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1 THE EFFECTS OF STRIP TILLAGE AND IRRIGATION IN PEANUT AND COTTON AND AN INVESTIGATION OF THE RELATIONSHIP BETWEEN COTTON SAP FLOW AND SOIL MOISTURE By JOSHUA LEE THOMPSON A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2012
2 2012 Joshua Lee Thompson
3 To my loving wife and best friend Sara, for always being loving and supportiv e of everything I do
4 ACKNOWLEDGMENTS For their support and guidance during my time as a graduate student at the University of Florida I would like to thank my committee: Dr. Diane Rowland, Dr. Barry Tillman, Dr. David Wright, and Dr. John Beasley. I am very grateful for each of their support and guidance during these past two years. I am blessed that I will be able to continue to learn from and work with each of them following my graduation. I would also like to extend special gratitude to Dr. Diane Rowland for all of the hard work and extra t ime she devoted to helping me with field research, presentations, data analyses and writing. I would also like to thank my fellow lab mates for their help, without whom, most of this would not have been possible. I would like to thank my wife, Sara, for su pporting me during this whole time. She spent hours analyzing root images for me, and for that I am grateful. I am also grateful for my parents, for always encouraging and supporting me in everything that I do.
5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 6 LIST OF FIGURES ................................ ................................ ................................ .......... 7 ABSTRACT ................................ ................................ ................................ ..................... 9 CHAPTER 1 LITERATURE REVIEW ................................ ................................ .......................... 11 Water Conservation for Southeastern U.S. Cropping Systems ............................... 11 Estimating Crop Water use in Irrigated Systems ................................ .................... 22 2 THE FEASIBILITY OF STRIP TILLAGE FOR WATER CONSE RVATION IN PEANUT AND COTTON PRODUCTION IN FLORIDA ................................ ........... 26 Summary ................................ ................................ ................................ ................ 26 Introduction ................................ ................................ ................................ ............. 27 Materials and Methods ................................ ................................ ............................ 32 Field Preparation and Crop Maintenance ................................ ......................... 32 Plant and Soil Measurements ................................ ................................ ........... 34 Statistical Analysis ................................ ................................ ............................ 36 Results and Discussion ................................ ................................ ........................... 36 Yield and Grade ................................ ................................ ............................... 3 7 In season Plant and Soil Characteristics ................................ .......................... 39 Summary ................................ ................................ ................................ .......... 46 3 AN INVESTIGATION OF THE RELATIONSHIP BETWEEN SOIL WATER CONTENT AND SAP FLOW IN COTTON UNDER IRRIGATED AND NON IRRIGATED CONDITIONS ................................ ................................ ..................... 87 Summary ................................ ................................ ................................ ................ 87 Introduction ................................ ................................ ................................ ............. 88 Materials and Methods ................................ ................................ ............................ 90 Field Preparation and Crop Maintenance ................................ ......................... 90 Plant and Soil Measurements ................................ ................................ ........... 91 Results and Discussion ................................ ................................ ........................... 92 LIST O F REFERENCES ................................ ................................ ............................. 105 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 113
6 LIST OF TABLES Table page 2 1 Cotton and Peanut Management ................................ ................................ ........ 47 2 2 Peanut and Cotton Yield.. ................................ ................................ ................... 48 2 3 ANOVA of Peanut and Cotton Yield.. ................................ ................................ 48 2 4 Peanut Grades.. ................................ ................................ ................................ 48 2 5 ANOVA Peanut Flower, Peg, and Pod Counts. ................................ .................. 49 2 6 ANOVA Leaf Area Index.. ................................ ................................ ................... 50 2 7 ANOVA Cotton Petiole Samples. ................................ ................................ ........ 51 2 8 ANOVA Cotton Root Architecture.. ................................ ................................ ..... 52 3 1 Relationship Between Soil Moisture and Sap Flow. ................................ ........... 97 3 2 ANOVA of Root Analyses.. ................................ ................................ ................. 98
7 LIST OF FIGURES Figure pag e 2 1 2011 Soil Moisture in Peanut. ................................ ................................ ............. 53 2 2 2011 Soil Moisture in Cotton.. ................................ ................................ ............. 56 2 3 2012 Soil Moisture in Peanut. ................................ ................................ ............. 59 2 4 2012 Soil Moisture in Cotton. ................................ ................................ .............. 62 2 5 Soil Temperature in Peanut. ................................ ................................ ............... 65 2 6 Soil Temperature in Cotton. ................................ ................................ ................ 66 2 7 2011 Florida 07 Flower, Peg, and Pod Counts. ................................ .................. 67 2 8 2011 Tifguard Flower, Peg, and Pod Counts. ................................ ..................... 69 2 9 2012 Florida 07 Flower, Peg, and Pod Counts.. ................................ ................. 71 2 10 2012 Tifguard Flower, Peg, and Pod Counts. ................................ ..................... 73 2 11 Leaf Area Index Peanut. ................................ ................................ ..................... 75 2 12 Leaf Area Index Cotton. ................................ ................................ ...................... 76 2 13 Average Nitrate and Potassium 2011 and 2012.. ................................ ............... 78 2 14 Cotton Petiole Potassium 2011 and 2012.. ................................ ........................ 79 2 15 TRL and TSA Cotton 2011.. ................................ ................................ ............... 80 2 16 TRL and TSA Cotton 2012.. ................................ ................................ ............... 81 2 17 Figure 2 17. Rooting Profile Cotton 2011.. ................................ ......................... 82 2 18 Rooting Profile Cotton 2012.. ................................ ................................ .............. 84 3 1 Rainfall and Irrigation Distribution. ................................ ................................ ...... 99 3 2 Cotton Total Daily Water Use. ................................ ................................ .......... 100 3 3 Soil Moisture. ................................ ................................ ................................ .... 101 3 4 Poly nomial Regression of TDWU with Soil Moisture.. ................................ ...... 102 3 5 Linear Regression of TDWU with Soil Moisture. ................................ ............... 103
8 3 6 Cotton Rooting Profile.. ................................ ................................ .................... 104
9 Abstract of T hesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science THE EFFECTS OF STRIP TILLAGE AND IRRIGATION IN PEANUT AND COTTON AND AN INVESTIGATION OF THE RELATIONSHIP BETWEEN COTTON SAP FLOW AND SOIL MOISTURE By Joshua Lee Thompson December 2012 Chair: Diane L. Rowland Co c hair : Barry Tillman Major: Agronomy Water availability for peanut and cotton has become a major limiting factor for production in the southeastern U.S. as rainfall has become less reliable and irrigation sources are being depleted. Conservation tillage as wel l as irrigation could provide relief during drought conditions Additionally, irrigated cotton growers are in need of an accurate standard by which to schedul e irrigation. Currently, soil moisture sensors are common ly used to support irrigation decisions but may not accurately represent crop water demand. The objective of t he first study was to compare the e ffects of strip tillage (ST), conventional tillage (CT) and irrigation on peanut and cotton production. The design was a randomized strip plot using t wo cultivars of peanut (Florida 07 and Tifguard) and cotton (Phytogen 375 and 499) Irrigation increased yields in 2011 for both crops and all cultivars tested. In 2012, total rainfall during the growing season was much greater than 2011 ( 102 vs. 47 cm ) and overcame pot ential differences between irrigated and non irrigated treatment s in either peanut or cotton. These findings indicate tha t ST may be a
10 viable option for irrigated or non irrigated peanut and cotton growers in north central Florida, although there may be no yield benefit over CT The purpose of the second study was to quantify the relatio nship between soil moisture and cotton water use. The design was a complete randomiz ed block design with irrigated and non irrigated conditions. S ap flow and soil moisture measurements were logged continuously from 30 June 2012 until 30 July 2012 during th e peak water use period for c otton. Soil moisture was measured at 20 and 60 cm depths to determine the depth of water uptake in the crop. A nalyses showed a significant quadratic relationship in non irrigated cotton sap flow with soil moisture at 60 cm only This relationship indicates that plant water use is related to soil moisture at certain depths and that scheduling irrigation using the appropriate depth is critical
