flowmeters (V100 1.6 cm diamet er bore with pulse output, AMCO Water Metering Systems Inc., Ocala, FL). In additi on to manual readings on a weekly basis, the flowmeters contained transducers that signal ed a switch closure every 18.9 L. The switch closures were recorded by data loggers ( HOBO event logger, Onset Computer Corp. Inc., Bourne, MA) and provided continuous data of water and fertigation application times, which were downloaded once a week. This data could be used to determine which events had occurred and which were bypassed.

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17 Table 1.2. System specification and agronom ic parameter summary for experiment 1. Table 1.3. Summary of system specifications for tomatoes grown in Experiment 2. Fertigation control and data capture hardware Fertilizer rates were applied according to IFAS recommended rates for a tomato crop on soils with low potassium levels in (Maynard et.al., 2004). For Experiment 1, 25% of the seasonal total nitr ogen (228 kg/ha), the phosphorou s and micro-nutrients were was applied pre-plant, and the remainder was applied by fertig ation throughout the season. Venturi injectors (model no. 484, Mazze i Injector Corp., Bakersfield, CA) were used to inject 4-0-8 solution (ammonia-nitrate based nitrogen s ource) liquid fertilizer into the fertigation distribution system. The amount of fertilizer applied is directly related to the amount of water applied using Venturi in jectors. Since the different irrigation System HardwareAgronomic Parameters Pump 745.7 kW (1HP) Maximum crop needs 2.5 mm/day Well tank 750 L with 25 35 m pressure control Surface per bed 91 m 2 Controller Rain-Bird ESP-12LX Max needs per bed 228 L/day Main line 50 mm lay-flat Max time to irrigate approx 48 min/plot/day Valves 24 VAC, 13mm dia. Solenoids Max no. of irrigations 4 per day Laterals 4 per bed (2 for irrigation two for fertilizer) Drip tape T-TAPE TSX 508-12-450 Time per irri. event 12 min/event/plot 16 mm internal dia. 0.30 m emitter spacing 5.6 L/min/100m nominal flow 5.6 m nominal head length 50 m (4 drip lines) for experimental plot 110 m (double lines) for demonstration plot inlet pressure 7 m System HardwareAgronomic Parameters Water supply 40 45 m pressure from main farm system Maximum crop needs 4.1 mm/day Controller Rain-Bird ESP-12LX Surface per bed 28 m 2 Main lines 13, 19 and 25 mm PE hose manifolds Max needs per bed 115 L/day Valves 24 VAC, 13mm dia. Solenoids Max time to irrigate 120 min/plot/day Laterals 2 per bed (1 for irrigation and 1 for fertilizer) Max no. of irrigations 5 per day Drip tape Chapin Watermatics Twin Wall BTF Time per irri. event 24 min/event/plot 10 mm diamter 0.20 m emitter spacing 6.2 L/min/100m nominal flow 6.89 m nominal head length 15.2 m inlet pres. 10 m (in manifolds)

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18 treatments were expected to apply different amounts of water, the water and fertigation applications were separated so that each tr eatment received a variable amount of water, but a common amount of fertilizer. A separate pipe distribution system was thus used to fertigate all treatments for the experimental plot Fertilizer was injected directly into the irrigation system of the demonstration plot as would be done in a commercial practice. The venturi injectors were calibrated before the start of the experiment, and were found to provide consistent injec tion rates with those specified by the manufacturer, and yet were low cost and low maintenance. Three ve nturies were used in Experiment 1, two to inject fertilizer into the experimental plot fertigation system, and one venturi injected fertilizer into the demonstration plots ir rigation system. The calibration yielded an average injection rate of 0.90 L/min w ith a standard deviation of 0.08 L/min. For Experiment 2 phosphorous fertilizer was broadcast at 110 kg/ha prior to bedding, along with a blanket of micronutri ents. Nitrogen, potassium and magnesium were all applied through fer tigation once per week and none was applied preplant. Calcium nitrate was the source of nitrogen and a total of 220 kg/ha of N was applied through the season. Potassium as supplied in the form of Muriate of Potash (KCl) and 250 kg/ha of K was given for the season. Ep som salts applied pr ovided the crop with 12.4 kg/ha of Mg for the season. Injection of the fertilizer in solution was carried out manually once a week with a peristaltic pump (Experiment 2). To quantify the volume and loads of nutri ents leached associated with each irrigation treatment, zero-tension lysimeters were installed into the fields. For Experiment 1 seven zero-tension bucket lysime ters per treatment were buried directly

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19 beneath the rooting zone of the crop (Figure 1.1 and 1.3). The capture area was 0.170 m2 and they had either 1 or 2 drip emitters posit ioned above them and contained 1-2 plants. For Experiment 2, larger zero-tension lysime ters were used to capture the leachate passing through the root zone of the crop. Four lysimeters were provided for each treatment (Figures 1.2 and 1.4). The lysime ters were constructed from 208-liter polyethylene drums and ha d a capture area of 1.52 m2. The larger capture area of the lysimeters in Experiment 2 collected leachat e from 3-4 drip emitters and had 3 plants in each. This provided less variabil ity compared to the lysimeters in Experiment 1, and the larger capture area would provide more a ssurance of capturing all the leachate. Figure 1.3. Bucket lysimeters used to quant ify leaching loads corresponding to different irrigation treatments on gravelly loam soil in Experiment 1. Lysimeters for both experiments were pumped out weekly, manually for Experiment 1, and using vacuum pumps seen in Figure 3 for Experiment 2. Sub-samples of were collected in bottles filtered and analyzed for NO3-N. In Experiment 1, a 20 mL portion of each sample was filtered thr ough a Whatman #42 filter paper for dissolved

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20 phosphorous (DP) determination. Unfiltered sa mples were digested for total P (TP) determination (USEPA, 1993). Both DP and TP were determined using the asorbic-acid method (EPA method 365.3, USEPA, 1993). For e xperiment 2 samples were stored at appropriate temperatures prior to analysis at the Environmen tal Quality Laboratory at the University of Florida. All values of n itrate and nitrite analyses are reported as NO3-N here (OI Analytical, 2001). Figure 1.4. Vacuum pumps extracting leachate from lysimeters positioned 60 cm under the beds of Experiment 2 on sandy soil. Analysis Methods The data showed an increasing variance with increasing treatment response. According to (Lyman Ott and Longnecker, 2001) a log transformation can reduce the over estimation of variance associated with sm aller sample values. A log transformation

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21 was applied to the dependent variables before statistical analyses were conducted. All dependent variables were analyzed using one-way ANOVA tests and their means were compared for treatment effect using th e Tukey-Kramer HSD (Honestly Significant Difference) test. This test is an exact alpha-level test if th e sample sizes are the same and conservative if the sample sizes are different (Hayter 1984). Comparisons were made at the 95% confidence level. The tests were carried out using JMP Version 5.1 software (Lehman et al., 2004). The independent variable was irrigation tr eatment and the dependent variables were yield, irrigation water use efficiency, volume l eached and load of nutrient leached. Crop evapotranspiration (ETc) for the seasons was estimated by multiplying reference evapotranspiration (Eto calculated from w eather data collected at the sites) by crop coefficients (Kc) presented by Brouwer and Heibloem (1986) that had been adjusted for plastic mulch field conditions by a reduction f actor of 35% determined by (Haddadin and Ghawi, 1983). According to Howell (2002) the irrigation water use efficiency (IWUE in kg/m3) is calculated as the increase in yield due to irrigation divi ded by the irrigation water. This is shown in Equation 1. IWUE = (Y-Yd)/(IRR*1000) [1] Where Y is the total marketable yield (kg/ha) Yd is the total marketable dryland or non-irrigated yield IRR is the applied irrigation water (mm) The non-irrigated yield is assumed to be approximately zero for plastic mulched tomatoes in Florida. Yields were the sum of two crop harvests for both experiments. The first harvest of Experiment 1 was on the 13th of January 2005 and the second on the 26th

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22 of January 2005. Harvests were from 5 m sec tions of the beds. The first harvest of Experiment 2 occurred on the 16th of June 2005, and the second harvest was on the 29th of June 2005. Harvests of the tomatoes for Experiment 2 occurred from 6 m sections of the beds. The final marketable yields consis ted of XL, L and M fru it as graded according to the Florida Tomato Committee standards, fr om the two harvests for each experiment. Results and Discussion Results will be presented for each experiment, and comparisons and trends between the two will then be highlighted and discussed to establish tre nds and draw conclusions. Experiment 1: Calcareous gravelly soil The analysis of treatment effects starts on the 29th of October 2004 when irrigation treatments were put into effect, and ignores the first two weeks of establishment irrigation that was common to all treatments. Water a pplication over the season for each treatment are presented in Figure 1.5, along with estimates of cr op evapotranspiration (ETc) estimated from plastic mulch adjusted crop coefficients. As can be seen the water application for the soil moisture-based treatments matched crop water needs much more closely than the time-based treatments, and did not over appl y water (Table 1.4). Table 1.4. Water application, yi eld, and irrigation water use efficiency (IWUE) averages for each treatment in Experiment 1 on calcareous gravelly soil. Different letters depict st atistically different means for P 0.05 (Tukey-Kramer method) [z] Total water per treatment includes the hour per day of establishment irriga tion which was treatment independent Total Water applied [z]Water by treatment YieldIWUE mmmmkg/ha k g /m3water I11 ( tensiometer ) 169 ( 13 ) 118 a49955 a 30 a I12 ( Dielectric probe ) 101 ( 30 ) 50 a40168 a 40 b I13 ( time based -ETc ) 370 ( 8 ) 319 b42191 a 11 c I14 (time based -local grower)570 ( 90)519 c45497 a 8 c Treatment

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23 Figure 1.5. Graph of cumulative season wate r application for the four irrigation treatments applied to the gravely loam soils of Experiment 1. Error bars represent one standard deviation. Significant differences were found for aver age water applicati ons between the soil moisture-based treatments and time-based tr eatments. Scheduling according to the crop growth curve I13 applied less wa ter than the constant rate of I14 through the season. The treatment employing switching tensiometers (I11) provided 71% water savings over the time-based treatment (I14), and the dielectric probe and QIC system (I12) achieved 83% savings over I14. The dielectric probe and QIC hardware required less maintenance and labor than the switching tensiometers. The te nsiometers had to be refilled on a weekly basis due to breakage of the water column and loss of connection with the soil water in the coarse textured soil. This is a comm on problem associated with tensiometers in DAT 020406080100 Water applied (mm) 0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 I11 (switching tensiometer) I12 (dielectric probe) I13 (ETc) I14 (time based local grower) ETc

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24 coarse soils. The dielectric probe and QIC were essentially maintenance free and worked reliably throughout the season once the thresh old had been set at the beginning of the season. Treatment effect had no significant differe nce on total marketable yields. Water use efficiencies followed applied water trends, with the soil moisture based treatments I11 and I12 using water more efficiently at 30 and 40 kg/m3 respectively, than the historical weather time-based and local grow er time-based treatments I13 and I14 which yielded only 11 and 8 kg/m3 of water, respectively. The average nutrient leaching data by treatments obtained from the lysimeters are summarized in Table 1.5. Table 1.5. Nutrient leaching data obtain ed from lysimeters in Experiment 1. Different letters depict sta tistically different means for P 0.05 (Tukey-Kramer HSD method) The volume leached correlated with water application volumes by treatment, with low water applications of I11 and I12 having lower volumes of leachate than I13 and I14 (Figure 1.6). Correspondingl y the ammonia-nitrogen load, dissolved phosphorous (DP) load, and total phosphorous (TP) load all we re all significantly reduced for the soil moisture based treatments I11 and I12 over the two time-based treatments I13 and I14. Phosphorous leaching was analyzed in this experiment due to its present importance in the Miami-Dade County, and to determine the potential of the system to reduce loading and help with the concerted effort to cont rol phosphorous levels in the Everglades and surrounding areas. The soil moisture-based schedules I11 and I12 had total phosphorous loadings of 0.23 and 0.08 kg/ha during the treatment period and Treatment Total TreatmentTotal TreatmentTotal TreatmentTotal TreatmentTotal Treatment mmmmkg/hakg/hakg/hakg/hakg/hakg/hakg/hakg/ha I1149.331.7 a0.040.03 a5.23.7 ab0.240.17 a0.490.23 a I1244.612.6 a0.040.02 a7.60.6 a0.170.06 a0.240.08 a I13137.4111.0 b1.31.28 b33.730.4 c0.550.46 b0.80.66 b I14180.8145.8 b1.490.26b14.310.3 bc0.710.56 b1.040.82 b TP VolumeN-NH4N-NO3DP

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25 DAT 020406080100120140 Vol leached (mm) 0 50 100 150 200 250 300 I11 I12 I13 I14 Figure 1.6. Cumulative average leached volume recorded by th e lysimeters per treatment for Experiment 1 on calcareous gravelly soil. reduced total phosphorous load by 70% on av erage over the 0.82 kg/ha loading of the local grower treatment I14. Dissolved phosphor ous leaching load trends were similar to total phosphorous loads and 79% on average redu ction was recorded for the soil moisture based treatments over the local grower treatment. This could be of great help to the region in reducing the add ition of phosphorous to an already over-loaded system. Treatment effect was limited for nitratenitrogen, and only I12, the dielectric probe soil moisture based treatment was significantly lower than I13, the time-based treatment. High variability within treatments of the nitr ate-nitrogen leached masked differences in the effect of soil moisture scheduling (Figure 1.7 ). As such, it could not be deduced that soil moisture based scheduling was the only factor in leaching differences.

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26 DAT 020406080100120140 Load NO3-N leached (kg/ha) 0 10 20 30 40 50 I11 I12 I13 I14 Figure 1.7. Cumulative load of nitrate captured in the ly simeters over the season for Experiment 1 on calcareous gravelly soil. Experiment 2: Sandy Soil Statistical analysis of water applied by each treatment and its effects on the dependant variables for the second experime nt started on the 27th of April 2005. Total water applied included 52 mm of water during establishment that was applied standard to all treatments and independent of treatment effect. Figur e 1.8 shows the water applied by the different irrigation treatments over the s eason. There was not replication of the control system, a single soil moisture probe a nd solenoid valve supplie d water to all four spatial replicates, which were used to capture soil, yield and leaching heterogeneities. The summaries of water application, yiel ds and irrigation water use efficiency (IWUE) are summarized in Table 1.6.

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27 DAT 020406080100 Total Water Applied (mm) 0 50 100 150 200 250 300 I21 (Dielectric probe+sub irri.) I22 (Dielectric probe) I23 (Time-based local grower) ETc Figure 1.8. Cumulative water application pe r treatment applied over the season to tomatoes in Experiment 2. Table 1.6. Water application, yield and water use efficien cy (WUE) for Experiment 2. [z] Total water includes the establishmen t irrigation of 52 mm (1 hour per day) The total water applied by the soil mo isture based treatment I21, 228 mm, was similar to the local grower treatment I23 which applied 248 mm, and larger than the 140 mm applied by I22. Both I21 and I23 over a pplied water and I22 slightly under applied water when compared to estimated crop ev apotranspiration (ETc = 151 mm) calculated for plastic mulched beds. The high water application of I21 is an exception to the soil moisture-based scheduling trends observed in Experiment 1 a nd in I22. This treatment applied a similar Treatment Total Applied Water [z]Water by TreatmentTotal Marketable YieldIWUE mmmmkg/ha kg/m3 water I21 (dielectric probe) sub-irrigation22817630 428 a 13.3 a I22 (dielectric probe)1408833 261 a 23.8 b I23 (time-based practice)24819618 730 b 7.6 a

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28 amount of water (10% less) as the time based treatment I23, and was attributed to the position of the soil moisture probe with respect to the irrigation line. The drip line for this treatment was buried at a depth of 15 cm under the surface. The probe was however positioned the same as I22 so that it averaged the soil moisture from the surface down to a depth of 20 cm. The top 15 cm of soil would have remained dry due to little or no capillary rise of water in the sandy soil. Th e probes position in th e drier soil near the surface resulted in few irrigation events being bypassed and savings were low (only 10%). A future recommendation for this set up of a buried irrigation line would be either to reduce the soil moisture th reshold, or a more recommended practice would be to bury the soil moisture probe closer to the irriga tion line and active root zone. Further study needs to address the implications of moving the probe within the in terconnected wetting zone of a buried line, and th e effective rooting zone. Significant differences in yield were r ecorded, and both soil moisture-based treatments I21 and I22 had higher marketable yields, 30,428 and 33,621 kg/ha respectively, than I23 which yielded 18,730 kg/ ha. The high water application of I21 (buried drip) compared to I22 resulted in the irrigation water use effi ciency for I21 being closer to the time-based treatment I23. Cumula tive leaching data is summarized in Table 1.7, and the cumulative volume leached over th e season and the cumulative load of nitrate-nitrogen leached over the season are presented graphically in Figures 1.9 and 1.10 respectively.

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29 DAT 020406080100 Volume Leached (mm) 0 10 20 30 40 50 60 Figure 1.9. Cumulative volume of leachate collected in the lysimeters per treatment over the season for Experiment 2. DAT 020406080100 Load NO3-N leached (kg/ha) 0 10 20 30 40 50 Figure 1.10. Cumulative nitratenitrogen load leached per treatment over the season for Experiment 2.

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30 Table 1.7. Average volume leached and nitrate-nitrogen load leached per treatment for Experiment 2 TotalTreatmentTotalTreatment mmmmkg/hakg/ha I21(Dielectric probe + subirri.)20.614.5 a5.83.7 a I22(Dielectric probe)6.85.0 b6.76.2 a I23(Time-based local grower)42.836.3 c37.334.1 b NO3-N load Treatment Volume leached Different letters depict sta tistically different means for P 0.05 (Tukey Kramer HSD method) The leaching volume differed significantly fo r all three treatments. Treatment I21 had a higher leached volume (14.5 mm) than I22 (5.0 mm) during the treatment period, corresponding to the higher wa ter application, but both soil moisture based treatments were considerably lower than the time-ba sed treatment I23 (36.3 mm). Total season leached volumes (including the establishmen t period) were on average 31% higher than leaching volumes during the treatment period. The load of nitrogen load leached by the soil moisture based treatments I1 and I2 were 3.7 and 6.2 kg/ha respectively and translated into a 89 to 84 % reduction from I23 (34.1 kg/ha for the treatment period). Although treatment I21 had high water applicat ions and higher leached volumes than I22, the loads of nitrate leached were lower, a resu lt of the fertigation line at the surface being above the buried irrigation line. The irri gation water did not pass through the soil zone near the surface with highest nitrate concentra tion. Better correlation of the buried drip irrigation tape and the soil moisture probe in this treatment would most likely further reduce leaching due to lower water applications closer to that of I22. The increase in load of nitrate-nitrogen bei ng leached towards the end of the season in treatment I22 was due to an increase in water applied towards the end of the season after a late increase in plant biomass and higher crop water requireme nts. The increase in irrigation water applied should not have substantially increa sed the leaching, as the crop according to soil

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31 moisture status required the water applie d. Better knowledge of position of the soil moisture probe in the root zone may help furt her reduce the portion of this water that is leached. Comparison of results A summary of the percentage changes in value of the dependant variables of the soil moisture-based treatments from the timebased local grower treatment are presented in Table 1.8. Averages for the soil moisture -based treatments are presented to help highlight the trends when compared to traditional time based practices. The soil moisture-based treatments applied less water than the time-based schedules for both experiments. For the treatment period the soil moisture-based schedule treatments of Experiment 1, I11 and I12 achieved 77% and 80% water savings compared to the local grower treatment resp ectively, and the treatm ents I21 and I22 for Experiment 2 yielded 10% and 64% water savings over the local grower treatment respectively. Table 1.8. Average values and the percentage change from the local grower treatment for the dependant variables measured in two experiments of tomatoes corresponding to different irri gation scheduling treatments. TensiometerECH2OAverage ECH2O+sub irri.ECH2OAverage I11I12(I11+I12)/2I21I22(I21+I22)/2 Dependent variableGravelly loamGravelly loamGravelly loamsandsandsand Total Irri. Water (mm)-70-82-8-50 Treatment Irri. Water (mm)-77-90-10-64 Yield (kg/ha)10-126278 IWUE (kg/m3)27540075216 Total Vol. Leached (mm)-73-75-74-52-84-68 Treatment Vol. Leached (mm)-78-91-85-60-86-73 Total Load N-NH4 (kg/ha)-97-97-97--Treatment Load N-NH4 (kg/ha)-88-92-90--Total Load N-NO3 (kg/ha)-64-46-55-84-82-83 Treatment Load N-NO3 (kg/ha)-64-94-79-89-82-85 Total Load DP (kg/ha)-66-76-71--Treatment Load DP (kg/ha)-70-89-79--Total Load TP (kg/ha)-53-77-65--Treatment Load TP (kg/ha)-56-85-70---Experiment 1Experiment 2 Soil moisture-based treatments Percentage change from the time based (local grower) treatment

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32 A large portion of the water savings occurred in the early part of the season when the crop was small and water requirements were low. The soil moisture based treatments minimized water application to suit crop n eeds during this period, while the fixed time based schedules over applied irrigation. This can be seen in Figures 1.4 and 1.7 showing the cumulative plots of water for the season fo r each experiment. Total water savings for the full season were similar but on average over both experiments 8% lower than the treatment period. The water applied during establishment was 52 mm for both experiments, which was a significant contri bution towards the total application for the soil moisture-based treatments. Irrigation rates decreased dramatically once the soil moisture-based treatments began to operate, but this did not have an effect on plant growth. This suggests that th e amount of water applied du ring the establishment period could be reduced. Further studies could determine what the practical level of establishment irrigation is needed before irrigation is switched to soil moisture-based scheduling, without affecting transplant gr owth and yield. Limiting water to the transplants must be done so with caution, as the plants roots are small and not well established. Probe placement at this period is critical. The irrigation rates for the soil moisture-based treatments were below those of the crop water requirements as calculated by historical evapotranspiration and crop coefficients presented in Ma ynard et al. (2004). Amayre h and Abed (2005) conducted a study on field grown tomatoes in the Jordan Vall ey to test the effect s drip irrigation and plastic mulch would have on evapotranspi ration and crop coefficients. Their study showed that crop coefficients using drip irrigation and plastic mulch were 36% lower than the crop coefficients in FAO 56 whic h assume a uniformly planted field. These

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33 results match those obtained by Brouwer and Heibloem (1986). This explains the lower crop needs and subsequent wate r use of the soil moisture-based treatments compared to traditional ETc calculations. Yields from Dade County (Experiment 1) were above the Florida average of 39,295 kg/ha suggested by Maynard et al. (2004) and ranged from 40,000 to 49,000 kg/ha. Total marketable yields from Experiment 1 were derived from two harvests for the crop. The Citra County (Experiment 2) yields were lower than average ranging from 18,600 to 33,200 kg/ha. Total marketable yield comprised of two harvests. Poor canopy development in the plants early stage as a result of disease and some nutrient stress, most likely reduced yields to some extent. Furthe rmore, the wettest treatment I4 in the Citra County (Experiment 2) had yi elds that were significantly lower than the two soil moisture-based treatments I1 and I2. This may be a result of th e increased nitrogen leaching and a loss of nutrient from the root zone of the crop. Another potential yield reducing factor was that during the middle of the season the plastic mulch started to loose its physical integrity, and provide incomplete coverage on a few of the beds. Where this occurred, the bed was recovered with plastic mulch manually. The damage was random, and did not occur near any instrumentation, but its effect on the yields is not certain. The mulch is designed to start to break down af ter a period of time, sufficiently longer than the cropping season. Reasons for this mulch to weaken after only 7 weeks are not known. The suppliers were contacted and informed of the problem. Irrigation water use efficiencies (IWUE) were much higher for the soil moisture based treatments. Soil moisture-based tr eatment IWUEs were 275 and 400% higher for Experiment 1 and 75 and 216% higher for Experiment 2 than the corresponding time-

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34 based local grower treatments. A previous experiment in the Miami-Dade County using similar soil moisture based scheduling methodology by Muoz-Carpena et al., (2004) found IWUEs of between 11 and 40 kg/m3. The high IWUE recorded for Experiment 1 in Miami-Dade County was also 40 kg/m3. This suggests that the methodology has the potential for consistently efficient water use. All nutrients tested for leaching showed subs tantial reductions in total loads of over 55% for the soil moisture-based treatments over the time based treatments. For surface based drip irrigation and fertigation the vol ume of water applied appeared to be the driving force, and volumes of leachate and nutrient loads followed water application trends. For the sub irrigation of treatmen t I21 in Experiment 2 the high water and leaching volumes did not displace much of th e nutrients from the soil as the irrigation was applied below the fertilizer application. The total leachate volumes averaged 74 and 68% lower for the Experiment 1 and Experiment 2 respectively. The lower amounts of water passing through the root zone did not resu lt in high concentrations of nutrients in the leachate, as reductions in nutrient loads were equal to or higher the corresponding reductions in leachate volumes. The highest redu ctions in nutrient load were recorded for ammonia-nitrogen (averaged 90% for the treat ment period) on Experiment 1 followed by nitrate-nitrogen (85% for the treatment peri od) on Experiment 2. The nitrate-nitrogen leaching in Experiment 1 had variability pr oblems within treatments that may have masked the results to some degree. The va riability was higher for all nutrients in Experiment 1 and was due to the smaller lysimeter capture area used. The smaller capture area were more vulnerable to impe rfect placement of the lysimeters under the crop in the beds, but also had a higher variabi lity of number of plants and emitters that

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35 they contained. For future experiments lysi meters with large as possible capture areas should be used to reduce leaching variability with in treatments. This will be of particular importance when finer soils are tested that have highe r lateral movement of soil moisture. The water applied to Experiment 2 was not replicated for each treatment. The replications were for yield an alysis and to account for soil he terogeneities. It would be recommended to operate each replicate of the treatments independently in future experiments. Each replicate would have it s own soil moisture probe and control valve, and give a better indication of the variabi lity associated with the methodology, and help eliminate the possibility of having one pr obe in an unrepresentative position for the whole treatment. The nutrient leaching data showed trends th at correlated with the water application amounts. Treatments with high water applica tions yielded higher volumes of leachate and higher loads of nutrients pa ssing through the root zone into the lysimeters. The form of nitrogen being applied differed between the two experiments, as Experiment 1 applied nitrogen in the ammonia form and Experiment 2 applied calcium nitrat e. Both nitrate and ammonia loads of nitrogen were determined from the leachate in Experiment 1 as the ammonia nitrogen in the lysimeters could sta nd for as long as three weeks before it was abstracted, and could undergo ni trification during this period Both experiments showed a significant reduction in leaching of nitrate, which is a contaminant of many surface and groundwater resources in Florida, the US and around the world. The ability of soil moisture-based irrigation to reduce nitrate load ing to local water resources on coarse soils is high. Further studies need to be conducted to test the effect diffe rent soils have on the methods ability to reduce nutrient loading.

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36 Conclusion This series of two experiments confirme d the potential of soil moisture based scheduling to reduce water applications as a pposed to traditional time based schedules and applied water less frequently and in highe r volumes. Soil moisture based treatments applied between 50 and 82% less water than co mparative time based schedules which are typically used for irrigation scheduling. Th e results show that the reduction in the amount of water applied can be achieved without significan t reductions in yield. The reduced water application of the soil moisture based treatments translates to a reduction in both volume of leaching, and the load of nut rients leached. Total nitrate leaching was reduced by 55% and 83% for the two experiments and total phosphorous leaching was 65% lower. Greater reductions in loads l eached (between 70 and 97% for all nutrients) during just the treatment period were obtained for the soil moisture-based schedules and suggest that there is potential for further savings at the begi nning of the season. Potential scheduling during the establishment must rec ognize the practical lim its of saving water and nutrients when the plants roots are limited. The reduc tions in nutrient losses could provide a grower with the means to reduce a pplication amounts and thus costs, and more importantly reduce the risk of surrounding wa ter resources to nutrient contamination. This is critical to the sustainability of ag riculture in Florida and many other areas of the world, where increasing population and public environmental awareness introduces a fierce competition for water resources.

