Evaluation and Demonstration of Soil Moisture Based On-demand

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					 Evaluation and Demonstration of Soil Moisture Based On-demand
           Irrigation Controllers for Vegetable Production (B228)
                                  SWFWMD Contract 06C00000052
                                          UF Project 000 604 82




                                         FINAL REPORT



                                                      By

                                            Lincoln Zotarelli1
                                      Research Scientist Investigator

                                            Michael D. Dukes1
                                            Faculty Investigator




                         Agricultural and Biological Engineering Department 1
                              Institute of Food and Agricultural Sciences
                                          University of Florida

                                             Submitted to
                             Southwest Florida Water Management District


                                               March 30, 2010




University of Florida - Agricultural & Biological Engineering Department
                                                       1
Table of Contents
  1. Executive Summary..........................................................................................................3
   2.     Evaluation of soil moisture sensor (SMS) irrigation controllers ........................................5
        Pepper fruit yield, plant biomass and water use efficiency ...................................................7
        Monitoring soil water percolation and nitrate leaching .........................................................8
        Soil moisture sensor performance, soil moisture and soil water percolation ....................... 10
        Drainage and nitrogen leaching ......................................................................................... 15
        Pepper biomass accumulation and leaf area ....................................................................... 20
        Pepper yield and irrigation water use efficiency ................................................................. 23
   3.     Use of soil moisture sensor in commercial field .............................................................. 28
        Demonstration Farm Overview .......................................................................................... 28
        On farm soil moisture monitoring ...................................................................................... 29
        Practical interpretation of soil moisture for a given field .................................................... 37
   4.     Identification of drawbacks of the use of SMS and future research needs ........................ 40
   5.     Summary ........................................................................................................................ 42
   6.     Cited References: ........................................................................................................... 43
   7.     Publication production .................................................................................................... 45




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1. Executive Summary

Florida is the most important center of production and distribution of vegetables in the

southeastern U.S. with 181,000 acres planted in 2006 and a crop value greater than $1.2 billion

dollars (USDA, 2008). Among the vegetable crops cultivated in Florida, tomato, bell pepper,

strawberry, cucumber are very important economically. Florida is the top water user in the humid

region of the U.S., ranking fourth in withdrawal of ground water for public supply in the United

States and ranking seventeenth nationally for agricultural water use (Hutson et al., 2004). In

2005, agriculture accounted for 40% of Florida freshwater withdrawals in the state, totaling

almost 2.7 billion gallons per day. About 47% of agricultural freshwater withdraws were ground

water. As the largest single water use category in Florida, agriculture has been forced to utilize

water more efficiently. Even though the adoption of agricultural practices such as the use of

polyethylene-mulch and drip irrigation have became very common for vegetable production,

there is still room for improvement regarding the irrigation scheduling of vegetable crops. The

use of improved irrigation scheduling techniques using soil moisture sensors to monitor soil

moisture and control irrigation events has been shown to greatly increase irrigation water use

efficiency. With more efficient water use, fertilizer is also retained in the effective root zone

longer and growers can attain maximum yields at lower N-fertilizer application rates. As a result,

better irrigation scheduling techniques will not only provide substantial water savings but can

also greatly reduce potential N-leaching losses and thus minimize water quality impacts. Field

experiments conducted between 2006 and 2008 revealed that the use of soil moisture sensors

(SMS) to control irrigation resulted in significant reductions in the volume of irrigation applied

(up to 50%) without reduction of marketable pepper yield. Pepper yield increased from 4% to

13% for SMS-based treatments compared to fixed time irrigation typically used by growers.


University of Florida - Agricultural & Biological Engineering Department
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Additional measurements during the field experiment confirmed that precise irrigation

management can greatly enhance N-fertilizer retention in the active root zone, reducing water

percolation and NO3-N leaching. Fixed irrigation schedules without a realistic evaluation of the

actual soil moisture status may result in over-irrigation and N leaching.

        In the second part of this project, the soil moisture sensor monitoring technology was

demonstrated at a commercial vegetable production field. The comprehensive field

demonstration has clearly shown the benefits of soil moisture sensor use to manage irrigation of

vegetable crops under drip irrigation. The utility of such information allows the irrigation

decision maker to continuously monitor the plant water demand in situ to assess critical trends in

soil water status. Real-time soil moisture monitoring combined with information obtained from

co-located measurements of atmospheric variables to estimate evapotranspiration provides a

framework to monitor short and long-term soil moisture storage changes such as during periods

of wet or dry conditions. We identified that the implementation of on demand automated

irrigation by growers will require further adaptation of the current irrigation systems to the soil

moisture sensor technology. Ideally, large areas will require wireless communication between

soil moisture sensors and a central computer. This central computer will store and process the

changes in soil moisture information according to the plant water requirement and ideal soil

moisture threshold defined from the experimental results achieved in this project. Simple

algorithms would be able to define the water requirement and automatically start the irrigation

pump and/or notify the irrigator by cell phone, text message or any other alert system when and

how much irrigate. For example, most of the current drip irrigation systems in the Manasota

basin have diesel pumps which are manually turned on, future adaptation of the startup system

will be required in order to make the on demand system ready to be used by growers.

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Commercially available soil moisture sensor irrigation control systems do not exist with all of

these features.

        This final report summarizes work performed on this project and reported in the previous

task reports and the recommendation for the implementation of the soil moisture sensor devices

on a commercial basis. Based on the information from this project, adoption of soil moisture

sensors for monitoring of commercial vegetable fields is strongly reccomended since this

practice may reduce irrigation water consumption while maintaing crop yield. Guidelines on

commercial automatic soil moisture based irrigation controls as a best management practices

should be developed for vegetables. The grower guidelines should include number of sensors

required and optimum placement relative to varying soil conditions of commercial production.

An economic assessment of costs associated with and benefits derived from conversion of

irrigation systems in vegetables from seepage to drip irrigation needs to be made to promote

water conservation by vegetable growers in Florida. Finally, multiple on-farm demonstrations of

this technology will likely be necessary for grower adoption.


2. Evaluation of soil moisture sensor (SMS) irrigation controllers

Between 2006 and 2008, field experiments were carried out at the University of Florida, Plant

Science Research and Education Unit, near Citra, FL. The field operations were similar to a

commercial vegetable production system. Before transplanting, the area was rototilled and raised

beds were constructed with 6 ft between bed centers, the soil was fertilized, fumigated and

plastic mulched. Irrigation was applied via drip tape and water applied by irrigation and/or

fertigation was recorded by positive displacement flowmeters. Green bell pepper transplants

variety “Brigadier” were set in early April of each year.



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        The experimental design consisted of a complete factorial arrangement of three N-rates

and 4 irrigation treatments in 2006, and same three N-rates and 5 irrigation treatments in 2007.

The N-rate treatments corresponded to 160, 200 and 300 lb ac-1 of N applied as calcium nitrate.

In 2008, 5 different irrigation treatments were studied under a single N-rate 200 lb ac-1. In all

studied years, the treatments were randomized within blocks with 4 replicates. Weekly N

application rates, expressed as a percentage of the total N application, corresponded to 5.5% at

weeks 1, 2 and 13; 7.1% at weeks 3, 4 and 12; and 8.9% at weeks 5-11 (Olson et al., 2005). Pre-

plant fertilization corresponded to the application of 100 lb ac-1 of P2O5. Fertilizer was banded

and mixed into soil during the bed formation. All nutrients (except phosphorus) were applied via

injection in the drip irrigation system (fertigation). Fertilizer sources and rates used were

potassium chloride at a rate of 186 lb ac -1 of K2O and magnesium sulfate at a rate of 9 lb ac -1 of

Mg.

        Irrigation treatments were regulated by the commercial RS500 soil moisture sensor

(SMS) controller manufactured by Acclima, Inc. (Meridian, ID, USA). The RS500 unit controls

irrigation application by bypassing time clock initiated irrigation events if soil moisture is at or

above a preset threshold of volumetric water content (VWC) at 0.08, 0.10 and 0.12 in3 in-3,

respectively, SS8, SS10 and SS12 in 2006 and 2007. In 2007, we introduced the use of double drip

irrigation (SD10), which was tested with SMS control and a threshold set at 0.10 in3 in-3 (Table

1). In the spring of 2008 the SMS treatments tested were preset at VWC of 0.04, 0.08 and 0.12

in3 in-3, respectively, SS4, SS8 and SS12; and with double drip irrigation at VWC of 0.08 in3 in-3

and 0.12 in3 in-3, respectively, SD8 and SD12 (Table 1). The soil moisture sensor probes were

installed at a 45 degree angle between two plants that measured the soil moisture in the top 6 in

of the bed. Timed irrigation windows were specified as five possible events per day, starting at

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8:00 am, 10:00 am, 12:00 pm, 2:00 pm, and 4:00 pm for 24 minutes each (2 hr d -1 total, or

equivalent to 0.23 in day-1 or 47.2 gal 100ft -1 d-1). A reference treatment (TIME) was established,

a time-based irrigation treatment with one fixed 2 hr irrigation event per day meant to represent a

common grower practice of fixed time based irrigation.