11 CHAPTER 1 LITERATURE REVIEW Water Conservation for Southeastern U.S. Cropping Systems Peanut ( Arachis hypogaea L.) and upland cotton ( Gossypium hirsutum L.) are crops well adapted to the climate and environment of the southeastern United States. These two crops have proven to work well in rotation in many parts of the southeast (FL, GA, AL ) and Virginia/Carolina region ( SC, NC, VA) with over 566,800 hectares of peanut and 5.1 million hectares of upland cotton planted in 2012, respectively (USDA/NASS, 2012). The commodities produced from these crops are essential for meeting national and gl obal needs for food and fiber as well as supporting local economies. Because of the critical economic importance of cotton and peanut, there is research that needs to be conducted investigating production methods that will rotect natural resources. A major factor that is currently affecting the profitability and sustainability of these two crops is water availability. Ground and surface waters are being depleted at alarming rates because of the expansion of urban water use, changes in precipitation patter n s in the past 2 3 decades, and increased agricultural irrigation use as necessitated by changes in precipitation patterns and growing demand for agricultural products. Consequently, the agricultural sector has received much of the blame for the depletion of water resources because irrigated agriculture uses approximately 60% of the total water withdrawals in the U.S. (Kenny et al., 2009). Therefore, it is essential that agricultural practices maximize the efficiency of water use. Part of the solution for improving water conservation in crop production is to utilize both rainfall and irrigation water in a way that maximizes the crop s water use
12 efficiency. This can partly be achieved by using conservation tillage, which is de fined tillage practices, often depending on climatic characteristics, soil types, crop species, and a variety of management factors including grower preference (Knowler and Bradshaw, 2007). All of these factors influence the amount of soil disturbance and crop residue within a conservation tillage system. Research on conservation til lage began in erosion (Cole, 1938). Since then, conservation tillage has been widely studied and adapted in the U.S. for its environmental and economic benefits. It is co mmonly used in corn and soybean production and to a lesser extent in other row crops such as cotton and peanut. The most common conservation tillage system in the southeast U.S. consists of utilizing winter cover crops to protect the soil against erosion a nd improve soil structure (Langdale et al., 1990). During the subsequent summer crop season, the winter crop residue can be rolled or left aboveground to provide a barrier against wind and water erosion as well provide some shade to inhibit weed seed germi nation during the growing season (Langdale et al., 1990) To plant the summer crop into the winter cover residue, many southeastern U.S. growers utilize a particular type of conservation tillage called strip tillage (ST). Strip tillage is an operation that typically tills 18 30 cm wide strips into the winter crop residue prior to planting. Planting will then occur in the middle of the se tilled strips. There are many purported benefits to conservation tillage that have been the subject of research over th e past several decades. First, c onservation tillage has been
13 shown to increase soil water infiltration (Arshad et al., 1999 ; Dao, 1993; Franzluebbers, 2002 ; Thierfelder and Wall 2009). Franzluebbers (2002 ) conducted a study that compared the soil organic c arbon and water infiltration rates between long term convention al till (CT) and no till ( a type of conservation tillage that involves direct seeding into an un tilled soil surface) sites that had been in crop production for approximately 25 years The no t ill system in this study proved to have greater soil organic carbon at shallow depths and thus, an infiltration rate that was 3 times greater than the soil under CT (Franzluebbers, 2002 ) Arshad et al (1999) similarly found that long term no tillage lead to increased soil organic matter, which improved the soil structure, allowing for greater water infiltration as compared to CT However some studies have found that conservation tillage can decrease soil wat er infiltration (Lindstrom and Onstad, 1984; Unger, 1992) due to increased soil bulk density, penetrometer resistance and presence of macropores in the top layers of soil. O ther research demonstrates that c onservation tillage can increase bulk soil volume tric water content (Blevins et al., 1971; Gantzer and Blake, 1978; Sullivan et al., 2007; Tollner et al., 1984), especially during the early season when surface evaporative losses of tilled soils are high (Zhai et al., 1990). Blevins et al. (1971) showed t hat under a no till system, soil water was conserved to a greater degree than under CT to a depth of 60 cm ; below which, no differences in soil moisture were detected. Gantzer and Blake (1978) also found that no till increased soil water content as compare d to CT in the top 30 cm of the soil profile, attributing the difference to increased evaporation in the loose soil of the conventionally tilled plots.
14 In addition to increasing plant available water in the soil, conservation tillage also has the capabil ity to enhance rooting depth and root proliferation possibly because of the formation of root channels formed by residual crop roots ( Loison et al., 2012; Wright et al., 2004 ; Rasse and Smucker, 1998 ). A study in West Texas in which rooting characteristic s were measured i n peanut and cotton with a minirhizotron system found that cotton roots explored deeper soil depths and had much greater rooting development in ST than in CT (Rowland et al., 2008). This study concluded that t he root channels left by the r ye ( Secale cereale L.) in the ST system likely provided space for cotton roots to explore deeper soil depths (Rowland et al., 2008) Other root studies comparing the effects of conservation and conventional tillage have been conducted on corn. Newell and W ilhelm (1987) conducted a study that examined corn root lengths near the soil surface (0 15 cm) and remaining rooting profile (15 150 cm) under irrigated, partially irrigated, and non irrigated conditions in both CT and conservational tillage systems. Thei r results showed that under conservational tillage, root length was increased in both surface and deeper profile regions compared to CT. They also noted that non irrigated roots tended to explore deeper into the soil profile and that conservation tillage m ay be a way to reduce irrigation requirements. Hilfiker and Lowery (1988) showed that reduced tillage increased corn root density as compared to CT, attributing the differences to increased wheel traffic in the CT plots. In contrast, Dwyer et al., (1996 ) s howed that reduced tillage actually decreased the rooting depth of corn This study compared root mass distribution in corn between CT and three forms of conservation tillage (chisel, ridge, and no till). Root mass was estimated from soil cores and taken i n 10 cm increments to a depth of 60 cm and it was found that rooting depth
15 was increased under increased tillage. They surmised that since soil moisture was decreased in the top layers of soil under CT, roots were then encouraged to explore deeper soil depths (Dwyer et al., 1996) Despite the benefits seen for some individual environmental characteri stics in systems utilizing conservation tillage, impacts on overall crop yield have been variable. This is likely due to the wide variability in tillage oper ations that are classified as conservation tillage, as well as variability caused by environmental and management factors that are unique to particular regions and field characteristics. For example, a study in Virginia compared corn grain yield under no t ill and CT and found that no tillage increased yields by an average of 1523 kg ha 1 which was attributed to greater soil moisture within the top 30 cm of the soil profile (Jones et al., 1969). Shear and Moschler (1969) also conducted a study in Virginia an d found that high corn grain yields could be maintained without rotation under no tillage into a killed winter cover crop. Olson and Schoeberl (1970) conducted a study in North Dakota that compared three vastly different reduced tillage methods with CT inc luding : planting directly into wheel tracks made into plowed soil, leaving the inter rows in roughly plowed condition; a single blade opener prior to the planter which was similar to no till; and the use of a lister to o pen a furrow to plant the seed. Des pite these broad operational differences, there were no significant impacts on yield among the tillage treatments A more recent study conducted in Georgia compared no till and CT as well as synthetic and organic (poultry litter) forms of nitrogen and the effects on corn yield (Endale et al., 2008). This study found that no till by itself increased grain yield by 11% and the combined effects of no till and poultry litter increased grain yield by 18% as compared to CT and synthetic
16 fertilizer. The increased yield from no till was attributed to the 18% greater soil moisture in the to p 10 cm of the no till system. A study conducted in Idaho compared the effects of reduced tillage to CT systems on winter wheat production. They found that no till yields were only 78% of conventional yields and attributed the yield decrease to impeded root growth and hindered exploration of deeper soil profiles (Hammel, 1995). Overall, there are many studies that have shown a yield benefit from conservation tillage (Smiley and Wilk ins, 1993; Wagger and Denton, 1989) ; while still others have shown that conservational tillage is detrimental to yield (Graven and Carter, 1991; Halvorson et al., 2006; Hammel, 1995.) In an effort to synthesize this variability among different study result s, meta analyses have been undertaken to determine overall yield impacts between conservation and conventional tillage. A meta analysis was conducted to compare crop yields under conventional and conservation tillage in 47 different studies in Europe with a variety of crops (Van den Putte et al., 2010). The analysis showed no reduction in yield under reduced tillage operations (excluding no till) for potato and sugar beets but a significant reduction in yield for grain corn and to a lesser extent in other cereals. The reason for this is uncertain ; however, these researchers believe that reduced tillage may hinder root proliferation and development in fibrous roots in cereals (Pietola, 2005; Quin et al., 2006). Miguez and Bollero (2005) conducted a meta anal ysis of 37 studies in the United States and Canada and showed that the presence of a winter cover crop, regardless of subsequent tillage operation s in the spring, increases the yield of corn, with a 21% increase for the use of a grass/legume mixture as com pared to fallow conditions in the winter The increase in