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38 CHAPTER 3 FERTIGATION METHODS FOR SOIL MOISTURE-BASED IRRIGATION OF VEGETABLE CROPS Introduction Commercial vegetable production require s optimal fertilizer and water-use management for high yields a nd maximum profits. In most cases nitrogen is the limiting element to crop growth, especially on coarse-t extured soils such as sands and gravels that have low organic matter (Scholberg et al., 2001). Efficient use of water and fertilizers are also highly critical for the sustainability of agriculture in increasingly competitive local and world markets, and in competition with ur ban environments for resources (Hebbar et al., 2004). In Florida vegetables are produ ced on nearly 120,000 ha and fertilizer is needed for profitable production of high-qua lity vegetables in the State (Hochmuth, 2000). The optimum management of fertilizer can promote sustainability in several ways, and application of N and K in excess of crop requirements can have significant adverse effects (Hartz and Hochmuth, 1996). Fi rstly, fertilization repr esents a significant input cost, accounting for 8 to 10 % of tota l cost of production for some vegetables. Secondly, nutrients such as N or K can be lo st due to leaching in the sandy soils of Florida under excess irrigation or heavy rainfall. Finally nutrient management is important because it reduces the nutrients introduced to the envi ronment that have a negative impact on the quality of surface and groundwater. There has been significant work conducted on rates of N and K applied to vegetable crops, and tomatoes in particular, and with improved nutrient and irrigation management

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39 the maximum recommended rates have decreased in recent years. Applied fertilizers used in Florida tomato production averag ed 350-225-605 kg/ha as surveyed by the Florida Agriculture Statistics Service for 1994 (Fla. Agr. Stat. Ser., 1995). These actual applied rates exceed IFAS current maxi mum recommendations of 175-150-225 kg/ha N P2O5 K2O, found through experiment to meet toma to requirements for high yields based on soils with low P and K concentrations (Hochmuth and Hanlon, 1995). Achieving the correct rate of fertilizer application is an e ssential part of optimal fertilizer management. This however needs to be coupled with good irrigation practices as the application of fertilizer and water are interlinked. Poor ir rigation management and efficiencies affects nutrient management. The higher applications of fertilizer than current recommendations partially balance the effect of inefficient irrigation practices. Improved Irrigation Management Modern methods of using soil moisture to schedule irrigation are yielding significantly improved irrigation water use, and at times has increased yield (MuozCarpena et al., 2005). A system has been de veloped by the University of Florida that utilizes soil moisture probes to schedule on an automated irrigation system (Dukes and Muoz-Carpena, 2005). Water savings on aver age of 60 70% and up to 80% compared to traditional time-based irrigation have been obtained by multiple experiments on vegetable crops (tomatoes, bell peppers and zu cchinis) on coarse soils in Florida. The system applies water in small amounts and at fr equent intervals (sever al times per day). The soil water is kept within an optimal range for plant growth rath er than being allowed to dry out and then be comp letely refilled by a single large irrigation event. The improved soil water management in the root zo ne of the crop decreases the potential for loss of nutrients by the leaching due to the lack of excess applied water. Other essential

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40 components of optimal fertilizer management are the method of application and the frequency of application. Fertigation Clark et al., (1991) found improved wate r and fertilizer management using tensiometers and fertigation with micro irri gation of market toma toes produced on sandy soils can result in reduced water and fertiliz er applications as compared with current irrigation methods. This statement brings two po ints into focus. Firstly as already stated irrigation and fertilizer management are in tricately linked. Secondly that fertigation using surface and subsurface drip has proved to be in many applications, more effective at supplying the crop with nutrients as needed by the crop. Benefits of Fertigation Dry fertilizers applied u nder traditional methods ar e generally not utilized efficiently by the crop. In fertigation with drip, nutrients are applied through the emitters directly into the zone of maximum root activit y and consequently fertilizer use efficiency can be improved compared to conventional methods of fertilizer application. Raskar, (2003) reported significant incr eases in yields of banana when soluble fertilizer was applied through fertigation compared to st raight fertilizer. Hebbar et al. (2004) conducted field experiments during two su mmers and found that 100% water soluble fertilizer applied through fertigation had si gnificantly higher yields than soil applied treatments. Yields were similar for half-soi l and half-fertigated treatments. Fertigation also resulted in less leaching of NO3-N and K to deeper layers of sandy loam soil. Fertilizer Injection It is important to design the drip irrigation system so that fertilizer injection can be achieved in a reasonable amount of time and the crop is not over watered while

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41 delivering the fertilizer. Concentrated material s are easier to inject because of the shorter injection cycle required, for the same amount of nutrient. Grow ers should purchase as high an analysis of liquid fertilizer as po ssible to avoid applying large amounts of water (Hochmuth and Smajstrla, 1998). Research on a sand soil in Florida shows that 45 minutes (young tomato crop) to 1.5 hours (matur e crop) would be sufficient to apply the amount of water required by the crop during any one irrigation cycle (Smajstrla, 1985; Clark et al., 1990). Fertigati on and subsequent irrigation cycles longer than 1.5 hours on a mature crop runs the risk of leaching th e nutrients below the root zone. Leaching occurs after a shorter dura tion on the gravelly loam soils in South Florida. Fertilizers may be injected as a precisel y managed level of concentration, or as a bulk mass of fertilizer with possible vary ing concentration leve ls. Concentration injection requires a precise in jection system, and is more costly and complex than bulk injection that simply involves the injection of a desired amount or volume of fertilizer into the system. The injection system must be calibrated for the irrigation system it is to be used within, or else expected applica tions will differ from actual applications. Variations in operating pressu re, system flow and even temperature can influence the calibration of the system (Hotchmuth and Smajstrla, 1998). Fertilizer application schedules The current preplant fertilizer recommenda tions are a fraction of the total seasonal fertilizer requirement, either liquid or dry, appl ied in the bed as a starter fertilizer for drip irrigated crops (Hochmuth and Smajstrla, 1998). This starter fertiliz er would contain all the phosphorous (P) and micronutrients, and up to 40% of the N and K. In most cropping situations approximately 35-45 kg/ha of N and K would suffice (Hochmuth and Smajstrla, 1998). Maynard et al. (2003) suggested broadcasting all P2O5, micronutrients,

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42 and 20-25% of the N and K2O in the bed area, for mulched dr ip irrigated crops. Preplant application of P is common for at least two reasons. Soluble P sources are more expensive than granular forms, and the potenti al problem of chemical precipitation in the drip line is avoided. Some research has found that applying some or all the fertilizer preplant provides higher yields than just incremental applica tions through the season. This is most often the case on soils with a higher pe rcentage fine particles or mo re organic matter. Preplant application of N (and K, if needed) is partic ularly important where initial soil levels are low (Locasio et al., 1985), or where early -season irrigation requirements are low. Preplanting fertilizer formul as of 6-6-12, 6-3-12 or 10-10-10 are satisfactory (Li et al., 2002). Locascio et al., (1997) applie d N-K in three different proportions of preplant, namely 0%, 40%, and 100% to tomato crops growing on an Arredondo fine sand and only N as above to an Orangeburg fine sandy lo am testing high in K. It was found that the lowest yields on the fine sand occurred fo r the 100% preplant, intermediate yields for the 0% preplant (all drip applied), and the highest yields for the 40% preplant and 60% fertigation. On the sandy loam the highest yields were obtaine d from 100% preplant, intermediate with 40% preplant and 60% drip applied, and lowest with all N drip applied. This suggests that soil texture plays a majo r role in determining what methods of fertilization are most appropriate. A further component of the work conducte d by Locascio et al., (1997) was to split the drip applied fertilizer into 6 or 12 equal or variable appl ications through the season. The variable application rate had most of the nutrients ap plied between weeks 5 and 10

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43 after transplanting. For the 100% drip appl ied N on the sandy soil, yield was higher for the 12 equal applications than th e12 variable applica tions of N. While work continues to optimize rates of N, P and K for different soils, the frequency of fertilizer application and its effects on nutrient use efficiency re mains less well understood. Thompson et al., (2003) stated that optimum fer tigation intervals for drip-irrigated crops has not been well researched. A study conducted subsequen tly by Thompson et al., (2003), found that broccoli grown on a sandy loam soil did not respond to any increase in frequency of fertigation using subsurface drip smaller than 28 days. Frequent injection might be needed on sandy soils that do not retain large amounts of nutrients, and for growers that wish to minimize injection pump size and cost (Hartz and Hochmuth, 1996). Fertiga tion frequency however in most situations is not as important as achieving a correct rate of nutrient application to the crops during a specific period (Cook and Saunders, 1991). What must be kept in mind is that water management and fertilizer management are linked. Change s in one program will affect the efficiency of the other program. Fertigation coupled with soil moisture-based irrigation Automation of fertigation within a soil moisture-based irrigation system has the potential for decreased labor as well as incr easing water and nutrient savings. Fertilizer can be injected with precise injection pumps on an indepe ndent automated schedule, or the fertilizer can be continuously injected using a venturi injector. A drawback of the automated injection pumping system is its co st. Venturi injectors are low cost devices that have proven to provide adequately accura te injection rates for fertigation purposes. Continuous injection with a ve nturi means injecting fertiliz er each time an irrigation event occurs. The flow of irrigation water across the venturi contraction causes a

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44 pressure differential that suck s a liquid fertilizer solution into the distribution system (Figure 2.1). Placing the vent uri across a pressure -regulating device such as a valve, or pressure regulator, or pump can enhance the pressure differential. Appendix A1 to A4 has different recommended layouts for incr easing the pressure differential across a venturi. Figure 2.1. A venturi injector schematic showing flow direc tions and operating principle (adapted from Mazzei Injectors Inc.) The venturi injection rate is relatively in sensitive to flow rate, and is controlled primarily by pressure at the inlet and outlet. Manufacturers such as Mazzei Injector Corporation provide charts for their different models to calculate injection rates. The concentration of fertilizer to be inj ected is determined by knowing the desired fertilizer application rate, the injection rate of the venturi, and the injection time (in this case the same as the irrigation schedule). For fixed time-based ir rigation schedules the irrigation schedule is predetermined and t hus the injection time is known. For dynamic soil moisture-based irrigation the duration of irrigation changes according to factors that effect soil moisture level. The irrigation sc hedule will vary from season to season when using soil moisture as the basis for schedu ling. An estimate was n eeded to predict the water use for the crop over the season. Th e crop evapotranspiration ETc is the IFAS recommended method for determining water use. Previous experiments on tomatoes by

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45 Munoz-Carpena et al. (2004) and (2005) repor ted consistent savings for two consecutive experiments in the Miami-Dade County on toma toes with the QIC and dielectric probe soil moisture-based scheduling over the ETc schedule. The savings were 51% and 58% for two experiments conducted during the wi nter seasons on Krome soil. By using results of water savings by soil moisture based irrigation schedu ling over ETc scheduling, derived from experiments conducted by the Un iversity of Florida, expected water applications can be derived. From thes e water applications, fertilizer solution concentrations can be determined for a known injection delivery rate. The aim of this research was to 1.) To test the management possibilities of continuous fertigation coupled with soil mois ture irrigation schedu ling, 2.) Compare the continuous ferigation with fixed event fertiga tion in terms of seasona l application rates, labor and management requirements, and cr op yield, and 3.) Make recommendations for future research. Methods and Materials Fieldwork was conducted for two years to test the continuous fertigation method. Both experiments were conducted on tomato crops, the first over the 2004/2005 winter cropping season in South Florida on a calcareous gravelly soil and the second during the 2005 spring season in Central North Florida on a sandy soil. For each experiment fixed event fertigation applied th rough drip lines was compared to continuous fertigation integrated into a soil moisture-based irri gation schedule also a pplied through drip. Tomatoes of the variety FL 47 were cropped on raised beds with plastic much spaced at 1.83 m. Sorghum-Sudan grass was grown as a cover crop the seas on prior to tomato cropping for each experiment.

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46 Experiment 1: South Florida gravelly soil This first experiment was conducted during the winter season in South Florida at the Tropical Research and Education Center, in Miami-Dade County on a gravel soil. The field was divided into two regions, an Experiment Plot, and a Demostration Plot for different purposes. The Experiment plot had different irrigation water scheduling treatments and was used to determine the effects of scheduling methods on water use, yield and leaching. Fertigati on was conducted through a separate distribution system to the irrigation water, and fertilizer was applied equally to all treatments on a fixed timebased schedule. The Demonstr ation Plot tested continuous fertigation coup led with soil moisture based irrigation, and provided visitors to the field with a display of a system working as it would in practice. Fertilizer was applied as fertigation through the same distribution system as the irri gation water. All injected in to the same line that supplied the irrigation water. All injection of the fert ilizer for fertigation of this experiment was carried out using venturi injectors (mode l no. 484, Mazzei Injector Crop., Bakersfield, CA). The venturi injectors we re installed across 10 m pressure regulators to help develop adequate pressure differential (Figure 2.2 a nd 2.3). A downstream pressure of 10 meters was chosen to minimize the pressure in the lay flat and thus reduce leaks but maintain sufficient pressure for the drip tapes that were rated at 7 m operating pressure. The upstream pressure to the venturi was the pres sure inside the well tank of 25 m. The 484 model of Mazzei venturi injectors have an ideal documented injection rate of 64 L/hr when with an upstream pressure of 25 m and a downstream pressure of 10m. This can be seen in the tables (Mazzei Injector Inc. http://www.mazzei.net/agriculture/table s/Performance%20Table%20Metric.pdf ) in Appendix A4.

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47 Figure 2.2. Pumphouse hardware layout for Experiment 1 Figure 2.3. Venturi injectors placed across pr essure regulators for added pressure differential.

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48 The injection hardware was installed and the distribution system was connected so that the venturi could be calibrated and actua l injection rates could be determined for fertilizer injection scheduli ng and for comparison to the ideal documented rate. The calibration consisted of inject ing a known volume of water and quantifying the time to inject this volume. The test was conducted three times for each venturi. The rates and measures of variability obtained from the calibration are presented in Table 2.1. Table 2.1. Venturi injection rate s and variability of injection rates from a calibration test conducted prior to the transplant of the tomato crop on Experiment 1 The variability of the injection rates for a particular venturi were very small and had coefficients of variation of 0.024, 0.013 and 0.010 L/hr for venturi 1A, 1B and 2 respectively. The variation of the injecti on rates between the three injectors can be attributed to a combination of Different downstream distribution system s (causing different downstream system pressures) Some air being injected with the water For both plots, 60 kg N/ha was applied prepla nt together with all the P required for the season. Liquid urea based fertilizer of solution 4-0-8 (N-P-K) injected by the venturi injectors supplied the remaining fertilizer. For the Experimental plot the liquid fertilizer was diluted to a 50% solution and injected on the fixed time schedule independent of the irrigation. A 50% dilution rate achieved maxi mum fertigation rates for the season within 30 minutes of injection. The to tal fertilizer application for the season was designed to be 200 kg N/ha (175 lb N/ac). Venturi number1A1B2 Demonstration Plot Average injection (L/hr)55.848.758.2 Stdev (L/hr)1.40.60.6 Experiment Plot

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49 For the Demonstartion plots continuous fertigation method integrated within the soil moisture based irrigation scheduling, the ir rigation schedule had to be predicted. It was estimated from previous experiments conducted by Munoz-Carpena et al. (2004) and (2005) that the water application for the soil moisture-based scheduling would be 40% of theoretical crop evapotraspir ation (which overestimates actual crop water needs for plastic mulched beds). This estimate of wa ter application (40% of theoretical ETc) was divided over the season according to the cr op curve. The tota l design fertilizer application for this plot was 266 kg/ha (237 lb/a c). The required dilu tion of 4-0-8 liquid fertilizer was initially 15% for the first 11 week s of the season and then 11% for the last 2 to 3 weeks when fertilizer rates are reduced. The actual fertilizer rate applied to the crop by the venturis on the time-based schedule for the Experiment Plot, was 196 kg/ha (174 lbs/ac) which complied very well with the IFAS recommended 175 lbs/ac. The continuous fertigation method in Demonstration plot applied 285 kg N/ha (250 lbs N/ac) that was comparable to the desired rate of 266 kg N/ha ( 237 lbs N/ac) by the procedure just mentioned (Figure X). Yields for continuous fertigation coupled with soil moisture-based scheduling were similar to yields achieved by treatment em ulating local growers, and averaged 47 260 kg/ha (42 100 lbs/ac) and 45 110 kg/ ha (40 180 lbs/ac) respectively. A second experiment was conducted the fo llowing spring to further test the continuous fertigation method on a different soil and season, a nd using a different fertilizer. Experiment 2: North Central Florida sandy soil Tomatoes were grown on a fine sand so il using plastic mulched beds in North Central Florida at the Plant Research and Education Unit in Citr a County. For this

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50 experiment, the continuous method was test ed against an injection pump, which was manually operated to injected fertil izer once a week (Figure 2.4). Figure 2.4. Weekly manual injection of fertiliz er solution carried out using a peristaltic pump for Experiment 2.

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51 For the manual injection treatment, th e season total calcium nitrate that corresponded to IFAS recommended rate of nitrogen, was divided into weekly increments that were small in the early s eason and increased towards the end of season. These weekly increments were weighed out and dissolved prior to injection with a peristaltic injection pump (Fi gure 2.4). Muriate of potash was the source of potassium for the crop. If left to sta nd, a solution of calcium nitrate and mutriate of potash forms a precipitation. As such no potassium was a dded to the continuous injection treatments tank and the potassium was manually inje cted using a pump for both treatments. Nitrogen in the form of calcium nitrate was dissolved in solution and continuously injected from a storage tank with a ve nturi (model no. 285, Mazzei Injector Corp., Bakersfield, CA). The system was similar to that of Experiment 1 and the venturi was placed across a 10 m pressure regulator. Agai n water application using the soil moisturebased irrigation schedule was predicted to be 40% of ETc. Figure 2.5. Cumulative nitrog en rates comparing continuous and manual fertigation treatments in Experiment 2 on sandy soil. 0 50 100 150 200 250 300 29-Mar18-Apr8-May28-May17-Jun7-Julkg/ha N N2 weekly manual N4 continuous

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52 The plot of fertilizer applied through th e season (Figure 2.5) shows how although a constant concentration of fertilizer was injected for the continuous fertigation treatment, the rate of application varied considerably th rough the season. Nutrient application rate was below the desired rate for most of the season. Lower than average temperatures during this period reduced evapotransoira tion and corresponding irrigation amounts based on soil moisture. Because irrigation driv es the fertilizer injection the fertigation was also low. The increase in appli cation rate later in the season (from 7th June onwards) can be attributed to an increase in irrigation as a result of increased evapotranspiration. The increase in evapotranspiration was the re sult of increasing biomass and plant cover, and a period of warmer weathe r conditions in early summer. The continuous fertigation system integrat ed within soil moisture-based irrigation is very successful at providing a system that is low cost with low labor and management requirements during average years and condition s. Due to the coupled nature of the water and nutrient applications the system is however vulnerable to weather and any other conditions that cause de viations from expected irrigation application. The lower irrigation water application its elf is not the problem, as the crop may have needed less water due to cooler conditions The soils moisturebased scheduling applies water as needed by the crop. The potential harm is the lower fertilizer a pplication induced by lower irrigation amounts. The crop may have re quired less water but no t less nutrients. Combining continuous methods with scheduled fertigation A solution to the problems of fertigati on within a soil moisture-based irrigation system is to combine the best components of the two methods of continuous fertigation and fixed schedule manual injection. The bene fit of the continuous fe rtigation is the low cost of the venturi injector and the ease of management and low labor requirements. By

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53 decoupling the fertigation from the irriga tion scheduling based on soil moisture, the systems vulnerability to extreme weat her and conditions is mitigated. Soil moisture-based irrigation as practiced by the University of Florida uses an irrigation timer to schedule potential events. These prescheduled events trigger a soil moisture probe to be queried. If soil moistu re is below a set thres hold a solenoid valve is opened and the event initiated. If the soil mo isture is above a set threshold, then the event is bypassed and water saved. For vegetable crops the maximum daily water requirements are divided into 4 or 5 sub-ev ents. To implement continuous fertigation with a venturi on a fixed schedule, one of th e sub-events is dedi cated to fertigation independent of soil moisture status. Any of the sub-events within the day could be used for fertigation as they are all sufficiently short to avoid excessive leaching and nutrient loss. Herdel et al. (2001) stat e that the uptake of nutrients and nitrate in particular is dependent on plant-internal relations and not nutrient availabilit y, but is three times higher during the day than at nigh t. The first event of the da y is the most appropriate as subsequent irrigation events may be bypassed if the water for fert igation wet the soil sufficiently. If the fertigation event were later in the day, the soil may already be wet from prior events, but water will still be adde d by fertigation, increa sing the potential for leaching. Furthermore, the first event of the day is the most likely due to drying out of the soil (although at a somewhat lower rate than the day), and the best time for a fixed event. The recommended control and distribution system hardware for fixed continuous fertigation within a so il moisture-based ir rigation schedule is pr esented in Figure 2.6.

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54 Figure 2.6. Fertigation system for decoupled time-based fertigation and soil moisturebased irrigation. Solenoid valve 1 is opened and closed by a quantified irrigati on controller (See Figure A5 in Appendix A), which interfaces the soil moisture probe with a RainBird ESP-12LX irrigation timer. Sole noid valves 2 and 3 control the single fertigation event per day and are operated simultaneously by an independent schedule on the RainBird Timer. A potential schedule that would be programmed into the timer is shown in Table A6 in Appendix A. Additional fertigation information Florida Law requires that a backflow pr evention system be installed on most irrigation systems when chemicals are being injected. When the water supply is not public water, irrigation wells for example, the minimum backflow prevention system

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55 requires a check valve, low pressure drain, and vacuum breaker on level piping between the point of injection and the irrigation pu mp to prevent water and chemicals flowing back to the water source (Smajs trla et al., 1985). No backfl ow prevention is required if the water source is not public water, and no chemicals are injected into the irrigation system (Smajstrla et al., 1994). To extend th e life of the system, and to maintain high irrigation uniformity by keeping the emitters unblocked, a filter should be placed after the fertilizer injection. A 200-mesh size disc filter should be used. Fertilizer should be purchased that is sol uble and quickly availa ble to the plant. Some liquid fertilizers are slow release and although my be effective at reducing leaching for single large applications are not suitable for daily injection when the nutrients are applied as the crop needs them. Suitable form ulations are 4-0-8 (N-P -K) liquid fertilizer, and soluble potassium nitrate (KNO3). Suggested IFAS daily fertigation rates are presented in Table 2.2. Table 2.2. IFAS suggested daily fe rtigation rates for tomatoes. When 25% total N and K is applied prep lant, the first two weeks can be omitted. To adjust the fertilizer application to fo llow crop growth and needs it is easier to adjust the fertigation time on the controller th an it is to change the solution of a large volume of fertilizer in the tank. The concentration shoul d be set so that the longest fertigation event is similar to the length of the sub-daily events. To ensure that the venturi is working correctly and that nutrients are reaching the crop, a simple check is to Week after transplantN (lbs/ac)N (kg/ha)K (lbs/ac)K (kg/ha) 1 and 21.51.71.51.7 3 and 422.222.2 5 through 112.52.833.4 1222.222.2 131.51.71.51.7 Season total 20022522525 3 Daily Injection rate NitrogenPotassium

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56 record and check the level of the fertilizer solution in the tank. The level can be compared to design levels that can be easil y calculated from the injection schedule and venturi injection rate. Conclusions Soil moisture-based irrigation has high poten tial for water savings and accurate soil moisture management for optimal crop growth. Fertigation combined with soil moisturebased irrigation can reduce leachi ng of nutrients and delivers nutri ents to the root zone of the crop. Continuous fertigation is a viable low cost and labor method that is driven by irrigation water application. When coupl ed with soil moisture-based irrigation scheduling it requires a prediction of season irrigation amount to determine concentrations to be applied for the upcoming season, and is vulnerable to weather, crop and soil effects that may reduce evapotrasnpiration a nd thus irrigation amount. Decoupling the continuous fe rtigation from soil moisture -based scheduling gives the system the reliability of a time-based schedule, while maintaining the benefits of both soil moisture-based irrigation and low cost and la bor fertigation. The two operations remain connected as the water that is applied with the fertilizer during fertigation contributes towards the soil moisture and irrigation is scheduled accordingly.

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57 CHAPTER 4 DIELECTRIC CAPACITANCE SOIL MO ISTURE PROBE CA LIBRATION AND SPATIAL SOIL MOISTURE DYNAMICS STUDY Introduction Optimal management of irrigation requires systematic estimation of soil moisture status to determine both the volume and timing of irrigation. Soil wa ter content must be maintained between specific lower and upper leve ls so that water is not limiting to plant growth, but leaching is prevented (Morgan et al. 2001). Measurements of soil moisture status under irrigated crops ove r time is part of integrated management that aims to minimize the economically detrimental eff ects of both under and over-irrigation on crop yield and quality, the environmental costs of wasted water and energy, and impaired water quality due to leaching. Integrated ir rigation management to achieve optimal soil moisture levels may be accomplished by util izing soil moisture monitoring devices in conjunction with rainfall records and knowle dge of plant needs (Munoz-Carpena et al. 2002). When using drip irrigation to apply wate r to the crop, the volume and profile of soil wetted by a single emitter is important. This must be known in order to determine the total number of emitters required to wet a la rge enough volume of soil to ensure that the plants water requirements are met. The vol ume of soil wetted from a point source is primarily a function of the so il texture and structure, application rates and the total amount of water applied (Lubana and Narda, 1998). Sandy soils also have low amounts of total soil water, and narrow ranges of plant-availa ble soil water. Morgan et al. (2001)

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58 found that the range of 100-50% plant available soil water in Apopka sand, a fine sand found in Florida, was only 0.08-0.045cm3cm-3 soil water content by volume and to 15 kPa soil water tension. The wetting profile in the root zone is dynamic and affected by crop root interactions with the soil. As the crop bi omass increases, evapotranspiration will increase and use more of the volume of water in the we tted profile. Crop and system factors that can affect the dynamic wetting profile and so il water volume other than soil hydraulic properties and emitter delivery rate are crop growth stage, root length and structure, and mulch type when mulches are used. The vol ume and shape of wetting profiles is not only important for emitter spacing and system design, but is important for soil moisture-based scheduling using soil moisture sensors. According to Lubana and Narda (1998) very little attention has been paid to the estimation of soil wa ter distribution during drip irrigation under realisti c field conditions. Due to the very vertical movement of wate r in coarse soils such as sand, large soil moisture gradients can exist across a small horizontal distance. Sensors placed in two positions only 15 cm apart within the wetting zo ne of an emitter can have very different readings during and after an irrigation even t. Sands are often water repellant and according to Bauters et al. (1998) research ha s shown that water repellant soils and sands have unstable wetting fronts and finger-like we tting patterns. These wetting patterns are generally directly related to the soil moisture retention curve (SWRC). It has also be shown (Kutilek and Nielsen, 1994) that labora tory determined SWRC s are significantly shifted to larger soil moisture values for gi ven soil matric potentials compared to those obtained under field conditions. The differen ces between laboratory and in-situ SWRCs

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59 are generally thought to be a result of a combin ation of entrapped air and/or alteration of bulk density in the laboratory samples. Because sensors provide the data that drives the automatic control of soil moisture based irrigation they are an extremely important component, and understanding the operating principles of a sensor and the e ffects of soil type on its performance is imperative (Zazueta et al., 1994). Poor sensor position that does not represent demographic soil moisture conditions in the root zone can either result in crop water stress, or over irrigation that negates th e water saving capabilities of soil moisture scheduling. From field experiments c onducted on two tomato crops, it became increasingly apparent how important knowledge of the effects of sensor placement position within the plastic mulched bed wa s for precise and reliable soil moisture management on coarse soils. The University of Florida has tested diffe rent types of sensors on plastic mulched vegetable crops. Munoz-Carpena et al., (2005) found that sw itching tensiometers worked well but required consistent refilling and maintenance, and granular matrix sensors behaved erratically due to slow response times. A diel ectric capacitance probe (ECH2O, Decagon Devices Inc., Pullman, WA) has proven to work reliably with low maintenance and is considerably lower cost than TDR sens ors. A general calibration curve is available for the ECH2O probe for sandy loam soils and accur acies of up to 1% soil moisture content by volume can be achieved using the general calibration curve for most soils. This equation for this linear cu rve is presented in Equation 4.1. Soil moisture = 0.0007*mV 0.29 [4.1]

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60 Campbell (2005a) has advised that a soil-specif ic calibration be conducted on soils with high sand or salt content. Campbell (2005b) has also noted a linear response of sensor out put to temperature, although recomm ends that temperature effects in soils are small due to the mediating effect of soil on temperature fluxes. Campbell (2005c) found that the ECH2O probe was generally not aff ected by low salinity on most soils, but readings of soil moisture deviated signifi cantly from actual values on sandy soils with high salinity. Considering the lack of knowledge of soil moisture profiles within the dynamic emitter-root zone continuum, the low plant av ailable water content of sandy soils, and the importance of good data from a soil moisture probe for soil moisture-based irrigation scheduling, an experiment was conducted on th e sandy soils at the plant science research and education unit (PSREU). The ai ms of this experiment were to: 1. Calibrate the ECH2O soil moisture probe for the fi ne sand soils found at the Plant science research and education unit. 2. Derive an in-field soil moisture characteristic curve for the fine sand 3. Gain knowledge of the spatial variability of soil moisture within the root zone of a plastic mulched crop and its corresponding effects of probe placement position on irrigation scheduling 4. Determine the effects of factors that may influence the dielectric capacitance probes mV readings Methods and Materials An irrigation field trial on a zucchini crop was conducte d during the fall season at the Plant Science Research and Education Unit in Citra County, Cent ral North Florida. The irrigation experiment was conducted to test the effects of soil moisture-based scheduling compared to regular time base d scheduling on water and nutrient use for plastic mulched vegetables. The soil mois ture-based treatments employed dielectric

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61 capacitance probes (ECH2O, Decag on Inc.) interfaced with an irrigation timer (RainBird ESP-LX12, Rain Bird Corp.) using quantifie d irrigation controlle rs (Dukes and MunozCarpena, 2005). The soil moisture probe is queried by the quantified irrigation controller (QIC) every time a prescheduled irrigation even t is to occur, and depending on if the soil moisture status is above or below a set thres hold, the event is initia ted or bypassed. Daily irrigation was divided into four possible subdaily events. This provides the crop with high frequency low volume irrigation, which ha s shown to manage soil moisture in a more optimal range and reduce water and nutri ent losses due to leaching than traditional high volume low frequency irrigation methods (Munoz and dukes papers). To achieve the optimal range of soil moisture for plant growth the soil moisture probe needs to: Have adequate accuracy for the application Be correctly calibrated for the particular soil type Reliable, and preferably low maintenance Positioned within the ro ot zone of the crop. Figure 4.1. ECH2O dielectric capacitance soil moistu re probe (Decagon Devices Inc., Pullman, WA).

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62 The dielectric probe being used for the e xperiment has an accuracy of typically 0.03 m/m or (3% volumetric moisture content) and a re solution of 0.002 m3/m3 (0.1%). With soil-specific calibration accuracies of 0.01 m/m ar e possible Campbell (2005). The probe dimensions (Model EC-20 in Fi gure 4.1) are 25.4cm 3.17cm 0.15cm. The probe determines the soil moisture from meas ures of the bulk conductivity of the soil in a region of soil approximately 2 times the wi dth of the probe (4cm) and averages the reading across the length of the shaft (F igure 4.1). The manufacturers provide calibrations for basic soil types, but a soilspecific calibration of the probe was conducted to improve the accuracy of the soil moisture data being used to schedule irrigation and monitor soil moisture for research purposes The calibration was conducted in the field, as laboratory studies often do not correlate with real conditions in th e field. The in field calibration would also allow a comparison between the soil mois ture probes being used to collect data and the probes scheduling the irrigation. A check could be made to test whether the threshold for irrigation scheduli ng corresponded to appropriate soil moisture levels. To determine the spatial variability of soil moisture in the area that probe placement has conventionally been used by the Univ ersity of Florida, sq uare grids of nine dielectric capacitance (ECH2O) probes spaced 14 cm apart were replicated in three beds of various irrigation scheduling treatments. The grids were centered directly between two plants, which were planted about 10 cm aw ay of the drip line (Figure 4.2). This was the same position used for the single dielec tric capacitance probe that was scheduling water to the crop.