Pepper fruit yield, plant biomass and water use efficiency

Plots were harvested on 58, 70 and 74 days after transplanting (DAT) in 2006; on 69 and 83

DAT in 2007 and on 62 and 76 DAT in 2008. The harvested area consisted of a central 30 ft long

region within each plot. Pepper fruits were graded into culls, U.S. Number 2 (medium), U.S.

Number 1 (large), and Fancy (extra-large) according to USDA (2005) grading standards for fresh

market sweet peppers. Marketable weight was calculated as total harvested weight minus the

weight of culls. The number and weight of fruits per grading class were recorded for individual

plots. Irrigation water use efficiency (IWUE) expressed in lb in-1, IWUE was calculated by

taking the quotient of the marketable yields (lb ac-1 ) and the total applied seasonal irrigation

depth (in). Plant biomass accumulation was evaluated by harvesting two representative plants per

treatment replicate at transplanting, 23, 34, 49 and 68 DAT. Vegetative and reproductive plant

parts were separated. Leaf area was determined for each sample using a LI-300 (Li-cor, Lincoln,

Nebraska). Shoot and fruit tissues were dried at 65 oC for subsequent dry weight determination.

Photosynthesis was measured at midday (around solar noon) on the youngest sun exposed, fully

expanded leaves, using a portable closed gas-exchange photosynthesis system (model LI-6200,

LI-COR, Inc. Lincoln, NE) equipped with a ventilated chamber.




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Table 1. Outline and description of irrigation treatments along with threshold volumetric water

           content (VWC), total number of irrigation events scheduled, allowed to irrigate and

           skipped.

  Treat. codes                  Irrigation                   Threshold          Max.        Number of irrigation events
                               description                     VWC           irrigation
                                                                 in3 in-3    frequency     Sched.    Irrigated   Skipped
                                                                            (events d-1)
  Spring 2006 (N-rates 160, 200 and 300 lb ac-1)
  SS8           Acclima Digital TDT RS-500 – single drip          0.08           5          330        137         193
  SS10                                                            0.10           5          330        298          32
  SS12                                                            0.12           5          330        302          28
  TIME           No soil moisture sensor, daily fixed time          -            1          66          66          0
                                  irrigation
  Spring 2007 (N-rates 160, 200 and 300 lb ac-1)
  SS8           Acclima Digital TDT RS-500 – single drip          0.08           5          320        175         145
  SS10                                                            0.10           5          320        175         145
  SS12                                                            0.12           5          320        253          67
  SD10          Acclima Digital TDT RS-500 – double drip          0.08           5          320        295          25
  TIME           No soil moisture sensor, daily fixed time          -            1          64          64          0
                                  irrigation
  Spring 2008 (N-rates 200 lb ac-1)
  SS4           Acclima Digital TDT RS-500 – single drip          0.04           5          266         77         189
  SS8                                                             0.08           5          266        106         160
  SS12                                                            0.12           5          266        117         149
  SD8           Acclima Digital TDT RS-500 – double drip          0.08           5          266        106         160
  SD12                                                            0.12           5          266        182          84
  TIME           No soil moisture sensor, daily fixed time          -            1          54          54          0
                                  irrigation
Note: all treatments have a maximum daily irrigation volume application volume of 0.23 in or 47.2 gal 100ft -1.




Monitoring soil water percolation and nitrate leaching

In collaboration with a Florida Department of Agriculture and Consumer Services (FDACS)

project #9189, water and nitrate leaching generated by the different irrigation treatments was

evaluated. The volumetric water content of the top soil of the production beds was monitored by

coupling time domain reflectometry (TDR) probes (CS-616, Campbell Scientific, Inc. Logan,

UT, USA) with a data logger (CR-10X, Campbell Scientific, Inc., Logan, UT). Soil moisture

probes were placed in the beds at two subsequent soil layers which recorded soil moisture values.

The upper probe was inserted at an angle in order to capture soil moisture in the top 10 in of the

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profile and the lower probe was inserted vertically below the upper probe recording soil moisture

between 10 in and 22 in.

        Zero tension drainage lysimeters were located 30 in below the surface of the bed

(Zotarelli et al. 2007). The drainage lysimeters were constructed out of 55 gal polyethylene

drums that were cut in half lengthwise with a length of 34 in, a diameter of 22 in, and a height of

11 in m (Fig.1). A total of 24 lysimeters were used to evaluate percolated volume and nitrate

leaching in all irrigation treatments under N-rate treatments of 200 and 300 lb ac -1 (4 replicates

for each treatment). A vacuum pump was used to extract the leachate accumulated at the bottom

of the lysimeter. The leachate was removed weekly one day prior to the next fertigation event by

applying a partial vacuum (5-6 psi) using 5 gal vacuum bottles for each drainage lysimeter. The

use of weekly samplings combined with a partial vacuum allowed for an effective extraction of

leachate at the bottom of the drainage lysimeter and the absence of anaerobic conditions. After

sampling, soil water in the bottom of the barrel dropped to 15 to 20% VWC and the soil system

remained oxygenated between samplings, thereby minimizing denitrification potential. Total

leachate volume was determined gravimetrically and subsamples collected from each bottle were

analyzed for NO3-N and thus total N loading rates could be calculated. Nitrate samples were

analysed using an air-segmented automated spectrophotometer (Flow Solution IV, OI Analytical,

College Station, TX, USA) coupled with a Cd reduction approach (modified US EPA Method

353.2 [Jones and Case, 1991]).




University of Florida - Agricultural & Biological Engineering Department
                                                       9
                                            6 ft

                                            38 in

                               Raised bed

                                                    Drip
                                                                       12 in
                                            22 in



                                       Drainage
          30 in    11 in               lysimeter




                                                                   Raised bed
                                              34 in


                                     Drainage Lysimeter

          38 in    Drip
                   Tape




                                                   Pump at
                                                    5-6 psi

                                 Bottle
                                 5 gal




                                          Drainage Lysimeter


Fig. 1. Overview of drainage lysimeter details.




Soil moisture sensor performance, soil moisture and soil water percolation

After plant transplanting, a crop establishment period was characterized by application of similar

irrigation volume to all irrigation treatments. This period lasted 14, 12 and 23 days after

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transplanting in 2006, 2007 and 2008, respectively. In the same year order above, the volume of

water applied via irrigation corresponded to 2.83, 2.51 and 5.19 in (equivalent to 1,058; 938 and

1,940 gal 100ft -1, respectively). Following this period, irrigation treatments were initiated. The

irrigation treatments controlled by SMS were programmed to bypass irrigation if the probe read

soil moisture at or above the set threshold at the beginning of a scheduled irrigation cycle (Table

1).

        During the crop season, programmed irrigation events were skipped which significantly

reduced the amount of water applied to soil moisture sensor (SMS) based treatments. The overall

percentage (average of three years) of bypassed events for each SMS threshold was 71%; 56%,

45% and 36%, for 0.04, 0.08, 0.10 and 0.12 in3 in-3 , respectively. Accordingly, the overall

volume of irrigation increased in the following order SS4 < SS8 < SS10 < SS12 < TIME, except in

2006 when SS10 received similar volume of irrigation water as SS12 and in 2007, when SS8 and

SS10 had similar volumes applied (Table 2). It was observed that both SMS treatments failed to

bypass irrigation events in the beginning of the season in 2006. The problem was attributed to

cross communication between the TDT sensors, causing each of the irrigation controllers to

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

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

Another important issue encountered during the experimental phase was the location of the probe

in the raised bed. Drip irrigation has a source point of irrigation which creates a gradient of soil

moisture from the drip emitter and the sides of the raised bed. Therefore, the location of the

sensor relative to drip line and plant row plays an important role in the sensing irrigation

systems. Even thought the treatments were set at different thresholds, for example, if the SS8 soil




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moisture probe was placed in a drier spot, it could result in higher irrigation volume applied than

the SS12.

        The contribution of rainfall to pepper water requirements was not directly considered in

the calculations, due to the presence of plastic mulch and the absence of a perched water table,

while coarse sandy soils also typically demonstrate very limited lateral flow. Although, it was

observed that high intensity precipitation events (> 0.31 in h-1) slightly increased the soil water

content as measured by TDR. For SMS treatments, there was no increase in number of skipped

irrigation events after rainfall. For example, precipitation events of 1.88 and 1.77 in occurring in

2006 and 2007, respectively, showed a slight increase (around 1%) in volumetric soil water

content (VWC) in the 0-10 in depth layer (data not shown).