17 corn yield was attributed to reduced soil erosion and improve d tilth as well as reduced weed pressure (Miguez and Bollero, 2005) Similar to the previous crops discussed above, the yield impacts of conservation tillage in peanut have been variable (Brandenburg, et al., 1998; Hurt et al., 2006; Marois and Wright, 2003; Tubbs and Gallaher et al., 2005; Zhao et al., 2009 ). Marois and Wright (2003) conducted a two year study to compare the effects of til lage on Tomato spotted wilt virus (TSWV) incidence in peanut an economically important disease that is vectored by thrips ( Frankliniella sp. ) The first year of the study they found that conservation tillage in the form of ST had 50% less TSWV incidence t han conventional till as well a significantly greater yield (2510 vs. 1900 kg per hectare) ; however the second year showed no differences in disease or yield. The first year of the study was a significantly drier year which resulted in up to 30% greater so il moisture in ST, likely contributing to increased yield that year (Marois and Wright, 2003) Tubbs and Gallaher (2005) conducted a two year study that compared peanut utilizing ST into terminated rye with CT and found no significant difference in peanut yields between the two tillage systems. Another study compared the yield of peanut strip tilled into a terminated bahia grass sod with conventionally tilled peanut (Zhao et al., 2009) and found a yield benefit to ST one year out of the two year study. Conv ersely, other studies have shown negative effects of ST in peanut (Wright and Porter, 1995; Wright and Porter 1991; Colvin et al., 1988;) Colvin et al. (1988) conducted a study of several different tillage methods in peanut including no till, strip till, a nd conventio nal till into cut wheat stubble. They found that yields were consistently higher in CT plots than in ST and no till plots attributing the result to lower water availability. The ST and no till equipment included
18 ripper or subsoil shanks which disrupted a shallow hardpan, resulting in drainage in these sandy soils which decreased water availability in the conservation tillage plots (Colvin et al, 1988) Finally, a 4 year study conducted in Virginia test ed the yield effects of ST on three v irgini a type cultivars, which have a more upright growth pattern and larger pods as compared to runner type cultivars, and found that ST reduced peanut yields by 15% compared to CT (Wright and Porter, 1995) In cotton, yields under ST have also been variable. L ascano et al. (1994) showed that in the high plains of Texas, ST reduced soil evaporation and increased crop transpiration leading to increased lint yield by 35% as compared to CT This study also observed greater leaf area index during the early part of t he season under ST as compared to CT In contrast, a study in the Florida panhandle showed that ST cotton into wheat residue did not increase yield over CT ( Wiatrak et al., 2005). Studies using other types of conservation tillage aside from ST, such as no till have a longer history in cotton A study in northern Alabama showed that no till increased lint yields as compared to conventional till by conserving soil moisture in the top 7 cm of the soil (Nyakatawa et al., 2000). Bauer et al. ( 2010 ) in coastal S outh Carolina conducted a six year study that coincided with a considerable five year drought (1998 2002) and found that no till increased cotton yields in each year except in the year with normal rainfall These results indicate that no till can be good insurance against drought conditions for non irrigated farmers in that region Other studies show either no differences in yield or decreased yield through the use of conservation tillage (Brown et al., 1985; Pettigrew and Jones, 2001; Stevens et al., 1992 ). Pettigrew and Jones (2001) conducted a study in the Mississippi delta which compared CT and no till cotton. They found that no till
19 generally delayed emergence and canopy growth until mid bloom, when leaf area ind ices reached those which were similar to CT. They saw an 11% decrease in lint yield under no till, attributing this difference to fewer bolls per plant. The variety of responses from peanut and cotton to ST and other types of conservation tillage are likely attributable to the wide range of envi ronments and tillage systems where these conservation tillage systems have been tested One major consideration that is not addressed in any of these studies is the quantification of the amount of cover crop residue in each conservation tillage system. Thi s amount could have a major effect, given that the majority of the benefits in conservation tillage come from the presence of crop residue (Langdale et al., 1990). Although the definition of conservation tillage includes a requirement of 30% or more of soi l surface to be covered in crop residue (CTIC, 2004), this requirement is not necessarily met in each of these studies claiming to test a form of conservation tillage. Additionally, soil type s on which these studies were performed were broadly variable So il types ranging from clay loams to fine sands were used in these studies and the impact of different tillage type s in these differing soils should be highly dependent on soil physical characteristics such as porosity and bulk density. With the exception of two (Colvin et al., 1988; Tubbs and Gallaher, 2005), none of these studies have been conducted in both a hot hu mid environment in combination with sandy, drought prone soils This is because the majority of peanut and cotton product ion in the southeast is not in north c entral Florida, and thus research has been focused elsewhere where production is greater. Further, irrigation may be heavily contributing to the variability i n yield results among studies on conservation tillage. Of the peanut and cotton studies mentioned
20 above, three were ir rigated throughout the season, three were partially irrigated, and five did not report the use of irrigation, implying irrigation was not used. None of these studies however, compared the use of ST with and without irrigation. The USDA Ag Census (2007) reported that there were over 1 million hectares of irrigated cropland in the southeastern U.S. production occurs (Alabama, Florida, Georgia). It is generally understood that irrigation will improve yields for both crops (Masters and Lamb 2003). An eight year study in Georgia showed that irrigation increased peanut yields 5 out of the 8 ye ars and by an average of 569 kg ha 1 (Lamb et al., 1997). There were 3 years of the study in which irrigation had no significant impact on yield, but these years were characterized by considerable rainfall which reduced the amount of supplemental irrigation needed Additionally, the study showed that the profitability of irrigation depended heavily on the annual commodity price (Lamb et al., 1997) Despite the benefit of irrigation on overall yield, many farmers do not have irrigation because of the high initial ex pense, high energy cost to run the systems and the difficulty of obtaining permits to drill wells for aquifer withdrawals. Because of the economic and environmental costs of irrigation, there is potential for decreasing the need for irrigation with conse rvation tillage and in particular ST. Strip tillage allows greater rainfall infiltration and storage in the soil thus reducing the amount of supplemental irrigation required (Arshad et al., 1999; Dao, 1993; Franzluebbers, 2001; Thierfelder and Wall 2009). A study in Georgia in 2007 was conducted to test the effects of simulated rainfall on conventional and conservation tillage studies across the state where 90% of the conservation tillage in these studies was ST (Sullivan et al., 2007). They estimated that conservation tillage decreased ir rigation requirements by 4
21 14%. Although ST may decrease irrigation requirements, the degree to which ST impacts irrigation benefits has not been documented in additional studies or regions outside of Georgia. It is theref ore imperative that further research be conducted to determine if ST can allow growers to reduce irrigation applications. Further, for non irrigated growers, it is important to document possible increases in plant available water in a n ST system. If conse rvation tillage is to have any effects compared to CT on soil water relations, soil physical properties, and ultimately crop growth and yield, we would expect those to be found under the sandy conditions and environment of n orth central Florida where low water holding capacity soils are coupled with high temperatures and seasonally sparse rainfall. Under these conditions the potential for differences between ST and CT should be high. Only a few of the studies mentioned above have invest igated plant characteristics such as leaf area index, reproductive development, or rooting characteristics along with yield under these conservational tillage systems (Lascano et al., 1994; Pettigrew et al ., 2004; Marois and Wright, 2003 ). The absence of t hese types of data to explain differences in yield prevent complete understanding of why peanut and cotton yields have been variable in conservation tillage. Therefore, there is a need for conservation tillage research in peanut an d cotton on the sandy soi ls of north central F lorida, and to study relevant crop responses to understand how this practice may effect crop production in a region that has great potential for improved water use efficiency. The objective of this study is to compare the effects of st rip tillage with and without irrigation on peanut and cotton yields in north c entral Florida. Additionally, this
22 study will characterize the effect of tillage on soil moisture, soil temperature, leaf area index, peanut reproductive development, cotton peti ole nutrition and cotton root development, along with yield of both crops under these treatments. Estimating Crop Water use in Irrigated Systems Cotton is an efficient user of water compared to other crops and has the potential to perform well even under water deficit (Ackerson & Krieg, 1977). However, t he sandy, drought prone soils in some parts of the southeast ern U.S. challenge the water use efficiency of cotton, especially in years when rainfall is not timely or is reduced. It is therefore important f or growers and researchers to understand how soil moisture is related to crop water use responses during changes in the soil moisture environment. Further, because many growers use supplemental irrigation, the relationship between soil moisture and crop w ater use has important implications for irrigation scheduling because soil moisture sensors are commonly used for triggering water application. Irrigated growers have a deep responsibility for water conservation and resource stewardship because irrigated agriculture is a primary user of both surface an d aquifer water sources (Hutson et al., 2004 ). This makes efficient irrigation scheduling critical to achieve sustainable water application systems. There are a variety of irrigation scheduling techniques from checkbook methods (Lundstrom and Stegman, 1988 ), evapotranspiration (ET) estimations (Wright and Jensen, 1978) and crop modeling (George et al., 2000) ; but many irrigation decision systems now rely solely on soil moisture estimations to determine cro p water use. Typically, a soil moisture threshold in terms of volumetric water content or soil matric potential is determined and soil moisture is monitored through the season so that when