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63 Nests of 3 TDR probes and 2 tensiometers fitted with pressure transducers were positioned between the next two plants to obtain measures of volumetric soil moisture content and soil moisture tension to derive a soil moisture release curve and against which to relate the output of the dielectric capacitance probes. These nests were also replicated three times. All probes were connected to Data loggers (CR10X, Campbell Scientific, Logan, UT) and recorded at 15-minute intervals. Figure 4.2. Grid of nine ECH2O probes pl aced between two activ ely growing zucchini plants to determine soil moisture distribution for probe placement in soil moisture-based irrigation

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64 Figure 4.3. TDR nest to measure soil mois ture for corresponding to mV irrigation threshold set point. Once a sufficient period of data was obtaine d to determine the spatial distribution of soil moisture using the grid of 9 diel ectric capacitance probe grids, the probe configurations were change d to calibrate the dielectri c capacitance probes mV output against the TDR soil moisture readings. Becau se the instruments were initially placed between two different plants with potentia lly different drip emitter positions, direct relations between soil moisture and mV readings were giving highly variable results. The dielectric capacitance probes were moved next to the TDR probes, as close as possible without interference. Two dielectric capac itance probes were placed next to each TDR centered between two plants and replicated twice for treatments I1 and I2. The replications were to help determine the inhere nt variability that exists due to different

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65 plants, emitter positions and possibly even soil moisture characteristics of the soil along the length of bed. A mean soil moisture vs dielectric capacitance probe mV curve could then be derived which may better describe the probe soil relationship. The irrigation system that was providi ng the crop with water was designed to maintain soil moisture within as close to optimal soil moisture conditions as possible. While this was good for the crop, it was not possible to derive extreme points for the soil moisture release curve, namely the very dry an d very wet regions of the curve. To obtain these points, instruments were installed at the end of a bed, and onc e sufficient irrigation had been provided to establish the plants co ntaining the instruments, the irrigation was terminated. Three tensiometers and three dielectric capacitance probes were installed between two plants (Figure 4.4). The plants in this portion of the bed continued to transpire and the soil moisture dropped towards wilting point. The probe cables were not long enough to reach the ends of the beds fr om the CR10X data loggers. According to the dielectric capacitance (ECH2O) user manual posted by Decagon Devices Inc. (Anon, 2005), any data logger that can produce a 2.5 to 5V excitation with approximately 10millisecond duration and read a volt-level signal w ith 12-bit or better resolution should be compatible with the ECHO probes. The current requirement at 2.5V is around 2mA, and at 5V it is 7-8mA. As such a small Hobo data logger (HOBO event logger, Onset Computer Corp. Inc., Bourne, MA), was used to power and record the ECH2O probes output. The small data loggers have the capac ity to simultaneously record four separate readings. It was found howeve r that the first port had insu fficient excitation period to power up the ECH2O probes and that good data was obtained for the other three probes. This method of data capture can provide a sm all low cost alternative to standard data

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66 loggers, especially for a few remote probes. The only maintenance needed was replacing the batteries. The batteries life was determ ined by the logging interval. Logging every 15 minutes, the batteries only needed to be changed once during the season (13 weeks) when three probes were operating. To ensure correct operation of the logger, it was placed in a watertight containe r (zip-lock bag) and covered w ith aluminum foil to prevent overheating. Figure 4.4. Nest of dielectric capacitance probes and tensiome ters used to generate the drier points of the soil moisture releas e curve for the fine sand at PSREU. The probe nests and positions used gave a good indication of the soil moisture status in the center of the bed between plants. To bette r understand the soil moisture distribution in a plants entire root zone an intensive probe layout was installed towards then end of the crop season once the roots had reached maturity in spatial distribution. A

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67 grid containing 33 dielectric capacitance probes was installed in one of the beds, and the fertilizer was terminated to this bed to avoid any salinity effects on the soil moisture readings. The grid covered the whole widt h of the bed, and was spread between three plants, completely covering the root zone of the middle plant (Figure 4.5). Figure 4.5. Probe grid of 33 dielectric capac itance probes to determine spatial dynamics in the root zone of a mature zu cchini crop in plastic mulched bed The data from the probes was analyzed and plotted in Sigmaplot Version 9 software. The software was used to gene rate 2 and 3D images to obtain visual representations of the spatial distributions. A first order Loess spatial smoothing function was applied to the data to generate a sm ooth 3-D image due to the distances between point readings.

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68 Presentation of Results The results obtained over a 5-week time by the grids of nine dielectric capacitance probes in treatments I1, I2 and I3 are pres ented in Figures 4.6, 4.7 and 4.8, respectively. Figures 4.6 and 4.7 show distinct daily and weekly patterns while Figure 4.8 is less ordered but still displa ys some weekly trends. The da ily pattern corresponds to the irrigation events during the day that keep the soil in a relatively constant soil moisture range. Some drying out of the soil occurs during the ni ght when evapotranspiration, although reduced compared to the day, conti nues. Weekly spikes in mV readings, appeared correspond to fertigat ion events that occurred once a week on Thursdays. The fertigation events were inde pendent of soil moisture, and occurred simultaneously during the day when irrigation events occurred due to soil moisture status. These events injected fertilizer into a separate drip line designated to fertigation. Th e fertilizer was applied as a 300 400 500 600 700 800 900 10/25/0510/30/0511/04/0511/09/0511/ 14/0511/19/0511/24/0511/29/0512/04/05 DatemV I1-E1 I1-E2 I1-E3 I1-E4 I1-E5 I1-E6 I1-E7 I1-E8 I1-E9 Figure 4.6. Dielectric capacitan ce probe readings for different spatial positions within the root zone of a plastic mulched cr op irrigated using a 475mV set-point.

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69 300 400 500 600 700 800 900 10/25/0510/30/0511/4/0511/9/0511/14/0511/19/0511/24/0511/29/0512/4/05 DatemV E10 E11 E12 E13 E14 E15 E16 E17 E18 Figure 4.7. Dielectric capacitan ce probe readings for different spatial positions within the root zone of a plastic mulched cr op irrigated using a 525mV set-point. 300 400 500 600 700 800 900 25-Oct-0530-Oct-054-Nov-059-Nov-0514-Nov-0519-Nov-0524-Nov-0529-Nov-054-Dec-05 DatemV E19 E20 E21 E22 E23 E24 E25 E26 E27 Figure 4.8. Dielectric capacitan ce probe readings for different spatial positions within the root zone of a plastic mulched crop irrigated using a 475mV set point, with fertigation at the surface and irrigation applied through a drip line buried at 15 cm.

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70 solution of the weekly requirements and inje cted using a peristaltic pump. Fertigation took approximately 15 minutes. This included a short peri od of irrigation before the injection of fertilizer to raise the de livery system to operating pressure, and approximately 5 minutes of irrigation after in jection was finished to flush the delivery system. What is not quantified is the possible effect of the salts adde d to the soil near the probes on mV reading. Figure 4.9. Bivariate plot of TDR and dielectric capacitance probes to obtain a linear relationship between soil moisture and mV. 95% confidence intervals are shown. The soil moisture vs mV output from the dielectric capacitance probes was plotted for five TDR and dielectric capacitance replicates. From these the average linear curve together with the 95% confidence intervals obtai ned from the spread of data (Figure 4.9). The soil moisture release curve presente d in Figure 4.10 was obtained by plotting soil moisture measurements from the outer bed probes. Dielectric capacitance mV readings logged by the hobo data loggers we re converted to soil moisture using the calibration presented in Figur e 4.9, and plotted against manual tensiometer readings.

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71 The soil moisture relation in Figure 4.11 was generated by plotting TDR readings against tensiometer readings and gives an indica tion of the variability in these quantities. The curve presented in Figure 4.10 is plotted with the data in Figure 4.11 and lies within the spread of data points. This suggests that the soil moisture values extracted from the dielectric capacitance probes using the calib ration curve correspond with TDR data, and that the hobo data logger was successful in capturing dielectric capacitance output data. A slight correction was made to the curve pr esented in Figure 4.10 by adjusting the drier points on the soil moisture release curve to better fit the data in Figure 4.11. This corrected curve and a fitted model is presente d in Figure 4.12. Extension of the curve in both the very wet and very dry direction will require further studies during a period when irrigation and soil moisture is not managed and kept within a certain range. The curves presented in Figure 4.10 and 4.11 are derived from field measurements of soil moisture using dielectric probes and will have some random errors common for dielectric soil moisture measurements. 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2 05101520253035404550 Tension (cbar)Soil moisture (m^3/m^3) Figure 4.10. Soil moisture releas e curve obtained from in-situ measurements for the fine sand at the Plant Science Research and Education Unit in Citra County.

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72 Figure 4.11. Plot of soil moisture release curve obtained from manual tensiometer readings and data obtained from nests of tensiometers and TDRs. Tension (cbar) 01020304050 Soil moisture (m3/m3) 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20 y = (a + x)/(b + cx) Where a = 13.0728 b = -42.5254 c = 23.6761 TDR vs Tensiometer Figure 4.12. Soil moisture rel ease curve and fitted model derived by ECH2O data and the calibration curve, corrected from nested tensiometer and TDR data.

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73 Having field calibrated the dielectric capaci tance probes mV output for the soil at PSREU, the grids of dielectric capacitance probe s outputs were plotted as soil moisture in 2 and 3D graphs. Figures 4.13 and 4.15 display the spatial distribution of average soil moisture for the 9 probe grids as positione d in Figure 4.2, in treatments I1 and I2 respectively. The average soil moisture wa s calculated over the period 14 48 DAP. Figures 4.14 and 4.16 show the standard deviations of the soil moisture in treatments I1 and I2 to display the temporal variability and how it changes across this portion of the root zones. Figure 4.13. Average soil moisture distributi on between two zucchini plants in a plastic mulched bed using soil moisture base d drip irrigation (threshold 475 mV). Figure 4.14. Variability of soil moisture with in the zone between two zucchini plants irrigated by soil moisture-based drip irrigation (threshold 475 mV) over a period of 5 weeks.

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74 Figure 4.15. Average soil moisture distributi on between too zucchini plants in a plastic mulched bed using soil moisture base d drip irrigation (threshold 525 mV) Figure 4.16. Variability of soil moisture with in the zone between two zucchini plants irrigated by soil moisture-based drip irrigation (threshold 525 mV) over a period of 5 weeks. The results from the complete spatial anal ysis of the soil moisture across the bed using the 33 dielectric capacitance probes that encompassed the entire root zone of a plant, is presented as soil moisture in Fi gure 4.17, and soil moisture variability in Figure 4.18.

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75 Figure 4.17. Average soil moisture distributi on for the root zone of a mature zucchini plant irrigated by soil moisture-bas ed scheduling (threshold 475 mV). Figure 4.18. Soil moisture variability for the root zone of a mature zucchini plant irrigated by soil moisture-based schedu ling (threshold 475 mV). Variability calculated as the standard deviation over 4-day period.

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76 Soil moisture tensions were calculated from the soil moisture release curve and plotted in Figure 4.19. Tensions greater than 50 cbar were left displa yed as such to avoid desensitizing the scale in low tensions. Furthermore, the soil moisture release curve was not calibrated for tensions greater than 50 cb ar as this was the maximum reading of the tensiometers. Figure 4.19. Average soil moisture tension for the root zone of a mature zucchini plant irrigated by soil moisture-based scheduling (threshold 475 mV). Soil moisture in the bed appears to be a function of distance away from the emitters and more generally the distance from the drip line. An average cross section of soil moisture was obtained by taking the average of all probes a parallel distance (y-value), and is presented in Figure 4.20.

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77 Distance from drip tape (m) -40-2002040 Soil moisture (m3/m3) 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 Average cross-section Soil moisture plot y = 1E-06x3 6E-05x20.0007x + 0.1232 Figure 4.20. Average cross-section profile of soil moisture across the bed with varying distance from drip tape for a mature zucchini crop on plastic mulched raised beds irrigated using soil moisture-based scheduling. Plants were positioned at cm from the drip line and spaced every 46cm. Discussion of results The results from this experiment have shown an inherent variability in soil moisture monitoring and the difficulties in pr oducing very consistent readings due to soil moisture holding heterogeneities and probe spacing for an in-situ field calibration. Results although containing variability do have the benefits of no repacking of the soil being conducted as in a laborat ory experiment. Other factors that may have played a part in variability of data were effective rain fall, salinity effects, blocked emitters, and incorrect probe readings.

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78Rainfall Rainfall did have an effect on some dielec tric capacitance probe readings, and soil moisture spikes were noted during rainfall event periods. This was evident in Figure 4.21, where some probes experienced spikes in soil moisture during rainfall periods and others did not. The probes that had a highe r incidence of effectiv e rainfall were those near the periphery of the bed, away from the cover of the plant biomass. This was however not a clear trend. Figure 4.21. Soil moisture time series show ing how soil moisture spikes during rainfall events are limited to probes on exterior of bed that are not significantly influenced by irrigation The cause of rainfall affecting some probe s and not others may have been cover for some probes from the plant canopy, or random ponding on the plastic mulch. Figure 4.21 shows how the outer probes (E1, E2 and E3 ) all spike during rainfall events, but not during normal irrigation events. The effect of rainfall on soil moisture readings is limited 0 0.05 0.1 0.15 0.2 0.25 0.3 11/19/200511/21/200511/23/200511/25/200511/27/200511/29/2005 DateSoil moisture I2 E1 I2 E2 I2 E3 I2 E4 I2 E5 I2 E6 I2 E7 I2 E8 I2 E950 40 30 20 10 0 Rainfall (mm)

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79 more to probes on the exterior of the be d, and is still somewhat random if ponding occurs. Temperature Documentation posted Campbell (2005c) for Decagon Devices Inc. the manufacturers of the ECH2O (dielectric capac itance) probe, suggest s that the probes mV out put, and thus soil moisture readings is affected by temperature fluxes. The magnitude of the temperature effect is related to soil mois ture content of the soil and is the largest at approximately 10 to 15% soil moisture, the range that is targeted for soil moisture-based irrigation. The maximum temperature eff ects of an experiment conducted by Campbell (2005) for a sandy loam soil were 0.2 % C-1 for a temperature range of 10 to 40 C. In field conditions the soil matrix has a mediati ng effect on temperature with depth. Diurnal temperature fluxes are lagged and reduced with depth. Thermocouples were installed just under the surface of the plastic mulched bed to determine the range of temperature fluxes and to help determine if temperature had a significant impact on soil moisture as generated by the dielectric capacitance probe. Figure 4.22 shows the temperatures recorded from three replicates of thermocoupl es each in a different bed. Temperature variations within the surface soil of the be ds were on average between the mid twenties and mid teens in degrees Celsius. A period of cooling was observed towards the end of the season as winter approached. The diurna l temperature flux of measured by the probes buried just under the surface had little affect on soil moisture readings. This was deduced by the lack of oscillation in the probes th at were positioned far enough away from the drip line and received very little irrigation water (Figure 4.23, probes I1-E2, E2 and E3). An oscillation is observed in I1-E2, but wa s most likely due to both temperature fluxes and water from irrigation events.

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80 Figure 4.22. Temperature fluxes within three plastic mulched beds in the fall season of 2005. Thermocouples were buried appr oximately 15 mm beneath the surface. The arrow in Figure 4.23 shows the increase in apparent soil moisture that could have been from temperature changes as it warm ed up in the morning. This increase in soil moisture occurs before 9:00 am, the occurrence of an irrigation event. The other probes show only a very small increase dur ing the warm period in the day. The maximum deviation from mean soil moisture fo r I1-E2 if only temperature changes were considered, was only 0.35%. Taking the potential for irrigation events to be contributing towards the increase, actual temperature effects on soil moisture are most likely lower. From these results, and the general spread of soil moisture readi ngs using dielectric sensing within a soil medium, the deduction is made that the probes buried vertically in the top 22 cm of soil are not significantly affected by norma l diurnal fluxes in temperature. 10 12 14 16 18 20 22 24 26 28 30 25-Oct-0530-Oct-0504-Nov-0509-Nov-0514-No v-0519-Nov-0524-Nov-0529-Nov-0504-Dec-05 DateDegrees C Temp I1 Temp I2 Temp I3

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81 0 0.05 0.1 0.15 0.2 0.25 0.3 11/12/0511/12/0511/13/0511/13/0511/14/0511/14/0511/15/0511/15/0511/16/05 DateSoil moisture I1-E1 I1-E2 I1-E3 I1-E4 I1-E5 I1-E6 I1-E7 I1-E8 I1-E9 Irrigation events Figure 4.23. Time series of soil moisture in bed I1 to show limited effects of temperature on outer probes that receive little irrigation water. Salinity Figures 4.25,4.26 and 4.27 show that soil moistures determined by applying the linear calibration to the ECH2O probe output have considerab le spikes that correspond with the days that fertigation occurred. Th ese considerable spikes are not simulated in the soil moisture data determined by TDR m easures. Different factors that could have caused these spikes in soil moisture as determined by the dielectric capacitance probes were examined. Rainfall only had a limited eff ect in probes that were not covered by the crop canopy, and the rainfall did not occur on a weekly cycle as th e spikes in soil moisture did. Temperature, a possible r eason for deviation of dielectric capacitance probe output showed to cause less than a 0, 35% change in soil moisture. Furthermore fluxes in temperatures were on a diurnal cycl e, and not a weekly effect. The third and

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82 possible external factor that may have cause d spikes in soil moisture as read by the dielectric capacitance probes was salinity effect s. The spikes in mV were highest just after feritigation events, when both water and fe rtilizer were introduced to the soil. From the 20-minute duration of fertigation ev ents, the system should have applied approximately 0.67 mm of water to the soil. For the 20cm depth that the probes averages the soil moisture over, this should result in only a 3.4% increase in soil moisture. Corresponding increases in the soil moisture readings by TDR during the fertigation events were only a few percent (Figures 4.25, 4.26 and 4.27). TDR data is assumed to be sufficiently accurate to compare the dielectric capacitance data against, as TDR readings are generally considered immune to salinity unless the salinity is so server that it masks the peak-to-peak frequency in the signal. The dielectric cap acitance probes close to the fertigation line for treatments I1 and I2 showed increases of up to 15% in soil moisture (Figures 4.25 and 4.26). Considering the negl igible effects that al l other likely factors mentioned had on dielectric capacitance probes output, it is proposed that high salinity after fertigation events is causing an incr ease in soil electrical conductivity, which is possibly transferred into a hi gher bulk conductivity and thus mV readings measured by the dielectric capacitance probes. A 12% highe r reading in soil moisture by the dielectric capacitance probes than the TDR readings woul d equate to an over reading of 170 mV by the dielectric capacitance. Campbell (2005c) showed an increase of up to 400 mV in dielectric capacitance readings for sa ndy soils at salinities of 12.9mmho.cm-1. Irrigation scheduling treatment I3 had soil moisture r eadings calculated from ECH2O mV output, that deviated the most from soil moistures measured by TDR. This treatment also underapplied water for the season when compared to treatment I2 (Figure 4.24).

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83 Figure 4.24. Water applications for the three soil moisture-based drip irrigation treatments I1 (9.5%), I2 (12.5%) and I3 (12.5% and buried drip) on a plastic mulched zucchini crop. Soil moisture determined from TDR 0 0.05 0.1 0.15 0.2 0.25 0.330-Oct-0507-Nov-0515-Nov-0523-Nov-05Soil moisture (m^3/m^3) TDR 51 TDR 52 Soil Moisture determined from ECH2O probes0 0.05 0.1 0.15 0.2 0.25 0.330-Oct-0507-Nov-0515-Nov-0523-Nov-05 I1-E4 I1-E5 I1-E6 I1-E7 I1-E8 I1-E9 Figure 4.25. Soil moisture time series s howing soil moisture determined by TDR and calculated by dielectric capacitanc e for soil moisture treatment I1.

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84 Soil moisture determined from TDR 0.05 0.1 0.15 0.2 0.25 0.3 0.3530-Oct-0507-Nov-0515-Nov-0523-Nov-05Soil moisture (m^3/m^3) TDR 54 TDR 55 TDR 56 Soil moisture determined from ECH2O probe0.05 0.1 0.15 0.2 0.25 0.3 0.3530-Oct-0507-Nov-0515-Nov-0523-Nov-05 I2 E4 I2 E5 I2 E6 I2 E7 I2 E8 I2 E9 Figure 4.26. Soil moisture time series s howing soil moisture determined by TDR and calculated by dielectric capacitanc e for soil moisture treatment I2. Soil moisture determined from TDR0 0.05 0.1 0.15 0.2 0.25 0.330-Oct-0507-Nov-0515-Nov-0523-Nov-05Soil moisture TDR I3 TDR I3 Soil moisture determined from ECH2O probes0 0.05 0.1 0.15 0.2 0.25 0.330-Oct-057-Nov-0515-Nov-0523-Nov-051-Dec-05 I3 E4 I3 E5 I3 E6 I3 E7 I3 E8 I3 E9 Figure 4.27. Soil moisture time series s howing soil moisture determined by TDR and calculated by dielectric capacitance for soil moisture treatment I3, which had its irrigation line buried 15cm below the surface and the fertigation line.

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85 If salinity was affecting mV readings, th en this could go some way in explaining the under application of water by the treatment. The probe would be recording mV and thus soil moisture readings higher than actual conditions and the mV threshold, and irrigation events would be bypassed. Salin ity readings and effects are however not quantified Spatial distribution trends The different spatial distributions of soil moisture showed that soil moisture corresponded to emitter and plant position, but mostly was a function of distance from the drip line. The curve fitted in Figure 4.20 suggests that the highest soil moisture occurred near or at the drip line and that th e lowest soil moisture occurred on the exterior of the plant side of the bed. This initially seems intuitive, as one would expect the plant to use up the available water and reduce the soil moisture on this side. The variability of soil moisture readings was greatest near the emitters and also higher on the plant side of the drip line (Figures, 4.14, 4.16 and 4.18). This is possibly due to the higher refilling and consumption by the plant roots cycl e in this region of the bed. The distributions of soil moisture show ed a fairly consistent band of high soil moisture up to 10 cm on either side of the dr ip line, with highest values occurring near the emitters. Variability in soil moisture s howed a greater relation to emitter position and plant position, than just distan ce to the drip line as soil moistu re did. This is evident in Figures 4.12, 4.14, and 4.18. To aid in the decision on probe placement and set point, the soil moisture release curve and tensiometric distributions need to be considered. Due to the particle distribution and hydrophobic nature of the sands, the soil moisture release curve has a large change in slope between 12% and 8% soil moisture. For soil moistures below 8% a small reduction in soil moisture can have a very large increase in soil

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86 moisture tension. This is not conducive to optimal plant growth a nd these ranges of soil moisture should be carefully avoided. This is evident in Figure 4.19, where the soil moisture tension distributi on increases dramatically beyond 20 cbar (approximately 15 cm either side of the drip line). Conclusions The dielectric capacitance probe was calibra ted for the soil (fine sand) at the Plant Science Research and Education Unit, as the probe needed site-specific calibration due to the high sand content. The calibration yielde d a linear relationship between soil moisture and probe mV output, similar to that published for most soils by the probe manufacturers. From this curve and tensiometric readings, a site-specific soil moistu re release curve was derived for the fine sand. The soil moisture release curve will help determine the plant water stress that a crop may experience for par ticular soil moisture set points. This is critical for optimal growth of the crop and ensuring that water is not a limiting factor while achieving water application savi ngs and reducing nutrient leaching. Soil moisture within the plastic mulched be d is dependant on distance from the drip line and emitters and to a much lesser extent distance from the plant. The average soil moisture at a point in the bed can be estim ated by a third order polynomial that is a function of distance from the drip line. The curve is almost parabolic and skewed slightly, possibly due to plant position within the bed. Soil moisture within the bed was lowest on the outer side of the plants. Soil mo isture variability was highest near the drip emitters and lower towards the outer edges of the bed, where soil moisture use and recharge by irrigation was almo st neglegible. External factors such as rainfall and temperature can have an effect on soil mois ture readings. Rainfall generally did not contribute substantially to soil moisture re adings, but during signi ficant rainfall events,

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87 probes that were on the exterior of the bed and not protected by the crop canopy did record increases of soil moisture up to 10% fo r large events. The trends were not clear, and the effects of rainfall were random, and did not contribute to probe readings in the center of the bed where probes should be posit ioned for soil moisture-based irrigation. The dielectric capacitance probes are affected by temperature variations, but the soil has a mediating effect on diurnal temperature fluxes and very little change in soil moisture (less than 0.35%) is experienced when the prob e is buried vertically in the top 22 cm of the plastic mulched bed, for normal ranges of temperature in a growing season. As such with good sealing for the probe in the plastic mulch, rainfall and temperature effects on probe readings of soil moisture should be negligible. Soil moistures determined by applying the linear calibration equation to di electric capacitance probe mV output had significant spikes corresponding to fertigation ev ents that were not replicated in the TDR measured soil moisture. The significant spikes in the dielectric capacitance data were not caused by rainfall or temperature affecting the mV output. It is proposed that the fertilizers added during fertigation events are increasing soil electrical conductivity, and increasing the dielectric capacitance probe s bulk conductivity reading and thus mV output. If this is the case, then the dielectr ic capacitance probe needs to be calibrated for higher salinity levels in sandy soils. From this in field calibration and soil moisture spatial distribution study, it has been shown that soil moisture measurements have inherent variability and good understanding of the factors affecting soil moisture within a plastic mulched bed on sandy soils is needed to reliably schedule irrigation with soil moisture probes. Soil moisture distributions show soil moisture profiles that correlate with proximity to the drip line and

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88 emitters. Further studies should address the potential problems of high salinity effects and the potential for integrating multiple probes into the systems operation.

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90 CHAPTER 5 SUMMARY AND CONCLUSIONS In the interest of promoting sustainability in agriculture the University of Florida has developed a methodology of irrigation scheduling and a low cost technology to implement the methodology. The technology has been tested on various locations, seasons, soils and crops for its ability to be su ccessfully applied to a wide range vegetable production. The system was applied to two plastic mu lched tomato crops. The first experiment was conducted in the winter, in South Florid a, on a gravelly loam soil. The second experiment was in North Central Florida, on fine sand in the spring of 2005. Both experiment results showed significant water application savings of between 50 and 82% can be achieved with the soil moisture-based irrigation scheduling compared to traditional local grower practices that applie d larger amounts of water less frequently. For both experiments, soil moisture-based sche duling yields were equa l to or above local grower treatments, and this achieved irrigati on water use efficiencies (IWUE) of between 216 and 415% greater. These reductions in wa ter application are very significant for many places in the world. In dry areas with water shortages, these high IWUEs can allow a grower to irrigate a larger area with the same water supply. Water savings can also be very beneficial wher e water laws require expensive licenses to access resources. In regions were power costs are high, lower water application combined with a well tank, if feasible, can significantly reduce pumping costs and improve profit margins. Plastic mulched beds combined with drip irrigation have significantly reduced disease incidence

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91 by separating the fruit from the soil. Keeping the soil at optimal levels for plant growth and avoiding over watering further helps reduce the changes for disease. In some cases this was one of the reasons for the higher yiel ds with the soil moisture-based scheduling compared to the traditional time based scheduling. The incidence of disease had more effect on yield for the wetter treatments. This may become a bigger factor as the consumer market is becoming more aware of th e use of chemicals to control diseases. In Florida, water savings are al so important in regions like South Florida. But, most importantly the application of less water and the precision level of soil moisture control have significant benefits fo r soil nutrient management. Florida is a unique region. Nitrogen is typically the most important nutrient in terms of limitations to growth and contaminati on to water resources in most places in the world. Florida not only has nitrogen issues, but also and to an even greater extent, phosphorous has become a major source for envi ronmental imbalance and is the focus of much work and restorative efforts. Alt hough most of the excess phosphorous has been introduced to the everglades system by the drainage of wetlands on exposure of the soil to oxidation, agriculture has also contributed to water resource loading. The soil moisture based-irrigation scheduling reduced total season loading of dissolved and total phosphorous from plastic mulched tomatoes by between 65 and 71%. Higher reductions (70-79%) were achieved during only the treatme nt period. From both experiments, the reductions in nitrogen loading to local wate r resources were between 55 and 90% for both nitrate and ammonia forms of nitrogen. Again reductions were higher if the establishment period was excluded (70%). Th ese reductions in nutrient leaching were primarily driven by reductions in volumes of water passing through the root zone. The total volume of leachate captured below the r oot zone in lysimeters was between 68 and

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92 78% lower for the soil moisture-based treatments compared to the traditional time based treatments. Between 73 and 85% less leaching by volume occurred during the treatment period. One soil moisture-based irrigation tr eatment had its irrigati on drip line buried 15 cm below the surface where its fertigation lin e was located. Water being applied below the fertilizer application furthe r reduced the concentration of nutrients in the leachate, and thus over all nutrient loading. Along with the reductions in nutrient lo ading, the system presents nutrient management possibilities. Fertigation events can be automated which means less labor requirements and precision nutri ent applications to the cr op. Different levels of automation and different frequencies of fer tilizer application thr ough fertigation were tested, namely; manual injection once a w eek using a peristaltic pump, automated injection twice a week using a venturi inject or controlled by the irrigation timer, and continuous injection using a vent uri injector that is driven by irrigation. Each method has its pro and cons. The manual injection wh ile being precise, required more labor and higher capital layout for the pump. Extra labor was needed for both connection and operation of the injection pump, and for meas uring out and dissolvi ng the fertilizer (if dry) into solution. The con tinuous injection method required virtually no labor to operate and a pre-dissolved or liquid solution of fe rtilizer was injected during each irrigation event. This system required knowledge of the seasons water applicati on so as to set the concentration level in the tank from which injection takes place. For a time-based schedule this is simple. For soil moisture-bas ed scheduling a more em pirical approach is needed. Water requirements for the crop are dynamic and related to climatic conditions and other growth factors. Previous experi ments water applications using soil moisturebased irrigation scheduling, were used as an estimate for water use for the coming season.

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93 Crop type, season, location and soil moistu re thresholds were also taken into consideration. Fertilizer solution was thus ca lculated on the predicte d water applications. This was done for two experiments. The fi rst experiments water application was very close to the predicted amount and fertilizer application was similar to that intended for the crop. The second experiment however had lower than expected water applications for most of the season, partial due to cold er than expected weather and reduced evapotranspiration, and partially due to some incidence of disease. The fertilizer application was thus lower than suggested a nd crop yield was slightly reduced. The same could happen in reverse effect a nd there could be an over applic ation of fertilizer if more water than expected is app lied. The third method of automated fertigation was not dependant on irrigation, but re tained its low labor benefits. At the cost 2 extra solenoid valves, the system can be controlled by the i rrigation timer on a separate schedule to the irrigation. The injection is via a venturi injector and the fertili zer solution is still stored in a tank to overcome the need to premix or meas ure out liquid fertilizer before each event. Other benefits are that the system can r un for a few minutes after the injection has stopped to flush the line, and the fertigation frequency can also be user set. Optimal fertigation frequency depends on th e fertilizer used and the soil type. Other research has found that higher frequencies are needed on sandy or coarse soils with low nutrient holding capacity. For the two experiments conducted no increases in yield or growth were found for the continuous or twice a week fertigation ove r the weekly manual events. It can be concluded that no be nefits for fertigation frequenc ies below a week are achieved on the sandy soils tested. The automated inde pendent fertilizer injection system is the most recommended for the reasons above men tioned. Some considerations that may cause a need for deviations from this system are, operating pressure and area fertigated.