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                                                      12
                                                                                      0-10 in depth                                                                                10-22 in depth
                                            0.25                                                                                                                                                                                                   0.25
                                                                                              SS4                                                                                          SS4
                                            0.20                                                                                                                                      Soil volumetric water content                                0.20
                                                                                                                                                                                      Skipped irrigation event
                                                                                                                                                                                      Irrigated event
                                            0.15                                                                                                                                                                                                   0.15
                                                                                                                                                                                   F Fertigation
                                            0.10                                                                                                                                                                                                   0.10

                                            0.05                                            F                                                                                                                                                      0.05
                                            0.25                                                                                                                                                                                                   0.25
                                                                                              SS8                                                                                          SS8
                                            0.20                                                                                                                                                                                                   0.20

                                            0.15                                                                                                                                                                                                   0.15

                                            0.10                                                                                                                                                                                                   0.10

                                            0.05                                            F                                                                                                                                                      0.05
                                            0.25                                                                                                                                                                                                   0.25
                                                                                             SS12                                                                                          SS12
                                            0.20                                                                                                                                                                                                   0.20
   Soil Volumetric Water Content (in in )




                                                                                                                                                                                                                                                          Soil Volumetric Water Content (in in )
  -3




                                                                                                                                                                                                                                                          -3
                                            0.15                                                                                                                                                                                                   0.15
  3




                                                                                                                                                                                                                                                          3
                                            0.10                                                                                                                                                                                                   0.10

                                            0.05                                           F                                                                                                                                                       0.05
                                            0.25                                                                                                                                                                                                   0.25
                                                                                              SD8                                                                                          SD8
                                            0.20                                                                                                                                                                                                   0.20

                                            0.15                                                                                                                                                                                                   0.15

                                            0.10                                                                                                                                                                                                   0.10

                                            0.05                                            F                                                                                                                                                      0.05

                                            0.25                                             SS12                                                                                                                                                  0.25
                                                                                                                                                                                           SS12
                                            0.20                                                                                                                                                                                                   0.20

                                            0.15                                                                                                                                                                                                   0.15

                                            0.10                                                                                                                                                                                                   0.10

                                            0.05                                             F                                                                                                                                                     0.05

                                            0.25                                            TIME                                                                                                                                                   0.25
                                                                                                                                                                                           TIME
                                            0.20                                                                                                                                                                                                   0.20

                                            0.15                                                                                                                                                                                                   0.15

                                            0.10                                                                                                                                                                                                   0.10
                                                                                             F
                                            0.05                                                                                                                                                                                                   0.05
                                                   05/01

                                                           05/02

                                                                   05/03

                                                                           05/04

                                                                                   05/05

                                                                                           05/06

                                                                                                   05/07

                                                                                                           05/08

                                                                                                                   05/09

                                                                                                                           05/10

                                                                                                                                   05/11

                                                                                                                                           05/12
                                                                                                                                                   05/01

                                                                                                                                                           05/02

                                                                                                                                                                   05/03

                                                                                                                                                                           05/04

                                                                                                                                                                                   05/05

                                                                                                                                                                                           05/06

                                                                                                                                                                                                   05/07

                                                                                                                                                                                                           05/08

                                                                                                                                                                                                                   05/09

                                                                                                                                                                                                                           05/10

                                                                                                                                                                                                                                   05/11

                                                                                                                                                                                                                                           05/12




Fig. 2. Example of 11 days of soil volumetric water content measured at 0-10 in (left graphs) and

10-22 in depth (right graphs) with scheduled irrigation events during pepper vegetative


University of Florida - Agricultural & Biological Engineering Department
                                                                                                                                               13
development in 2008. The dotted line represents date of soil moisture sensor treatments

initiation.

        The soil moisture content was monitored throughout the season at depth layers of 0 to 10

in and 10 to 22 inches by TDR probes. In general, the soil moisture had a noticeable increase

after each irrigation event for SMS treatments and TIME (Fig. 2, left side graphs). However, due

to the higher number of bypassed irrigation events for the SMS treatment, variations in soil

moisture at 0-10 in soil depth layer were not as distinct as for the TIME treatment.

        The advantage of SMS based irrigation compared to TIME treatment is that the SMS-

based system irrigated for short periods of time, in this case, 24 min, and with an interval of at

least 2 hours between irrigation events. This irrigation approach results in a relatively small

increase in soil moisture in the upper soil layer, and the interval between irrigation events

provided time for soil water redistribution, consequently decreasing the volume of percolate in

deeper soil layer (Fig. 2 right side graphs). Slight oscillations in soil moisture were observed

during the irrigation events in the deep monitored soil layer for higher SMS settings (e.g. SS10

and SS12 treatments). On the other hand, the fixed TIME treatment irrigated for a longer time

period (2 hr), which resulted in very pronounced soil moisture fluctuations (Fig. 2). These spikes

in soil moisture were only temporary, as excess soil moisture that rapidly drained below the root

zone in this sandy soil. Soil moisture content returned to field capacity within 12 h. The spikes

also indicate that the soil water content as measured by the TDR probes rapidly reaches a point

above the soil water holding capacity in the soil upper layer, inducing percolation to deeper soil

layers, and explaining the higher percolate values for the TIME treatment compared to the SMS

treatments . In fact, similar spikes in soil water content were observed at 10-22 inches showing

appreciable soil water percolation though the soil profile throughout the entire production cycle

University of Florida - Agricultural & Biological Engineering Department
                                                      14
(Fig. 3). In terms of soil water availability to the plants, the TIME treatment initially may

provide more favorable growth conditions since the soil remains wetter, thus reducing potential

water stress. However, the long term excessive water percolation also increased nitrate leaching

and reduced crop N supply and thereby reducing yield for green bell pepper (Fig. 3 and Table 2).




Drainage and nitrogen leaching

For 2006 and 2007 seasons, water percolation during crop establishment was identical for all

treatments; 0.4 and 0.3 inches, respectively. According to the statistical analysis for the post-

establishment period, an overall decrease (P ≤ 0.05) in soil water percolation was obtained when

SMS-based irrigation controlled the water application. The TIME treatment resulted in the

highest volume of water percolated below the effective root zone and captured in the lysimeters

(Figs. 3 and 4). The volume percolated ranged between 0.7 and 2 inches (Figs. 3 and 4), which

corresponded to 10% to 16% of the applied irrigation water. In 2007 season, the volume

percolated under SS10 treatment was 0.6 inches, which corresponded to only 5% of the total

irrigation water applied. Similar comparison showed that SS12 treatment percolated 1.3 inches,

which was translated to 11% of the total irrigation water applied.

        In 2006 and 2007, there was no interaction between irrigation and N-rate treatments for

cumulative nitrate loads below root zone. The TIME treatment resulted in the most NO3-N

leaching. Cumulative NO3-N leaching values were ranged between 37 to 70 lb ac-1 for TIME

treatment (Fig. 4). The single high volume daily application of the TIME treatment is likely the

cause of the appreciable drainage and NO3-N leaching below the rootzone compared to the

irrigation scheduling. A consistent reduction in NO3-N leaching was observed when scheduling

irrigation associated to the use of SMS was adopted. These reductions were on the order of 25%

University of Florida - Agricultural & Biological Engineering Department
                                                      15
to 74%, which can be translated to range of 9 to 31 lb ac-1 of N. Independently of the irrigation

treatment, the increase in N-rate from 220 to 330 kg ha -1, significantly (P ≤ 0.05) increased the

NO3-N leaching.

          In 2008, cumulative nitrate leaching at the end of the crop season was significantly higher

for TIME2h with 23 lb NO3 ac-1 leached. The measured values for SS4, SS8, SS12 and SD12 ranged

from 8 to 12 lb NO3 ac-1 following the same patterns observed for percolated volume (Fig. 4

right).

          Excessive soil water percolation and nitrate leaching were clearly associated with over-

irrigation. Our results clearly show that appropriate irrigation scheduling and matching irrigation

amounts with the water holding capacity of the effective root zone thus may provide ways to

minimize the incidence of excess nitrogen leaching associated with over-irrigation. Figure 4 is a

visual example of the effectiveness of appropriate irrigation scheduling to reduce the volume of

water percolated in the soil profile compared to fixed time irrigation.




University of Florida - Agricultural & Biological Engineering Department
                                                      16
                                                                            Percolated Volume                                                                 Nitrate Leaching
                                                              2.5                                                                              70
                                                                                   2006                                                        60      N-Rate        2006
                                                              2.0                                     a                                                         -1
                                                                            SS10                                                                      200 lb ac
                                                                                                                                               50
                                                                                                      a



                          Cumulative percolated volume (in)
                                                                            SS12                                                                           SS10
                                                              1.5




                                                                                                          Cumulative NO3-N leached (lb ac-1)
                                                                            TIME                      b                                        40          SS12

                                                              1.0                                                                              30          TIME

                                                                                                                                               20
                                                              0.5
                                                                                                                                               10
                                                              0.0                                                                               0
                                                              2.5                                                                              70
                                                                                    2007                                                       60      N-Rate        2007
                                                              2.0                                                                                     300 lb ac
                                                                                                                                                                -1
                                                                                                                                               50           SS10
                                                              1.5                                 a                                            40           SS12
                                                                                                  b
                                                              1.0                                                                              30           TIME

                                                                                                  c                                            20
                                                              0.5
                                                                                                                                               10
                                                              0.0                                                                               0
                                                                    0 7 14 21 28 35 42 49 56 63 70 7784                                             0 7 14 21 28 35 42 49 56 63 70 7784
                                                                                            Days after transplanting

Fig.3. Cumulative leachate volume (left) and cumulative NO3-N mass leached for different irrigation scheduling and soil moisture

sensor irrigation treatments during spring 2006 and 2007. Treatment means followed by same letter are not different according to

Duncan’s Multiple Range Test at P≤0.05. Note: N-rates of 200 and 300 lb ac-1.