23 levels fall below the threshold irrigation is applied (Campbell a nd Campbell, 1982). The most common measure of soil moisture has been by measuring soil matric potential (SMP) and SMP sensors for irrigation scheduling have been shown to be effective for many crops including many vegetable crops (Thompson et al., 2007) a nd field crops such as cotton and rice (Vellidis et al., 2008; Kukal et al., 2005) In particular, Irrigator Pro for cotton, a commonly used irrigation scheduling system for cotton in the southeast ( www.ars.usda.gov ), utilizes gypsum block sens ors for sche duling irrigation. However, in all of the irrigation scheduling systems utilizing measurements of soil moisture, the identification of acc urate thresholds and soil depths which represent crop water use are essential. I f soil moisture thresholds used for irrigation decisions are too high, the potential for improving water use efficiency is removed. The key to optimizing water use efficiency would be to insure there was an accurate match between soil moisture measurement and actual crop water use. Further, determining which soil depth represents the zone of active root activity and, thus is the most appropriate for soil moisture monitoring, is often not known and little studied. Despite the heavy reliance on soil moisture sensors for triggering irrigation, few studies have investigated and quantified the direct measure of soil moisture with crop water use during the growing season to verify that soil moisture is an adequate surrogate for indicating crop water need. To bet ter understand the relationship between soil moisture and actual plant water use, a comparison between soil moisture dynamics and direct measurements of plant water use is needed. To measure water use directly on an individual plant, the heat pulse method can be used (Baker and van Bavel, 2006 ). The heat pulse method is
24 able to calculate the flow of sap through the stem using an insulated collar containing a heating strip with one thermocouple on either side. The temperature difference between the thermocou ples is measured several times per second as well as the amount of time between the exertion of the heat pulse and the return of the sap to its initial temperature. These calculations, indexed to a stem diameter provide a direct calculation of stem sap f low from a given plant (Smith and Allen, 1996). Cohen et al., (1988) demonstrated that the heat pulse method can be effectively used on cotton and Lascano (2000) demonstrated that cotton sap flow measurements can be more effective for irrigation scheduling than ET replacement models. Water uptake and transpiration in cotton increases relative to canopy d evelopment so that the crop can transpire between 5 7 mm of water per day when the canopy is fully mature (Lascano and Baumhardt, 1996; Lascano, 2000). If c otton is under water deficit stress, however, osmotic adjustment will occur and transpiration will decrease (Oosterhuis and Wullschlegger, 1987). This would indicate that transpiration would be lower in a cotton plant that does not receive supplemental irr igation or has experienced some drought stress compared to a plant that receive s ample irrigation. Measurements of sap flow in cotton h ave been used successfully to identify proper crop coefficients to calculate ET (Lascano, 2000) which could be used for scheduling irrigation However if soil moisture methods are to be used, identification of the appropriate soil depths to monitor for irrigation scheduling is also essential to matching sap flow with measurements of soil moisture. I nformation about basic ro ot architecture would be needed to accomplish this and c ould provide important insight into how to manage deficit irrigation in cotton production in particular Few studies relate root
25 architecture to both direct and indirect measurements of crop water u se ( Taylor and Klepper, 1974; Lascano and van Bavel, 1984). Therefore, what is needed to justify the use of soil moisture monitoring for cotton irrigation scheduling is a simultaneous measurement of soil moisture at varying depths and sap flow, combined wi th quantification of rooting architecture over time. To address this research need, the objective in this study was to correlate measurements of soil moisture at two depths that are likely active zones of water uptake for southeastern cotton (20 and 60 cm ) with daily sap flow during the mid to late season, a period represent ing peak water use in the crop. Further, root growth and architecture were quantified and related back to patterns of soil moisture and water up take rates that were observed. This infor mation could then be used to confirm the utility of soil moisture sensors for scheduling irrigation in southeastern cotton.
26 CHAPTER 2 THE FEASIBILITY OF STRIP TILLAGE FOR WATER CONSERVATION IN PEANUT AND COTTON PRODUCTION IN FLORIDA Summary Water availability for peanut and cotton production has become and will continue to be a major production factor in the southeastern U.S., including Florida, as rainfall has become less reliable and irrigation sources are being depleted. Further, the deep sandy soils in many parts of the region critically exacerbate any water deficit experienced during the growing season. Conservation tillage coupled with irrigation could provide increased plant available water and ensure crop production even during drought conditions in this region. The objective of this 2 year study was to compare the effects of strip tillage (ST) and conventional tillage (CT) as well as irrigation on peanut and cotton production in the sandy soils of north central Florida. The study was l ocated Florida. The design was a randomized strip plot with tillage (CT and ST) as the main plots and irrigation (irrigated or non irrigated) assigned to the sub plot, with three replications. Two cultivars of peanut (Florida 07 and Tifguard) and two cultivars of cotton (Phytogen 375 and 499) were used. In 2011, peanut cultivar Florida 07 produced fewer pegs per plant in ST. Irrigation increased yields in 2011 for both crops and all cultivars tested, with 15 and 19% increases for Florida 07 and Tifguard peanut cultivars; and 43 and 25% for Phytogen 375 and 499 cotton cultivars, respectively. In 2012, total rainfall during the growing season was much greater than 2011: 102 vs. 47 cm, minimizing potential differences between irrigated and non irrigated treatment s in either peanut or cotton. These findings indicate that ST may be a viable option for irrigated or non irrigated peanut and cotton growers in north central Florida, alt hough there may be
27 no yield benefit over CT. However, decreased fuel consumption associated with conservation tillage systems may make ST a sustainable option for this region even without significant yield increases. Introduction Water availability is a ma jor factor affecting the success of peanut and cotton growers in the southeastern U.S. and because these two crops represent approximately 32% of total harvested crop acres in this region (USDA/NASS), increasing water use efficiency is essential. Addition ally, disputes over the use of water in the lower southeast (Alabama, Georgia, Florida) will continue to be an issue as the three states fight for access to water for residential commercial and agricultural use (Ruhl, 200 9 ). It is therefore imperative tha t peanut and cot ton producers in the southeast maximize the water use efficiency of their operations. One method of improving crop water use efficiency is through the use of conservation tillage. g system that covers 30 tillage encompasses a range of tillage practices which are used to improve soil structure. This is compared to more intensive forms of tillage, consid ered conventional tillage (CT), which usually involve moldboard plowing and subsequent harrowing or cultivation. It has been demonstrated that conservation tillage can redu ce run off and can increase soil water infiltration (Arshad et al., 1999; Dao, 1993; Franzluebbers, 2001; Katsvairo et al., 2006; Thierfelder and Wall 2009) and increase volumetric soil water content (Blevins et al., 1971; Gantzer and Blake, 1978; Sullivan et al., 2007; Tollner et al., 1984), especially during the early season when surfac e evaporative losses from tilled soils are high (Zhai et al., 1990).
28 The most common conservation tillage system in the southeast ern U.S. consists of utilizing winter cover crops to protect the soil against erosion and improve soil structure (Langdale et al., 1990). During the subsequent summer crop season, the winter crop residue can be rolled or left aboveground to provide a barrier against wind an d water erosion as well as provide shade to inhibit weed seed germination during the growing season (Langdal e et al., 1990) When planting the summer crop into the winter cover residue, many southeastern U.S. growers utilize a particular type of conservation tillage called strip tillage (ST). Strip tillage is an operatio n that typically tills 18 30 cm wide strip s into crop residue prior to planting. The crop is then planted in the middle of the previously tilled strips. However, the yield effects of ST in the southeastern U.S. for peanut and cotton have been variable. In peanut both benefits and yield losses in ST systems have been documented (Brandenburg, et al., 1998; Hurt et al., 2006; Marois and Wright, 2003; Tubbs and Gallaher et al., 2005; Zhao et al., 2009). Marois and Wright (2003) conducted a two year study to compare the effects of tillage on Tomato sp otted wilt virus (TSWV), an economically important disease that is vectored by thrips ( Frankliniella sp. ) T hey found that ST peanuts had 50% less TSWV incidence than CT as well a s a significantly greater yield (2510 vs. 1900 kg ha 1 ) in year one; however the second year showed no differences in disease or yield. The first year of the study was a significantly drier year which resulted in up to 30% greater soil moisture in ST, likely contributing to the increased yield that year. Similarly, T ubbs and Galla her (2005) found no significant difference in peanut yields between ST and CT in a two year study conducted near Gainesville, FL Another study compared the yield of peanut strip tilled into a terminated
29 bahia grass sod with conventionally tilled peanut (Z hao et al., 2009) and found a yield benefit from ST in one year out of the two year study. Conversely, other studies have shown negative effects of ST (Wright and Porter, 1995; Wright and P orter 1991; Colvin et al., 1988 ) Most relevant for the feasibility of the use of ST in Florida, Colvin et al. (1988) conducted a study near Williston, FL (within 20 miles of the experimental area in the current study ) and found yields in CT were consistently higher than in ST and no till plots, attributing the result to l ower water availability. The ST and no till equipment included ripper or subsoil shanks which disrupted a shallow hardpan, resulting in drainage in these sandy soils which decreased water availability in the conservation tillage plots. In cotton, yields under ST have also been variable. Lascano et al. (1994) showed that in the high plains of Texas, ST reduced soil evaporation and increased crop transpiration thereby increas ing lint yield by 35% as compared to conventional tillage. This study also observe d greater leaf area index during the early part of the season under ST as compared to conventional tillage. Relevant to Florida production conditions, a study in the panhandle showed that ST cotton did not increase yield over conventional tillage (Wiatrak et al., 2005). Some studies have shown that the benefits of ST are more prevalent under drought conditions. Bauer et al. (2010) in coastal South Carolina conducted a six year, non irrigated study that coincided with a considerable 5 year drought (1998 2002) and found that no till increased cotton yields in the five years of the study that were under drought conditions. These results indicate that the benefits of a conservation tillage system may be solely or mostly evident in dry prod uction years.