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94 The venturi operates best when placed over a pressure differential creating device (pressure regulator, booster pump etc.). If th is is a drop in pressure, then the operating pressure of the pump will need to be higher to compensate for the drop and still deliver enough pressure for the drip lines to opera te. This may increase pumping costs and distribution pipe classes. The magnitude of this effect will depend on the area irrigated. A large area may also require fe rtilizer injection rates that are too large for the available commercial injectors and operating pressures that are very high. In this circumstance, an injection pump would be more pr actical. Filtration is also im perative for the life of the system, and this is particularly important when fertilizers are being stored in a tank. Care must be taken to purchase liquid fertilizer or fertilizers that remain in solution and do not form precipitates. The soil moisture-based irrigation has potenti al to save water nu trients and labor as mentioned above. All of these benefits and th e successful performance of the system rely on the data being provided by the soil moisture sensor in the field that drives the scheduling. If the probe reading is below act ual soil moisture levels the system will overirrigate and water savings will be minimal. This would eliminate any water, pumping, nutrient saving, and environmental benefits that the system possesses. A lower than real soil moisture reading is however the less detrimen tal error. If the probe reading is higher than actual soil moisture, less water is supplie d by the system, as the soil appears to be sufficiently wet for good plant growth. Errors of this nature can cau se yield loss. The system relies on a sufficiently accurate and reliable soil moisture probe to make automated irrigation scheduling decisions. Th e accuracy of the readings obtained from the probe depend on a number of factors, all of which need to be addressed to ensure that the probe works reliably. Such factors are; soil type, crop, irrigation system, salinity,

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95 probe placement, cost and probe type. The EC H2O dielectric probes that has been tested are well suited to coarse soils as it responds quickly to fast changes in soil moisture, are suitable for most crops and irrigation systems as it can be buried at the required root depth and averages the soil moisture read ing over its 20 cm length, are low cost compared to other dielectric probes, and can achieve accurate results for most soils without calibration. The probe however does need calibration fo r sandy soils, and for soils with high salinity. A ca libration was thus carried out for the sandy soils at PSREU where regular research is conducted on the so il moisture-based ir rigation system. The calibration was an in-situ calib ration during a fall cropping season of zucchinis on plastic mulched beds. Nesting tensiometeric, and TDR probes together with the ECH2O probes gave simultaneous readings from which a lin ear soil moisture versus ECH2O probe mV output was derived and a soil moisture release curve generated. Th e linear curve derived for the ECH2O probe was SM = 0.0006*mV 0.1901 This is similar to the general curve th at Decagon Devices In c. (makers of the ECH2O) provide for most soils. The 95% confidence intervals we re also provided to give an idea of the heterogeneity of the soil and probe dynamic. The probe is sensitive to temperature and if temperature ranges are large and the probe is buried at or near the surface, no r eal-time correction for th e readings by the QIC is currently available. From this study, it appe ared that if the probe is buried vertically in the top 20 cm of the soil in the plastic mulc hed bed, that temperat ure did not have any significant effect. No diurnal flux in soil mois ture readings were measured greater than 0.35%. This was for a difference in maximu m and minimum temperature differential of 15 degrees Celsius. Temperature differences much larger than this are not common

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96 during the production of vegetable crops, and at a 0.35% error in actual soil moisture reading as a result of temperature is negligib le when compared to the general variability inherent in soil moisture sensi ng using dielectric probes. High salinity levels possibly had an aff ect on the mV output of the ECH2O probe, and this was noticed as a weekly spike in readings of probes within 8 cm of the fertigation line emitters just after fertigation events. Burying the irrigation drip line at 15 cm, and keeping the fertigation line at the surface potentially exacerbated the salinity effect. The probe was not calibrated for high salinity, and this is recommended for future work in this field. The linear mV curve wa s derived from data from beds that had both drip lines at the surface and a period without a fertigation ev ent was chosen to eliminate salinity effects. Grids of probes were placed within the plastic mulched beds to improve knowledge of soil moisture distributions and its dynami cs in the active root zone of a crop under irrigation. The previous two seasons experi ments suggested a high variability in soil moisture across within a small spatial extent fo r the coarse soils tested. This agrees with the knowledge we have of very vertical wet ting bulbs from drip emitters on coarse soils and the low lateral movement of water. Results show that soil moisture is primarily a function of distance from the drip line. Em itters were sufficiently close enough together such that readings of soil moisture parallel to the drip line were fairly consistent for a point in time. Over time however the variabil ity of soil moisture readings was greatest in probes positioned close to the emitters of the drip line, due to spikes in soil moisture at irrigation events. This variability in soil mo isture within the root zone should be taken into consideration when choosing a position for the soil moisture-based scheduling probe. Good probe position and set point can be determined from the 3rd order polynomial that

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97 describes soil moisture according to distan ce from the drip line, and soil moisture variability. Soil moisture based irrigation has proven to have high potential for water and nutrient management. As resources become scarcer this methodology of irrigation could become more and more vital for the survival of both growers, and the environment. For the system to operate reliably and on a wide range of conditions, good knowledge of the soil, probe and crop water requirements are essen tial. Further studies of issues that have been highlighted are summarized here: 1. Integrating multiple probes into the QIC so that soil moisture readings are from two or more positions within the root zones of more than one plant. Multiple probe readings could be averaged or a medi an could be used to obtain a more representative measure of soil moisture within the bed, and reduce the potential for negative impacts of inherently heterogeneity in soils. 2. Test different methods of scheduling wate r to the transplant during the first two weeks of establishment. How is the soil moisture based irrigation system going to be applied to the small transplant with limited root systems? Can thresholds be changed to account for the limited root system? Can more water savings be achieved in this period? 3. Test different crops, different micro irrigation systems, a nd different soils to get an indication of the systems application to a wide spread of conditions. 4. Calibrate the ECH2O probes response to salinity levels in sandy soils. 5. Measure temperature fluxes and corresponding probe readings at different depths and moisture contents, to evaluate the tr ue impact temperature fluxes can have on the ECH2O probe. 6. Market, promote and continue the syst em research as a methodology and not a brand specific technology. Future succe ss of the system requires the use of soil suitable probes, and good extension serv ices to promote understanding of the systems operation to growers.

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99 APPENDIX A FERTIGATION FOR SOIL MO ISTURE-BASED IRRIGATION This appendix contains materials relating to Chapter 3. Presented within are figures of suitable methods of creating a pre ssure differential across a venturi injector, a Mazzei venturi injector performance table for op erating pressures in the range suitable to high value crop prodction, figures of the hardwa re for soil moisture based irrigation and a procedure for estimating water use for a plas tic mulched soil moisture based irrigated crop. Figure A.1. Bypass venturi assembly for fertig ation using either a pressure regulator or a control valve.

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100 Figure A.2. Bypass assembly with a booste r pump for venturi injection fertigation. Figure A.3. Bypass assembly with venturi in jector installed across an irrigation pump.

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101 Table A.1. Mazzei injectors performance tabl es (Mazzei Injector Corp., Bakersfield, CA).

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102 Figure A.4. Automated soil moisture-based irrigation scheduling ha rdware developed by the University of Florida including soil moisture probe, QIC interface, and solenoid valve. Table A.2. Example of irrigation timer (RainBird ESP-12LX) setup for decoupled continuous fertigation and soil moisture-based irrigation for the setup displayed in Figure 3. The management of continuous fertiga tion for the Demonstration plot of Experiment 1 was demanding as it was coupl ed with soil moisture-based irrigation scheduling. Fertilizer was continuous injected into the irrigation distribution system Program AProgram BProgram CProgram D Cyclenot usednot usedEverydayEveryday Start times8:0010:00 12:00 14:00 16:00 StationDescription 1Solenoid 1 (soil moisture probe and QIC)14 min(max possible) 2Solenoid 2 and 3 (fertigation)week 0-2: 6 min week 2-4: 9 min week 5-11: 12 min week 12: 9 min week 13: 6 min

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103 every time irrigation occurred. The fertilizer applied was thus driven by the irrigation. The complexity comes from the dynamic nature of soil moisture-based irrigation scheduling which depends on the soil moisture characteristics of the soil, and the crop evapotranspiration, which is driven by clim atic conditions and crop growth stage. The irrigation schedule will vary from season to season when using soil moisture as the basis for scheduling. An estimate was needed to predict the water use for the crop over the season. Crop evapotranspiration (ETc ) is the IFAS recommended method for determining water use. Previous experi ments on tomatoes by Munoz-Carpena et al. (2004) and (2005) reported consistent savings for two consecutive experiments in the Miami-Dade County on tomatoes with the QIC and dielectric probe soil moisture-based scheduling over the ETc schedule. The savi ngs were 51% and 58% for two experiments conducted during the winter seasons on Krome so il. Both these savi ngs were recorded for soil moisture tension thresholds of 15c bar. The threshold being employed on the proposed experiment was 25 cbar and the hi gher value was likely to further increase savings. The savings expected for the 25 cb ar threshold were t hus taken as 60%. Although the total season water use expected was 60% lower, water use should still follow the crop growth curve with low water re quirements early in the season and higher requirements once the crop is mature. The e xpected water use was thus determined by reducing the ETc daily amount, which follows cr op growth, by 60%. This can be seen in Figure A.5.

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104 Figure A.5. Cumulative water use for ETc and the estimate for soil moisture-based scheduling using the QIC and dielectric probe set to 25 cbar soil moisture tension. Knowing the injection rate of the venturi injector form the calibration, and having an estimate of water application, the concen tration of fertilizer can be calculated to achieve the IFAS recommended fert ilizer rates. The dilution of 4-0-8 liquid fertilizer was adjusted until the fertilizer applied by injec tion with the irrigation water (estimated 40% of ETc) equaled the desired IFAS rate. This was done on a daily time step. The resultant dilution ratios are plotted in Figure A.6. Graph of Cumulative Water Use estimate for soil moisture-based scheduling obtained from 40% ETc0 20 40 60 80 100 120 140 160 180 200 020406080100120Day in seasonWater Use (mm) 100% ETc soil moisture scheduling estimate(40% ETc)

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105 Figure A.6. Required 4-0-8 liquid fertilizer dilution to achieve IFAS rates when driven by estimated soil moisture-based water application. The fluctuations of the desired dilution rati o are a result of the step-wise properties of the functions (ETo and Kc) that were used to determine the water use estimate. Actual ETc and Kc values shown gradual changes that are governed by climatic factors. Where the required rate fluctuated w ithout consistent trend, an average dilution ratio was chosen. This reduced the rigors of changing the diluti on of the fertilizer in the storage tank and helped with management of the system. This can be seen in Figure A.7. Graph of Required Fertilizer Concentration to achieve IFAS rates0.000 0.020 0.040 0.060 0.080 0.100 0.120 0.140 0.160 0.180 0.200 020406080100120Days after TransplantFertilizer concentration (ratio) Required concentration Actual concentration

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106 Figure A.7. Step-wise estimated evapotranspi ration functions vs. likel y actual functions.

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107 APPENDIX B SOIL MOISTURE DISTRIBUTIONS WITHIN A PLASTIC MULCHED BED The material presented in this appe ndix supports the conetent and message presented in Chapter 4. Figure B.1. Probe layout and numbering, used to determine soil moisture distribution within the root zone of a mature zucch ini plant grown in plastic mulched beds.

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108 Figure B.2. ECH2O probes placed next to drip line, mV output. Figure B.3. ECH2O probes placed perpendicu lar to drip tape to drip, line mV output. Probes along drip tape length (Y=0)400 450 500 550 600 650 700 750 08-Dec-0609-Dec-0610-Dec-0611-Dec-0612-Dec-0613-Dec-0614-Dec-06mV 13 27 28 8 18 26 3 23 Probes perpendicular to drip tape (X=0)300 350 400 450 500 550 600 650 08-Dec-0609-Dec-0610-Dec-0611-Dec-0612-Dec-0613-Dec-0614-Dec-06mV 13 32 31 12 14 30 11 15

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109 Figure B.4. ECH2O probes parallel to and 30 cm from the drip line, mV output. Figure B.5. ECH2O probes parallel to and 15 cm from the drip line, mV output. Probes parrallel to drip tape (Y=15)0 100 200 300 400 500 600 700 08-Dec-0609-Dec-0610-Dec-0611-Dec-0612-Dec-0613-Dec-0614-Dec-06mV 2 7 12 17 22 Probes parrallel to drip tape (Y=30)0 100 200 300 400 500 600 700 08-Dec-0609-Dec-0610-Dec-0611-Dec-0612-Dec-0613-Dec-0614-Dec-06mV 1 6 11 16 21

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110 Figure B.6. ECH2O probes parallel to a nd cm from the drip line, mV output. Figure B.7. ECH2O probes parallel to a nd cm from the drip line, mV output. Probes parrallel to drip tape (Y=-15)300 350 400 450 500 550 600 650 08-Dec-0609-Dec-0610-Dec-0611-Dec-0612-Dec-0613-Dec-0614-Dec-06mV 4 9 14 19 24 Probes parrallel to drip tape (Y=-30)0 100 200 300 400 500 600 08-Dec-0609-Dec-0610-Dec-0611-Dec-0612-Dec-0613-Dec-0614-Dec-06mV 5 10 15 20 25

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111 Figure B.8. ECH2O probes perpendicular to and 30 cm from the drip line, mV output. Figure B.9. ECH2O probes perpendicular to and 15 cm from the drip line, mV output. Probes perpendicular to drip tape (X=30)0 100 200 300 400 500 600 700 800 08-Dec-0609-Dec-0610-Dec-0611-Dec-0612-Dec-0613-Dec-0614-Dec-06mV 1 2 3 4 5 Probes perpedicular to drip tape (X=15)300 350 400 450 500 550 600 650 08-Dec-0609-Dec-0610-Dec-0611-Dec-0612-Dec-0613-Dec-0614-Dec-06mV 6 7 8 10 9

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112 Figure B.10. ECH2O probes perpendicular to and 15 cm from the drip line, mV output. Probes perdindiculaer to drip tape (X=-15)0 100 200 300 400 500 600 700 08-Dec-0609-Dec-0610-Dec-0611-Dec-0612-Dec-0613-Dec-0614-Dec-06mV 17 18 19 16 20

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113 LIST OF REFERENCES Anonymous. 2005. ECH2O probe manual, Version 1.2. Decagon Devices Inc., Pullman, WA. Download literature, ECH2O products, manuals. http://www.ech2o.com/SupportDocumentation.htm last accessed 03/01/06. Bauters, T.W.J., D.A. DiCarlo, T.S. Steenhuis, and J.Y. Parl ange. 1998. Preferential Flow in Water Repellent Sands. Soil Scie nce Society of America Journal 62 (5): 1185-1190. Campbell, C.S. 2005a. Calibrating the ECH2O probes. Decagon Devices Inc., Pullman, WA. Download literature, ECH2O products, technical papers. http://www.ech2o.com/SupportDocumentation.htm lasted accessed 02/01/06. Campbell, C.S. 2005b. Response of the ECH2O soil moisture probe to variations in water content, soil type and solution el ectrical conductivity. Decagon Devices Inc., Pullman, WA. Download literature, ECH2O products, technical papers. http://www.ech2o.com/SupportDocumentation.htm last accessed 02/27/06. Campbell, C.S. 2005c. Response of ECH2O soil moisture sensor to temperature variations. Decagon Devices Inc., Pullm an, WA. Download literature, ECH2O products, technical papers. http://www.ech2o.com/SupportDocumentation.htm last accessed 02/26/06. Clark, G.A., C.D. Stanley, and D.N. Mayna rd. 1994. Tensiometer control vs. tomato crop coefficients for irrigation scheduli ng. ASAE Paper No. 94-2118. Amer. Soc. Agr. Eng., St. Joseph, Mich. Clark, G.A., D.N. Maynard, C.D. Stanley, G.J. Hochmuth, E.A. Hanlon, and D.Z. Haman. 1990. Irrigation scheduling and ma nagement of microirrigated tomatoes. Fla. Coop. Ext. Serv. IFAS. University of Florida. Circ. 872. Cook, W.P. and D.C. Sanders. 1991. Nirtoge n application frequency for drip-irrigated tomatoes. Hortscience 26 (3): 250-252. Amer Soc Horticultural Science. Dukes, M.D. and R. Muoz-Carpena. 2005. So il water sensor based automatic irrigation of vegetable crops. In: S. W. Trimble, B.A. Stewart and T.A. Howell (eds). Encyclopedia of water science. Ma rcel-Dekker, Inc : New York. Dukes, M.D., E.H. Simonne, W.E. Davis, D.W. Studstill, and R. Hochmuth. 2003. Effect of sensor-based high frequency irrigation on bell pepper yield and water use, P. 665-674. In: Proc. 2nd Int. Conf. Irr. And Drainage, 12-15 May, Phoenix, Ariz.

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114 Fares A. and AK. Alva. 2000. Evaluation of capacitance probes for optimal irrigation of citrus through soil moisture monitoring in an entisol profile. Irrigation Science 19 (2): 57-64 Jan 2000. Florida Agricultural Statistics Service. 1995. Vegetable chemical use. 8pp. Fla. Agric. Stat. Serv., Orlando, FL. Haddadin, S. H. and I. Ghawi. 1983. Effect of plastic mulches on soil water conservation and soil temperature in field grown tomato in the Jordan Valley. Dirasat 13(8): 2534. Hartz, T.K., and G.J. Hochmuth. 1996. Fertilit y management of drip-irrigated vegetables. UC Davis. Vegetable Research and Information Center. Hebbar, S.S., B.K. Ramachandrappa, H.V. Na njappa, and M. Probhakar. 2004. Studies on NPK drip fertigated field grown tomato. Europ. J. Agronomy 21: 117-127. Herdel, K., P. Schmidt, R. Feil, A. Muhr, and U. Schurr. 2001.Dynamics in the concentrations and nutrient fluxes in the xylem of Ricinus communis-diurnal course, impact of nutrient av ailability and nutrient uptake. Plant, Cell and Env., 24:41-52. Hochmuth G.J. 2000. Management of nut rients in vegetable production systems in Florida. Soil and crop science society of Florida proceedings 59:11-13. Soil Crop Science Florida. Hochmuth, G.J., and A.G. Smajstrla. 1998. Fe rtilizer application and management for micro (drip)-irrigated vegetables in Florid a. Fla. Coop. Ext. Serv. IFAS. University of Florida. Circ. 1181. Hochmuth, G.J., and E.A. Hanlon. 1995. IFAS Standardized fertilizer recommendations for vegetable crops. Fla. Coop. Ext. Serv. IFAS. University of Florida. Circ. 1152. Hoppula, K.I. and T.J. Salo. 2005. Tens iometer-based irrigation scheduling with different fertilizer methods in blackcu rrant cultivation. ACTA Agriculturae Scandinavica, Section B-Soil and Pl ant Science 55(3):229-235 Sep 2005. Howel, T. 2002. New ideas for improving irrigation water use efficiency. USDA Research Project Meeting: Irrigation methods, technology and management for increased water use efficiency. http://www.ars.usda.gov/research/pub lications/Publicati ons.htm?seq_no_115=1329 22 last accessed 07/04/06. Kukal, S.S, G.S. Hira, and A.S. Sidhu. 2005. Soil matric potential-based irrigation scheduling to rice (Oryza Sativa). Irri. Science 23( 4):153-159. Kutilek, M. and D.R. Nielsen. 1994. Soil hydrology. Catena Verlag, CremligenDestedt, Germany. Pp. 75-76.

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115 Li, Y.C., Bryan, H.H., Klassen, W., La mberts, M., and T. Olczyk. 2002. Tomato Production in Miami-Dade County, Florida. Fla. Coop. Ext. Serv. IFAS. University of Florida. Circ. HS858. Locascio, S.J., G.J. Hochmuth, S.M. Olson, R.C. Hochmuth, A.A. Csizinsky, and K.D. Shuler. 1997. Potassium source and rate for polyethylene-mulched tomatoes. Hortscience 32 (7): 1204-1207. Locascio, S.J., S.M. Olson, F.M. Rhoads, C. D. Stanley, and A.A. Csizinsky. 1985. Water and fertilizer riming for trickle irrigate d tomatoes. Proc. Fla. State Hort. Soc. 98:237-239. Lubana, P.P.S., and N.K. Narda. 1998. Soil water dynamics model for trickle irrigated tomatoes. Agricultural Water Manage ment, 37:145-161. Elsevier Science. Lyman Ott R., and M. Longnecker. 2001. An introduction to statistical methods and data analysis. 5th Edition. Duxbury, Thompson Learning. Maynard, D.N., G.J. Hochmuth, S.M. Olson, C.S. Vavrina, W.M. Stall, T.A. Kucharek, S.E. Webb, T.G. Taylor, S.A. Smith, and E.H. Simonne. 2003. Tomato production in Florida. Chapter 41. In: S.M. Olson, and E. Simonne. Vegetable production guide for Florida 2003-2004. Fla. Coop. Ext. Serv. IFAS. University of Florida. Morgan, K.T., L.R. Parsons, and T.A Wheaton. 2001. Comparison of laboratoryand field-derived soil water rete ntion curves for a fine sand soil using tensiometric, resistance and capacitance methods. Plant and Soil, 234: 153-157. Munoz-Carpena, R. 2004. Field devices for so il water content. Bull. 343. Fl. Coop. Extension Serv. IFAS, University of Florida, Gainesville. Muoz-Carpena, R. and M.D. Dukes. Design an d field evaluation of a new controller for soil moisture-based irrigation. Submitted to Applied Engineering in Agriculture (Manuscript no. SW-06008-2005, August 2005). Muoz-Carpena, R., M.D. Dukes, L.W. Miller, Y.C. Li, and W. Klassen. 2004. Design and field evaluation of a new controller for soil moisture-based irrigation control. Unpublished draft for presentation in 2004 ASAE/CSAE Ann. Int. Meet., 1-4 Aug. Ottawa, Onario, Canada. Muoz-Carpena, R., M.D. Dukes, Y.C. Li, a nd W. Klassen. 2005. Field comparison of t ensiometer and granular matrix sensor automatic drip i rrigation on tomato. HortTechnology 15 (3) Munoz-Carpena, R., Y.C. Li, and T. Olczyk. 2002. Alternatives of low cost soil moisture monitoring devices for vege table production in south Miami-Dade County. Doc ABE 333. Fl. Coop. Extensi on Serv. IFAS, University of Florida, Gainesville.

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116 Muoz-Carpena, Y. Li, and T. Olczyk. 2002. Low cost moisture monitoring devices for vegetable production in the south MiamiDade County agricultural area: Part 1Alternatives. Fla. Coop. Ext. Serv. IF AS. University of Florida. ABE 333. OI Analytical. @001. Nitrate plus nitrite nitrogen, USEPA by segmental flow analysis (SFA) or flow injection an alysis (FIA). Publication 14900301. College Station, TX. Qualls, R.J., J.M. Scott, and W.B. DeOreo 2001. Soil moisture sensors for urban landscape irrigation Effectiveness and Reliability. Journal of the American Water Res. Ass. 37 (3): 547-559 Jun 2001. Raskar, B.S. 2003. Effect of planting t echnique and fertigation on growth, yield and quality of banana (Musa sp). Indian J ournal of Agronomy 48 (3): 235-237. Indian Soc Agronomy, Indian Agr Res Inst Di v Agronomy, New Delhi 110012, India. Scholberg, J., B.L. McNeal, K.J. Boote, J.W. Jones, S.L. Locascio, and S.M. Olson. 2000. Nitrogen stress effects on growth and nitrogen accumulation by field-grown tomato. Agr. Journal., Amer. Soc. of Agro, 92: 159-167. Shae, J.B., D.D. Steele, and B.L. Gregor 1999. Irrigation scheduling methods for potatoes in the northern Great Plains. Transactions of ASAE, 42 (2): 351-360 MarApr. Shock C.C., E.B.G. Feibert, and L.D. Saunders 2000. Onion yield and quality affected by soil water potential as irrigation threshold. Hortscience 33 (7): 1188-1191 Dec. Shock C.C., E.B.G. Feibert, and L.D. Saunders 1998. Potato yield and quality response to deficit irrigation. Hortscience 33 (4): 655-659 Jul. Simonne, E.H., M.D. Dukes, and D.Z. Haman. 2004. Principles and practices of irrigation management for vegetables. Chapter 8 in: Vegetable production guide for Florida 2003-2004. IFAS, Citrus and Vegetable Magazine. Smajstrla, A.G and S.J. Locascio. 1994. Irrigation cutback effects on drip-irrigated tomato yields. Proc. Fla. State Hort. Soc., 107: 113-118. Smajstrla, A.G. and S.J. Locascio. 1996. Tensiometer-controlled drip irrigation scheduling of tomato. Appl. Eng. Agr. 12: 315-319. Smajstrla, A.G., D.S. Harrison, W.J. Becker, F.S. Zazueta, and D.Z. Hamon. 1985. Backflow prevention requirements for Florid a irrigation systems. Fla. Coop. Ext. Serv. IFAS. University of Florida. Extension Mimeo Report 84-21 (revised). Smajstrla, A.G., G.A.Clark, D.Z. Haman, a nd F.S. Zazueta. 1994. Design of agricultural irrigation systems in Florida. Fla. Coop. Ext. Serv. IFAS. University of Florida. Bul. 294.

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117 Thompson T.L., S.A. White, J. Walworth, and G.J. Sower. 2003. Fertigation frequency for subsurface drip-irrigated broccoli. Soil Science Society of American Journal 67 (3): 910-918. Soil Sci Soc Amer, Madison, WI. USEPA. 1993. Methods for the determinati on of inorganic substances in environmental samples. EPA/600/R-93/100. U.S. Gov. Print. Office, Washington, DC. Wang, Q., W. Klassen, A.A. Abdul-Baki, H.H. Bryan, Y.C. Li, and M. Codallo. 2004. Influence of summer cover crops and irriga tion rates on tomato yields and quality in a subtropical area. Proc. Fl a. State Hort. Soc. 116: 140-143. Zazueta, F.S., A.G. Smajstrla and G.A. Clark. 1994. Irrigation system controllers. Fla. Coop. Ext. Serv. IFAS. University of Florida. SS-AGE-22

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118 BIOGRAPHICAL SKETCH Born in South Africa in October 1981, J onathan Schroder attended elementary and high schools on the East Coast of South Africa n ear the City of Durban. He was awarded academic honors and partook in multiple sports such as cricket, tennis, surfing and rugby. He then attended the University of Natal (subsequently changed to the University of KwaZulu Natal) where he achieved his bachelor s degree in agricultural engineering cum laude. After completing his undergraduate degree he accepted an offer to study for his Master of Engineering, which has culminated in this document.


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Material Information

Title: Soil Moisture-Based Drip Irrigation for Efficient Use of Water and Nutrients and Sustainability of Vegetables Cropped on Coarse Soils
Physical Description: Mixed Material
Copyright Date: 2008

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Source Institution: University of Florida
Holding Location: University of Florida
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SOIL MOISTURE-BASED DRIP IRRIGATION FOR EFFICICENT USE OF WATER
AND NUTRIENTS AND SUSTAINABILITY OF VEGETABLES CROPPED ON
COARSE SOILS














By

JONATHAN H SCHRODER


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF ENGINEERING

UNIVERSITY OF FLORIDA


2006

































Copyright 2006

by

Jonathan H Schroder

































This document is dedicated to the graduate students of the University of Florida.
















ACKNOWLEDGMENTS

To achieve the opportunity of studying at a wonderful institute like the University

of Florida I would like to thank my parents. They have given me the desire and platform

to study and grow and look for more out of every situation. I also thank Dr. Greg Kiker

for his enthusiasm towards my studies. He made my passage into the USA possible, and

started me out on a great academic experience from my first undergraduate year in South

Africa.

For their assistance in Hieldwork at the TREC I thank Tina Dispenza and Harry

Trafford. For their assistance at Pine Acres, I thank Kristen Femminella, Jason Icerman,

Lincoln Zotarelli, and the Pine Acres Hield crew. For his continued encouragement, and

help in many Hields, thank you to Paul Lane.

For all their support, advice and examples in academic research I thank Dr. Michael

Dukes and Dr. Yuncong Li. For his continued guidance, motivation, energy and advice,

along with racquet ball games and good wine, I want to thank my chair, Dr. Rafael

Mufioz-Carpena. I have learned many things from his Eine examples and standards. My

experience, thanks to all these people and many more whom I have not listed, has been a

great one, and I am grateful for having had this time here.




















TABLE OF CONTENTS


page

ACKNOWLEDGMENT S .............. .................... iv


LI ST OF T ABLE S ............ ..... ._ .............. vii...


LIST OF FIGURES ............ ..... .__ ..............viii..


AB STRAC T ................ .............. xii


CHAPTER


1 INTRODUCTION ................. ...............1.......... ......


Rationale ................ ...............1.......... ......

Obj ectives ................. ...............5.......... ......

2 SOIL MOISTURE BASED DRIP IRRIGATION FOR IMPROVED WATER
USE EFFICIENCY AND REDUCED LEACHING ON TOMATOES ......................6


Introducti on ................. ...............6.................
Method s and Material s............... ...............9
Soil Characteristics ................. ...............9.................

Experimental Design ................. ................. 10..............
Field layout. .............. ..... ... ... ...... ......... .............1
Irrigation control and data capture hardware .............. ....................1
Fertigation control and data capture hardware ................. ............. .......17
Analy si s Method s .............. ............... 20....
Results and Discussion .............. ........ ..............2

Experiment 1: Calcareous gravelly soil ................. ...............................22
Experiment 2: Sandy Soil ................. ......... ...............26.....
Compari son of re sults ................. ...............3.. 1......... ...
Conclusion ................ ...............36.................


3 FERTIGATION METHODS FOR SOIL MOISTURE-BASED IRRIGATION OF
VEGETABLE CROPS .............. ...............38....


Introducti on ................. ............ ...............38 .....

Improved Irrigation Management............... ...............3
Fertigation............... ..............4












Benefits of Fertigation............... .............4
Fertilizer Injection ................. ...............40.................
Fertilizer application schedules .............. .... .... .............4
Fertigation coupled with soil moisture-based irrigation............... ...............4
Methods and Materials ............... .. ............ ...........4

Experiment 1: South Florida gravelly soil .............. .....................4
Experiment 2: North Central Florida sandy soil............... ...............49..
Combining continuous methods with scheduled fertigation ............... ...............52
Additional fertigation information .............. ...............54....
Conclusions .............. ...............56....


4 DIELECTRIC CAPACITANCE SOIL MOISTURE PROBE CALIBRATION
AND SPATIAL SOIL MOISTURE DYNAMICS STUDY ........._._............_.....57


Introducti on ........._._ ...... .. ...............57...
Methods and Materials .............. ...............60....
Presentation of Results .............. ...............68....
Discussion of results ........._._ ...... .... ...............77...
Rainfall .............. ...............78....