University of Florida - Agricultural & Biological Engineering Department
                                                                                                   17
                                                       Percolated Volume                                                                                 Nitrate Leaching
                            4.0                                                                                30.0




                                                                                                                              Plant establishment
                                      Plant establishment                  SS4




                                                                                                                                (5.19 in applied)
                                        (5.19 in applied)                  SS8                                 25.0                                                                a
   Percolated volume (in)




                                                                                             a
                            3.0                                            SS12




                                                                                                   N-NO3 (lb ac )
                                                                                                  -1
                                                                           SD12                                20.0
                                                                           Time2h
                            2.0                                                                                15.0
                                                                                                                                                                                   b
                                                                                                                                                                                   bc
                                                                                             b                 10.0
                                                                                             bc                                                                                    c
                            1.0                                                              bc
                                                                                             c                      5.0


                            0.0                                                                                     0.0
                                  0   10                    20   30   40   50     60   70   80    90                      0   10                    20    30   40   50   60   70   80   90

                                                                                        Days after transplanting

Fig.4. Cumulative leachate volume (left) and cumulative NO3-N mass leached for different irrigation scheduling and soil moisture

sensor irrigation treatments during spring 2008. Treatment means followed by same letter are not different according to Duncan’s

Multiple Range Test at P≤0.05. Note: N-rate of 200 lb ac-1.



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                                                                                                   18
          8 in                                             8 in            16 in




                                    25 in

                                                                                    +35 in
      16 in




Fig. 4. Demonstration of the effectiveness of soil moisture sensor based irrigation systems in

enhancing nutrient retention for soil moisture sensor irrigation (top row) due to small frequent

irrigation events compared to fixed time irrigation schedule with single daily large irrigation

events (bottom row) applying dye through the fertigation drip lines. Soil moisture sensor

irrigation (top row) and fixed time schedule irrigation (bottom row) at after 24 h (left), after 3 d

(center) and after 7 d (right) of the injection of dye. (Photos: L. Zotarelli).




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                                                      19
         The fixed TIME irrigation treatment resulted in the highest volume of water percolated

below the effective root zone and captured in the lysimeters (Fig. 3). The volume percolated for

TIME treatment ranged between 1.25 and 3.15 inches which corresponded to 10% to 23% of the

applied irrigation water. A significant reduction in soil water percolation was achieved by using

SMS to control irrigation in all studied years, regardless of SMS threshold. Figure 3 shows an

example of the use of SMS on soil water percolation control. In spring 2008, the overall leachate

amounts since transplanting were 0.94, 0.86, 1.18, 1.06 and 3.14 in, for SS4, SS8, SS12, SD12 and

TIME2h, respectively. However, most of the water percolation occurred during the establishment

period, except for TIME2h, which consistently percolated about 0.27 – 0.32 inches wk-1 (Fig. 3

left).

         Similarly to the percolated soil water volume, the TIME treatment resulted in the most

NO3-N leaching (Fig. 3, right). Cumulative NO3-N leaching values were ranged between 22 and

42 lb ac-1 for TIME treatment. The single high volume daily application of the TIME treatment is

likely the cause of the appreciable drainage and NO3-N leaching below the rootzone compared to

the SMS irrigation scheduling. A consistent reduction in NO3-N leaching was observed when

scheduling irrigation with SMS systems was adopted. These reductions were on the order of 25%

to 74%, which can be translated to range of 9 to 31 lb ac-1 of less N being lost by leaching.


Pepper biomass accumulation and leaf area

Shoot dry biomass accumulation ranged between 720 to 750 lb ac-1 in 2006 and 970 to 1,161 lb

ac-1 in 2007. There was no significant (P ≤ 0.05) difference between SMS-based treatments and

TIME treatments, neither between N-rates. In 2008, overall shoot (leaves and stem) dry weight

ranged between 1,250 and 1,700 lb ac-1 with no differences between treatments (Fig. 5 bottom).

A reduced leaf area was observed for SS4 and SS8 treatments, while other treatments showed a
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                                                      20
leaf area above 527 in2 plant-1. Interestingly, the leaf area for TIME 2h treatment reached a plateau

around 50 DAT, indicating earlier plant maturity, which may be associated to the excessive

leaching and lack of nitrogen, compared to the other treatments (Fig. 5 top). On the other hand,

the reduction in leaf area for treatments SS 4 and SS8 was related to the soil water availability and

irrigation water distribution. Besides the reduced number of irrigation events for SS4 and SS8

compared to the other SMS treatments, the amount of water applied to these two treatments was

not enough to wet soil between 6-12 inches and VWC decreased below 10% several days after

the treatments started (Fig. 2 right column).




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                                                      21
                                                                               Single drip                       Double drip                   Single Drip
                                                          800
                                                                           Soil Moist. Sensor                 Soil Moist. Sensor               Fixed Time
                                                                                                      a                               a
                                                          700                                                                         a




                               Leaf area (in 2 plant-1)
                                                          600                                                                                                     ab
                                                                                                      b
                                                          500
                                                          400
                                                          300                                  SS4                             SD8                       TIME
                                                          200                                  SS8                             SD12
                                                          100                                  SS12
                                                            0
                                                                0                 20      40   60         0     20        40   60         0   20   40        60    80
                                                                                                          Days after transplanting
                         Plant biomass (lb ac -1)




                                            2000
                                                                    Plant establishment




                                            1500
                                                                           period




                                            1000
                                                                                               SS4
                                                          500                                  SS8                              SD8                     TIME
                                                                                               SS12                             SD12
                                                           0
                                                                0                20       40   60         0     20        40   60         0   20   40        60    80
                                                                                                          Days after transplanting
Fig.5. Leaf area (top row) and cumulative plant biomass (bottom row) of pepper as affected by different irrigation scheduling and soil

moisture sensor irrigation treatments during spring 2008.




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Pepper yield and irrigation water use efficiency

The overall marketable yield for green bell pepper ranged between 12,990 to 15,270 lb ac-1 in

2006; 21,255 to 26,525 lb ac-1 in 2007; and 23,578 and 37,688 lb ac-1 in 2008. Except in 2006,

when unfavorable environmental conditions occurred, bell pepper yield obtained in these

experiments were in the range of those reported in the literature for sandy soils in Florida (Dukes

et al. 2003; Maynard and Santos 2007; Simonne et al. 2006). The lower yield in 2006 compared

to 2007 and 2008 was attributed to the effect air temperature on plant development and

flowering. Low night time temperatures were shown to have a considerable effect on flower

morphology and functioning, larger flowers, with swollen ovaries and shorter styles in

comparison with flowers grown under higher temperature conditions. This effect of low

temperatures has a direct effect on pepper production by decreasing the total number of pollen

grains formed and by reducing their viability and germination capacity. A detailed analysis of

measured air temperature during the entire crop cycle revealed that in 2006, pepper plants were

exposed to temperatures below 57.2 ºF during 311 hours, while in 2007 and 2008, the cumulative

hours with low temperatures (<57.2 ºF) were 181 and 185 hours, respectively. In addition,

temperatures below 57.2 ºF occurred during the entire plant development and reproduction stages

in 2006, while in 2007, low temperatures occurred throughout the season for short periods of

time, however, between 49 and 63 DAT (peak of flowering stage) there was no occurrence of

low temperatures.

        The use of soil moisture sensor irrigation control significantly affected the irrigation

water use efficiency (IWUE) (Table 2). The treatment ranking for IWUE was as follows: SS4 >

SS8 >SS10 > SS12 > TIME. The TIME treatment had a lowest IWUE values (< 2.2 lb in-1) due to

the high irrigation rates applied. In 2006, reduced yields associated to the high volume of

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                                                      23
irrigation applied for all treatments were responsible for the lower IWUE values (<3.94 lb in-1,

Table 2). It is important to point out that high irrigation rates as applied for TIME did not

increase yield, conversely, the use of scheduling irrigation by using SMS allowed application of

less water, divided in five possible irrigation events per day (low volume, high frequency), which

resulted in higher IWUE values. While TIME treatment had a single irrigation event (high

volume, low frequency), which promotes excessive water percolation.



Table 2. Irrigation treatments effects on marketable pepper fruit yield, irrigation water

application, and irrigation water use efficiency (IWUE) for pepper, spring 2006, 2007 and 2008.

                       Mkt. Yield (lb ac-1)     Irrig. (inches)      IWUE2 (kg frt m-3)        Water savings (%)
Spring 2006
SS8                            15,272 a1               7.01                    2.18 a                 51 %
SS10                           13,039 a               12.99                    1.00 b                  8%
SS12                           13,129 a               12.44                    1.06 b                 12 %
TIME                           14,468 a               14.17                   1.02 cb                    -
Spring 2007
SS8                            26,525 a                6.73                    3.94 a                 45 %
SS10                           24,560 ab               7.17                    3.43 b                 42 %
SS12                           21,256 b               10.31                    2.06 c                 16 %
SD10                           24,828 ab              11.89                    2.09 c                  3%
TIME                           21,970 b               12.28                    1.79 c                    -
Spring 2008
SS4                            23,578 c                3.19                    7.39 a                 76 %
SS8                            27,418 bc               4.61                   5.95 ab                 66 %
SS12                           31,616 ab               5.43                   5.82 ab                 60 %
SD8                            26,972 c                4.41                   6.12 ab                 67 %
SD12                           38,228 a                7.91                   4.83 bc                 41 %
TIME                           29,472 bc              13.43                    2.20 d                    -
1
  Yield and water use efficiency means followed by the same letter in the column do not differ (P>0.05) by Duncan’s
Multiple Range test. 2Calculated based on total yields excluding the irrigation volume during the establishment
phase.