30 Greater root proliferation under conservation tillage may be at least partially responsible for the enhanced benefits of reduced tillage under drought conditions. Along with increasing plant available water in the soil, conservation tillage also has the capability to enhance rooting depth and root proliferation because of the formation of root channels formed by crop roots ( Katsvairo et al., 2006; Wright et al., 2004). A study in West Texas, in which rooting characteristics were measured on peanuts and cotton with a minirhizotron system, showed that cotton roots explored deeper soil depths and had much greater rooting development in ST than in CT (Rowland et al., 2008). Other root studies comparing the effects of conservation and conventional tillage have been conducted on corn. Newell and Wilhelm (1987) conducted a study that examined corn root lengths near the soil surface (0 15 cm) and remaining rooting profile (15 150 cm) under irrigated, partially irrigated, and non irrigated conditions i n both CT and conservational tillage systems. Their results showed that under conservation tillage, root length was increased in both surface and deeper profile regions compared to CT. They also noted that non irrigated roots tended to explore deeper into the soil profile and that conservation tillage may be a way to reduce irrigation requirements. Hilfiker and Lowery (1988) also showed that reduced tillage increased corn root density as compared to CT, attributing the differences to increased wheel traffic in the CT plots. In contrast, Dwyer et al., (1996 ) showed that reduced tillage actually decreased the corn rooting depth. This study compared root mass distribution in corn between CT and three forms of conservation tillage (chisel, ridge, and no till). R oot mass was estimated from soil cores and taken in 10 cm increments to a depth of 60 cm and found that rooting depth was increased under increased tillage. They surmised that since soil moisture was
31 decreased in the top layers of soil under CT, roots were then encouraged to explore deeper soil depths. Because there is evidence that the benefits of ST may be enhanced under dry conditions, the interaction between irrigation and conservation tillage w ould be important to consider. The benefits of ST may be ad ditively enhanced by irrigation; may disappear; or ST may be detrimental under irrigation. Very few studies have even considered the reciprocal action of conservation tillage and irrigation, yet describing the dynamic of these two production management st rategies is critical for determining the water conservation potential of each alone, or in combination. Since the economic and environmental costs of irrigation are high and increasing, there is potential for decreasing the need for irrigation with the use of ST. Strip tillage allows greater rainfall infiltration and storage in the soil thus possibly reducing the amount of supplemental irrigation required (Arshad et al., 1999; Dao, 1993; Franzluebbers, 2001; Thierfelder and Wall 2009). A study in Georgia i n 2007 was conducted to test the effects of simulated rainfall on conventional and conservation tillage studies (90% of which utilized ST) across the state (Sullivan et al., 2007). They estim ated that conservation tillage decreased ir rigation requirements by 4 14%. Although ST may decrease irrigation requirements, it has not been documented in additional studies or regions outside of Georgia; nor is it widely thought of by producers as a primary reason for adopting ST. It is therefore imperative that furthe r research be conducted to determine if ST can allow growers to reduce irrigation applications. Further, for non irrigated growers, it is important to document possible increases in plant available water in a n ST system.
32 The objective of this study was to compare the effects of tillage and irrigation on peanut and cotton production yield and grade. To understand the mechanisms behind the interaction of these two factors, this study quantified the root architecture, leaf area index, peanut reproductive deve lopment, and cotton petiole nutrition throughout the growing season Materials and Methods Field Preparation and Crop Maintenance and Education Unit (PSREU) located near Ci elevation 21 meters) on a Sparr fine sand (loamy, siliceous, subactive, hyperthermic Grossarenic Paleudults). Field trials were conducted in 2011 and 2012 using plots consisting of eight rows spaced at 0 .91 m apart and 19 .8 m in length in a randomized strip plot design with tillage being the strip treatment and irrigation being the sub treatment. Treatments included: two crops (peanut and cotton); two cultivars of each (Florida 0 7 and Tifguard for peanut; Phytogen 375 and Phytogen 499 for cotton); two tillage treatments (conventional and strip); and irrigated and non irrigated conditions. Secale cereal L.) was planted in late December 2010 across the entire experiment al area. At the senescence of the rye cover crop in March 2011, the rye was cut at a 0.2 m height with flail chopper and removed from the conventional tillage plots. Plots where then disked twice, turned with a moldboard plow and smoothed by disk harrow an d field cultivator. During this same time period in the ST plots, the rye was rolled with a flat drum roller. In the fall of 2011, the rye cover crop was planted in mid November only in the strip till plots, and the peanut and cotton plots were rotated wit h each other the following spring. Other field
33 operations remained the same. The rye biomass dry weight was on average 10,500 and 6,550 kg ha 1 in 2011 and 2012, respectively. After completion of field preparation, cotton and peanut were planted In the f irst year of the study, both peanut and cotton were initially planted on 2 May 2011. However, due to an equipment issue which caused large skips in the peanut plantng, peanuts were replanted on 24 May 2011. The second year of the study peanut and cotton we re planted on 17 April and 16 April 2012, respectively. The plots for both crops were planted with a two row Monosem (Edwardsville, KS) planter with an intra row seed population of 19.7 seed m 1 for peanut and 13.1 seed m 1 for cotton. The strip tilled cot ton and peanut plots were tilled with a two row KMC Rip Strip tiller (Tifton, GA) prior to planting. The tiller and planter were linked for cotton (in 2011 only) and were s eparate operations for peanut in both years. Irrigation for peanut and cotton was s cheduled according to measurements of potential evapotranspiration ( ET ) modified by a crop coefficient for peanut ( FAO 1998 ) The daily potential ET values calculated from th e Penman Monteith model (Monteith, 1965) were obtained from the Florida Automat ed Weather Network (www.fawn.ifas.ufl.edu) located at the PSREU The irrigation treatment was applied to replace ET losses minus rainfall. This was calculated from the following equation where K c is the crop coefficient for peanut relating to growth stage and ET p is the potential ET derived from a standard Penman Monteith ET calculation : Management of pesticide s growth regulators, and fertilization was conducted according to University of Florida IFAS (Institute of Food and Agricultural Sciences)
34 recommendations. Tables 2 1 and 2 2 identify the specific applications and timings of pesticides, growth regulators, and fertilizer. The peanut crops were managed exactly the same both years ; however, cot ton management varied slightly between years. Recommended bloom fertilizer based on petiole analyses were followed in 2011, but no plant response to additional N and K according to these recommendations occurred during that phase. Consequently the petiole recommendations were not followed in 2012 and a standard IFAS fertilizer recommendation was followed Yield was determined from four center rows within each eight row plot that were 15.2 m in length for both peanut and cotton. In 2011, pea nuts were mechan ically dug on 30 September (non irrigated) and 3 October (i rrigated) Both peanut and cotton were harvested mechanically using a two row peanut combine (Lilliston 7500 Lilliston Corporation, Albany, GA ) and two row cotton picker (John Deere 9910 John Dee re and Company, Moline, IL ) respectively. Harvest occurred on 4 October (non irrigated) and 14 October (i rrigated) for peanut; while c otton was picked on 16 September ( Phytogen 375) and 4 October ( Phytogen 499). In 2012, peanuts were dug on 31 August (all ) and cotton was picked on 12 September (all). Peanut samples were dried to 10% moisture content before recording yield weights. Lint yield was estimated using the relationship of 44.2% of seed cotton being lint weight based on an average lint yield obtain from ginning samples from a portion of the plots in 2011. Plant and Soil Measurements Soil moisture measurements at 10, 20, 30, 40, 60, and 100 cm depths were taken from in row points with a capacitance probe three times per week from each plot to quantif y soil moisture status in 2011 and 2012. The device used was the PR2 soil moistur e probe from Delta T technologies (www.delta t.co.uk). In 2012 soil