Temperature ........._._ ...... .... ...............79...
Salinity ........._..... ... .... ............... 1.....
Spatial distribution trends ........._._. ...._. ...............85...
Conclusions............... ..............8


5 SUMMARY AND CONCLUSIONS ...._. ......_._._ .......__. ............9


APPENDIX


A FERTIGATION FOR SOIL MOISTURE-BASED IRRIGATION ................... ........99


B SOIL MOISTURE DISTRIBUTIONS WITHIN A PLASTIC MULCHED BED ..107


LIST OF REFERENCES ................. ...............113................


BIOGRAPHICAL SKETCH ................. ...............118......... ......

















LIST OF TABLES


Table pg

1.1 Scheduling treatments applied to two irrigation experiments on tomato crops. ......11

1.2 System specification and agronomic parameter summary for experiment 1. ..........17

1.3 Summary of system specifications for tomatoes grown in Experiment 2..............17

1.4 Water application, yield, and irrigation water use efficiency (IWUE) averages
for each treatment in Experiment 1 on calcareous gravelly soil. ............. ................22

1.5 Nutrient leaching data obtained from lysimeters in Experiment 1...........................24

1.6 Water application, yield and water use efficiency (WUE) for Experiment 2. .........27

1.7 Average volume leached and nitrate-nitrogen load leached per treatment for
Experim ent 2 .............. ...............30....

1.8 Average values and the percentage change from the local grower treatment for
the dependant variables measured in two experiments of tomatoes ......................3 1

2.1 Venturi inj section rates and variability of inj section rates from a calibration test
conducted prior to the transplant of the tomato crop on Experiment 1 ........._.........48

2.2 IFAS suggested daily fertigation rates for tomatoes. ............... ...................5

A. 1 Mazzei injectors performance tables (Mazzei Inj ector Corp., Bakersfield, CA)...101

A.2 Example of irrigation timer setup for decoupled continuous fertigation and soil
moisture-based irrigation for the setup displayed in Figure 3............... ................102

















LIST OF FIGURES


Figure pg

1.1 Irrigation distribution system and control system layout for Experiment 1.............12

1.2 Field layout and irrigation treatments for Experiment 2. ............. ....................13

1.3 Bucket lysimeters used to quantify leaching loads corresponding to different
irrigation treatments on gravelly loam soil in Experiment 1.............. ..................19

1.4 Vacuum pumps extracting leachate from lysimeters positioned 60 cm under the
beds of Experiment 2 on sandy soil. ............. ...............20.....

1.5 Graph of cumulative season water application for the four irrigation treatments
applied to the gravely loam soils of Experiment 1 ................ ........................23

1.6 Cumulative average leached volume recorded by the lysimeters per treatment for
Experiment 1 on calcareous gravelly soil. ............. ...............25.....

1.7 Cumulative load of nitrate captured in the lysimeters over the season for
Experiment 1 on calcareous gravelly soil. ............. ...............26.....

1.8 Cumulative water application per treatment applied over the season to tomatoes
in Experiment 2. ............. ...............27.....

1.9 Cumulative volume of leachate collected in the lysimeters per treatment over the
season for Experiment 2. .............. ...............29....

1.10 Cumulative nitrate-nitrogen load leached per treatment over the season for
Experim ent 2. ............. ...............29.....

2.1 A venturi injector schematic showing flow directions and operating principle
(adapted from Mazzei Inj ectors Inc.) ................. .........__ ......44.........

2.2 Pumphouse hardware layout for Experiment 1 .................... ..............4

2.3 Venturi inj ectors placed across pressure regulators for added pressure
differential ............. ...............47.....

2.4 Weekly manual inj section of fertilizer solution carried out using a peristaltic
pump for Experiment 2. ............. ...............50.....










2.5 Cumulative nitrogen rates comparing continuous and manual fertigation
treatments in Experiment 2 on sandy soil. ............. ...............51.....

2.6 Fertigation system for decoupled time-based fertigation and soil moisture-based
irrigation. .............. ...............54....

4.1 ECH20 dielectric capacitance soil moisture probe (Decagon Devices Inc.,
Pullman, W A)............... ...............61..

4.2 Grid of nine ECH20 probes placed between two actively growing zucchini
plants to determine soil moisture distribution for probe placement ................... ......63

4.3 TDR nest to measure soil moisture for corresponding to mV irrigation threshold
set point. ............. ...............64.....

4.4 Nest of dielectric capacitance probes and tensiometers used to generate the drier
points of the soil moisture release curve for the fine sand at PSREU.....................66

4.5 Probe grid of 33 dielectric capacitance probes to determine spatial dynamics in
the root zone of a mature zucchini crop in plastic mulched bed .............. .............67

4.6 Dielectric capacitance probe readings for different spatial positions within the
root zone of a plastic mulched crop irrigated using a 475mV set-point. ........._......68

4.7 Dielectric capacitance probe readings for different spatial positions within the
root zone of a plastic mulched crop irrigated using a 525mV set-point. ........._.....69

4.8 Dielectric capacitance probe readings for different spatial positions within the
root zone of a plastic mulched crop irrigated using a 475mV set point...................69

4.9 Bivariate plot of TDR and dielectric capacitance probes to obtain a linear
relationship between soil moisture and mV ......_. ..........._. ........._._.....70

4.10 Soil moisture release curve obtained from in-situ measurements for the fine sand
at the Plant Science Research and Education Unit in Citra County ................... ......71

4.11 Plot of soil moisture release curve obtained from manual tensiometer readings
and data obtained from nests of tensiometers and TDRs. ............. ................72

4.12 Soil moisture release curve and fitted model derived by ECH20 data and the
calibration curve, corrected from nested tensiometer and TDR data. ......................72

4.13 Average soil moisture distribution between two zucchini plants in a plastic
mulched bed using soil moisture based drip irrigation (threshold 475 mV)............73

4.14 Variability of soil moisture within the zone between two zucchini plants
irrigated by soil moisture-based drip irrigation (threshold 475 mV) .......................73










4.15 Average soil moisture distribution between too zucchini plants in a plastic
mulched bed using soil moisture based drip irrigation (threshold 525 mV)............74

4.16 Variability of soil moisture within the zone between two zucchini plants
irrigated by soil moisture-based drip irrigation (threshold 525 mV) .......................74

4.17 Average soil moisture distribution for the root zone of a mature zucchini plant
irrigated by soil moisture-based scheduling (threshold 475 mV). ...........................75

4.18 Soil moisture variability for the root zone of a mature zucchini plant irrigated by
soil moisture-based scheduling (threshold 475 mV) ................. .......................75

4.19 Average soil moisture tension for the root zone of a mature zucchini plant
irrigated by soil moisture-based scheduling (threshold 475 mV). ...........................76

4.20 Average cross-section profile of soil moisture across the bed with varying
distance from drip tape for a mature zucchini crop ................. ................ ...._.77

4.21 Soil moisture time series showing how soil moisture spikes during rainfall
events are limited to probes on exterior of bed .............. ...............78....

4.22 Temperature fluxes within three plastic mulched beds in the fall season of 2005.
Thermocouples were buried approximately 15 mm beneath the surface. ................80

4.23 Time series of soil moisture in bed Il to show limited effects of temperature on
outer probes that receive little irrigation water. ............. ...............81.....

4.24 Water applications for the three soil moisture-based drip irrigation treatments II,
I2 and I3 on a plastic mulched zucchini crop. .............. ...............83....

4.25 Soil moisture time series showing soil moisture determined by TDR and
calculated by dielectric capacitance for soil moisture treatment II. ........................83

4.26 Soil moisture time series showing soil moisture determined by TDR and
calculated by dielectric capacitance for soil moisture treatment 12. ........................84

4.27 Soil moisture time series showing soil moisture determined by TDR and
calculated by dielectric capacitance for soil moisture treatment I3 .........................84

A. 1 Bypass venturi assembly for fertigation using either a pressure regulator or a
control valve. .............. ...............99....

A.2 Bypass assembly with a booster pump for venturi inj section fertigation. ...............100

A.3 Bypass assembly with venturi inj ector installed across an irrigation pump. .........100

A.4 Automated soil moisture-based irrigation scheduling hardware developed by the
University of Florida ................ ...............102................










A.5 Cumulative water use for ETc and the estimate for soil moisture-based
scheduling using the QIC and dielectric probe set to 25 cbar soil moisture ..........1 04

A.6 Required 4-0-8 liquid fertilizer dilution to achieve IFAS rates when driven by
estimated soil moisture-based water application ................. ........................105

A.7 Step-wise estimated evapotranspiration functions vs. likely actual functions.......106

B.1 Probe layout and numbering, used to determine soil moisture distribution within
the root zone of a mature zucchini plant grown in plastic mulched beds. .............107

B.2 ECH20 probes placed next to drip line, mV output. ............. ....................10

B.3 ECH20 probes placed perpendicular to drip tape to drip, line mV output............1 08

B.4 ECH20 probes parallel to and 30 cm from the drip line, mV output. ...................109

B.5 ECH20 probes parallel to and 15 cm from the drip line, mV output. ..................109

B.6 ECH20 probes parallel to and -15 cm from the drip line, mV output. .................110O

B.7 ECH20 probes parallel to and -30 cm from the drip line, mV output. .................110O

B.8 ECH20 probes perpendicular to and 30 cm from the drip line, mV output. .........111

B.9 ECH20 probes perpendicular to and 15 cm from the drip line, mV output. .........111

B. 10 ECH20 probes perpendicular to and -15 cm from the drip line, mV output.........112
















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

SOIL MOISTURE-BASED IRRIGATION: A SCHEDULING METHOD TO
IMPROVE FUTURE RESOURCE USE EFFICIENCIES AND PROMOTE
AGRICULTURE SUSTAINABLITY

By

Jonathan Schroder

May 2006

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

To improve water and nutrient use efficiency, growers need to maintain the soil

water in the crop root zone at optimal levels for plant growth and minimal nutrient

leaching. An automated drip irrigation system has been developed that interfaces a

dielectric capacitance probe to evaluate soil moisture and control irrigation accordingly.

If the soil moisture is below a user-set threshold the scheduled irrigation event is

initiated. If soil moisture is above the threshold, the event is bypassed and water is

conserved. Multiple small volume events are scheduled per day. The aims of this three-

season proj ect were to quantify the water applications and the leached loads of nutrients

for soil moisture-based irrigation and traditional time-based irrigation; to develop a

fertigation methodology that could be integrated with soil moisture-based irrigation; and

to calibrate the soil moisture probe for sandy soils common in Florida, and gain

knowledge on the spatial dynamics of soil moisture within the plastic mulched beds.









Two experiments were conducted on tomato crops, one on Krome, a calcareous gravely

loam soil in South Florida, and another on a fine sandy soil in North Central Florida.

Replicates of soil moisture-based scheduling and time-based scheduling were applied.

Soil moisture-based scheduling applied 55 to 80% less irrigation water and yielded

Irrigation Water Use Efficiencies (IWUE' s) of 200% to 415% higher than time-based

scheduling. Leachate volumes were 68-74% lower, a 90% reduction of leached NH4-N,

a 75-89% reduction in NO3-N, and an 85% reduction in dissolved and total phosphorous

loads leached, and were obtained by soil moisture-based treatments compared to the time

based treatments. To further improve the system's nutrient management an automated

fertigation system to be integrated within a soil moisture-based irrigation system was

developed and tested. The system used a venturi injector and provided sufficiently

accurate fertilizer applications to meet the crop nutrient needs throughout the season.

The system is easy to manage and relatively inexpensive. An experiment on a plastic

mulched zucchini crop was conducted to better understand spatial soil moisture

dynamics. This is critical, as the information from the soil moisture probe drives the

irrigation. Soil moisture in a narrow zone of up to 15 cm away from the drip line was

influenced by irrigation events in the fast draining sand soil. Soil moisture tensions were

found to increase rapidly beyond 8% soil moisture by volume. Temperature, and rainfall

showed very little effect on output readings of the dielectric capacitance probe, but

salinity effects could be significant and need to be calculated. The system has proved to

be successful at improving water and nutrient use efficiencies, and shows potential for

improved coexistence of vegetable production agriculture with environmental systems.















CHAPTER 1
INTTRODUCTION

For the purpose of motivation of research this first chapter will briefly introduce

water management issues pertaining particularly to agriculture in Florida. Focus will be

given to areas where water management challenges have prompted agriculture to advance

its systems and become more competitive and sustainable.

Rationale

The Everglades and associated costal ecosystems of South Florida are unique and

highly valued ecosystems. One of the world's largest water management systems has

been developed in South Florida over the past 50 years to provide flood control, urban

and agricultural water supply, and drainage of land for development. However this

system has inadvertently caused extensive degradation of the South Florida ecosystems

and elimination of whole classes of ecosystems. The hydrodynamics and water quality in

Everglades National Park and adj acent lands are now being restored in accordance with

the Comprehensive Everglades Restoration Plan (CERP). CERP

authorizes modifications of the existing surface water management system, so as to re-

establish historic freshwater flows that restore more natural hydro-patterns in the Park

and contribute to ecosystem restoration. Part of CERP's mission is also to protect the

water resources in Central and Southern Florida by balancing and improving water

quality and supply. Lack of knowledge about the hydrological system and its effects on

crops, local and regional flow, and chemical transport patterns are all maj or concerns for

all stakeholders in the area (Mufioz-Carpena, 2004). As such, farmers in the area have









taken a key role in promoting the need for scientific investigation into the possible impact

of CERP on the sustainability of agriculture in South Florida.

To understand the scale of the industry that is being impacted by the need for

environmental compatibility one needs to look at the extent of agriculture in Florida.

Florida ranks second among the states in fresh market vegetable production on the basis

of area cultivated (9.6%) and in value (13%) of the crops grown. Tomato production

accounted for over 30% of the state' s total production in value in 2001-2002. According

to the National Resources Conservation Service (1995), Dade County produces roughly a

quarter of the state's tomatoes. Higher yields than more northern growing areas, and the

ability to produce a crop during the winter season when other regions are inactive, have

helped establish this region's importance in the tomato market. The Miami-Dade County

vegetable crops industry also employs over 6000 people, and has a $491 million impact

on the state economy.

Florida tomato growers are at a competitive disadvantage due to off-shore

competition from countries where labor is considerably cheaper than in the United States.

This disadvantage is even greater with the phase out of methyl-bromide in the U.S, but

not in other developing countries. Apart from environmental benefits, the vegetable

industry in Florida is hugely in need of methodologies that improve resource use and

decrease operating costs.

Water is a vital resource and is a driving force for much of crop production. With

its large contribution to industry in Florida, agricultural self-supply accounts for 35% of

fresh ground water withdrawals, and 60% of fresh surface water withdrawals, which

makes it the largest component of freshwater use in Florida (Marella, 1999). Overall,









82% of the farms in the Miami-Dade County have irrigation systems. The primary use of

this water is irrigation to supplement rainfall during dry crop periods (Muhioz-Carpena et

al., 2004). The high yields of the Biscayne Aquifer were originally attractive for growers

and have lead to the general perception among growers that water is not a limiting factor.

But as urban pressure in the Miami-Dade County area increases, water could become a

more scarce resource (Muhioz-Carpena et al., 2002). Despite the potential shortages,

over-irrigation is a problem in the area and may be explained by the low water holding

capacity and high permeability of Florida' s sandy soils, and especially the gravelly soils

found in the south Miami-Dade County agricultural area. Analysis shows that irrigation

efficiency is highly sensitive to both soil texture and irrigation volume. Over irrigation

can also be attributed to inadequate irrigation scheduling (Muhioz-Carpena et al., 2004).

Traditional irrigation based on low frequency and high volumes usually results in

inefficient water use. With this type of irrigation, a substantial volume of the applied

water percolates quickly to the shallow groundwater, potentially carrying with it nutrients

and other agrochemicals applied to the soil (Muhioz-Carpena et al., 2003a).

For some important reasons, drip irrigation of raised beds covered with plastic

mulch is the most suited form of micro irrigation for high value vegetable production. Its

slower more precise application of water is suitable to easily drained soils and one of the

maj or benefits of drip irrigation is the capacity to conserve water and fertilizer compared

to overhead sprinklers and subirrigation. Drip irrigation also helps reduce foliar disease

incidence compared to overhead sprinkler systems, which wet the plant foliage. By

maintaining drier plants drip irrigation reduces susceptibility to outbreaks of bacteria and

fungal diseases, and reduces the need for bactericides and fungicides (Hochmuth and










Smajstrla, 1998). Drip irrigation provides for precise timing and application of nutrients

and certain pesticides in vegetable production. Fertilizers can be prescription-applied

during the season in amounts that the crop needs and at particular times when those

nutrients are needed. These small, controlled applications of fertilizer under plastic

mulch not only save fertilizer, but also have the potential to reduce groundwater pollution

due to fertilizer leaching from heavy rainstorms or irrigation.

Drip irrigation however has become the standard for plastic mulched raised bed

vegetable production, and no longer gives any benefits over competitors. Furthermore,

the design and implementation of a good irrigation system requires good scheduling for it

to operate efficiently. The University of Florida' s Institute of Food and Agricultural

Sciences, a leader in developing best management practices, recommends scheduling

according to crop evapotranspiration requirements combined with soil moisture

monitoring. A methodology of scheduling has recently been developed to automatically

schedule water according to soil moisture status. Preliminary tests have shown the

system has potential for large savings in water application from traditional methods of

irrigation scheduling.

More and more, water conservation appears on top priority lists for proj ecting,

planning and managing future water needs, not just in South Florida, but statewide and

globally as well (Anon, 2003).

The following Chapters will introduce and discuss an automated drip irrigation

system and management practices that have been developed and tested by the University

of Florida. Different aspects of the system will be analyzed, namely the system

configuration and hardware, the system's ability to conserve water and reduce leaching









with results from field trials, and the potential of integrating soil moisture based

scheduling with continuous fertigation. Although these studies have focused on a

specific hardware technology, it must be strongly emphasized that it is not the specific

technology that is of highest importance, but the methodologies presented here within.

The potential of the system lies within the methodology; the technologies are important

for optimization of the method.

Obj ectives

Chapter 2

1. To test and mange water and fertilizer application with the automated soil
moisture based irrigation system
2. To quantify the load of nutrients being leached from the root zone of the
crop for different irrigation scheduling methods to determine the
effectiveness of the proposed system in reducing leaching loses
3. To demonstrate that with proper management that yields can be maintained
while reducing water and nutrient application from local grower standards

Chapter 3

4. To evaluate the potential and effectiveness of integrating soil moisture
based irrigation scheduling and automatic continuous fertigation

Chapter 4

5. To better understand soil moisture distribution within plastic mulched beds
and its effects on probe placement for soil moisture based irrigation
6. To calibrate the soil moisture probe used with the UF developed automated
soil moisture based system for the fine sand soils at local research site

Chapter 5


7. To hi-light potential issues for future research within this field.















CHAPTER 2
SOIL MOISTURE BASED DRIP IRRIGATION FOR IMPROVED WATER USE
EFFICIENCY AND REDUCED LEACHING ON TOMATOES

Introduction

Florida tomato growers are at a competitive disadvantage due to off-shore

competition from countries where labor is cheaper than in the United states (Munoz-

Carpena et.al., 2005). Improving irrigation efficiency can contribute to reducing

production costs of vegetables and make the industry more competitive and sustainable.

Through proper irrigation, average yields can be maintained or increased (Shae, et al.,

1999) while minimizing environmental impacts caused by excess water application and

subsequent agrichemical leaching. Tomatoes are typically grown in raised beds with

plastic mulch and drip irrigation. Although this method has the potential to be very

efficient, over-irrigation is a common occurrence in Florida due to inadequate irrigation

scheduling and low soil water holding capacity of soils commonly used for agriculture.

Traditional irrigation of applying large volumes of water at low frequencies (a few times

per week) results in a large portion of the irrigated water percolating quickly through the

root zone to the shallow groundwater, potentially carrying with it nutrients and other

agrochemicals in the soil. In addition, excess water in the root zone can reduce tomato

yields (Wang et al., 2004).

Recent technological advances have made low-cost soil water sensors available for

efficient and automatic operation of irrigation systems (Dukes and Mufioz-Carpena,

2005). Automation of irrigation systems based on soil moisture sensors may improve









water use efficiency by maintaining soil moisture at optimum levels in coarse soils (sands

and gravels) rather than a cycle of very wet to very dry as a result of typical low

frequency high volume irrigation. This is particularly critical in Florida' s sand and gravel

soils where available soil moisture is typically 6-8% by volume or less (Dukes et al.,

2003).

Soil moisture probes can be installed at representative points in an agricultural field

to provide repeated moisture readings over time for irrigation scheduling and

management. The target soil water status is usually set in terms of soil tension (or matric

potential expressed in kPa or cbar), or volumetric moisture content. Care needs to be

taken when using these soil moisture sensor devices in coarse soils, as most devices

require good contact with the soil matrix, which is difficult coarse soils (Dukes and

Munoz-Carpena, 2005). In addition soil moisture sensing devices need to be able to

capture fast soil water changes typical to coarse soils. Tensiometers have been widely

used in soil moisture based scheduling in various applications such as tomato production

(Clark et al, 1994; Smaj strla and Locascio, 1994), blackcurrent production (Hoppula and

Salo, 2005), and rice (Kukal, et al., 2005). Due to their direct reading of soil matrix

potential and thus plant water stress, tensiometers provide good scheduling applications.

Tensiometers however need to be carefully maintained (e.g. refilled) and the ceramic cup

has the potential to loose contact with coarse soils, requiring reinstallation. Dielectric

probes however need little maintenance and can be accurate without soil specific

calibrations, although soil-specific calibration increases accuracy, and is recommended

on certain soils (Munoz-Carpena, 2004). A drawback of some dielectric probes is the

cost due to the complex electronics.









Soil moisture based scheduling has resulted in water savings on coarse soils in

Florida. Smaj strla and Locascio (1996) reported reductions of irrigation of 40 to 50%

compared to local practices without affecting yield using switching tensiometers to

irrigate tomatoes on fine sands in Florida. Scheduling according to soil matric potential

measuring devices achieved a 70% reduction in water applications against time based

practices for tomato grown on a calcareous soil in South Florida compared to local

grower practices was reported by Mufioz-Carpena et al., (2005). The methodology of

using soil moisture based scheduling has been used successfully on other crops and

applications such as citrus (Fares and Alva, 2000), potatoes (Shae et al., 1999) and

(Shock et al., 1998), onions (Shock et al., 2000), and for the automatic irrigation of urban

landscapes (Qualls et al., 2001).

Corresponding reductions in nutrient leaching loads due to reduced water

applications are expected. Hebbar et al. (2003) found improved fertilizer use efficiencies

with all drip irrigated and fertigated treatments over furrow irrigation, as well as reduced

NO3-N leaching from soil analysis at varying depths. Drip irrigation and fertilizer

applied through fertigation, combined with soil moisture based scheduling has high

potential for reducing leaching of nutrients, but little quantification of the loads leached

have be reported.

The obj ective of this proj ect were to determine the effect of the soil moisture-based

irrigation scheduling applied to plastic mulched tomatoes grown on two soil types and

seasons. The soil moisture based-irrigation scheduling was compared to traditional

time-based scheduling. Different dependant variables were studied to determine the

effect of the independent variable (irrigation scheduling method). The different variables









that were studied were 1) water application by treatment, 2) yield and water use

efficiency for each treatment, 3) volume of leachate passing through the root zone as a

result of different treatment water applications, and 4) the load of nutrients in the leachate

lost from the root zone corresponding to each treatment.

Methods and Materials

Two Hield trials were conducted on plastic mulched tomato crops using the soil

moisture based drip irrigation system. The first experiment was conducted during the

2004/2005 winter cropping season on gravelly loam soil in Homestead, Miami-Dade

County in South Florida. The second experiment was conducted during the 2005 spring

cropping season on sandy soils in Marion County, North Central Florida.

Soil Characteristics

The Hield site of the first experiment was at the Tropical Research and Education

Center (TREC) in Homestead, Miami-Dade County. The region is dominated by three

calcareous soils, namely Krome, Chekika, and Marl (Munoz-Carpena et al., 2002). The

soil at TREC is Krome, a calcareous soil artificially made by rock-ploughing the top

layer of the limestone coral bedrock. It is a bimodal soil and has 51% gravel particles

and the remainder is loam texture. The highly permeable gravel component the soil

presents soil water management challenges to growers in the area. A large portion of the

soil water (approx. 50%) can easily be leached during regular water applications, due to

the low water holding potential of the gravel component of the soil.

The second field site was at the Plant Research and Education Unit (PSREU) in

Marion County, on sandy soils. Buster (1979) classified the soil at the PSREU research

site as a Candler sand and Tavares sand. These soil types contain 97% sand-sized

particles and have a field capacity of 5.0% to 7.5% by volume in the upper 100 cm of the









soil profile (Carlise et al., 1978). Like the Krome soil in South Florida, the sandy soils of

this region are highly permeable and also have a low water holding capacity and high

potential for leaching.

Experimental Design

Tomatoes were grown according to local agronomic practices in each region. The

field in Experiment 1 had sorghum sudangrass grown as cover crops prior to the

cultivation and the tomato-cropping season. The tomato seedlings of the cultivar, 'FL

47', were transplanted on the 15th of October 2004 (Experiment 1), and the 5th of April

2005 (Experiment 2) into raised black plastic mulched beds. The beds were spaced 1.83

m apart, center-to-center, and seedlings were planted in one row per bed with plants

spaced 0.46 m apart. Dual drip lines under the plastic mulch were used to supply

irrigation water to the crop on the gravelly loam soil (Experiment 1), and single lines

were used for the sandy soil (Experiment 2). Dual lines were employed on Experiment 1

as the gravelly loam soil was only 35-45 cm deep and the wider wetting area would

provide a larger soil water storage volume, which is common horticultural practice.

Field layout

For Experiment 1 the field was divided into two areas, an experimental plot, and a

demonstration plot (Figure 1.1). All experimental data was obtained from the experiment

plot, and the demonstration plot was used as an extension service and provided visitors

with an example of the system working as it would in commercial practice. Four

irrigation-scheduling treatments were applied to the experimental plot. Two of these

treatments were soil moisture based scheduling (Ill and Il2), and two of the treatments

were time based scheduling (113 and Il4). Each treatment consisted of three

replications of 50 m long beds, individually controlled by a separate sensor.










To reduce wiring treatments were not spatially randomized and control points could

be kept close together in the field and supplied by a single multiple station cable. The

demonstration plot consisted of two treatments, a soil moisture based treatment 112, and

the local grower time based treatment 114. Figure 1.1, shows the field layout.

For Experiment 2 on the gravelly loam soil, a randomized complete block design

was used. Three irrigation treatments consisted of two soil moisture-based schedules,

and the third treatment was a time-based local grower schedule. Each treatment was

replicated four times (four 15 m beds) and a common valve and soil moisture probe

controlled all four replicates. Treatments I21 and 122 were soil moisture-based

treatments and 123 was a time-based treatment, similar to grower practices (Table 1.1).

Table 1.1. Scheduling treatments applied to two irrigation experiments on tomato crops.
Experiment Treatment Scheduling Method Devicelpractice

1 111 Soil moisture-based Switching tensiometers
112 Soil moisture-based ECH20 dielectric probe
113 time-based ETc based on historical weather data
114 time-based Local grower practice

2 121 Soil moisture-based ECH20 dielectric probe
122 Soil moisture-based ECH20 dielectric probe
123 Time-based Local grower practice

The field layout and treatments can be seen in Figure 2. A single drip tape supplied

the irrigation water and a second line supplied the fertilizer. For treatments 122 and 123

these two lines were placed next to each other in the middle of the bed at the surface

under the plastic mulch. For treatment I21, the irrigation line was buried 15 cm beneath

the surface and 15 cm offset from the fertigation line, which was at the surface. Plats

were transplanted 10 cm away from the drip lines. In treatment 121 this was 10cm from

the fertilizer line at the surface.














50mn


113 Time based crop evapotranlspiration I
(single control)



114 Timne based local grower
(single control)


114 Demnonstrationl plot controlled by a separate system


12



Pipe Distribution Network


Experimental Plot
111 Switching tenslometers


Experimental Plot
112 OIC and dlelectric probe


Experimental Plot
113 Time based ETc



Experimental Plot
114 Time based local grower

110m


Irrigation and fertigation
Ilne (laytlat)
c Double drip lines
O Flow meter
__Zero-tention lysimeter


LEGEND
-Irrigation line (laytlat)
Fertigation line (layflat)


Control System Network


Wiring of Valvesr, QC's and sill
moleture sensing devices


111- Switchinlg tensiomneter
(3conltrorl replicationls)


112 QIC and dielectric probe
(3 control replicationls)


LEGEND
Salenid valve in pump house
Salenoid valve in feld
Echo2 probe
aIC
Switching tensiometer


Conltrol valve fo~r Experimnent
plot fertigation


ch Control valve for 112 Demaonstrationl
plot irrigation and fertigation


Figure 1.1. Irrigation distribution system and control system layout for Experiment 1.

















I I


.123

I121


I _


I I


[ i


II,


I I


LEGEND


123, Irrigation trleatmenmt
Irrigatlon Ilnes
Fsrtiatlan lne

I 1. tro*CORsIOR 9lm lHBtISYS


.Solenalilvrale

-I a 01 ad O lele ctic ilrobe


Figure 1.2. Field layout and irrigation treatments for Experiment 2.


FloWr meter~










Irrigation control and data capture hardware

The soil moisture-based treatments applied water during preset events depending

on soil moisture status. An irrigation timer was used to preset sub-daily irrigation events.

When it was time for an event to occur the soil moisture sensor was queried. If soil

moisture was below a set threshold the soil moisture sensor would allow a set event to

occur. If soil moisture was above the threshold set point, the event would be bypassed.

For Experiment 1 treatments Il l and Il2 used switching tensiometers (LT-RA, Irrometer

Co., Inc., CA), and dielectric capacitance probes (ECH20, Decagon Devices Inc.,

Pullman, WA) respectively. The switching tensiometer irrigation set point was set at a

soil matric potential of 25 cbar. The ECH20 probes were interfaced with an irrigation

timer by a quantified irrigation controller (QIC) developed by the University of Florida

Agricultural and Biological Engineering Department (Dukes and Munoz-Carpena, 2005).

The irrigation threshold for the QIC was set to 400mV, which corresponded to a soil

matric potential of approximately 25 cbar for the gravelly soil and dielectric probe.

Treatments Il3 and Il4 were time based with 113 derived from historic weather data and

IFAS recommended crop coefficients (Simonne et al., 2004), and Il4 following local

grower practices, which corresponded to 1 hour of irrigation per day for the system (4

mm/day) .