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                                                        24
                            30
                                                              SMS
                                                           0.12 in3 in-3                SMS
                            20                                                       0.10 in3 in-3
Relative pepper yield (%)




                            10                                                                          SMS
                                                                                                     0.08 in3 in-3

                             0
                                    Fixed
                                    Time
                            -10   Reference


                            -20
                                         RY% = -0.0011 +1.0839*WS - 1.9668*WS2                                    SMS
                                         R2 = 0.99                                                             0.04 in3 in-3
                            -30


                                    0         10      20          30            40         50           60           70        80

                                                           Relative water savings (%)

Fig. 6. Relative marketable yield of bell pepper with increase of relative water savings using soil

moisture sensors (SMS) to control irrigation in different volumetric water (VWC) content

settings.



                             A relationship between irrigation water saving and relative pepper marketable yield were

established using combined results from three years of scheduling irrigation using SMS

compared to a fixed irrigation. Reduction in irrigation water application and its relative

contribution to pepper yield was estimated by a quadratic regression (Fig. 6). The response of

pepper yield increased when irrigation water application was reduced. The yield plateau was

reached at 25-30% of irrigation water reduction, which was obtained when SMS were set at 0.12

in3 in-3, which was slightly above soil field capacity for the experiment site. After reaching the
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                                                                           25
plateau, the yield response was reduced as water savings increased (lower setting of SMS),

indicating that relative water savings higher than 55% may result in plants under water stress

followed by yield reduction.


        Because of the high demand for and the importance of water to the plants, anytime that

water becomes limiting, photosynthesis rate is reduced, as well as plant growth and yield. This

was clearly demonstrated by the drier irrigation treatments with a threshold below the soil field

capacity point. On the other hand, due to the low soil water retention capacity, additional

irrigation water application above the soil field capacity will result in excessive water percolation

and nutrient leaching, although this practice will not affect the water supplied to the plant, it will

negatively affect the plant mineral nutrition and nitrate leaching. In fact, pepper photosynthetic

rates along the crop season decreased with the increase of irrigation water saving (Fig. 7), there

was no significant differences in photosynthetic rate between TIME and SMS treatments set near

the soil field capacity point (0.12 in3 in-3), showing that the potential photosynthetic rate. Soil

moisture sensor settings at 0.08 in3 in-3 and lower, resulted in lower photosynthetic rate and

yield, which was associated to soil water deficit (Figs. 6 and 7).


        The experimental approach allowed us to analyze both extremes of the irrigation

management, from over-irrigation (TIME) to sub-irrigation condition (SS4) and determine an

ideal soil moisture target level (safe irrigation zone) that maximize fruit yield with the least

amount of irrigation water application, and consequently reduce leaching resulting in loss of

water and nutrients.




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                                                      26
                              30                                                                             20




                                                                    Relative pepper photosyntetic rate (%)
                                                                                                                                                         PR% = 0.0336 - 0.5699*WS
                              25                                                                                                                         R2 = 0.82
 Photosynthesis (mmol m s )
-1
-2




                                                                                                              0
                              20                                                                                     Fixed
                                                                                                                     Time
                                                                                                                   Reference
                              15
                                                                                                                                       SMS
                                                                                                             -20                    0.12 in3 in-3
                              10



                              5                                                                                                                                SMS
                                                                                                             -40
                                                                                                                                                            0.08 in3 in-3            SMS
                                                                                                                                                                                  0.04 in3 in-3
                              0
                                                             TIME




                                   SS4   SS8 SS12 SD8 SD12
                                                                                                                     0         10   20        30    40        50        60   70          80
                                            Treatments                                                                                   Relative water savings (%)


Fig.7. Season average of pepper photosynthesis rate as affected by different irrigation scheduling and soil moisture sensor irrigation

treatments during spring 2008 (left) and relative photosynthetic rate of bell pepper with increase of relative water savings using soil

moisture sensors (SMS) to control irrigation in different volumetric water (VWC) content settings (right). Bars indicate standard error.




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3. Use of soil moisture sensor in commercial field

The introduction of soil moisture sensors to a commercial vegetable field created a unique

opportunity to evaluate the performance, applicability and potential use of SMS by a grower on

irrigation management at a production scale. In fact, during the project several questions were

raised as well as ideas to better adapt SMS to the grower conditions.


Demonstration Farm Overview

The Weirs-Turner Farms LLC cultivates vegetable crops in five different farms located in

Manatee County. In the fall of 2008, the area planted in vegetables included 270 acres of

peppers, 200 acres of tomatoes, 180 acres of cucumbers and 125 acres of squash. Crop

management was typical of vegetable production in the Manasota basin with drip irrigation,

plastic mulch, and raised beds (Fig. 8).




Fig. 8. Manasota Basin map. The red arrows indicate the location of the farms. (Map source:

SWFWMD, http://www.swfwmd.state.fl.us/data/map/manasotamap.html).



        The irrigation system of each farm was equipped with a diesel pump, which was

manually switched on. The decision of when and how much irrigate was supported by several
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                                                      28
tensiometers installed across the fields. According to the farmer, there were two tensiometers per

irrigation block. Tensiometer data were acquired manually by two employees. Routinely during

the vegetable season, farm workers would drive around the farms and write down the

tensiometer readings before 9 am. The soil moisture info provided by tensiometers for each

irrigation field was then analyzed manually by the irrigation manager and the decision of

irrigation was then made.

        In July 2008, a field test and demonstration of soil moisture sensors was initiated at

selected pepper area of 41 acres. The area was divided in 3 irrigation zones. The soil of the

demonstration area is classified as Spodosol, which is a sandy mineral soil, low in organic matter

and natural fertility in the surface layer. The area slope was 1% and the water table is found

between 24 and 36 inches depth depending of the location in the landscape.

        The pepper variety was HM 2641. The transplanting occurred on September 15. Green

bell pepper was transplanted in twin staggered rows at 16 inches within row spacing and 10

inches between plants in the row. The area was roto-tilled and raised beds (8 inches) were

constructed in a North-South arrangement with 6 feet between bed centers in July 2008.

Fertilizer was incorporated into the bed at rate of 160 lb N ac -1 ; 120 lb P ac-1 and 320 lb K ac-1.

The beds were fumigated after placement of drip irrigation and plastic mulch.


On farm soil moisture monitoring

        On 17 September 2008, four wireless data recorders wired to four soil moisture sensors

each (SD12 – Acclima, Inc.) were installed in 41 acres area planted with green bell peppers

(Zones 5, 6 and 7, Figs. 9-10). These commercial products were similar probes for soil moisture

sensing as used in earlier tasks of this study and measure electrical conductivity and temperature

along with soil moisture content. Unlike previous plot work in this project, soil moisture,
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                                                      29
electrical conductivity, and temperature data were measured and acquired by a data recorder

measured by the probes. The soil moisture probes were not configured to automatically start the

irrigation as in plot work. These probes and controllers are not readily adapted to irrigation

controlled by diesel pumps that need to be started manually. These devices are capable of

providing soil moisture data from surface and subsurface soil depth layer for the farmer to make

irrigation decisions. The subsurface soil moisture provides information about the fluctuation of

water table level, which is frequently related to the rainfall and potential of occurrence of pepper

root diseases.




                    A
                                                                           D




                                                                     C
                                                                                              N
                                B




Fig. 9. Aerial photo of the “SK Kenny’s Fall Field” zones 5, 6 and 7. The pattern area represents

the 41 acres and the letters indicate the position of soil moisture sensor data recorders. White

arrows indicate descending slope. Photo source: Web Soil Survey, NRCS.

http://websoilsurvey.nrcs.usda.gov/app/.



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     The sensor data recorders were distributed in the field in order to monitor the soil moisture and

     EC along the irrigated beds (North-South) and along the manifold (West-East). The 41 acre area

     was irrigated by a main manifold (irrigation water source) located at the north side of the field.

     The field is divided by the farmer into 3 irrigation zones with one flush valve per zone (Fig. 10).

                                                       2,170 ft

                               Manifold

                     Zone 4                            5                        6


                     A
                                                                                    D
                                          Drip Lines
980 ft



                                                                       C
                                                                                    N

                                 B

                    Flush valves
                    Sensor Data recorder (Acclima SD12)
                    Manifold
                    Drip lines

     Fig. 10. Irrigation zones 4,5 and 6 and irrigation scheme and distribution of soil moisture sensor

     data recorders in the demonstration pepper field. The arrows indicate the water flow.



             Soil moisture and electrical conductivity (EC) was monitored at 0-6; 6-12; 12-24 and 24-

     36 inches depth layers. The soil moisture and EC data was be recorded every 15 minutes for each

     sensor. The data was retrieved monthly.

             The soil moisture nodes were placed in different points of the topography. In this case,

     node A was located in the highest point of the landscape, followed by node D, C and B (lowest

     point). At the installation of the soil moisture sensors, a perched water table at different depths

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                                                                  31
for each node location was observed. The depth of the water table ranged between 35” at node A

location (Fig. 11) and 18”at node C location (Fig. 12). The level of the water table was

monitored by probes installed at 12-24” and 24-30” depth layers.