35 temperatures were logged every hour using a Hobo temperature pend a nt (Onset Computer Corporation; www.onset comp.com ) buried at a depth of 7.5 cm. This depth recorded the soil temperature that represented the pegging environment. Crop measurements included : root architecture in cotton; leaf area index (LAI) in peanut and cotton; reproductive development (number of flowers, pegs, and pods per plant) in peanut ; and petiole nutrient levels in cotton. Root architecture was measured using a minirhizotron camera system (Bartz Technology Corp; www.bartztechnology.com ) which allows in situ non de structive measurements of roots throughout the growing seas on. The technology uses acrylic access tubes inserted within and parallel to a crop row at a 45 degree angle from the plane of the soil. This tube allows access to a camera that images the roots growing along the top sur face of the tube which can then be analyzed on a computer program for characteristics including rooting depth, root length, and root surface area The images are taken along the tube at the same locations over time so changes in these parameters during th e growing season can be quantified Within two weeks after planting, 12 mini rhizotron tubes were installed into strip and conventional tillage plots in irrigated cotton plots Images were taken for the cultivar Phytogen 375 WRF approximately once per month in 2011 beginning on 23 June and repeated on 2 August and 1 September; and once every three weeks in 2012 on 25 May, 15 June, 6 July, 26 July, and 9 August. Individual root image analyses were grouped into 10 zones (0 9), each zone encompassing consecut ive 10 cm depth sections beginning at the surface of the s oil. Images were analyzed using the Win RHIZO Tron software (Regent Instruments, Inc., Canada) for values of total root length (TRL) and total root surface area (TSA). Leaf
36 area index was measure d us ing the LAI 2200 (LiCor Environmental Sciences; Lincoln, NE) approximately every two weeks beginning on 29 June and ending on 30 August in 2011 ; and beginning on 6 June and ending on 9 August in 2012. Leaf area index was measured in the peanut cultivar Flo rida 07 and the cotton cultivar Phy togen 499 (in 2011 and 2012 ) and Phy togen 375 (in 2012) in each tillage and irrigation treatment. The number of peanut flowers, pegs and pods were recorded on a per plant basis in both cultivars by sampling 3 plants per p lot every week once flowering began and continuing until approximately 90 days after planting ( DAP ) Cotton petiole s from Phy togen 499 (in 2011 an d 2012 ) and Phy togen 375 (in 2012) were collected once per week during the 9 week bloom period beginning on 27 and 20 June 2011 and 2012, respectively; samples were Camilla GA) for levels of nitrate, phosphate, potassium and sulfur. Statistical Analysis Data were analyzed using Generalized Linear Mix ed Models for a randomized strip plot design using JMP 9.0 software (SAS Institute Inc., Cary, NC). Tillage, irrigation level, date (when applicable) and all interactions were treated as fixed effects and rep lication and all interactions between replicati on and fixed effects were treated as random effects. Years were analyzed separately because the year effect was significant at P < 0.001. For root analyses, each depth zone (0 9) was analyzed separately for the effects of tillage and irrigation. Results an d Discussion The 2011 and 2012 cropping seasons proved to be very different in terms of total rainfall with 47 cm (cotton) and 42 cm (peanut) in 2011 and 102 cm (cotton and peanut)
37 in 2012. G reater rainfall in 2012 is mostly attributed to several tropical storms that occurred in July and August of 2012. Yield and Grade In 2011 overall peanut yields were substantially less than in 2012 with the average across all plots being 3740 kg ha 1 in 20 11 and 6172 kg ha 1 in 2012 (Table 2 2). The decreased yields in 2011 were likely due to the late replanting which may have increased the heat stress and disease pressure in the late summer. In 2011, tillage type did not affect yield in either peanut culti var; while irrigation increased pod yield in F lorida 07 by an average of 15% (540 kg ha 1 ) and in Tifguard by an average of 19% (639 kg ha 1 ). Conversely, irrigation and tillage had no effect on peanut yields in 2012 (Table 2 3). The lack of a n irrigation effect in 2012 is probably because of rainfall received (102 cm) during that year that was absent in 2011 (40 cm). Grade was not affected by tillage or irrigation in either cultivar or year; average farmer grades were 72.8 and 74.3 for F lorida 07 and Tifg uard, respectively (Table 2 4). Normally, irrigation has a significant benefit to peanut yield in the southeast but is highly dependent on annual precipitation A 3 year study in Georgia showed that sprinkler irrigation increased peanut yields by an ave rage of 906 kg ha 1 but benefits were absent in the last year of the study when rainfall was high (Lamb et al., 2004). Additionally an 8 year study in Georgia showed that irrigation increased peanut yield and grade 5 out of the 8 years and by an average of 569 kg ha 1 (Lamb et al., 1997). The current study results are in agreement with the utility of irrigation being evident primarily in 2011 when precipitation amounts were relatively low. In this study, there were no significant differences between ST and CT. This is not surprising because the effects of ST on peanut yield have been variable across
38 studies Some have found ST to be beneficial to yield (Brandenburg, et al., 1998; Hurt et al. 2006; Marois and Wright, 2003; Zhao et al., 2009); while others h ave found it to be detrimental; ( Wright and Porter, 1995; Wright and P orter 1991 ; Colvin et al., 1988 ); or to have no benefit (Tubbs and Gallaher, 2005; Wiatrak et al., 2004). The cases in which ST was beneficial, yield increases were attributed to: decrea sed insect feeding; decreased Tomato spotted wilt virus ; and increased soil water content and soil water infiltration. Of t he two studies that were conducted on soils in the same region as the current study in north central Florida one showed no effect on yield (Tubbs and Gallaher, 2005) and one showed a slight decrease (Colvin et al., 1988) Similar to Tubbs and Gallaher (2005), the current study found that ST did not affect yield. In contrast to peanut, cotton yields were much lower in 2012 than in 2011 with ave rage yields of 1453 and 712 kg ha 1 (Table 2 2). The reason for the decrease in yield is unclear; however heavy rains in 2012 during squaring and boll formation may have leached nutrients in the sandy soils resulting in N and K deficiency as shown in petiole sampling taken during the bloom period of each year (Figure 2 13). In 2011, irrigation increased yields by 43% and 25% in Phytogen 375 and Phytogen 499 respectively (Table 2 3). I ncreased yield due to irrigation in 2011 is supported by other d ata that report irrigation can substantially increas e yield in dry years (Masters and Lamb, 2003) by reducing water stress which can limit production and retention of cotton bolls (Guinn and Mauney, 1984). Tillage type did not a ffect lint yield in 2011; however, there was an interaction between tillage and irrigation for Phytogen 499 in 2011, where irrigation increased yields in ST but not in CT. In 2012, neither tillage nor irrigation affect ed lint yield in either cultivar. As with pe anuts, the lack of an impact of irrigation in 2012 may in
39 part be due to increased precipitation that year. In our study ST showed no effect on lint yield in either year. Others have similarly found no yield advantage to ST or other types of conservation t illage ( Brown et al., 1985; Pettigrew and Jones, 2001; Stevens et al., 1992 ; Wiatrak et al., 2005 ) Brown et al. (1985) conducted a study that compared CT with no till cotton and found that no till reduced yields unless additional N was applied. In contras t, the study by Wiatrak et al. (2005) showed that cotton lint yields were similar between ST and CT. The benefit to cotton yield by ST may only be evident in regions where the vapor pressure deficit is high (unlike the conditions in the current study) and the often increased soil moisture in ST may translate into a yield advantage. For example, Lascano et al. (1994) in Texas showed that ST reduced soil evaporation increased crop transpiration and thereby increased lint yield by 35% as compared to conven tional tillage in this semi arid environment In season Plant and Soil Characteristics Soil environmental conditions and overall crop physiological functioning were similar across irrigation and tillage treatments in both years of the study. This supports the yield results and indicates that tillage and irrigation d id not have a dramatic impact on soil conditions and the resulting crop performance. Further, it appears that both peanut and cotton cultivars reacted similarly to the tillage and irrigation tre atments, indicating that there is consistent cultivar performance under north central Florida environments. Over both years, soil moisture in irrigated peanut and cotton plots appeared to remain higher than non irrigated plots for the majority of the seaso n ( Figure s 2 1, 2 2, 2 3, 2 4). Further, soil moisture trends tended to be higher at the 10, 20 and 30 cm depths under CT as compared to ST in both crops. This may have been related to greater
40 water infiltration in the ST because of the open pore spaces le ft by decaying cover crop resid u e. Conseq uently, ST may have had greater water storage at the deeper depths (40, 60 and 100 cm) in the irrigated peanut and cotton plots and may explain the often higher soil moisture readings at these depths (particularly i n the cotton) in the ST compared to the CT plots ( Figure s 2 1, 2 2, 2 3, 2 4). Despite the immense rainfall in 2012, these trends were still very noticeable. Shallow soil temperatures generally seemed to be greater in non irrigated plots than irrigated pl ots throughout the season likely because of the cooling effects of irrigation in both peanut and cotton ( Figure s 2 5, 2 6). The rye mat in the ST plots appeared to decrease shallow soil temperatures throughout the season but with the greatest effects seen in the beginning of the season prior to canopy closure when the CT plots would have higher evaporative losses and temperature increases due to incident solar radiation. The responses of peanut flower, peg and pod development to tillage and irrigation ap pear to be very similar for both the cultivars Florida 07 and Tifguard. The only disparity between 2011 and 2012 in flower, peg, and pod production was for Florida 07 which had more pegs and pods produced in irrigated plots and more pegs in CT plots. This slight disparity between years was likely caused by the major differences in rainfall between 2011 and 2012; with less rainfall in 2011 perhaps increasing the impact of irrigation on improved peg and pod numbers, at least for Florida 07. Differences in re productive development between tillage and irrigation occurred more commonly in Florida 07 than in Tifguard, indicating that Florida 07 may be more sensitive to environmental changes that are related to plant available water. For