For Experiment 2 treatments I21 and 122 used dielectric, capacitance probes

(ECH20, Decagon Devices Inc., Pullman, WA) interfaced with an irrigation timer using

QICs (Munoz-Carpena and Dukes, 2005). The irrigation threshold for the QICs was 500

mV, which corresponds to soil moisture content by volume of roughly 10-13 % for the

sandy soil using dielectric capacitance probes. Treatment 121 had its irrigation drip-tape

buried in the soil 15 cm beneath the surface of the bed, and its fertigation line on the









surface. Treatment 123 was the local grower practice time based treatment, and irrigated

once a day for 1 hour (2.1 mm/day) for the first 45 days after transplanting, and 2 hours

(4.2 mm/day) for the remaining 40 days in the season.

Soil moisture based scheduling with an automated system can apply water in two

different procedures. The soil moisture probes can continuously read the soil moisture

status and initiate irrigation whenever the level gets below a threshold, and switch the

irrigation off when once the profie has been sufficiently wetted which is an "on-demand"

technique (Dukes and Mufioz-Carpena, 2005). This technique has negative design

complications. The maximum flow rate of the system is not known, as the time at which

irrigation events occur during a day is dynamic, and there could be many valves open at

once or none. To accommodate the possibility that all the soil moisture treatment valves

could be open at once the system pipe network would have use large diameter pipes.

This would be particularly impractical in commercial systems where larger areas are

irrigated. As such, a Eixed schedule of sub-daily events was employed where the soil

moisture sensor control system could bypass these timed events if soil moisture was

adequate (Dukes and Mufioz-Carpena, 2005).

For Experiment 1 four events of 12 minutes per event were employed per day.

This corresponded to maximum daily needs for the season (2.5 mm/day) calculated from

historical weather data (ETo = 2.79 mm/day) and crop coefficients (Kcmax = 0.9).

Experiment 2 was conducted during the following spring-summer season when warmer

temperatures increase crop water needs. As such Hyve events per day were chosen. For

the beginning of the season each event was 12 minutes long. After 48 days the event

length was extended to 24 minutes (4.1 mm/day), which corresponded to the maximum










daily water requirement for a tomato crop in the area, and was derived from historical

weather data (ETo = 4.57mm/day) and crop evapotranspiration coefficients (Kcmax = 0.9).

Crop coefficients and historical weather data were obtained from (Simonne et al., 2004).

A schedule was programmed into an irrigation timer. The schedule consisted of 4

events per day (Experiment 1), and five events per day (Experiment 2). Each of the 4

events in Experiment 1 was 12 minutes long, and the 5 events in Experiment 2 were 12

minutes long for the first 45 days after transplant and 24 minutes long for the remaining

40 days. The soil moisture probes then either allowed or bypassed a prescheduled event

according to in-field soil moisture status, and a set threshold. The sub-daily events were

staggered and spread out through the day so that only one treatment was irrigated, if

needed, at a time. As a result of this scheduling set up, water is still delivered to the crop

as determined by the soil moisture probes, but the maximum flow rates are explicit and

reduced. The system specifications for Experiments 1 and 2 are presented in Table 1.2

and 1.3.

Water applications per treatment for Experiment 2, and per replication (individual

beds) within treatments for Experiment 1 were manually recorded from positive

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

Metering Systems Inc., Ocala, FL). In addition to manual readings on a weekly basis, the

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

closures were recorded by data loggers (HOBO event logger, Onset Computer Corp. Inc.,

Bourne, MA) and provided continuous data of water and fertigation application times,

which were downloaded once a week. This data could be used to determine which events

had occurred and which were bypassed.







17



Table 1.2. System specification and agronomic parameter summary for experiment 1.
System Hardware Agronomic Parameters


Table 1.3. Summary of system specifications for tomatoes grown in Experiment 2.
System Hardware Agronomic Parameters


Fertigation control and data capture hardware

Fertilizer rates were applied according to IFAS recommended rates for a tomato


crop on soils with low potassium levels in (Maynard et.al., 2004). For Experiment 1,

25% of the seasonal total nitrogen (228 kg/ha), the phosphorous and micro-nutrients were


was applied pre-plant, and the remainder was applied by fertigation throughout the


season. Venturi injectors (model no. 484, Mazzei Injector Corp., Bakersfield, CA) were


used to inject 4-0-8 solution (ammonia-nitrate based nitrogen source) liquid fertilizer into


the fertigation distribution system. The amount of fertilizer applied is directly related to


the amount of water applied using Venturi injectors. Since the different irrigation


745.7 kW (1HP) Maximum crop needs
750 L with 25 35 m pressure control Surface per bed
Rain-Bird ESP-12LX Max needs per bed
50 mm lay-flat Max time to irrigate
24 VAC, 13mm dia. Solenoids Max no. of irrigations
4 per bed (2 for irrigation two for fertilizer)
Drip tape T-TAPE TSX 508-12-450 Time per irri. event
16 mm internal dia.
0.30 m emitter spacing
5.6 L/min/100m nominal flow
5.6 m nominal head
length 50 m (4 drip lines) for experimental plot
110 m (double lines) for demonstration plot
inlet pressure 7 m


2.5 mm/day
91 m2
228 L/day
approx 48 min/plot/day
4 per day

12 minlevent/plot


Pump
Well tank
Controller
Main line
Valves
Laterals


Water supply
Controller
Main lines
Valves
Laterals


40 45 m pressure from main farm system
Rain-Bird ESP-12LX
13, 19 and 25 mm PE hose manifolds
24 VAC, 13mm dia. Solenoids
2 per bed (1 for irrigation and 1 for fertilizer)
Drip tape Chapin Watermatics Twin Wall BTF
10 mm diameter
0.20 m emitter spacing
6.2 L/min/100m nominal flow
6.89 m nominal head
length 15.2 m
inlet pres. 10 m (in manifolds)


Maximum crop needs
Surface per bed
Max needs per bed
Max time to irrigate
Max no. of irrigations
Time per irri. event


4.1 mm/day
28 m2
115 L/day
120 min/plot/day
5 per day
24 minlevent/plot









treatments were expected to apply different amounts of water, the water and fertigation

applications were separated so that each treatment received a variable amount of water,

but a common amount of fertilizer. A separate pipe distribution system was thus used to

fertigate all treatments for the experimental plot. Fertilizer was inj ected directly into the

irrigation system of the demonstration plot as would be done in a commercial practice.

The venturi inj ectors were calibrated before the start of the experiment, and were found

to provide consistent inj section rates with those specified by the manufacturer, and yet

were low cost and low maintenance. Three ventures were used in Experiment 1, two to

inj ect fertilizer into the experimental plot fertigation system, and one venturi inj ected

fertilizer into the demonstration plots irrigation system. The calibration yielded an

average inj section rate of 0.90 L/min with a standard deviation of 0.08 L/min.

For Experiment 2 phosphorous fertilizer was broadcast at 110 kg/ha prior to

bedding, along with a blanket of micronutrients. Nitrogen, potassium and magnesium

were all applied through fertigation once per week and none was applied preplant.

Calcium nitrate was the source of nitrogen and a total of 220 kg/ha of N was applied

through the season. Potassium as supplied in the form of Muriate of Potash (KC1) and

250 kg/ha of K was given for the season. Epsom salts applied provided the crop with

12.4 kg/ha of Mg for the season. Injection of the fertilizer in solution was carried out

manually once a week with a peristaltic pump (Experiment 2).

To quantify the volume and loads of nutrients leached associated with each

irrigation treatment, zero-tension lysimeters were installed into the fields. For

Experiment 1 seven zero-tension bucket lysimeters per treatment were buried directly










beneath the rooting zone of the crop (Figure 1.1 and 1.3). The capture area was 0.170 m2

and they had either 1 or 2 drip emitters positioned above them and contained 1-2 plants.

For Experiment 2, larger zero-tension lysimeters were used to capture the leachate

passing through the root zone of the crop. Four lysimeters were provided for each

treatment (Figures 1.2 and 1.4). The lysimeters were constructed from 208-liter

polyethylene drums and had a capture area of 1.52 m2. The larger capture area of the

lysimeters in Experiment 2 collected leachate from 3-4 drip emitters and had 3 plants in

each. This provided less variability compared to the lysimeters in Experiment 1, and the

larger capture area would provide more assurance of capturing all the leachate.





Dri p I rri gatio~n yier
lines Lsree
drainage pipe


Bled soil -~s em

Filter Saul 3 c
Z ero-te n si on Limestone
b~uckett lysimeter




Figure 1.3. Bucket lysimeters used to quantify leaching loads corresponding to different
irrigation treatments on gravelly loam soil in Experiment 1.

Lysimeters for both experiments were pumped out weekly, manually for

Experiment 1, and using vacuum pumps seen in Figure 3 for Experiment 2. Sub-samples

of were collected in bottles filtered and analyzed for NO3-N. In Experiment 1, a 20 mL

portion of each sample was filtered through a Whatman #42 filter paper for dissolved










phosphorous (DP) determination. Unfiltered samples were digested for total P (TP)

determination (USEPA, 1993). Both DP and TP were determined using the asorbic-acid

method (EPA method 365.3, USEPA, 1993). For experiment 2 samples were stored at

appropriate temperatures prior to analysis at the Environmental Quality Laboratory at the

University of Florida. All values of nitrate and nitrite analyses are reported as NO3-N

here (OI Analytical, 2001).

















Figure1.4. Vcuum umps etractng leahate rom :lysietes osiioed 0 m ude
the eds f Exerimnt 2on sndy oil


Anlysis Metphods





The daa showd an icreasig varincewt nraigtramnepne

Accrdngto(Lma Ot ndLognckr, 01 o rnfrmaio ca I'reduceth

ove esimaionof arinceassciaed ithsmalersamle alus. lo trnsfrmaionc~~









was applied to the dependent variables before statistical analyses were conducted. All

dependent variables were analyzed using one-way ANOVA tests and their means were

compared for treatment effect using the Tukey-Kramer HSD (Honestly Signifieant

Difference) test. This test is an exact alpha-level test if the sample sizes are the same and

conservative if the sample sizes are different (Hayter 1984). Comparisons were made at

the 95% confidence level. The tests were carried out using JMP Version 5.1 software

(Lehman et al., 2004).

The independent variable was irrigation treatment and the dependent variables were

yield, irrigation water use efficiency, volume leached and load of nutrient leached. Crop

evapotranspiration (ETc) for the seasons was estimated by multiplying reference

evapotranspiration (Eto calculated from weather data collected at the sites) by crop

coefficients (Kc) presented by Brouwer and Heibloem (1986) that had been adjusted for

plastic mulch field conditions by a reduction factor of 35% determined by (Haddadin and

Ghawi, 1983). According to Howell (2002) the irrigation water use efficiency (IWUE in

kg/m3) is calculated as the increase in yield due to irrigation divided by the irrigation

water. This is shown in Equation 1.

IWUE = (Y-Yd)/(IRR*1000) [1]

Where Y is the total marketable yield (kg/ha)

Yd is the total marketable dryland or non-irrigated yield

IRR is the applied irrigation water (mm)

The non-irrigated yield is assumed to be approximately zero for plastic mulched

tomatoes in Florida. Yields were the sum of two crop harvests for both experiments. The

first harvest of Experiment 1 was on the 13th of January 2005 and the second on the 26th










of January 2005. Harvests were from 5 m sections of the beds. The first harvest of

Experiment 2 occurred on the 16th of June 2005, and the second harvest was on the 29th

of June 2005. Harvests of the tomatoes for Experiment 2 occurred from 6 m sections of

the beds. The final marketable yields consisted of XL, L and M fruit as graded according

to the Florida Tomato Committee standards, from the two harvests for each experiment.

Results and Discussion

Results will be presented for each experiment, and comparisons and trends between

the two will then be highlighted and discussed to establish trends and draw conclusions.

Experiment 1: Calcareous gravelly soil

The analysis of treatment effects starts on the 29th of October 2004 when irrigation

treatments were put into effect, and ignores the first two weeks of establishment irrigation

that was common to all treatments. Water application over the season for each treatment

are presented in Figure 1.5, along with estimates of crop evapotranspiration (ETc)

estimated from plastic mulch adjusted crop coefficients. As can be seen the water

application for the soil moisture-based treatments matched crop water needs much more

closely than the time-based treatments, and did not over apply water (Table 1.4).

Table 1.4. Water application, yield, and irrigation water use efficiency (IWUE) averages

Treatment Total water applied [z] Water by treatment Yield IWUE
mm mm kg/ha kq/m 3 Water
111 tensiometerr) 169 (a 13) 118 a 49955 a 30 a
112 (Dielectric probe) 101 (1 30) 50 a 40168 a 40 b
113 (time based -ETc) 370 (1 8) 319 b 42191 a 11 c
114 (time based -local grower) 570 (1 90) 519 c 45497 a 8 c
for each treatment in Experiment 1 on calcareous gravelly soil.
? Different letters depict statistically different means for P 0.05 (Tukey-Kramer method)
[z] Total ivater per treatment includes the hour per day of establishment irrigation which ivas treatment independent













700

650 -* 111I (switching tensiometer)
600 -1 -0- 112 dielectricc probe)
-Y 113 (ETc)
550 -6 14 (time based local grower)
500 -1 ETc

E 450-
-rs 400-
5. 350-
S300-
S250-
200-
150-
100-

50

0 20 40 60 80 100

DAT
Figure 1.5. Graph of cumulative season water application for the four irrigation
treatments applied to the gravely loam soils of Experiment 1. Error bars
represent one standard deviation.

Significant differences were found for average water applications between the soil

moisture-based treatments and time-based treatments. Scheduling according to the crop

growth curve Il3 applied less water than the constant rate of Il4 through the season. The

treatment employing switching tensiometers (Il l) provided 71% water savings over the

time-based treatment (114), and the dielectric probe and QIC system (112) achieved 83%

savings over Il4. The dielectric probe and QIC hardware required less maintenance and

labor than the switching tensiometers. The tensiometers had to be refilled on a weekly

basis due to breakage of the water column and loss of connection with the soil water in

the coarse textured soil. This is a common problem associated with tensiometers in










coarse soils. The dielectric probe and QIC were essentially maintenance free and worked

reliably throughout the season once the threshold had been set at the beginning of the

season.

Treatment effect had no significant difference on total marketable yields. Water

use efficiencies followed applied water trends, with the soil moisture based treatments

Ill and Il2 using water more efficiently at 30 and 40 kg/m3 TOSpectively, than the

historical weather time-based and local grower time-based treatments Il3 and Il4 which

yielded only 11 and 8 kg/m3 Of water, respectively. The average nutrient leaching data

by treatments obtained from the lysimeters are summarized in Table 1.5.

Table 1.5. Nutrient leaching data obtained from lysimeters in Experiment 1.
Treatment Volume N-NH4 N-NOz DP TP
Total Treatment Total Treatment Total Treatment Total Treatment Total Treatment
mm mm k g/h a k g/h a k g/h a k g/h a k g/h a k g/h a k g/h a k g/h a
111 49.3 31.7 a 0.04 0.03 a 5.2 3.7 ab 0.24 0.17 a 0.49 0.23 a
112 44.6 12.6 a 0.04 0.02 a 7.6 0.6 a 0.17 0.06 a 0.24 0.08 a
113 137.4 111.0 b 1.3 1.28 b 33.7 30.4 c 0.55 0.46 b 0.8 0.66 b
114 180.8 145.8 b 1.49 0.26b 14.3 10.3 bc 0.71 0.56 b 1.04 0.82 b
t Different letters depict statistically different means for P 0.05 (Tukey-Kramer HSD method)

The volume leached correlated with water application volumes by treatment, with

low water applications of Ill and Il2 having lower volumes of leachate than Il3 and Il4

(Figure 1.6). Correspondingly the ammonia-nitrogen load, dissolved phosphorous (DP)

load, and total phosphorous (TP) load all were all significantly reduced for the soil

moisture based treatments Ill and Il2 over the two time-based treatments Il3 and Il4.

Phosphorous leaching was analyzed in this experiment due to its present

importance in the Miami-Dade County, and to determine the potential of the system to

reduce loading and help with the concerted effort to control phosphorous levels in the

Everglades and surrounding areas. The soil moisture-based schedules Il l and Il2 had

total phosphorous loadings of 0.23 and 0.08 kg/ha during the treatment period and













30 0


-* I1 1 -
2501 -0 112
-Y 113
~-- 114
S200 --



.c 150-


> 100-







0 20 40 60 80 100 120 140

DAT
Figure 1.6. Cumulative average leached volume recorded by the lysimeters per treatment
for Experiment 1 on calcareous gravelly soil.

reduced total phosphorous load by 70% on average over the 0.82 kg/ha loading of the

local grower treatment 114. Dissolved phosphorous leaching load trends were similar to

total phosphorous loads and 79% on average reduction was recorded for the soil moisture

based treatments over the local grower treatment. This could be of great help to the

region in reducing the addition of phosphorous to an already over-loaded system.

Treatment effect was limited for nitrate-nitrogen, and only Il2, the dielectric probe

soil moisture based treatment was significantly lower than Il3, the time-based treatment.

High variability within treatments of the nitrate-nitrogen leached masked differences in

the effect of soil moisture scheduling (Figure 1.7). As such, it could not be deduced that

soil moisture based scheduling was the only factor in leaching differences.











50--



40-
c-* 1111
f-0- 112
-7 1 113_
o -6- 114
a, 30-



0 20-

O

10-




0 20 40 60 80 100 120 140

DAT

Figure 1.7. Cumulative load of nitrate captured in the lysimeters over the season for
Experiment 1 on calcareous gravelly soil.

Experiment 2: Sandy Soil

Statistical analysis of water applied by each treatment and its effects on the

dependant variables for the second experiment started on the 27th of April 2005. Total

water applied included 52 mm of water during establishment that was applied standard to

all treatments and independent of treatment effect. Figure 1.8 shows the water applied by

the different irrigation treatments over the season. There was not replication of the

control system, a single soil moisture probe and solenoid valve supplied water to all four

spatial replicates, which were used to capture soil, yield and leaching heterogeneities.

The summaries of water application, yields and irrigation water use efficiency

(IWUE) are summarized in Table 1.6.






































0 20 40 60 80 100

DAT

Figure 1.8. Cumulative water application per treatment applied over the season to
tomatoes in Experiment 2.

Table 1.6. Water application, yield and water use efficiency (WUE) for Experiment 2.
Treatment Total Applied Water 12 Water by Treatment Total Marketable Yield IWUE
mm mm kg/ha kg/m 3 ae
121 dielectricc probe) sub-irrigation 228 176 30 428 a 13.3 a
122 dielectricc probe) 140 88 33 261 a 23.8 b
123 (time-based practice) 248 196 18 730 b 7.6 a
[z] Total water includes the establishment irrigation of 52 mm (1 hour per day)

The total water applied by the soil moisture based treatment I21, 228 mm, was

similar to the local grower treatment 123 which applied 248 mm, and larger than the 140

mm applied by 122. Both 121 and 123 over applied water and 122 slightly under applied

water when compared to estimated crop evapotranspiration (ETc = 151 mm) calculated

for plastic mulched beds.

The high water application of 121 is an exception to the soil moisture-based

scheduling trends observed in Experiment 1 and in 122. This treatment applied a similar


300 -



250 -



200 -



150 -



100 -


121 (Dielectric probe+sub irri.)
2 21 (Dielectric probe)


--


------ 123 (Time-based local grower)
ar



J









amount of water (10% less) as the time based treatment 123, and was attributed to the

position of the soil moisture probe with respect to the irrigation line. The drip line for

this treatment was buried at a depth of 15 cm under the surface. The probe was however

positioned the same as 122 so that it averaged the soil moisture from the surface down to

a depth of 20 cm. The top 15 cm of soil would have remained dry due to little or no

capillary rise of water in the sandy soil. The probe's position in the drier soil near the

surface resulted in few irrigation events being bypassed and savings were low (only

10%). A future recommendation for this setup of a buried irrigation line would be either

to reduce the soil moisture threshold, or a more recommended practice would be to bury

the soil moisture probe closer to the irrigation line and active root zone. Further study

needs to address the implications of moving the probe within the interconnected wetting

zone of a buried line, and the effective rooting zone.

Significant differences in yield were recorded, and both soil moisture-based

treatments I21 and 122 had higher marketable yields, 30,428 and 33,621 kg/ha

respectively, than 123 which yielded 18,730 kg/ha. The high water application of 121

(buried drip) compared to 122 resulted in the irrigation water use efficiency for 121 being

closer to the time-based treatment 123. Cumulative leaching data is summarized in Table

1.7, and the cumulative volume leached over the season and the cumulative load of

nitrate-nitrogen leached over the season are presented graphically in Figures 1.9 and 1.10

respectively.





























Of- I


0 20 40 60 80 100

DAT
Figure 1.9. Cumulative volume of leachate collected in the lysimeters per treatment over
the season for Experiment 2.


O 20 40 60 80


DAT
Figure 1.10. Cumulative nitrate-nitrogen load leached per treatment over the season for
Experiment 2.










Table 1.7. Average volume leached and nitrate-nitrogen load leached per treatment for
Experiment 2
Volume leached NO,-N Ioad
Treatment Total Treatment Total Treatment
mm mm k g/ha kg/h a
121 (Dielectric probe + subirri.) 20.6 14.5 a 5.8 3.7 a
122 (Dielectric probe) 6.8 5.0 b 6.7 6.2 a
123 (Time-based local grower) 42.8 36.3 c 37.3 34.1 b

t Different letters depict statistically different means for P 0.05 (Tukey Kramer HSD method)

The leaching volume differed significantly for all three treatments. Treatment 121

had a higher leached volume (14.5 mm) than 122 (5.0 mm) during the treatment period,

corresponding to the higher water application, but both soil moisture based treatments

were considerably lower than the time-based treatment 123 (36.3 mm). Total season

leached volumes (including the establishment period) were on average 31% higher than

leaching volumes during the treatment period. The load of nitrogen load leached by the

soil moisture based treatments II and I2 were 3.7 and 6.2 kg/ha respectively and

translated into a 89 to 84 % reduction from 123 (34.1 kg/ha for the treatment period).

Although treatment 121 had high water applications and higher leached volumes than 122,

the loads of nitrate leached were lower, a result of the fertigation line at the surface being

above the buried irrigation line. The irrigation water did not pass through the soil zone

near the surface with highest nitrate concentration. Better correlation of the buried drip

irrigation tape and the soil moisture probe in this treatment would most likely further

reduce leaching due to lower water applications closer to that of 122. The increase in

load of nitrate-nitrogen being leached towards the end of the season in treatment 122 was

due to an increase in water applied towards the end of the season after a late increase in

plant biomass and higher crop water requirements. The increase in irrigation water

applied should not have substantially increased the leaching, as the crop according to soil











moisture status required the water applied. Better knowledge of position of the soil


moisture probe in the root zone may help further reduce the portion of this water that is

leached.


Comparison of results

A summary of the percentage changes in value of the dependant variables of the


soil moisture-based treatments from the time-based local grower treatment are presented


in Table 1.8. Averages for the soil moisture-based treatments are presented to help


highlight the trends when compared to traditional time based practices.

The soil moisture-based treatments applied less water than the time-based


schedules for both experiments. For the treatment period the soil moisture-based


schedule treatments of Experiment 1, Ill and Il2 achieved 77% and 80% water savings


compared to the local grower treatment respectively, and the treatments I21 and 122 for


Experiment 2 yielded 10% and 64% water savings over the local grower treatment


respectively .

Table 1.8. Average values and the percentage change from the local grower treatment for
the dependant variables measured in two experiments of tomatoes
corresponding to different irrigation scheduling treatments.
Soil moisture-based treatments Percentage change from the time based (local grower) treatment
Experiment 1 Experiment 2
Tensiometer ECH20 Average ECH20+sub irri. ECH20 Average
111 112 (1 11+1 12)/2 121 122 (121+122)/2
Dependent variable Gravelly loam Gravelly loam Gravelly loam sand sand sand
Total Irri. Water (mm) -70 -82 -8 -50
Treatment Irri. Water (mm) -77 -90 -10 -64
Yield (kg/ha) 10 -12 62 78
IWUE (kg/m3) 275 400 75 216
Total Vol. Leached (mm) -73 -75 -74 -52 -84 -68
Treatment Vol. Leached (mm) -78 -91 -85 -60 -86 -73
Total Load N-NH4 (kg/ha) -97 -97 -97
Treatment Load N-NH4 (kg/ha) -88 -92 -90
Total Load N-NO3 (kg/ha) -64 -46 -55 -84 -82 -83
Treatment Load N-NO3 (kg/ha) -64 -94 -79 -89 -82 -85
Total Load DP (kg/ha) -66 -76 -71
Treatment Load DP (kg/ha) -70 -89 -79
Total Load TP (kg/ha) -53 -77 -65
Treatment Load TP (kg/ha) -56 -85 -70









A large portion of the water savings occurred in the early part of the season when

the crop was small and water requirements were low. The soil moisture based treatments

minimized water application to suit crop needs during this period, while the fixed time

based schedules over applied irrigation. This can be seen in Figures 1.4 and 1.7 showing

the cumulative plots of water for the season for each experiment. Total water savings for

the full season were similar but on average over both experiments 8% lower than the

treatment period. The water applied during establishment was 52 mm for both

experiments, which was a significant contribution towards the total application for the

soil moisture-based treatments. Irrigation rates decreased dramatically once the soil

moisture-based treatments began to operate, but this did not have an effect on plant

growth. This suggests that the amount of water applied during the establishment period

could be reduced. Further studies could determine what the practical level of

establishment irrigation is needed before irrigation is switched to soil moisture-based

scheduling, without affecting transplant growth and yield. Limiting water to the

transplants must be done so with caution, as the plants roots are small and not well

established. Probe placement at this period is critical.

The irrigation rates for the soil moisture-based treatments were below those of the

crop water requirements as calculated by historical evapotranspiration and crop

coefficients presented in Maynard et al. (2004). Amayreh and Abed (2005) conducted a

study on field grown tomatoes in the Jordan Valley to test the effects drip irrigation and

plastic mulch would have on evapotranspiration and crop coefficients. Their study

showed that crop coefficients using drip irrigation and plastic mulch were 36% lower

than the crop coefficients in FAO 56 which assume a uniformly planted field. These









results match those obtained by Brouwer and Heibloem (1986). This explains the lower

crop needs and subsequent water use of the soil moisture-based treatments compared to

traditional ETc calculations.

Yields from Dade County (Experiment 1) were above the Florida average of 39,295

kg/ha suggested by Maynard et al. (2004), and ranged from 40,000 to 49,000 kg/ha.

Total marketable yields from Experiment 1 were derived from two harvests for the crop.

The Citra County (Experiment 2) yields were lower than average ranging from 18,600 to

33,200 kg/ha. Total marketable yield comprised of two harvests. Poor canopy

development in the plants early stage as a result of disease and some nutrient stress, most

likely reduced yields to some extent. Furthermore, the wettest treatment I4 in the Citra

County (Experiment 2) had yields that were significantly lower than the two soil

moisture-based treatments II and 12. This may be a result of the increased nitrogen

leaching and a loss of nutrient from the root zone of the crop. Another potential yield

reducing factor was that during the middle of the season the plastic mulch started to loose

its physical integrity, and provide incomplete coverage on a few of the beds. Where this

occurred, the bed was recovered with plastic mulch manually. The damage was random,

and did not occur near any instrumentation, but its effect on the yields is not certain. The

mulch is designed to start to break down after a period of time, sufficiently longer than

the cropping season. Reasons for this mulch to weaken after only 7 weeks are not

known. The suppliers were contacted and informed of the problem.

Irrigation water use efficiencies (IWUE) were much higher for the soil moisture

based treatments. Soil moisture-based treatment IWUE's were 275 and 400% higher for

Experiment 1 and 75 and 216% higher for Experiment 2 than the corresponding time-









based local grower treatments. A previous experiment in the Miami-Dade County using

similar soil moisture based scheduling methodology by Mufioz-Carpena et al., (2004)

found IWUE's of between 11 and 40 kg/m3. The high IWUE recorded for Experiment 1

in Miami-Dade County was also 40 kg/m3. This suggests that the methodology has the

potential for consistently efficient water use.

All nutrients tested for leaching showed substantial reductions in total loads of over

55% for the soil moisture-based treatments over the time based treatments. For surface

based drip irrigation and fertigation the volume of water applied appeared to be the

driving force, and volumes of leachate and nutrient loads followed water application

trends. For the sub irrigation of treatment 121 in Experiment 2 the high water and

leaching volumes did not displace much of the nutrients from the soil as the irrigation

was applied below the fertilizer application. The total leachate volumes averaged 74 and

68% lower for the Experiment 1 and Experiment 2 respectively. The lower amounts of

water passing through the root zone did not result in high concentrations of nutrients in

the leachate, as reductions in nutrient loads were equal to or higher the corresponding

reductions in leachate volumes. The highest reductions in nutrient load were recorded for

ammonia-nitrogen (averaged 90% for the treatment period) on Experiment 1 followed by

nitrate-nitrogen (85% for the treatment period) on Experiment 2. The nitrate-nitrogen

leaching in Experiment 1 had variability problems within treatments that may have

masked the results to some degree. The variability was higher for all nutrients in

Experiment 1 and was due to the smaller lysimeter capture area used. The smaller

capture area were more vulnerable to imperfect placement of the lysimeters under the

crop in the beds, but also had a higher variability of number of plants and emitters that










they contained. For future experiments lysimeters with large as possible capture areas

should be used to reduce leaching variability within treatments. This will be of particular

importance when finer soils are tested that have higher lateral movement of soil moisture.

The water applied to Experiment 2 was not replicated for each treatment. The

replications were for yield analysis and to account for soil heterogeneities. It would be

recommended to operate each replicate of the treatments independently in future

experiments. Each replicate would have its own soil moisture probe and control valve,

and give a better indication of the variability associated with the methodology, and help

eliminate the possibility of having one probe in an unrepresentative position for the

whole treatment.

The nutrient leaching data showed trends that correlated with the water application

amounts. Treatments with high water applications yielded higher volumes of leachate

and higher loads of nutrients passing through the root zone into the lysimeters. The form

of nitrogen being applied differed between the two experiments, as Experiment 1 applied

nitrogen in the ammonia form and Experiment 2 applied calcium nitrate. Both nitrate and

ammonia loads of nitrogen were determined from the leachate in Experiment 1 as the

ammonia nitrogen in the lysimeters could stand for as long as three weeks before it was

abstracted, and could undergo nitrification during this period. Both experiments showed

a significant reduction in leaching of nitrate, which is a contaminant of many surface and

groundwater resources in Florida, the US and around the world. The ability of soil

moisture-based irrigation to reduce nitrate loading to local water resources on coarse soils

is high. Further studies need to be conducted to test the effect different soils have on the

methods ability to reduce nutrient loading.