        Detailed oscillations in soil moisture during fall and winter of 2008 can be observed in

the figures 11 and 12. After each irrigation event there was a noticeable increase in soil moisture

content in the 0-6” depth. The degree to which the soil moisture content increases is dependent

on the duration of the irrigation event. For example, short irrigation run times result in a

relatively small increase in soil moisture, consequently decreasing the volume of percolate

(water moving below the root zone). Alternatively, when the irrigation occurred for a longer time

period, a relatively larger increase in soil moisture was observed, and consequently increasing

the soil moisture in deeper depths, especially at 6-12” depth layer, and eventually to the deeper

soil layers. This spike in soil moisture is temporary, as the irrigation water rapidly drains,

ultimately bringing the soil moisture content back to where it was before the event in a relatively

short period of time. This rapid spike in soil water content indicates that the soil water content as

measured by the soil moisture probes rapidly reaches a point above the soil water holding

capacity and the water starts to percolate down to deeper soil layers. Excessive water percolation

may result in nutrient leaching and reduced yield. In other words, the length of irrigation event

could be reduced, or an irrigation event could be skipped to avoid deep percolation.




University of Florida - Agricultural & Biological Engineering Department
                                                      32
Fig. 11. Soil moisture content measured at depth layers of 0-6”, 6-18”, 12-24”, 24-30” by Data Recorder A during pepper Fall season of

2008.


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                                                                           33
Fig. 12. Soil moisture content measured at depth layers of 0-6”, 6-18”, 12-24”, 24-30” by Data Recorder C during pepper Fall season of

2008.


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                                                                           34
          During the soil moisture monitoring period, situations were observed when proper

irrigation management was performed and alternatively situations when the irrigation could have

been skipped or the volume of irrigation water reduced. For example, Zone 4 (East side), the

period of 11/1 until 12/3 (Fig. 11) might be considered as an example of the proper irrigation

management, which no excessive water percolation from irrigation was detected (increase of

volumetric soil water content in depth). This period was characterized by irrigation events that

did not increase the soil water content at the 12-24” soil layer depth. During this period there was

no irrigation, and it was observed that the level of the water table decreased below 18 inches. In

addition, during some periods with large rainfall events (specifically for 10/7; 10/23; 1/13),

irrigation events were skipped by the farmer and they were resumed when soil moisture levels

decreased to critical levels. Conversely, there were some periods that the irrigation could have

been safely skipped, or the irrigation event length could have been reduced. For example, on the

days of 10/25; 10/28; 12/12 and 12/24 (Fig. 11) when over-irrigation clearly occurred, evidenced

by the spikes in moisture content in the deeper soil layers. The depth of irrigation should

consider the depth of the plant root system, in other words, it is not necessary to irrigate the

entire soil profile to maximize the plant water uptake. In our previous work, we have shown that

about 80% of the root of pepper and tomato was found in the 0-12” depth (Zotarelli et al., 2009)

and it is from that particular depth that most of the water and nutrients are taken up by vegetable

plants.

          It was also observed that soil moisture sensor probes installed at 12-24” and 24-30” of

Node B and C (Fig. 11) showed a higher soil moisture content than the probe located at upper

layers. In fact, during the installation of the probes, a perched water table level was observed

frequently below 20” depth, indicating that the probes below 24” depth would be in the perched

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                                                      35
water table. Values of soil moisture content above 0.30 in3/in3 is an indication that soil layer is

close to the saturation. All monitored points of the irrigation zones showed soil saturated

conditions at 30” depth (Figs. 11 and 12).

        One of the main concerns of the grower was high water table conditions that can reach

close enough to the root zone to have a direct influence on the vigor and productivity of

vegetable on raised beds. Another negative effect of the high water table for long periods, which

is common during the in fall due to the hurricane season, is the high occurrence of root diseases.

On the other hand, during high water table periods, the irrigation events can be dramatically

reduced.

        In early December of 2008, there was a slight increase of the water table level observed

by the increasing of volumetric water content values in the soil layer of 12-24”depth. This fact

can be explained by the increase of rainfall in that period. The influence of rainfall events on the

soil moisture content can be noticed in this period as a result of similar spikes of soil moisture at

depths of 0-6”, 6-12” and 12-24”, simultaneously. Again, the irrigation could be discontinued in

the days after the rainfall until the soil moisture reaches some critical level when irrigation

should be resumed. However, the grower rarely suspended irrigation practices as a result of

rainfall events of this magnitude or lower.

        It is important to note that the grower was not fully relying in the soil moisture sensor

data as the exclusive decision support to irrigate or not. He stated that he was frequently

checking the sensor data to understand oscillations in water table and how his irrigation

management affected the soil moisture content. Therefore, more than one season of work will be

necessary to demonstrate and prove that the farmer can manage an entire field based on few

measurement points.

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                                                      36
        In our interaction with the farmer, we also realized that he preferentially liked the

graphical soil moisture data rather than tables of data. Automated and reliable data acquisition

and automatic transfer to a database seems to be essential for a practical operation of the system.

In addition, a simple interface where the user can consult past and current soil moisture

information from different points on the farm is required. These characteristics seemed to be

essential to the adoption of the SMS system by vegetable growers.


Practical interpretation of soil moisture for a given field

An important point to be considered for the successful adoption of the soil moisture sensor

technology it the practical interpretation of the soil moisture patterns and understand how

irrigation practices/rainfall can affect the soil water content. Once installed, soil moisture

sensors can be successfully used to monitor volumetric water content and guide irrigation

management. However a correct interpretation of the soil moisture readings is very important to

assure a proper irrigation management and avoid over irrigation.

        There is a very simple way to interpret and evaluate soil moisture characteristics using

SMS when soil moisture trends are available in graphical format to the grower. Figure 13 shows

volumetric soil water content at depth of 0-6 inches measured by a capacitance sensor during a

period of four days. There were two irrigation events on 11/06 and 11/09 at 7:00 am. For the soil

field capacity point determination, we intentionally applied an irrigation depth that resulted in

saturation of studied soil depth layer, in this particular case 0-6 inches.




University of Florida - Agricultural & Biological Engineering Department
                                                      37
                                                     0.16
                                                                                         Irrigation event
                                                                                            64 gal/100ft
                                                                                              (0.17 in)
           Volumetric soil water content (in3/in3)   0.14                                                         (                ) Volumetric soil water content at 0- 6" depth
                                                                                                                  (                ) Irrigation event
                                                                                                                  (                ) Rate of water use and drainage
                                                                                                                  (                ) Day period
                                                     0.12                                                         (                ) Night period



                                                     0.10


                                                     0.08           slope of drainage
                                                                   and extraction lines
                                                                   = soil field capacity
                                                     0.06


                                                     0.04
                                                            11/06 0:00

                                                                         11/06 6:00




                                                                                                                      11/07 0:00

                                                                                                                                    11/07 6:00




                                                                                                                                                                              11/08 0:00

                                                                                                                                                                                           11/08 6:00




                                                                                                                                                                                                                                    11/09 0:00

                                                                                                                                                                                                                                                 11/09 6:00
                                                                                      11/06 12:00

                                                                                                    11/06 18:00




                                                                                                                                                  11/07 12:00

                                                                                                                                                                11/07 18:00




                                                                                                                                                                                                        11/08 12:00

                                                                                                                                                                                                                      11/08 18:00




                                                                                                                                                                                                                                                              11/09 12:00
Fig.8. Example of practical determination of soil field capacity for sandy soil after irrigation

event.

         The depth of irrigation applied was 0.17 inches (34 gal 100 ft-1). After both irrigation

events, there was an expected increase in soil moisture content. The degree to which the soil

moisture content increases, however, is dependent upon volume of irrigation, which is normally

set by the duration of irrigation event. For plastic mulched drip irrigation in sandy soils, long

time period of irrigation results in a relatively large increase in soil moisture in the area below

the drip emitter. In Figure 8, the spike in soil moisture was temporary, as the irrigation water

rapidly drained down beyond the 6 inch zone (11/06, between 9:00 am and 7:00 pm). This rapid
University of Florida - Agricultural & Biological Engineering Department
                                                                                                                                                 38
spike in soil water content indicates that the soil water content as measured by the SMS probes

rapidly reaches a point above the soil water holding capacity and the water percolated down to

deeper soil layers. Between 11/06 at 6pm and 11/07 at 7:00 pm (Fig. 13), the soil water content

declined to a constant rate due “slower” soil water extraction by drainage, occurred during the

day and night and evapotranspiration, occurred exclusively during the daylight. For sandy soils,

the change in the slope of drainage and extraction lines, in other words, changing from “rapid” to

“slower” decrease in soil water content can be assumed as the “field capacity point”. At this

time, the water has moved out from the large soil pores (macropores), and its place has been

taken by air. The remaining pore spaces (micropores) are still filled with water and will supply

the plants with needed moisture. It is very important the irrigation manager understands this

concept of “field capacity” to establish an irrigation control strategy goals of providing optimum

soil moisture for plant growth, productivity, and reduction of fertilizer nutrient leaching.