41 example, Rowland et al. (2 007) conducted a two year study on peanut reproductive development and found that in one year ST increased number of flowers per plant as compared to CT. This increase, however, did not result in a greater number of total pegs per plant. When examining th e patterns of individual reproductive structure, some differences due to date were the most prominent. Flower production during both years and for both cultivars was not affected by tillage or irrigation (Table 2 5) ; h owever, there were differences among s ampling dates in both years as would be expected because flower production typically increases over the season, reaches a peak, and begins to decline (Rowland et al., 2007 ). In 2011, peak flower production was reached at approximately 59 DAP for both cultivars (Figures 2 7, 2 8); while in 2012 this peak occurred 74 78 DAP for Florida 07 and 78 DAP fo r Tifguard (Figures 2 9, 2 10). The difference in peak flowering between years was likely caused by the cooler air temperatures linked to increased precipi tation experienced in 2012 which could have delayed the physiological maturity of the peanut plants (Johnson and Thornley, 1985) Since heat units accumulated faster in 2011 (data not shown) peanut flowering occurred earlier in than in 2012. The number o f pegs per plant w as affected by both tillage and irrigation for F lorida 07 but not Tifguard (Table 2 5). Over the season in 2011, F lorida 07 irrigated treatments had an average of 4.4 more pegs per plant than did non irrigated treatments and CT treatments had an average of 2.4 more pegs per plant than did ST. In 2011 and 2012, peg numbers were significantly different among dates for both cultivars and the pattern was for more peg s across the season up to the last measurement date (Figures 2 7, 2 8, 2 9, 2 10). Similar to pegs, the number of
42 pods per plant was affected by irrigation for F lorida 07 in 2011 (Table 2 5); on average, this cultivar had an increase of 3 pods per plant throughout the measurement period in irrigated plots and on the last date of m easurement, the pod numbers were on average 26 and 14.5 pods per plant in irrigated and non irrigated plots, respectively ( Figure 2 7). This increase in pod numbers per plant was evidenced in the increased yield under irrigated conditions. Pod numbers were not significantly affected by tillage for either cultivar in both years; or by irrigation in either year for Tifguard (Table 2 5). The lack of effect of irrigation on Tifguard pod numbers in 2011, however, was not congruent with the 19% increase in yield that occurred. This could be because the weekly pod samples included any pod that was at the match head stage (about 5 mm diameter) or larger. Since there was no size differentiation during the sampling, it could be that the non irrigated plots had greater numbers of smaller pods that never reached maturity, explaining how the pod number per plant was not affected by irrigation and yet the final yield was. Sam p ling d ate had an effect, with pod production initiating in 2011 and 2012 in both cultivars approxi mately 51 60 DAP and increasing over time nearly linearly to the last measurement date ( Figure s 2 7, 2 8, 2 9, and 2 10). Leaf area index for both peanut and cotton was not affected by tillage or irrigation in either 2011 or 2012 but was different among sampling dates (Table 2 6). For the peanut cultivar Florida 07 in 2011, LAI increased linearly up to the last measurement date (98 DAP), while in 2012, it reached a peak at 80 DAP and began to decrease ( Figure 2 11). Peak values in both years approached 7 00 Cotton LAI for both cultivars tended to peak at 80 DAP in both years with the average LAI being 1.10 higher in 2011 than in 2012 ( Figure 2 12). This difference in years was likely due to nutrient leaching caused by more than double the
43 amount of rainfa ll in 2012 as compared to 2011. This effect is evidenced in the overall lower levels of nitrate and potassium levels in petioles sampled during the bloom period ( Figure 2 13). The effects of tillage on peanut LAI have not been previously documented to date This lack of information provokes the need for more research on the effects of ST on peanut phenology. Canopy development and closure may be a concern for some growers considering adopting ST, since canopy closure is necessary for effective weed manageme nt and disease prevention in some cases. The current study indicates that ST will not r educe canopy closure in peanut. For cotton, the research on cotton canopy development under CT and reduced tillage systems is also limited and variable. A study in the h igh plains of West Texas reported that plant height and LAI were greater under ST than under CT in the early part of the season; after which, the difference between the two tillage treatments was negligible (Lascano and Baumhardt, 1996 ). This study suggest ed that the early season benefit was attributed to the protective qualities of the cover crop residue for the cotton seedlings against harmful strong winds and insect injury. A study in the Mississippi Delta has shown the opposite effect: no till signific antly reduced LAI in cotton only in the pre bloom and mid bloom growth stages, after which LAI in no till was similar to that of CT (Pettigrew and Jones, 2001). The current study showed that ST had no effect on cotton LAI, which is important considering th at excessive canopy growth can make mechanical harvesting difficult and reduced canopy can limit yield potential, especially in the humid southeastern production regions. There were minor impacts on cotton petiole nutrient levels by tillage and irrigation in both 2011 and 2012; of the 4 nutrients tested (nitrate, potassium, phosphorous, and sulfur) only K and P content were affected by irrigation or tillage (Table 2 7). Potassium
44 levels were increased by irrigation in 2011 and 2012 for the cultivar Phytogen 499 and i n 2012 for Phytogen 375 ( Figure 2 13). Conversely, there were effects of tillage only for phosphorus in 2012 in the cultivar Phy togen 375 where ST increased P uptake ( Figure 2 15) In general, irrigation increased petiole K levels and tillage inc reased petiole P levels in 2012. There were strong effects of sampling date on most nutrients measured in both years and cultivars; petiole nutrients generally decreased during the 9 week bloom period in 2011 and 2012 (results for K shown as an example of seasonal trends, Figure 2 14). This seasonal trend is indicative of mobilization of leaf nutrients towards the bolls (Hsu et al., 1978; MacKenzie et al., 1963). The lack of a strong effect of tillage is similar to results found by Ishaq et al. (2001), whe re no till and CT were shown to have no effect on leaf N, P, or K over the two year study. These findings indicate that ST does not appear to change nutrient uptake in cotton, but irrigation can be beneficial in increasing K uptake. Root development in cot ton was much greater during 2012 than in 2011 with total root length (TRL) r eaching a maximum of 1300 mm in 2012 compared to 600 mm in 2011 ( Figure s 2 15 and 2 16 ). This is surprising considering the overall decreases in LAI from 2011 to 2012 ( Figure 2 12) ANOVA revealed n o differences between ST and CT in TRL or total surface area ( TSA ) in 2011 or 2012 either by zones or over the entire rooting profile (Table 2 8). When examining the distribution of the roots throughout the soil profile, it did appear tha t ST generally had more roots than CT at deeper depth s in 2011 during the middle of the season (92 DAP, Figure 2 17 ) and throughout the season in 2012 ( Figure 2 18 ). This deeper rooting habit in ST may have been influenced by
45 available soil moisture: the data in the ST plots indicated greater soil moisture at deeper depths (40 100 cm) than CT. Other research on cotton rooting in ST or any type of conservation tillage is very limited. In one study, comparing ST and CT cotton using a minirhizotron system in west Texas, it was found that ST increased TRL in cotton in the single year that the study was conducted (Rowland et al., 2008). Other studies in corn have shown that conservation tillage increases overall root length and rooting depth (Hilfiker and Lower y, 1988; Newell and Wilhelm, 1987), possibly by crop roots inhabiting root channels left by decaying cover or previous crop roots (Rasse and Smucker, 1998). Similarly, it has been shown that a rye cover crop preceding cotton has the ability to reduce compa ction and increase rooting in cotton compared to deep tillage (CT) which increased compaction and hindered root growth (Bussch l results indicate that ST did not increase overall root length or depth in cotton, but it did have an impact on overall architecture by increasing TRL at deeper depths compared to CT in the second year of the study. This characteristic may be vital for dryland cotton producers in years when rainf all is limiting A deeper rooting system would a llow the crop to exploit water at depths that would otherwise be inaccessible. A key point from this study is that roots under ST were much deeper during the second year of the study indicating that the tillage history may be an important factor in improv ing root growth. The effects of reduced tillage take time to accum ulate which indicates that two years may not be long enough to fully realize the benefits of ST on cotton rooting.