Conclusion

This series of two experiments confirmed the potential of soil moisture based

scheduling to reduce water applications as apposed to traditional time based schedules

and applied water less frequently and in higher volumes. Soil moisture based treatments

applied between 50 and 82% less water than comparative time based schedules which are

typically used for irrigation scheduling. The results show that the reduction in the

amount of water applied can be achieved without significant reductions in yield. The

reduced water application of the soil moisture based treatments translates to a reduction

in both volume of leaching, and the load of nutrients leached. Total nitrate leaching was

reduced by 55% and 83% for the two experiments and total phosphorous leaching was

65% lower. Greater reductions in loads leached (between 70 and 97% for all nutrients)

during just the treatment period were obtained for the soil moisture-based schedules and

suggest that there is potential for further savings at the beginning of the season. Potential

scheduling during the establishment must recognize the practical limits of saving water

and nutrients when the plants roots are limited. The reductions in nutrient losses could

provide a grower with the means to reduce application amounts and thus costs, and more

importantly reduce the risk of surrounding water resources to nutrient contamination.

This is critical to the sustainability of agriculture in Florida and many other areas of the

world, where increasing population and public environmental awareness introduces a

Hierce competition for water resources.















CHAPTER 3
FERTIGATION METHODS FOR SOIL MOISTURE-BASED IRRIGATION OF
VEGETABLE CROPS

Introduction

Commercial vegetable production requires optimal fertilizer and water-use

management for high yields and maximum profits. In most cases nitrogen is the limiting

element to crop growth, especially on coarse-textured soils such as sands and gravels that

have low organic matter (Scholberg et al., 2001). Efficient use of water and fertilizers are

also highly critical for the sustainability of agriculture in increasingly competitive local

and world markets, and in competition with urban environments for resources (Hebbar et

al., 2004). In Florida vegetables are produced on nearly 120,000 ha and fertilizer is

needed for profitable production of high-quality vegetables in the State (Hochmuth,

2000). The optimum management of fertilizer can promote sustainability in several

ways, and application of N and K in excess of crop requirements can have significant

adverse effects (Hartz and Hochmuth, 1996). Firstly, fertilization represents a significant

input cost, accounting for 8 to 10 % of total cost of production for some vegetables.

Secondly, nutrients such as N or K can be lost due to leaching in the sandy soils of

Florida under excess irrigation or heavy rainfall. Finally nutrient management is

important because it reduces the nutrients introduced to the environment that have a

negative impact on the quality of surface and groundwater.

There has been significant work conducted on rates ofN and K applied to vegetable

crops, and tomatoes in particular, and with improved nutrient and irrigation management









the maximum recommended rates have decreased in recent years. Applied fertilizers

used in Florida tomato production averaged 350-225-605 kg/ha as surveyed by the

Florida Agriculture Statistics Service for 1994 (Fla. Agr. Stat. Ser., 1995). These actual

applied rates exceed IFAS current maximum recommendations of 175-150-225 kg/ha N -

P20s K20, found through experiment to meet tomato requirements for high yields based

on soils with low P and K concentrations (Hochmuth and Hanlon, 1995). Achieving the

correct rate of fertilizer application is an essential part of optimal fertilizer management.

This however needs to be coupled with good irrigation practices as the application of

fertilizer and water are interlinked. Poor irrigation management and efficiencies affects

nutrient management. The higher applications of fertilizer than current recommendations

partially balance the effect of inefficient irrigation practices.

Improved Irrigation Management

Modern methods of using soil moisture to schedule irrigation are yielding

significantly improved irrigation water use, and at times has increased yield (Mufioz-

Carpena et al., 2005). A system has been developed by the University of Florida that

utilizes soil moisture probes to schedule on an automated irrigation system (Dukes and

Mufioz-Carpena, 2005). Water savings on average of 60 70% and up to 80% compared

to traditional time-based irrigation have been obtained by multiple experiments on

vegetable crops (tomatoes, bell peppers and zucchinis) on coarse soils in Florida. The

system applies water in small amounts and at frequent intervals (several times per day).

The soil water is kept within an optimal range for plant growth rather than being allowed

to dry out and then be completely refilled by a single large irrigation event. The

improved soil water management in the root zone of the crop decreases the potential for

loss of nutrients by the leaching due to the lack of excess applied water. Other essential









components of optimal fertilizer management are the method of application and the

frequency of application.

Fertigation

Clark et al., (1991) found improved water and fertilizer management using

tensiometers and fertigation with micro irrigation of market tomatoes produced on sandy

soils can result in reduced water and fertilizer applications as compared with current

irrigation methods. This statement brings two points into focus. Firstly as already stated

irrigation and fertilizer management are intricately linked. Secondly that fertigation

using surface and subsurface drip has proved to be in many applications, more effective

at supplying the crop with nutrients as needed by the crop.

Benefits of Fertigation

Dry fertilizers applied under traditional methods are generally not utilized

efficiently by the crop. In fertigation with drip, nutrients are applied through the emitters

directly into the zone of maximum root activity and consequently fertilizer use efficiency

can be improved compared to conventional methods of fertilizer application. Raskar,

(2003) reported significant increases in yields of banana when soluble fertilizer was

applied through fertigation compared to straight fertilizer. Hebbar et al. (2004)

conducted Hield experiments during two summers and found that 100% water soluble

fertilizer applied through fertigation had significantly higher yields than soil applied

treatments. Yields were similar for half-soil and half-fertigated treatments. Fertigation

also resulted in less leaching ofNO3-N and K to deeper layers of sandy loam soil.

Fertilizer Injection

It is important to design the drip irrigation system so that fertilizer inj section can be

achieved in a reasonable amount of time, and the crop is not over watered while









delivering the fertilizer. Concentrated materials are easier to inj ect because of the shorter

injection cycle required, for the same amount of nutrient. Growers should purchase as

high an analysis of liquid fertilizer as possible to avoid applying large amounts of water

(Hochmuth and Smaj strla, 1998). Research on a sand soil in Florida shows that 45

minutes (young tomato crop) to 1.5 hours (mature crop) would be sufficient to apply the

amount of water required by the crop during any one irrigation cycle (Smaj strla, 1985;

Clark et al., 1990). Fertigation and subsequent irrigation cycles longer than 1.5 hours on

a mature crop runs the risk of leaching the nutrients below the root zone. Leaching

occurs after a shorter duration on the gravelly loam soils in South Florida.

Fertilizers may be inj ected as a precisely managed level of concentration, or as a

bulk mass of fertilizer with possible varying concentration levels. Concentration

inj section requires a precise inj section system, and is more costly and complex than bulk

inj section that simply involves the inj section of a desired amount or volume of fertilizer

into the system. The inj section system must be calibrated for the irrigation system it is to

be used within, or else expected applications will differ from actual applications.

Variations in operating pressure, system flow and even temperature can influence the

calibration of the system (Hotchmuth and Smaj strla, 1998).

Fertilizer application schedules

The current preplant fertilizer recommendations are a fraction of the total seasonal

fertilizer requirement, either liquid or dry, applied in the bed as a starter fertilizer for drip

irrigated crops (Hochmuth and Smaj strla, 1998). This starter fertilizer would contain all

the phosphorous (P) and micronutrients, and up to 40% of the N and K. In most cropping

situations approximately 35-45 kg/ha of N and K would suffice (Hochmuth and

Smajstrla, 1998). Maynard et al. (2003) suggested broadcasting all P205, micronutrients,









and 20-25% of the N and K20 in the bed area, for mulched drip irrigated crops. Preplant

application of P is common for at least two reasons. Soluble P sources are more

expensive than granular forms, and the potential problem of chemical precipitation in the

drip line is avoided.

Some research has found that applying some or all the fertilizer preplant provides

higher yields than just incremental applications through the season. This is most often

the case on soils with a higher percentage fine particles or more organic matter. Preplant

application of N (and K, if needed) is particularly important where initial soil levels are

low (Locasio et al., 1985), or where early-season irrigation requirements are low.

Preplanting fertilizer formulas of 6-6-12, 6-3-12 or 10-10-10 are satisfactory (Li et al.,

2002).

Locascio et al., (1997) applied N-K in three different proportions of preplant,

namely 0%, 40%, and 100% to tomato crops growing on an Arredondo fine sand and

only N as above to an Orangeburg fine sandy loam testing high in K. It was found that

the lowest yields on the fine sand occurred for the 100% preplant, intermediate yields for

the 0% preplant (all drip applied), and the highest yields for the 40% preplant and 60%

fertigation. On the sandy loam the highest yields were obtained from 100% preplant,

intermediate with 40% preplant and 60% drip applied, and lowest with all N drip applied.

This suggests that soil texture plays a maj or role in determining what methods of

fertilization are most appropriate.

A further component of the work conducted by Locascio et al., (1997) was to split

the drip applied fertilizer into 6 or 12 equal or variable applications through the season.

The variable application rate had most of the nutrients applied between weeks 5 and 10









after transplanting. For the 100% drip applied N on the sandy soil, yield was higher for

the 12 equal applications than thel2 variable applications of N. While work continues to

optimize rates of N, P and K for different soils, the frequency of fertilizer application and

its effects on nutrient use efficiency remains less well understood. Thompson et al.,

(2003) stated that optimum fertigation intervals for drip-irrigated crops has not been well

researched. A study conducted subsequently by Thompson et al., (2003), found that

broccoli grown on a sandy loam soil did not respond to any increase in frequency of

fertigation using subsurface drip smaller than 28 days.

Frequent inj section might be needed on sandy soils that do not retain large amounts

of nutrients, and for growers that wish to minimize inj section pump size and cost (Hartz

and Hochmuth, 1996). Fertigation frequency however in most situations is not as

important as achieving a correct rate of nutrient application to the crops during a specific

period (Cook and Saunders, 1991). What must be kept in mind is that water management

and fertilizer management are linked. Changes in one program will affect the efficiency

of the other program.

Fertigation coupled with soil moisture-based irrigation

Automation of fertigation within a soil moisture-based irrigation system has the

potential for decreased labor as well as increasing water and nutrient savings. Fertilizer

can be inj ected with precise inj section pumps on an independent automated schedule, or

the fertilizer can be continuously injected using a venturi injector. A drawback of the

automated injection pumping system is its cost. Venturi injectors are low cost devices

that have proven to provide adequately accurate injection rates for fertigation purposes.

Continuous inj section with a venturi means inj ecting fertilizer each time an irrigation

event occurs. The flow of irrigation water across the venturi contraction causes a










pressure differential that sucks a liquid fertilizer solution into the distribution system

(Figure 2.1). Placing the venturi across a pressure-regulating device such as a valve, or

pressure regulator, or pump can enhance the pressure differential. Appendix Al to A4

has different recommended layouts for increasing the pressure differential across a

venturi .

Pressure differential created
across venturi contraction



............... ................ ............. F e rtili z e r
irrigation
water
solutions


Injected fertilizer

Figure 2.1. A venturi injector schematic showing flow directions and operating principle
(adapted from Mazzei Inj ectors Inc.)

The venturi injection rate is relatively insensitive to flow rate, and is controlled

primarily by pressure at the inlet and outlet. Manufacturers such as Mazzei Injector

Corporation provide charts for their different models to calculate inj section rates.

The concentration of fertilizer to be inj ected is determined by knowing the desired

fertilizer application rate, the inj section rate of the venturi, and the inj section time (in this

case the same as the irrigation schedule). For fixed time-based irrigation schedules the

irrigation schedule is predetermined and thus the inj section time is known. For dynamic

soil moisture-based irrigation the duration of irrigation changes according to factors that

effect soil moisture level. The irrigation schedule will vary from season to season when

using soil moisture as the basis for scheduling. An estimate was needed to predict the

water use for the crop over the season. The crop evapotranspiration ETc is the IFAS

recommended method for determining water use. Previous experiments on tomatoes by









Munoz-Carpena et al. (2004) and (2005) reported consistent savings for two consecutive

experiments in the Miami-Dade County on tomatoes with the QIC and dielectric probe

soil moisture-based scheduling over the ETc schedule. The savings were 51% and 58%

for two experiments conducted during the winter seasons on Krome soil. By using

results of water savings by soil moisture based irrigation scheduling over ETc scheduling,

derived from experiments conducted by the University of Florida, expected water

applications can be derived. From these water applications, fertilizer solution

concentrations can be determined for a known inj section delivery rate.

The aim of this research was to 1.) To test the management possibilities of

continuous fertigation coupled with soil moisture irrigation scheduling, 2.) Compare the

continuous ferigation with fixed event fertigation in terms of seasonal application rates,

labor and management requirements, and crop yield, and 3.) Make recommendations for

future research.

Methods and Materials

Fieldwork was conducted for two years to test the continuous fertigation method.

Both experiments were conducted on tomato crops, the first over the 2004/2005 winter

cropping season in South Florida on a calcareous gravelly soil and the second during the

2005 spring season in Central North Florida on a sandy soil. For each experiment fixed

event fertigation applied through drip lines was compared to continuous fertigation

integrated into a soil moisture-based irrigation schedule also applied through drip.

Tomatoes of the variety 'FL 47' were cropped on raised beds with plastic much spaced at

1.83 m. Sorghum-Sudan grass was grown as a cover crop the season prior to tomato

cropping for each experiment.










Experiment 1: South Florida gravelly soil

This first experiment was conducted during the winter season in South Florida at

the Tropical Research and Education Center, in Miami-Dade County on a gravel soil.

The Hield was divided into two regions, an Experiment Plot, and a Demostration Plot for

different purposes. The Experiment plot had different irrigation water scheduling

treatments and was used to determine the effects of scheduling methods on water use,

yield and leaching. Fertigation was conducted through a separate distribution system to

the irrigation water, and fertilizer was applied equally to all treatments on a Eixed time-

based schedule. The Demonstration Plot tested continuous fertigation coupled with soil

moisture based irrigation, and provided visitors to the Hield with a display of a system

working as it would in practice. Fertilizer was applied as fertigation through the same

distribution system as the irrigation water. All injected into the same line that supplied

the irrigation water. All injection of the fertilizer for fertigation of this experiment was

carried out using venturi inj ectors (model no. 484, Mazzei Inj ector Crop., Bakersfield,

CA). The venturi injectors were installed across 10 m pressure regulators to help develop

adequate pressure differential (Figure 2.2 and 2.3). A downstream pressure of 10 meters

was chosen to minimize the pressure in the lay flat and thus reduce leaks but maintain

sufficient pressure for the drip tapes that were rated at 7 m operating pressure. The

upstream pressure to the venturi was the pressure inside the well tank of 25 m. The 484

model of Mazzei venturi inj ectors have an ideal documented inj section rate of 64 L/hr

when with an upstream pressure of25 m and a downstream pressure of 10m. This can be

seen in the tables (Mazzei Inj ector Inc.

http:.//www.mazzei .net/agri culture/tabl es/Performance%20Tabl e%20Metri c. pdf) in

Appendix A4.



































Figure 2.2. Pumphouse hardware layout for Experiment 1


Figure 2.3. Ventun injectors placed across pressure regulators for at
differential.










The inj section hardware was installed and the distribution system was connected so

that the venturi could be calibrated and actual injection rates could be determined for

fertilizer inj section scheduling and for comparison to the ideal documented rate. The

calibration consisted of inj ecting a known volume of water and quantifying the time to

inject this volume. The test was conducted three times for each venturi. The rates and

measures of variability obtained from the calibration are presented in Table 2.1i.

Table 2.1i. Venturi inj section rates and variability of inj section rates from a calibration test
conducted prior to the transplant of the tomato crop on Experiment 1
Ve ntu ri n um be r 1A 1B 2
Experiment Plot Demonstration Plot
Ave rag e injectio n (L/h r) 55.8 48.7 58.2
Stdev (L/h r) 1.4 0.6 0.6

The variability of the inj section rates for a particular venturi were very small and

had coefficients of variation of 0.024, 0.013 and 0.010 L/hr for venturi 1A, 1B and 2

respectively. The variation of the injection rates between the three inj ectors can be

attributed to a combination of

* Different downstream distribution systems (causing different downstream system
pressures)

* Some air being inj ected with the water

For both plots, 60 kg N/ha was applied preplant together with all the P required for

the season. Liquid urea based fertilizer of solution 4-0-8 (N-P-K) inj ected by the venturi

inj ectors supplied the remaining fertilizer. For the Experimental plot the liquid fertilizer

was diluted to a 50% solution and inj ected on the fixed time schedule independent of the

irrigation. A 50% dilution rate achieved maximum fertigation rates for the season within

30 minutes of inj section. The total fertilizer application for the season was designed to be

200 kg N/ha (175 lb N/ac).









For the Demonstartion plot' s continuous fertigation method integrated within the

soil moisture based irrigation scheduling, the irrigation schedule had to be predicted. It

was estimated from previous experiments conducted by Munoz-Carpena et al. (2004) and

(2005) that the water application for the soil moisture-based scheduling would be 40% of

theoretical crop evapotraspiration (which overestimates actual crop water needs for

plastic mulched beds). This estimate of water application (40% of theoretical ETc) was

divided over the season according to the crop curve. The total design fertilizer

application for this plot was 266 kg/ha (237 lb/ac). The required dilution of 4-0-8 liquid

fertilizer was initially 15% for the first 1 1 weeks of the season and then 1 1% for the last 2

to 3 weeks when fertilizer rates are reduced.

The actual fertilizer rate applied to the crop by the venturi's on the time-based

schedule for the Experiment Plot, was 196 kg/ha (174 lbs/ac) which complied very well

with the IFAS recommended 175 lbs/ac. The continuous fertigation method in

Demonstration plot applied 285 kg N/ha (250 lbs N/ac) that was comparable to the

desired rate of 266 kg N/ha (237 lbs N/ac) by the procedure just mentioned (Figure X).

Yields for continuous fertigation coupled with soil moisture-based scheduling were

similar to yields achieved by treatment emulating local growers, and averaged 47 260

kg/ha (42 100 lbs/ac) and 45 110 kg/ha (40 180 lbs/ac) respectively.

A second experiment was conducted the following spring to further test the

continuous fertigation method on a different soil and season, and using a different

fertilizer.

Experiment 2: North Central Florida sandy soil

Tomatoes were grown on a fine sand soil using plastic mulched beds in North

Central Florida at the Plant Research and Education Unit in Citra County. For this









experiment, the continuous method was tested against an inj section pump, which was

manually operated to injected fertilizer once a week (Figure 2.4).


j/ Injection pump ~


I


Fertilier~ solution iii








Figure 2.4. Weekly manual inj section of fertilizer solution carried out using a peristaltic
pump for Experiment 2.










For the manual inj section treatment, the season total calcium nitrate that

corresponded to IFAS recommended rate of nitrogen, was divided into weekly

increments that were small in the early season and increased towards the end of season.

These weekly increments were weighed out and dissolved prior to inj section with a

peristaltic injection pump (Figure 2.4). Muriate of potash was the source of potassium

for the crop. If left to stand, a solution of calcium nitrate and mutriate of potash forms a

precipitation. As such no potassium was added to the continuous injection treatment's

tank and the potassium was manually inj ected using a pump for both treatments.

Nitrogen in the form of calcium nitrate was dissolved in solution and continuously

inj ected from a storage tank with a venturi (model no. 285, Mazzei Inj ector Corp.,

Bakersfield, CA). The system was similar to that of Experiment 1 and the venturi was

placed across a 10 m pressure regulator. Again water application using the soil moisture-

based irrigation schedule was predicted to be 40% of ETc.





250

200

15 -*-N2 weekly manual
N4 continuous

100

50



29-Mar 18-Apr 8-May 28-May 17-Jun 7-Jul

Figure 2.5. Cumulative nitrogen rates comparing continuous and manual fertigation
treatments in Experiment 2 on sandy soil.










The plot of fertilizer applied through the season (Figure 2.5) shows how although a

constant concentration of fertilizer was inj ected for the continuous fertigation treatment,

the rate of application varied considerably through the season. Nutrient application rate

was below the desired rate for most of the season. Lower than average temperatures

during this period reduced evapotransoiration and corresponding irrigation amounts

based on soil moisture. Because irrigation drives the fertilizer injection the fertigation

was also low. The increase in application rate later in the season (from 7th JUne Onwards)

can be attributed to an increase in irrigation as a result of increased evapotranspiration.

The increase in evapotranspiration was the result of increasing biomass and plant cover,

and a period of warmer weather conditions in early summer.

The continuous fertigation system integrated within soil moisture-based irrigation

is very successful at providing a system that is low cost with low labor and management

requirements during average years and conditions. Due to the coupled nature of the

water and nutrient applications the system is however vulnerable to weather and any

other conditions that cause deviations from expected irrigation application. The lower

irrigation water application itself is not the problem, as the crop may have needed less

water due to cooler conditions. The soils moisture-based scheduling applies water as

needed by the crop. The potential harm is the lower fertilizer application induced by

lower irrigation amounts. The crop may have required less water but not less nutrients.

Combining continuous methods with scheduled fertigation

A solution to the problems of fertigation within a soil moisture-based irrigation

system is to combine the best components of the two methods of continuous fertigation

and fixed schedule manual inj section. The benefit of the continuous fertigation is the low

cost of the venturi inj ector and the ease of management and low labor requirements. By









decoupling the fertigation from the irrigation scheduling based on soil moisture, the

systems vulnerability to extreme weather and conditions is mitigated.

Soil moisture-based irrigation as practiced by the University of Florida uses an

irrigation timer to schedule potential events. These prescheduled events trigger a soil

moisture probe to be queried. If soil moisture is below a set threshold a solenoid valve is

opened and the event initiated. If the soil moisture is above a set threshold, then the

event is bypassed and water saved. For vegetable crops the maximum daily water

requirements are divided into 4 or 5 sub-events. To implement continuous fertigation

with a venturi on a fixed schedule, one of the sub-events is dedicated to fertigation

independent of soil moisture status. Any of the sub-events within the day could be used

for fertigation as they are all sufficiently short to avoid excessive leaching and nutrient

loss. Herdel et al. (2001) state that the uptake of nutrients and nitrate in particular is

dependent on plant-internal relations and not nutrient availability, but is three times

higher during the day than at night. The first event of the day is the most appropriate as

subsequent irrigation events may be bypassed if the water for fertigation wet the soil

sufficiently. If the fertigation event were later in the day, the soil may already be wet

from prior events, but water will still be added by fertigation, increasing the potential for

leaching. Furthermore, the first event of the day is the most likely due to drying out of

the soil (although at a somewhat lower rate than the day), and the best time for a fixed

event.

The recommended control and distribution system hardware for fixed continuous

fertigation within a soil moisture-based irrigation schedule is presented in Figure 2.6.










Soil Moisture
Prob~e S l i




Solenoid
Valve 2 oeni



VValve 3
IW : =:"\Solnoi Vave 3oleoid Liqluid fertilizer
Irrigation Tirner source




_] Solenoid Valve

Pressure regulator

31 Venturi injector





Figure 2.6. Fertigation system for decoupled time-based fertigation and soil moisture-
based irrigation.

Solenoid valve 1 is opened and closed by a quantified irrigation controller (See

Figure A5 in Appendix A), which interfaces the soil moisture probe with a RainBird

ESP-12LX irrigation timer. Solenoid valves 2 and 3 control the single fertigation event

per day and are operated simultaneously by an independent schedule on the RainBird

Timer. A potential schedule that would be programmed into the timer is shown in Table

A6 in Appendix A.

Additional fertigation information

Florida Law requires that a backflow prevention system be installed on most

irrigation systems when chemicals are being injected. When the water supply is not

public water, irrigation wells for example, the minimum backflow prevention system










requires a check valve, low pressure drain, and vacuum breaker on level piping between

the point of inj section and the irrigation pump to prevent water and chemicals flowing

back to the water source (Smaj strla et al., 1985). No backflow prevention is required if

the water source is not public water, and no chemicals are inj ected into the irrigation

system (Smaj strla et al., 1994). To extend the life of the system, and to maintain high

irrigation uniformity by keeping the emitters unblocked, a filter should be placed after the

fertilizer injection. A 200-mesh size disc filter should be used.

Fertilizer should be purchased that is soluble and quickly available to the plant.

Some liquid fertilizers are slow release and although my be effective at reducing leaching

for single large applications are not suitable for daily inj section when the nutrients are

applied as the crop needs them. Suitable formulations are 4-0-8 (N-P-K) liquid fertilizer,

and soluble potassium nitrate (KNO3). Suggested IFAS daily fertigation rates are

presented in Table 2.2.

Table 2.2. IFAS suggested daily fertigation rates for tomatoes.
Daily Injection rate
Week after Nitrogen Potassium
transplant N (lbs/ac) N (kg/ha) K (lbs/ac) K (kg/ha)
1 and 2 1.5 1.7 1.5 1.7
3 and 4 2 2.2 2 2.2
5 through 11 2.5 2.8 3 3.4
12 2 2.2 2 2.2
13 1.5 1.7 1.5 1.7
Season total 200 225 225 253
t When 2500 total N and K is applied preplant, the first two weeks can be omitted.

To adjust the fertilizer application to follow crop growth and needs it is easier to

adjust the fertigation time on the controller than it is to change the solution of a large

volume of fertilizer in the tank. The concentration should be set so that the longest

fertigation event is similar to the length of the sub-daily events. To ensure that the

venturi is working correctly and that nutrients are reaching the crop, a simple check is to









record and check the level of the fertilizer solution in the tank. The level can be

compared to design levels that can be easily calculated from the inj section schedule and

venturi inj section rate.

Conclusions

Soil moisture-based irrigation has high potential for water savings and accurate soil

moisture management for optimal crop growth. Fertigation combined with soil moisture-

based irrigation can reduce leaching of nutrients and delivers nutrients to the root zone of

the crop. Continuous fertigation is a viable low cost and labor method that is driven by

irrigation water application. When coupled with soil moisture-based irrigation

scheduling it requires a prediction of season irrigation amount to determine

concentrations to be applied for the upcoming season, and is vulnerable to weather, crop

and soil effects that may reduce evapotrasnpiration and thus irrigation amount.

Decoupling the continuous fertigation from soil moisture-based scheduling gives the

system the reliability of a time-based schedule, while maintaining the benefits of both soil

moisture-based irrigation and low cost and labor fertigation. The two operations remain

connected as the water that is applied with the fertilizer during fertigation contributes

towards the soil moisture and irrigation is scheduled accordingly.















CHAPTER 4
DIELECTRIC CAPACITANCE SOIL MOISTURE PROBE CALIBRATION AND
SPATIAL SOIL MOISTURE DYNAMICS STUDY

Introduction

Optimal management of irrigation requires systematic estimation of soil moisture

status to determine both the volume and timing of irrigation. Soil water content must be

maintained between specific lower and upper levels so that water is not limiting to plant

growth, but leaching is prevented (Morgan et al. 2001). Measurements of soil moisture

status under irrigated crops over time is part of integrated management that aims to

minimize the economically detrimental effects of both under and over-irrigation on crop

yield and quality, the environmental costs of wasted water and energy, and impaired

water quality due to leaching. Integrated irrigation management to achieve optimal soil

moisture levels may be accomplished by utilizing soil moisture monitoring devices in

conjunction with rainfall records and knowledge of plant needs (Munoz-Carpena et al.

2002).

When using drip irrigation to apply water to the crop, the volume and profile of soil

wetted by a single emitter is important. This must be known in order to determine the

total number of emitters required to wet a large enough volume of soil to ensure that the

plants water requirements are met. The volume of soil wetted from a point source is

primarily a function of the soil texture and structure, application rates and the total

amount of water applied (Lubana and Narda, 1998). Sandy soils also have low amounts

of total soil water, and narrow ranges of plant-available soil water. Morgan et al. (2001)









found that the range of 100-50% plant available soil water in Apopka sand, a fine sand

found in Florida, was only 0.08-0.045cm3Cm-3 Soil water content by volume and -5 to -

15 kPa soil water tension.

The wetting profile in the root zone is dynamic and affected by crop root

interactions with the soil. As the crop biomass increases, evapotranspiration will increase

and use more of the volume of water in the wetted profile. Crop and system factors that

can affect the dynamic wetting profile and soil water volume other than soil hydraulic

properties and emitter delivery rate are crop growth stage, root length and structure, and

mulch type when mulches are used. The volume and shape of wetting profiles is not only

important for emitter spacing and system design, but is important for soil moisture-based

scheduling using soil moisture sensors. According to Lubana and Narda (1998) very

little attention has been paid to the estimation of soil water distribution during drip

irrigation under realistic field conditions.

Due to the very vertical movement of water in coarse soils such as sand, large soil

moisture gradients can exist across a small horizontal distance. Sensors placed in two

positions only 15 cm apart within the wetting zone of an emitter can have very different

readings during and after an irrigation event. Sands are often water repellant and

according to Bauters et al. (1998) research has shown that water repellant soils and sands

have unstable wetting fronts and finger-like wetting patterns. These wetting patterns are

generally directly related to the soil moisture retention curve (SWRC). It has also be

shown (Kutilek and Nielsen, 1994) that laboratory determined SWRC's are significantly

shifted to larger soil moisture values for given soil matric potentials compared to those

obtained under field conditions. The differences between laboratory and in-situ SWRCs










are generally thought to be a result of a combination of entrapped air and/or alteration of

bulk density in the laboratory samples.

Because sensors provide the data that drives the automatic control of soil moisture

based irrigation they are an extremely important component, and understanding the

operating principles of a sensor and the effects of soil type on its performance is

imperative (Zazueta et al., 1994). Poor sensor position that does not represent

demographic soil moisture conditions in the root zone can either result in crop water

stress, or over irrigation that negates the water saving capabilities of soil moisture

scheduling. From field experiments conducted on two tomato crops, it became

increasingly apparent how important knowledge of the effects of sensor placement

position within the plastic mulched bed was for precise and reliable soil moisture

management on coarse soils.

The University of Florida has tested different types of sensors on plastic mulched

vegetable crops. Munoz-Carpena et al., (2005) found that switching tensiometers worked

well but required consistent refilling and maintenance, and granular matrix sensors

behaved erratically due to slow response times. A dielectric capacitance probe (ECH20,

Decagon Devices Inc., Pullman, WA) has proven to work reliably with low maintenance

and is considerably lower cost than TDR sensors. A general calibration curve is available

for the ECH20 probe for sandy loam soils and accuracies of up to 1% soil moisture

content by volume can be achieved using the general calibration curve for most soils.

This equation for this linear curve is presented in Equation 4. 1.

Soil moisture = 0.0007*mV 0.29 [4.1]










Campbell (2005a) has advised that a soil-specific calibration be conducted on soils

with high sand or salt content. Campbell (2005b) has also noted a linear response of

sensor out put to temperature, although recommends that temperature effects in soils are

small due to the mediating effect of soil on temperature fluxes. Campbell (2005c) found

that the ECH20 probe was generally not affected by low salinity on most soils, but

readings of soil moisture deviated significantly from actual values on sandy soils with

high salinity.