        One of the advantages of the SMS technology over the tensiometers is that they can be

attached to a data logger that allows growers to have access to soil moisture trends according to

the past irrigation events at different soil depths (e.g. Fig. 11) and locations across field.

Depending on the commercial system, data may be available wirelessly or through an internet

portal. This enhanced access to the field data allows irrigation manager to better evaluate his

own irrigation practices and improve irrigation scheduling accordingly to the plant needs and to

the previous irrigation events. We envision that in commercial farms, automated visual

presentation in a graphical format and with very easy access would be a very useful tool to the

irrigation manager fast evaluates the trends of soil moisture on a relative basis.




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                                                      39
4. Identification of drawbacks of the use of SMS and future research needs

        We identified that the implementation of the use of SMS by growers will require further

adaptation of the current irrigation systems to the SMS technology and vice-versa. The

performance of the SMS for by-pass automated irrigation system with pressurized water sources

like we used in our experimental site, resulted in significant water savings and sometimes an

increase in vegetable yields. However, irrigation systems adopted by commercial growers have

diesel pumps and in general the diesel pumps are manually switched on. On demand irrigation

will require a pressurized system or specific mechanism to start the pump engine remotely. This

technology was not available by the vendors SMS systems that we used in the research plots. In

our demonstration site we observed that some irrigation blocks took up to an hour to fully

pressurize the drip system due to the length of the beds. The required times to fully pressurize the

systems can be a problem when soil moisture sensors are used for on demand irrigation,

especially in the determination of the irrigation duration. The areas closer to the main irrigation

lines will be wetter than the end of the drip lines. In this case, proper localization of the soil

moisture sensors needs to be investigated to assure that the sensor probe is located in a

representative area, not in a wetter or drier spot than the average of the area controlled by the

SMS. In some cases, irrigation blocks may need to be redesigned to adapt SMS control. The

farm we worked on has a typical irrigation system with large blocks which lead to gross soil

moisture control within the field with limited numbers of sensors.

        The expansion of the use of soil moisture sensor technology to monitor and control

irrigation in large areas requires a more detailed study of soil moisture in the upper soil layer.

The variance of soil moisture spatial patterns is expected to be dominated by soil type,

topography and vegetation. In addition, the characterization of soil moisture variability can be


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related to the topographical attributes such as slope, elevation, and distance from the drainage

channel. This information would be crucial to a successfully implementation of SMS system

especially for areas susceptible to flooding or with high water infiltration rates. The number of

soil moisture sensors needed to effectively control irrigation or monitor soil in cropped areas is

still unknown. However, independent of the number of SMS sensors installed in a given area,

wireless communication between them with a master unit or to a central computer where the

irrigation manager can have easy access to the data is essential. More advanced communication

systems will integrate long range communication between sensor nodes with a central unit which

will make the data available in the internet. This central computer will store and process the

changes in soil moisture information according to the plant water requirement and ideal soil

moisture threshold defined from the experimental results achieved in this project. For on-demand

irrigation, simple algorithms would be able to define the water requirement and automatically

start the irrigation pump and/or notify the irrigator by cell phone text message or any other alert

system when and how much irrigate. For example, most of the current drip irrigation systems in

the Manasota basin have diesel pumps which are manually turned on, future adaptation of the

startup system will be required in order to make the on demand system ready to be used by

growers.

        We also envision that a next step on the evolution of the use of SMS in the agriculture

will be the full automation of the irrigation system. At the present, there are two types of

automated irrigation control using SMS, they are called on-demand and bypass control. On-

demand irrigation control consists of a control system that irrigates in response to soil moisture

measurements in the irrigated zone to maintain soil moisture content within low and high

thresholds. Thus, this type of control system must determine when to start and when to terminate

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irrigation, which is controller and sensor intensive. That is to say that there is little room for

error in the control system or sensor performance. Alternatively, bypass control simply bypasses

timed irrigation events when measured soil moisture exceeds preset thresholds (e.g. field

capacity as the upper limit). This type of control is simpler from a controller standpoint;

however, the user must program the number and length of irrigation events to correspond to plant

water requirements.


5. Summary

        Soil moisture sensor based irrigation of vegetable crops has a strong potential for saving

irrigation water. Advances in soil moisture sensors and irrigation controllers have made them

easier to use and the cost of energy has made sensor a more viable alternative. In the past, soil

moisture sensors have not been used widely by growers due to costs, the level of technical skill

required and sensor maintenance required. Continued restrictions aimed at reducing nutrient

leaching and recent increases in energy costs have increased grower interest in use of improved

technologies. However, more work is needed to develop irrigation scheduling recommendations

and automated control systems that the majority of vegetable crop growers would use. The

implementation of on demand automated irrigation by growers will require further adaptation of

the current irrigation systems to the soil moisture sensor technology. In some cases, vegetable

irrigation blocks may need to be redesigned to adapt SMS control technology. Detailed analysis

of sensor position in microirrigated crops, particularly plastic mulched vegetable systems is

needed. Guidelines on commercial automatic soil moisture based irrigation controls as a best

management practices should be developed for vegetables. The grower guidelines should include

number of sensors required and optimum placement relative to varying soil conditions of

commercial production. An economic assessment of costs associated with and benefits derived

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from conversion of irrigation systems in vegetables from seepage to drip irrigation needs to be

conducted to promote water conservation by vegetable growers in south Florida. Finally,

multiple on-farm demonstrations of this technology will likely be necessary for grower adoption

over time.


6. Cited References:

Dukes, M.D., E.H. Simonne, W.E. Davis, D.W. Studstil, and R. Hochmuth. 2003. Effect of
        sensor-based high frequency irrigation on bell pepper yield and water use, pp. 665-674
        Proc. 2nd Intl.Conf. Irr. and Drainage, Phoenix, Ariz.
Hutson, S.S., N.L. Barber, J.F. Kenny, K.S. Linsey, D.S. Lumia, and M.A. Maupin. 2004.
        Estimated use of water in the United States in 2000. U.S. Geological Survey Circ. 1268.
Jones, J.B.J., and V.W. Case. 1991. Sampling, handling, and analyzing plant tissue samples, p.
        289-427, In R. L. Westerman, ed. Soil Testing and Plant Analysis, 3rd ed, Madison, WI.
Maynard, D.N., and B.M. Santos. 2007. Yields of vegetables, p. 95-96, In S. M. Olson and E.
        Simonne, eds. Vegetable Production Handbook for Florida 2007-2008. IFAS,
        Gainesville.
Olson, S.M., D.N. Maynard, G. Hochmuth, C.S. Vavrina, W.M. Stall, M.T. Momol, S.E. Webb,
        T.G. Taylor, S.A. Smith, and E. Simonne. 2005. Tomato production in Florida, p. 357-
        375, In S. M. Olson and E. Simonne, eds. Vegetable Production Handbook for Florida
        2005-2006. IFAS, Gainesville.
Simonne, E.H., M.D. Dukes, R.C. Hochmuth, D.W. Studstill, G. Avezou, and D. Jarry. 2006.
        Scheduling Drip Irrigation for Bell Pepper Grown with Plasticulture. Journal of Plant
        Nutrition 29:1729 - 1739.
USDA. 2005. United States standards for grades of sweet peppers USDA, Washighton, DC.
USDA. 2008. Vegetables, April 2008 Report National Agricultural Statistics Service (NASS),
        Agricultural Statistics Board, U.S. Department of Agriculture, Washington, D.C. 22 Oct.
        2008. <http://usda.mannlib.cornell.edu/usda/current/Vege/Vege-04-03-2008.pdf>.
Zotarelli, L., J.M. Scholberg, M.D. Dukes, R. Munõz-Carpena, and J. Icerman. (2009). Tomato
        yield, biomass accumulation, root distribution and water use efficiency on a sandy soil, as
        affected by nitrogen rate and irrigation scheduling. Agricultural Water Management,
        96(1), 23-34.
Zotarelli, L., M.D. Dukes, J.M.S. Scholberg, K.L. Femminella, and R. Munoz Carpena (2010).
       Irrigation scheduling of green bell pepper using capacitance soil moisture sensors.
       Journal of Irrigation and Drainage Engineering (accepted).
Zotarelli, L., J. M. Scholberg, M. D. Dukes, R. Muñoz-Carpena. (2007) Assessing methods for
       monitoring N leaching dynamics of raised-bed plastic-mulched vegetables produced on a
       sandy soil. J. of Environ. Qual. 36 (4) 953-962.




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7. Publication production

Publications listed below were generated from research finding of “SWFWMD - Evaluation and

Demonstration of Soil Moisture Based On-demand Irrigation Controllers for Vegetable

Production - (B228)” and “FDACS - Developing Production Practices for Efficient Fertilizer &

Irrigation Use in Vegetable Crops (#9198)” projects.


Research Publications - Refereed
    1. Zotarelli, L., M.D. Dukes, J.M.S. Scholberg, K.L. Femminella, and R. Munoz Carpena
       (2010). Irrigation scheduling of green bell pepper using capacitance soil moisture
       sensors. Journal of Irrigation and Drainage Engineering (accepted).
    2. Dukes, M.D., Zotarelli, L., Morgan, K.T. (2010). Use of irrigation technologies for
       vegetable crops in Florida. Horttecnology 20 (1). (In press).
    3. Zotarelli, L., M.D. Dukes, J.M. Scholberg, R. Munõz-Carpena, and J. Icerman. (2009).
       Tomato nitrogen accumulation and fertilizer use efficiency on a sandy soil, as affected by
       nitrogen rate and irrigation scheduling. Agricultural Water Management 96:1247-1258.
    4. Scholberg, J. M., Zotarelli, L., Tubbs, S.R., M. D. Dukes, R. Muñoz-Carpena. (2009).
       Nitrogen uptake efficiency and growth of bell pepper in relation to time of exposure to
       fertilizer solution. Communication in Soil Science and Plant Analysis 40:2111-2131.
    5. Zotarelli, L., J.M. Scholberg, M.D. Dukes, R. Munõz-Carpena, and J. Icerman. (2009).
       Tomato yield, biomass accumulation, root distribution and water use efficiency on a
       sandy soil, as affected by nitrogen rate and irrigation scheduling. Agricultural Water
       Management, 96(1), 23-34.
    6. Zotarelli, L., M. D. Dukes, J. M. Scholberg, T. Hanselman, K. Femminella, R. Muñoz-
       Carpena. (2008) Nitrogen and water use efficiency of squash for a plastic mulch bed
       system on a sandy soil, as affected by nitrogen rate and irrigation method. Scientia
       Horticulturae, 116:8-16.
    7. Zotarelli, L., J. M. Scholberg, M. D. Dukes, R. Muñoz-Carpena. (2007) Assessing
       methods for monitoring N leaching dynamics of raised-bed plastic-mulched vegetables
       produced on a sandy soil. J. of Environ. Qual. 36 (4) 953-962.


Extension Publications
   1. Simonne, E.H., M.D. Dukes, and L. Zotarelli (2010). Principles and Practices of
       Irrigation Management for Vegetables, p. XX-XX, In S. M. Olson and E. Simonne, eds.
       Vegetable Production Handbook for Florida 2010-2011. IFAS, Gainesville, FL. (In
       press).
    2. Zotarelli, L., M. D. Dukes (2010) Interpretation of soil moisture content to determine soil
University of Florida - Agricultural & Biological Engineering Department
                                                      45
        field capacity and avoid over irrigation in sandy soils using soil. EDIS (In review).
    3. Zotarelli, L., M. D. Dukes, T.P. Barreto. (2009). Interpretation of Soil Moisture Content
       to Determine Soil Field Capacity and Avoid Over Irrigation in Sandy Soils Using Soil
       Moisture Measurements. Issue No. 550, October 2009. (Available at:
       http://www.hos.ufl.edu/vegetarian/09/Oct/Interpretation%20of%20Soil%20Moisture%20
       -%20Avoid%20Over%20Irrigation.html)
    4. Zotarelli, L., M. D. Dukes. (2009). Irrigation strategies to minimize nitrate leaching for
       drip irrigated tomatoes. The Vegetarian Newletter. Issue No. 543 March 2009. (Available
       at:
       http://www.hos.ufl.edu/vegetarian/09/Mar/Irr%20Strategies%20Minimize%20N%20Lea
       ching%20Drip%20Irrigated%20Tomatoes.html)
    5. Zotarelli, L., M. D. Dukes. (2008) Use of soil moisture sensing and irrigation scheduling
       for pepper production”. The Vegetarian Newletter. Issue No. 538 October 2008.
       (Available at:
       http://www.hos.ufl.edu/vegetarian/08/Oct%2008/Use%20of%20Soil%20Moisture%20Se
       nsing%20and%20Irrigation%20Scheduling%20for%20Pepper%20Production.html)
    6. Zotarelli, L., M. D. Dukes. (2008) Improving water use efficiency for tomato production
       using soil moisture sensing and irrigation scheduling. The Vegetarian Newletter. Issue
       No. 531 March 2008. (Available at:
       http://www.hos.ufl.edu/vegetarian/08/March%2008/Zotarelli%20&%20Dukes%20-
       %20March%202008%20Vegetarian%20Newsletter.pdf)
    7. Morgan, K.T., M.D. Dukes, L. Zotarelli (2008). Use of irrigation technologies for
       production of horticultural crops in Florida. In: Proccedings of the 2008 Workshop on
       BMP Research and Education Priorities for Horticultural Crops. Ed. Obreza, Simonne, E.
       And Boman, B. Apopka, FL. May 20-21, 2008.
    8. Zotarelli, L., J. M. Scholberg, M. D. Dukes and R. Muñoz-Carpena. 2005. Nitrogen and
       Irrigation Management: Is it possible to improve water use efficiency and reduce nitrate
       leaching of vegetables crops in Florida? 2005 Nutrient Management Education Core
       Group Newsletter. Soil and Water Science Department, University of Florida, IFAS
       Extension, Gainesville. FL.
Non-refereed Publications

    1. L. Zotarelli, Dukes, M.D., Barreto, T.P. (2010). Indirect determination of crop-coefficient
       of bell pepper using soil moisture sensors. (Submitted to the 5th National Decennial
       Irrigation Conference, Phonex, AZ).
    2. L. Zotarelli, Dukes, M.D., R. Muñoz-Carpena (2009). Soil water distribution and nitrate
       leaching of drip irrigation controlled by soil moisture sensors. Estudios en la Zona no
       Saturada del Suelo. Vol IX, O. Silva et al. Barcelona, 18 a 20 de Noviembre, 2009.
    3. L. Zotarelli, Dukes, M.D. (2009) Physiological and yield response of green bell pepper to
       soil moisture sensor controlled drip irrigation. In: Proc. of the World Environmental &
       Water Resources Congress, May 17-21, 2009, Kansas City. ASCE:Reston, VA.

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    4. L. Zotarelli, Dukes, M.D. (2009) Potential and limitation of the use of soil moisture
       sensor controllers on drip irrigation. In: Proc. of the ASABE Annual International
       Meeting, June 21-24, 2009. Reno, NV. ASCE.
    5. L. Zotarelli, Dukes, M.D. (2009) Use of soil moisture sensor-based irrigation on
       vegetable crops. Proc. Fla. State Hort. Soc. Paper No.V7. Vegetable Section, Irrig. Water
       Manag.
    6. Zotarelli, L., M.D. Dukes, J.M. Scholberg, R. Munõz-Carpena, and J. Icerman. 2008. Soil
       moisture, soil electrical conductivity and tomato root distribution of automated drip
       irrigation system controlled by soil moisture sensors. In: Proc. of the ASA-CSSA-SSSA
       International Annual Meeting, Nov 5-8, 2008, Houston, TX. ASA - CDROM.
    7. Dukes, M.D., R. Muñoz-Carpena, L. Zotarelli, J. Icerman, J.M.Scholberg. 2007. Soil
       moisture-based irrigation control to conserve water and nutrients under drip irrigated
       vegetable production. In: Jornada de Investigación en la Zona no Saturada. Vol. VIII,
       Nov 14-16, 2007. Cordoba, Spain. CD-ROM.
    8. Dukes, M.D., L. Zotarelli, J.M. Scholberg, R. Muñoz-Carpena. 2006. Irrigation and
       nitrogen best management practices under drip irrigated vegetable production. In: Proc.
       of the World Environmental & Water Resources Congress, May 21-25, 2006, Omaha,
       Nebraska. ASCE:Reston, VA.
    9. Scholberg, J.M., K.T. Morgan, L. Zotarelli, E.H. Simonne, and M.D. Dukes. 2006.
       Integrating root interception capacity and crop N demand into BMPs for vegetable crops.
       HortScience, 41(4) p. 987.
    10. L. Zotarelli, J.M. Scholberg, M.D. Dukes, H. Snyder, and R. Munoz-Carpena. 2006.
        Interaction between water and nitrogen application on yields and water use efficiency of
        tomato and pepper in sandy soil. HortScience, 41(4) p. 981.
    11. L. Zotarelli, J.M. Scholberg, M.D. Dukes, H. Snyder, and R. Munoz-Carpena. 2006.
        Nitrate leaching, yields and water use efficiency of zucchini squash under different
        nitrogen rates, irrigation methods in a sandy soil. HortScience, 41(4) p. 988.
    12. L. Zotarelli, J.M. Scholberg, M.D. Dukes, and R. Munoz-Carpena. 2006. Nitrogen and
        irrigation management to improve water use efficiency and reduce nitrate leaching of
        pepper and tomato crops in Florida. In: 18th World Congress of Soil Science, 9-15 July,
        2006, Philadelphia. p. 1-2.
    13. Scholberg, J.M., L. Zotarelli, K. Morgan, C. Cherr, and M.D. Dukes. 2005. Integrating N
        uptake dynamics of vegetable crops into production guidelines for more efficient N-
        fertilizer use. In: Proc. of the ASA-CSSA-SSSA International Annual Meeting, Nov 6-
        10, 2005, Salt Lake City, Utah. ASA - CDROM.
    14. Zotarelli, L., J.M.S. Scholberg, M.D. Dukes, and R. Munoz-Carpena. 2005. Quantifying
        nitrate leaching dynamics in vegetable production systems on sandy soils. In: Proc. of the
        ASA-CSSA-SSSA International Annual Meeting, Nov 6-10, 2005, Salt Lake City, Utah.
        ASA - CDROM.



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