Considering the lack of knowledge of soil moisture profies within the dynamic

emitter-root zone continuum, the low plant available water content of sandy soils, and the

importance of good data from a soil moisture probe for soil moisture-based irrigation

scheduling, an experiment was conducted on the sandy soils at the plant science research

and education unit (PSREU). The aims of this experiment were to:

1. Calibrate the ECH20 soil moisture probe for the fine sand soils found at the Plant
science research and education unit.

2. Derive an in-field soil moisture characteristic curve for the Eine sand

3. Gain knowledge of the spatial variability of soil moisture within the root zone of a
plastic mulched crop and its corresponding effects of probe placement position on
irrigation scheduling

4. Determine the effects of factors that may influence the dielectric capacitance
probes mV readings

Methods and Materials

An irrigation Hield trial on a zucchini crop was conducted during the fall season at

the Plant Science Research and Education Unit in Citra County, Central North Florida.

The irrigation experiment was conducted to test the effects of soil moisture-based

scheduling compared to regular time based scheduling on water and nutrient use for

plastic mulched vegetables. The soil moisture-based treatments employed dielectric











capacitance probes (ECH20, Decagon Inc.) interfaced with an irrigation timer (RainBird

ESP-LX12, Rain Bird Corp.) using quantified irrigation controllers (Dukes and Munoz-


Carpena, 2005). The soil moisture probe is queried by the quantified irrigation controller


(QIC) every time a prescheduled irrigation event is to occur, and depending on if the soil

moisture status is above or below a set threshold, the event is initiated or bypassed. Daily


irrigation was divided into four possible sub-daily events. This provides the crop with


high frequency low volume irrigation, which has shown to manage soil moisture in a

more optimal range and reduce water and nutrient losses due to leaching than traditional


high volume low frequency irrigation methods (Munoz and dukes papers). To achieve

the optimal range of soil moisture for plant growth the soil moisture probe needs to:


* Have adequate accuracy for the application
* Be correctly calibrated for the particular soil type
* Reliable, and preferably low maintenance
* Positioned within the root zone of the crop.







Sensor
(capacitance Electro-magnetic field
plates) (volume of soil that
contrinutes to reading)
-12cm













Photograph Schematic


Figure 4.1. ECH20 dielectric capacitance soil moisture probe (Decagon Devices Inc.,
Pullman, WA).









The dielectric probe being used for the experiment has an accuracy of typically &

0.03 m/m or (3% volumetric moisture content) and a resolution of 0.002 m3/m3 (0. 1%).

With soil-specific calibration accuracies off 0.01 m/m are possible Campbell (2005).

The probe dimensions (Model EC-20 in Figure 4.1) are 25.4cm x 3.17cm x 0.15cm. The

probe determines the soil moisture from measures of the bulk conductivity of the soil in a

region of soil approximately 2 times the width of the probe (4cm) and averages the

reading across the length of the shaft (Figure 4.1i). The manufacturers provide

calibrations for basic soil types, but a soil-specific calibration of the probe was conducted

to improve the accuracy of the soil moisture data being used to schedule irrigation and

monitor soil moisture for research purposes. The calibration was conducted in the field,

as laboratory studies often do not correlate with real conditions in the field. The in field

calibration would also allow a comparison between the soil moisture probes being used to

collect data and the probes scheduling the irrigation. A check could be made to test

whether the threshold for irrigation scheduling corresponded to appropriate soil moisture

levels.

To determine the spatial variability of soil moisture in the area that probe

placement has conventionally been used by the University of Florida, square grids of nine

dielectric capacitance (ECH20) probes spaced 14 cm apart were replicated in three beds

of various irrigation scheduling treatments. The grids were centered directly between

two plants, which were planted about 10 cm away of the drip line (Figure 4.2). This was

the same position used for the single dielectric capacitance probe that was scheduling

water to the crop.









Nests of 3 TDR probes and 2 tensiometers fitted with pressure transducers were

positioned between the next two plants to obtain measures of volumetric soil moisture

content and soil moisture tension to derive a soil moisture release curve and against

which to relate the output of the dielectric capacitance probes. These nests were also

replicated three times. All probes were connected to Data loggers (CR10X, Campbell

Scientific, Logan, UT) and recorded at 15-minute intervals.


Figure 4.2. Grid of nine ECH20 probes placed between two actively growing zucchini
plants to determine soil moisture distribution for probe placement in soil
moisture-based irrigation











I


Figure 4.3. TDR nest to measure soil moisture for corresponding to mV irrigation
threshold set point.

Once a sufficient period of data was obtained to determine the spatial distribution

of soil moisture using the grid of 9 dielectric capacitance probe grids, the probe

configurations were changed to calibrate the dielectric capacitance probes mV output

against the TDR soil moisture readings. Because the instruments were initially placed

between two different plants with potentially different drip emitter positions, direct

relations between soil moisture and mV readings were giving highly variable results. The

dielectric capacitance probes were moved next to the TDR probes, as close as possible

without interference. Two dielectric capacitance probes were placed next to each TDR

centered between two plants and replicated twice for treatments II and 12. The

replications were to help determine the inherent variability that exists due to different










plants, emitter positions and possibly even soil moisture characteristics of the soil along

the length of bed. A mean soil moisture vs dielectric capacitance probe mV curve could

then be derived which may better describe the probe soil relationship.

The irrigation system that was providing the crop with water was designed to

maintain soil moisture within as close to optimal soil moisture conditions as possible.

While this was good for the crop, it was not possible to derive extreme points for the soil

moisture release curve, namely the very dry and very wet regions of the curve. To obtain

these points, instruments were installed at the end of a bed, and once sufficient irrigation

had been provided to establish the plants containing the instruments, the irrigation was

terminated. Three tensiometers and three dielectric capacitance probes were installed

between two plants (Figure 4.4). The plants in this portion of the bed continued to

transpire and the soil moisture dropped towards wilting point. The probe cables were not

long enough to reach the ends of the beds from the CR10X data loggers. According to

the dielectric capacitance (ECH20) user manual posted by Decagon Devices Inc. (Anon,

2005), any data logger that can produce a 2.5 to 5V excitation with approximately 10-

millisecond duration and read a volt-level signal with 12-bit or better resolution should be

compatible with the ECHO probes. The current requirement at 2.5V is around 2mA, and

at 5V it is 7-8mA. As such a small Hobo data logger (HOBO event logger, Onset

Computer Corp. Inc., Bourne, MA), was used to power and record the ECH20 probes

output. The small data loggers have the capacity to simultaneously record four separate

readings. It was found however that the first port had insufficient excitation period to

power up the ECH20 probes and that good data was obtained for the other three probes.

This method of data capture can provide a small low cost alternative to standard data









loggers, especially for a few remote probes. The only maintenance needed was replacing

the batteries. The batteries life was determined by the logging interval. Logging every

15 minutes, the batteries only needed to be changed once during the season (13 weeks)

when three probes were operating. To ensure correct operation of the logger, it was

placed in a watertight container (zip-lock bag) and covered with aluminum foil to prevent

overheating.












ECH20 Prais
,,,,, ,~ 1*2 probw*


;t HibdlFlge
Fiue .. et fdilcti cpctac poesadesimtesusdt geeatth
drie ponso h olmituerlaecrefrth esn tPRU

The prob net an oiin sdgv odiniaino h olmitr









distribtoni a4 plantso deentrire rooct zne anbe indtensivepobelaotwas instled towgneardst





then end of the crop season once the roots had reached maturity in spatial distribution. A









grid containing 33 dielectric capacitance probes was installed in one of the beds, and the

fertilizer was terminated to this bed to avoid any salinity effects on the soil moisture

readings. The grid covered the whole width of the bed, and was spread between three

plants, completely covering the root zone of the middle plant (Figure 4.5).




21 16 11l jl 1

















_inz th otzon of e a, matur zuchin cro in plsi muce e








regreesetaton Pof te spaialo disletribuins firsctac pord o eer Loes spatial smothngfuctio




was applied to the data to generate a smooth 3-D image due to the distances between

point readings.










Presentation of Results

The results obtained over a 5-week time by the grids of nine dielectric capacitance

probes in treatments II, I2 and IS are presented in Figures 4.6, 4.7 and 4.8, respectively.

Figures 4.6 and 4.7 show distinct daily and weekly patterns while Figure 4.8 is less

ordered but still displays some weekly trends. The daily pattern corresponds to the

irrigation events during the day that keep the soil in a relatively constant soil moisture

range. Some drying out of the soil occurs during the night when evapotranspiration,

although reduced compared to the day, continues. Weekly spikes in mV readings,

appeared correspond to fertigation events that occurred once a week on Thursdays. The

fertigation events were independent of soil moisture, and occurred simultaneously during

the day when irrigation events occurred due to soil moisture status. These events injected

fertilizer into a separate drip line designated to fertigation. The fertilizer was applied as a


9000


800


700






4 00 -/111 1 I -lE


300 ~ lE



10/25/05 10/30/05 11/104/05 11/109/05 11/14/05 11/19/05 11/24/05 11/29/05 12/04/05
Date

Figure 4.6. Dielectric capacitance probe readings for different spatial positions within the
root zone of a plastic mulched crop irrigated using a 475mV set-point.











900



800



700



E600



500



400


300 '
10/25/05 10/30/05 11/14/05 11/19/05 11/14/05 11/19/05 11/124/05 11/129/05 12/4/05
Date

Figure 4.7. Dielectric capacitance probe readings for different spatial positions within the
root zone of a plastic mulched crop irrigated using a 525mV set-point.


V


9000



800



700












400


25-Oct-05 30-Oct-05 4-Nov-05 9-Nov-05 14-Nov-05 19-Nov-05 24-Nov-05 29-Nov-05 4-Dec-05
Date


Figure 4.8. Dielectric capacitance probe readings for different spatial positions within the
root zone of a plastic mulched crop irrigated using a 475mV set point, with
fertigation at the surface and irrigation applied through a drip line buried at 15
cm.


-I


300










solution of the weekly requirements and injected using a peristaltic pump. Fertigation

took approximately 15 minutes. This included a short period of irrigation before the

inj section of fertilizer to raise the delivery system to operating pressure, and

approximately 5 minutes of irrigation after injection was Einished to flush the delivery

system. What is not quantified is the possible effect of the salts added to the soil near the

probes on mV reading.










S-Linear Fitl

0.12 "TDR= 0.0006*ECH20 -0. 1901







500 600
ECH20 mV

Figure 4.9. Bivariate plot of TDR and dielectric capacitance probes to obtain a linear
relationship between soil moisture and mV. 95% confidence intervals are
shown.

The soil moisture vs mV output from the dielectric capacitance probes was plotted

for Hyve TDR and dielectric capacitance replicates. From these the average linear curve

together with the 95% confidence intervals obtained from the spread of data (Figure 4.9).

The soil moisture release curve presented in Figure 4. 10 was obtained by plotting

soil moisture measurements from the outer bed probes. Dielectric capacitance mV

readings logged by the hobo data loggers were converted to soil moisture using the

calibration presented in Figure 4.9, and plotted against manual tensiometer readings.










The soil moisture relation in Figure 4. 11 was generated by plotting TDR readings

against tensiometer readings and gives an indication of the variability in these quantities.

The curve presented in Figure 4. 10 is plotted with the data in Figure 4. 11 and lies within

the spread of data points. This suggests that the soil moisture values extracted from the

dielectric capacitance probes using the calibration curve correspond with TDR data, and

that the hobo data logger was successful in capturing dielectric capacitance output data.

A slight correction was made to the curve presented in Figure 4.10 by adjusting the drier

points on the soil moisture release curve to better fit the data in Figure 4. 11. This

corrected curve and a fitted model is presented in Figure 4. 12. Extension of the curve in

both the very wet and very dry direction will require further studies during a period when

irrigation and soil moisture is not managed and kept within a certain range. The curves

presented in Figure 4. 10 and 4. 11 are derived from field measurements of soil moisture

using dielectric probes and will have some random errors common for dielectric soil

moisture measurements.




















O 5 10 15 20 25 30 35 40 45 50
Tension (cbar)
Figure 4. 10. Soil moisture release curve obtained from in-situ measurements for the fine
sand at the Plant Science Research and Education Unit in Citra County.
















































Figure 4. 11. Plot of soil moisture release curve obtained from manual tensiometer
readings and data obtained from nests of tensiometers and TDRs.


0.20


0.18 -


- y = (a + x)/(b + cx)
Where
a =13.0728
b =-42.5254
c = 23.6761


*TDR vs Tensiometer


0.06- -


0.04
0 10 20 30 40 50

Tension (cbar)

Figure 4. 12. Soil moisture release curve and fitted model derived by ECH20 data and
the calibration curve, corrected from nested tensiometer and TDR data.


Pn





BI-






E
5
I
P
e
nr
a


8~




a,17~i


1~35


--- 44; 75


Tambon [char)


~B W 10 IU


0.16 -


0.14 -


0.12 -


0.10 -


0.08 -


+mp~da~
5~615










Having field calibrated the dielectric capacitance probes mV output for the soil at

PSREU, the grids of dielectric capacitance probes outputs were plotted as soil moisture in

2 and 3D graphs. Figures 4. 13 and 4. 15 display the spatial distribution of average soil

moisture for the 9 probe grids as positioned in Figure 4.2, in treatments II and I2

respectively. The average soil moisture was calculated over the period 14 48 DAP.

Figures 4. 14 and 4. 16 show the standard deviations of the soil moisture in treatments II

and I2 to display the temporal variability and how it changes across this portion of the

root zones.











Sil nat- IrgrIta:In lin and ermula







Fiue41.Vraiiyo si osuewti h oe ewe w uciipat
irigte bysi osuebsddi rigto trsod45m)oe
period of weks












m.,,,~ Irgation Ilne and editor
ISall me.Ibsur

mmI







Fiue41.Aeaesi osuedsrbtinbtentozchn lnsi lsi
muce e sn si osuebsd rpirgto (hehl 2 V

So A m. F..., ..a: rs te













Figure 4.16. AVariabiito soil moisture witibthin tezn between two zucchini plants i lsi
irrigaed bydusn soil moisture-based drip irrigation (threshold 525 mV) oe
period of1i~ 5 weeks.rlmit
Thel reut ro h omlt pailaalsso he ol osur cosh beds

usig he 3 ielctic apcitnc prbe tht ncopase lr8theA entre~l ~rootr zon ofra~
plbant ispeetdasolmitrinFgr4.7ansolmitrvaibltiniue
4.18. ~.ad













)O



lo



I II

E
la
--u



( n


P;l~snt
~05111i~


.ld


IO kr


x ~i~ tR1]


Figure 4. 17. Average soil moisture distribution for the root zone of a mature zucchini

plant irrigated by soil moisture-based scheduling (threshold 475 mV).


Stdev soil
rnoisture

aga0000
usO002
g0 004
lo o 00
O 008
~O 010
O 012



Drip lie







Plant

position


S0 006

0 004

O 002



-0002






0014

Stdev soil
moisture


-0-


YDara


Y -30
30


-20 -10 0
x Data (m)


10 20


Figure 4.18. Soil moisture variability for the root zone of a mature zucchini

irrigated by soil moisture-based scheduling (threshold 475 mV).
calculated as the standard deviation over 4-day period.


plant
Variability


6all MOlsh~BB

I ;;1

I iil~
...1.
ni
i~ri


II



Soll Mads~lur











Soil moisture tensions were calculated from the soil moisture release curve and


plotted in Figure 4.19. Tensions greater than 50 cbar were left displayed as such to avoid


desensitizing the scale in low tensions. Furthermore, the soil moisture release curve was


not calibrated for tensions greater than 50 cbar as this was the maximum reading of the


tensiometers.



so- Soil Moisture
Tension

20 10
.. 20
S25
,'st10 E 30
140
N 45

so Drlp Ilne




0 0 30
S20
S30
O 40
S50

Soil Moisture Tension -20 -10 0 10 20
x Data (rn)



Figure 4. 19. Average soil moisture tension for the root zone of a mature zucchini plant
irrigated by soil moisture-based scheduling (threshold 475 mV).

Soil moisture in the bed appears to be a function of distance away from the emitters


and more generally the distance from the drip line. An average cross section of soil


moisture was obtained by taking the average of all probes a parallel distance (y-value),


and is presented in Figure 4.20.







77





0.16


0.14-


,- 0.12-


0.10 --


S0.08-


c0 0.06-


0.04 -*- Average cross-section Soil moisture plot
y = 1E-06x3 6E-05x2- 0.0007x + 0.1232
0.02
-40 -20 0 20 40

Distance from drip tape (m)
Figure 4.20. Average cross-section profile of soil moisture across the bed with varying
distance from drip tape for a mature zucchini crop on plastic mulched raised
beds irrigated using soil moisture-based scheduling. Plants were positioned at
-15cm from the drip line and spaced every 46cm.

Discussion of results

The results from this experiment have shown an inherent variability in soil

moisture monitoring and the difficulties in producing very consistent readings due to soil

moisture holding heterogeneities and probe spacing for an in-situ field calibration.

Results although containing variability do have the benefits of no repacking of the soil

being conducted as in a laboratory experiment. Other factors that may have played a part

in variability of data were effective rainfall, salinity effects, blocked emitters, and

incorrect probe readings.







78


Rainfall

Rainfall did have an effect on some dielectric capacitance probe readings, and soil

moisture spikes were noted during rainfall event periods. This was evident in Figure


4.21, where some probes experienced spikes in soil moisture during rainfall periods and

others did not. The probes that had a higher incidence of effective rainfall were those

near the periphery of the bed, away from the cover of the plant biomass. This was

however not a clear trend.


0.3 0



0.25 1 ~ 110
Rainfall
(mm)

0.2 11 20



S0.15 -'30


12 El


-12 E7

0.05 50 -12 E8
12 E9



11/19/2005 11/21/2005 11/23/2005 11/25/2005 11/27/2005 11/29/2005
Date

Figure 4.21. Soil moisture time series showing how soil moisture spikes during rainfall
events are limited to probes on exterior of bed that are not significantly
influenced by irrigation

The cause of rainfall affecting some probes and not others may have been cover for

some probes from the plant canopy, or random ponding on the plastic mulch. Figure 4.21

shows how the outer probes (El, E2 and E3) all spike during rainfall events, but not

during normal irrigation events. The effect of rainfall on soil moisture readings is limited










more to probes on the exterior of the bed, and is still somewhat random if ponding

occurs.

Temperature

Documentation posted Campbell (2005c) for Decagon Devices Inc. the

manufacturers of the ECH20 dielectricc capacitance) probe, suggests that the probes mV

out put, and thus soil moisture readings is affected by temperature fluxes. The magnitude

of the temperature effect is related to soil moisture content of the soil and is the largest at

approximately 10 to 15% soil moisture, the range that is targeted for soil moisture-based

irrigation. The maximum temperature effects of an experiment conducted by Campbell

(2005) for a sandy loam soil were 0.2 %oC1 for a temperature range of 10 to 40 oC. In

field conditions the soil matrix has a mediating effect on temperature with depth. Diurnal

temperature fluxes are lagged and reduced with depth. Thermocouples were installed just

under the surface of the plastic mulched bed to determine the range of temperature fluxes

and to help determine if temperature had a significant impact on soil moisture as

generated by the dielectric capacitance probe. Figure 4.22 shows the temperatures

recorded from three replicates of thermocouples each in a different bed. Temperature

variations within the surface soil of the beds were on average between the mid twenties

and mid teens in degrees Celsius. A period of cooling was observed towards the end of

the season as winter approached. The diurnal temperature flux of measured by the probes

buried just under the surface had little affect on soil moisture readings. This was deduced

by the lack of oscillation in the probes that were positioned far enough away from the

drip line and received very little irrigation water (Figure 4.23, probes Il-E2, E2 and E3).

An oscillation is observed in Il-E2, but was most likely due to both temperature fluxes

and water from irrigation events.





















o -Temp 11
S20 ---- -Temp 12
-Temp 13










25-Oct-05 30-Oct-05 04-Nov-05 09-Nov-05 14-Nov-05 19-Nov-05 24-Nov-05 29-Nov-05 04-Dec-05
Date

Figure 4.22. Temperature fluxes within three plastic mulched beds in the fall season of
2005. Thermocouples were buried approximately 15 mm beneath the surface.

The arrow in Figure 4.23 shows the increase in apparent soil moisture that could

have been from temperature changes as it warmed up in the morning. This increase in

soil moisture occurs before 9:00 am, the occurrence of an irrigation event. The other

probes show only a very small increase during the warm period in the day. The

maximum deviation from mean soil moisture for Il-E2 if only temperature changes were

considered, was only 0.35%.

Taking the potential for irrigation events to be contributing towards the increase,

actual temperature effects on soil moisture are most likely lower. From these results, and

the general spread of soil moisture readings using dielectric sensing within a soil

medium, the deduction is made that the probes buried vertically in the top 22 cm of soil

are not significantly affected by normal diurnal fluxes in temperature.












0.3



0.25



0.
Irrigation events 15
--ll-E2
g! I / I11-E3
j; I I R r\ I11-E4
S0.15 ~r~t ~ ~ -ll-E5
... -ll-E6
Si --ll-E7
--ll-E8
0.1 11\ l-E9



0.05




11/12/05 11/12/05 11/13/05 11/13/05 11/14/05 11/14/05 11/15/05 11/15/05 11/16/05
Date

Figure 4.23. Time series of soil moisture in bed Il to show limited effects of temperature
on outer probes that receive little irrigation water.


Salinity


Figures 4.25,4.26 and 4.27 show that soil moistures determined by applying the


linear calibration to the ECH20 probe output have considerable spikes that correspond


with the days that fertigation occurred. These considerable spikes are not simulated in


the soil moisture data determined by TDR measures. Different factors that could have


caused these spikes in soil moisture as determined by the dielectric capacitance probes


were examined. Rainfall only had a limited effect in probes that were not covered by the


crop canopy, and the rainfall did not occur on a weekly cycle as the spikes in soil


moisture did. Temperature, a possible reason for deviation of dielectric capacitance


probe output showed to cause less than a 0,35% change in soil moisture. Furthermore


fluxes in temperatures were on a diurnal cycle, and not a weekly effect. The third and









possible external factor that may have caused spikes in soil moisture as read by the

dielectric capacitance probes was salinity effects. The spikes in mV were highest just

after feritigation events, when both water and fertilizer were introduced to the soil. From

the 20-minute duration of fertigation events, the system should have applied

approximately 0.67 mm of water to the soil. For the 20cm depth that the probes averages

the soil moisture over, this should result in only a 3.4% increase in soil moisture.

Corresponding increases in the soil moisture readings by TDR during the fertigation

events were only a few percent (Figures 4.25, 4.26 and 4.27). TDR data is assumed to be

sufficiently accurate to compare the dielectric capacitance data against, as TDR readings

are generally considered immune to salinity unless the salinity is so server that it masks

the peak-to-peak frequency in the signal. The dielectric capacitance probes close to the

fertigation line for treatments II and I2 showed increases of up to 15% in soil moisture

(Figures 4.25 and 4.26). Considering the negligible effects that all other likely factors

mentioned had on dielectric capacitance probes output, it is proposed that high salinity

after fertigation events is causing an increase in soil electrical conductivity, which is

possibly transferred into a higher bulk conductivity and thus mV readings measured by

the dielectric capacitance probes. A 12% higher reading in soil moisture by the dielectric

capacitance probes than the TDR readings would equate to an over reading of 170 mV by

the dielectric capacitance. Campbell (2005c) showed an increase of up to 400 mV in

dielectric capacitance readings for sandy soils at salinities of 12.9mmho.cm~l Irrigation

scheduling treatment IS had soil moisture readings calculated from ECH20 mV output,

that deviated the most from soil moistures measured by TDR. This treatment also under-

applied water for the season when compared to treatment I2 (Figure 4.24).














11
500
450 -
400 -
S350 -
S300 -
S250 -
S200 -
'E150 -
100 -
50 -

9/30 10/16 11/1 11/17 12/3 12/19


12
500
450-
400-
350-
S300-
S250-
S200-

100-

50

9/30 1CV16 11/1 11/17 12/3 12/19


13
500
450 aterApplication
400-
350 -I Total imrgation wter applied ~ Total water
E 300 -Il 133men Il 163mtdn
12 257 rmn 12 319 mrnn
~2501 I S 107 rmn IS 151 rmn
t 200-





9/30 10/16 11/1 11/17 12/3 12/19



Figure 4.24. Water applications for the three soil moisture-based drip irrigation
treatments II (9.5%), I2 (12.5%) and I3 (12.5% and buried drip) on a plastic
mulched zucchini crop.


Soil Moisture determined from ECH20 probes


Soil moisture determined from TDR


0 1 1 O I0
30-Oct-05 07-Nov-05 15-Nov-05 23-Nov-05 30-Oct-05 07-Nov-05 15-Nov-05 23-Nov-05
-TDR 51 -TDR 52 11-E4 -1-ll-5 --ll-E6 --ll-E7 --ll-E8 11-E9

Figure 4.25. Soil moisture time series showing soil moisture determined by TDR and
calculated by dielectric capacitance for soil moisture treatment II.





Soil moisture determined from ECH20 probe
0 35



03



0 25



02



0 15


01a




0 05
30-Oct-05 07-Nov-05 15-Nov-05 23-Nov-05
12 E4 12 E5 -12 E6 -12 E7 -12 E8 12 E9


Soil moisture determined from TDR


035



03



" 0 25



~02



S0 15


0 05 I
30-Oct-05 07-Nov-05 15-Nov-05 23-Nov-05
-TDR 54 -TDR 55 TDR 56


Figure 4.26. Soil moisture time series showing soil moisture determined by TDR and
calculated by dielectric capacitance for soil moisture treatment 12.


Soil moisture determined from TDR


Soil moisture determined from ECH20 probes


0.3



0.25



0.2
-


O 0.15

-

0.1



0.05


--~~ -- -


0 1 ,I
30-Oct-05 07-Nov-05 15-Nov-05 23-Nov-05

-TDR 13 TDR 13


o!
30-Oct-05 7-Nov-05 15-Nov-05 23-Nov-05 1-Dec-05

13 E4 13 E5 -13 E6 13 E7 13 E8 13 E9


Figure 4.27. Soil moisture time series showing soil moisture determined by TDR and
calculated by dielectric capacitance for soil moisture treatment IS, which had
its irrigation line buried 15cm below the surface and the fertigation line.









If salinity was affecting mV readings, then this could go some way in explaining

the under application of water by the treatment. The probe would be recording mV and

thus soil moisture readings higher than actual conditions and the mV threshold, and

irrigation events would be bypassed. Salinity readings and effects are however not

quantified

Spatial distribution trends

The different spatial distributions of soil moisture showed that soil moisture

corresponded to emitter and plant position, but mostly was a function of distance from

the drip line. The curve fitted in Figure 4.20 suggests that the highest soil moisture

occurred near or at the drip line and that the lowest soil moisture occurred on the exterior

of the plant side of the bed. This initially seems intuitive, as one would expect the plant

to use up the available water and reduce the soil moisture on this side. The variability of

soil moisture readings was greatest near the emitters and also higher on the plant side of

the drip line (Figures, 4. 14, 4. 16 and 4. 18). This is possibly due to the higher refilling

and consumption by the plant roots cycle in this region of the bed.

The distributions of soil moisture showed a fairly consistent band of high soil

moisture up to 10 cm on either side of the drip line, with highest values occurring near

the emitters. Variability in soil moisture showed a greater relation to emitter position and

plant position, than just distance to the drip line as soil moisture did. This is evident in

Figures 4. 12, 4. 14, and 4. 18. To aid in the decision on probe placement and set point, the

soil moisture release curve and tensiometric distributions need to be considered. Due to

the particle distribution and hydrophobic nature of the sands, the soil moisture release

curve has a large change in slope between 12% and 8% soil moisture. For soil moistures

below 8% a small reduction in soil moisture can have a very large increase in soil









moisture tension. This is not conducive to optimal plant growth and these ranges of soil

moisture should be carefully avoided. This is evident in Figure 4. 19, where the soil

moisture tension distribution increases dramatically beyond 20 cbar (approximately 15

cm either side of the drip line).

Conclusions

The dielectric capacitance probe was calibrated for the soil (fine sand) at the Plant

Science Research and Education Unit, as the probe needed site-specific calibration due to

the high sand content. The calibration yielded a linear relationship between soil moisture

and probe mV output, similar to that published for most soils by the probe manufacturers.

From this curve and tensiometric readings, a site-specific soil moisture release curve was

derived for the fine sand. The soil moisture release curve will help determine the plant

water stress that a crop may experience for particular soil moisture set points. This is

critical for optimal growth of the crop and ensuring that water is not a limiting factor

while achieving water application savings and reducing nutrient leaching.

Soil moisture within the plastic mulched bed is dependant on distance from the drip

line and emitters and to a much lesser extent distance from the plant. The average soil

moisture at a point in the bed can be estimated by a third order polynomial that is a

function of distance from the drip line. The curve is almost parabolic and skewed

slightly, possibly due to plant position within the bed. Soil moisture within the bed was

lowest on the outer side of the plants. Soil moisture variability was highest near the drip

emitters and lower towards the outer edges of the bed, where soil moisture use and

recharge by irrigation was almost neglegible. External factors such as rainfall and

temperature can have an effect on soil moisture readings. Rainfall generally did not

contribute substantially to soil moisture readings, but during significant rainfall events,










probes that were on the exterior of the bed and not protected by the crop canopy did

record increases of soil moisture up to 10% for large events. The trends were not clear,

and the effects of rainfall were random, and did not contribute to probe readings in the

center of the bed where probe's should be positioned for soil moisture-based irrigation.

The dielectric capacitance probes are affected by temperature variations, but the soil has a

mediating effect on diurnal temperature fluxes and very little change in soil moisture

(less than 0.35%) is experienced when the probe is buried vertically in the top 22 cm of

the plastic mulched bed, for normal ranges of temperature in a growing season. As such

with good sealing for the probe in the plastic mulch, rainfall and temperature effects on

probe readings of soil moisture should be negligible. Soil moistures determined by

applying the linear calibration equation to dielectric capacitance probe mV output had

significant spikes corresponding to fertigation events that were not replicated in the TDR

measured soil moisture. The significant spikes in the dielectric capacitance data were not

caused by rainfall or temperature affecting the mV output. It is proposed that the

fertilizers added during fertigation events are increasing soil electrical conductivity, and

increasing the dielectric capacitance probes bulk conductivity reading and thus mV

output. If this is the case, then the dielectric capacitance probe needs to be calibrated for

higher salinity levels in sandy soils.

From this in field calibration and soil moisture spatial distribution study, it has been

shown that soil moisture measurements have inherent variability, and good understanding

of the factors affecting soil moisture within a plastic mulched bed on sandy soils is

needed to reliably schedule irrigation with soil moisture probes. Soil moisture

distributions show soil moisture profiles that correlate with proximity to the drip line and