46 Summary The objective of this study was to determine if a n ST tillage sys tem was a viable option for irrigated and non irrigated peanut and cotton growers in north central Florida with possible application to other areas with deep, sandy soils. Additionally, the study sought to characterize the effects of this system on: canopy and root development of cotton; reproductive development in peanut; and cotton nutrition. We found that responses were somewhat different between years likely related to differences in total precipitation during the growing season In 2011, irrigation in creased yield in all crops and cultivars, as well as benefited peanut peg and pod production (F lorida 07 only) and increased K uptake in cotton ( Phytogen 499). The only effects of tillage in either year was in 2011 w h ere ST decreased average peg numbers p er plant in the cultivar F lorida 07 and in 2012 where ST increased P content in cotton petioles In 2012, irrigation did not have any e ffects on peanut or cotton Our data suggest that ST with or without irrigation is a viable option for peanut and cotto n growers in north central Florida, but that benefits achieved by conservation tillage in other regions may not be evident unless conditions of water scarcity are particularly severe. However, overall fuel costs may be reduced in ST due to decreased equipm ent operations, which may override the lack of differences in yields and make ST a more sustainable choice for growers in this region. Irrigation may benefit peanut and cotton yields in north central Florida; however, in wet years like 2012, it does not appear to be needed for optimal production.
47 Table 2 1 Cotton and Peanut Management. List of pesticide and fertilizer applications. Note that indicates L/ha of product applied and ** indicates kg/ha of product --during that particular year. DAP (2011/2012) Pesticide Fertilizer Cotton 0/0 8.4 **phorate 2/2 2.34 *pendamethalin 560** 3 9 18 16/16 2.34 *glyphosate 44/36 0.01 *trioxysulfuron 38/ --180** 15 5 20 --/37 60** 15 5 20 --/48 60** 15 5 20 51/ --1.16 *mepiquat chloride --/54 2.34 *glyphosate 64/ --0.15 *acetamiprid 180** 15 5 20 1.16 *mepiquat chloride --/64 180** 15 5 20 72/94 0.23 *spinetoram --/91 0.87 *pyraclostrobin 80/ --118** 15 0 15 --/94 11** 20 20 20(foliar) --/100 11** 20 20 20(foliar) --/104 11** 20 20 20(foliar) Peanut 0/0 8.4 **phorate 2/2 2.34 *pendimethalin 560 ** 3 9 18 0.03 *diclosulam 14/14 2.34 *s metolachlor 0.03 ** boron 1.16 *paraquat 0.03 ** boron 30/30 1.75 *chlorothalonil 45/45 1.75 *chlorothalonil 1.75 *imazapic 58/58 0.58 *prothioconazole 72/72 1.46 *azoxystrobin 1.17 *clethodim 86/86 0.88 *chlorothalonil 5.25 *tebuconazole 100/100 8.76 *pyraclostrobin 114/114 1.75 *chlorothalonil
48 Table 2 2 Peanut and Cotton Yield. Pod and lint yield in kg/ha separated by tillage, irrigation and year. Conventional Irrigated Conventional Non Irrigated Strip Irrigated Strip Non Irrigated Florida 07 2011 3819 3229 4343 3854 2012 6339 6245 6495 6233 Tifguard 2011 3812 3003 4201 3732 2012 6412 5808 6305 5655 PHY 375 2011 1623 1149 1511 1043 2012 629 560 803 540 PHY 499 2011 1640 1423 1874 1389 2012 897 788 759 742 Table 2 3. ANOVA of Peanut and Cotton Yield. F values for treatment effects on pod and lint yield in 2011 and 2012. 2011 FL 07 Tifguard PHY 375 PHY 499 Effect df Tillage 1 1.2765 1.5822 0.5479 0.6571 Irrigation 1 50.1653* 25.9873* 48.7537* 0.0355* Tillage*Irrigation 1 0.1091 4.3984 0.0289 0.0109* 2012 Tillage 1 0.0609 1.6435 17.2991 0.9181 Irrigation 1 0.6930 6.3249 9.8476 0.4859 Tillage*Irrigation 1 0.4359 0.0351 2.4929 0.1622 indicates P < 0.05 Table 2 4. Peanut Grades. Farmer stock peanut grade values (recorded as percent total sound mature kernels, or TSMK) represented by the sum of sound mature kernels (SMK) and sound split (SS) kernels Conventional Irrigated Conventional Non Irrigated Strip Irrigated Strip Non Irrigated Florida 07 2011 2012 74.3 71.2 73.5 71.9 72.4 73.0 74.5 71.9 Tifguard 2011 2012 75.5 75.1 74.6 74.0 74.2 73.9 73.1 74.1 indicates P < 0.05
49 Table 2 5. ANOVA Peanut Flower, Peg, and Pod Counts. F values of treatment effects on peanut flower, peg, and pod counts per plant for Florida 07 and Tifguard cultivars in 2011 and 2012. 2011 Florida 07 Tifguard Effect df Flowers Pegs Pods Flowers Pegs Pods Date 6 14.4608* 56.4679* 41.5511* 28.6374* 44.2960* 39.5252* Tillage 1 0.3858 21.6582* 2.6503 4.6110 0.2595 18.3775 Irrigation 1 3.5011 20.8991* 48.9496* 0.3001 7.6127 2.0847 Tillage*Irrigation 1 9.5526 1.0710 0.0079 0.6975 2.9910 0.5129 Tillage*Date 6 3.7776* 1.7283 1.5097 1.3240 0.6497 1.6480 Irrigation*Date 6 1.7410 4.2434* 7.7318* 2.7501 1.5480 1.8289 Irrigation*Date*Tillage 6 0.4007 6.2651* 0.8095 0.4108 0.9868 2.2101 2012 Date 7 11.9492* 181.1202* 228.8256* 8.1914* 126.9580* 404.1850* Tillage 1 1.4089 0.0931 1.8909 1.5819 4.2284 1.1675 Irrigation 1 0.1737 0.0278 3.0424 0.3387 0.2955 0.8015 Tillage*Irrigation 1 0.0135 0.0052 0.4472 0.2139 1.2564 85.1654* Tillage*Date 7 1.2406 0.4388 0.1606 1.4747 7.4925 0.3744 Irrigation*Date 7 1.9218 1.0641 2.2492 1.1025 0.1920 0.6754 Irrigation*Date*Tillage 7 0.5747 0.1513 0.1276 1.1278 0.5393 1.09924 indicates P < 0.05
50 Table 2 6. ANOVA Leaf Area Index. F values for treatment effects shown for leaf area index in peanut cultivar FL 07, and cotton cultivars Phytogen 375 and 499. 2011 2012 Effect df FL 07 PHY 499 FL 07 PHY 499 PHY 375 Date 4 102.7521* 19.6374* 187.1246* 24.1956* 11.2034* Tillage 1 5.3460 0.0041 0.0544 0.8277 0.2304 Irrigation 1 2.0436 0.8446 9.6862 3.8891 3.2750 Date*Tillage 4 0.6371 0.5974 0.3109 0.7003 1.0991 Date*Irrigation 4 3.6301 0.2093 1.7605 0.1340 0.1477 Date*Irrigation*Tillage 4 0.5928 0.8777 0.1207 0.0619 0.2239 Irrigation*Tillage 1 0.1838 0.8773 1.9032 1.0302 1.8334 indicates P < 0.05
51 Table 2 7. ANOVA Cotton Petiole Samples. F values of treatment effects on potassium, nitrate, phosphorous, and sulfur contents of cotton petiole samples over the 9 week bloom period in 2011 and 2012 by cultivar. PHY 499 2011 Effect df K F value NO 3 F value P F value S F value Week 8 119.1902* 30.4558* 110.9888* 53.5469* Tillage 1 7.6235 0.0042 0.2693 0.2516 Irrigation 1 23.1002* 18.1060 0.4227 0.1484 Week*Tillage 8 0.2401 0.4475 0.7852 1.9736 Week*Irrigation 8 11.6017* 6.2510* 1.1348 1.3340 Tillage*Irrigation 1 0.2676 0.0293 0.0077 0.0000 Week*Irrigation*Tillage 8 1.1752 0.1990 2.0242 1.0971 PHY 499 2012 Week 8 168.9524* 2.3194 9.5875* 19.7539* Tillage 1 0.0030 1.2565 11.5554 1.3044 Irrigation 1 19.6053* 3.1072 8.8840 10.5369 Week*Tillage 8 1.5585 0.7105 0.5836 0.2803 Week*Irrigation 8 3.8413* 2.5689 2.9008* 1.8802 Tillage*Irrigation 1 1.6226 1.2706 2.7153 0.1364 Week*Irrigation*Tillage 8 0.1457 1.1608 1.0302 0.3637 PHY 375 2012 Week 8 76.1559* 6.3588* 2.2290* 10.4626* Tillage 1 4.1845 5.7348 158.8375* 0.0908 Irrigation 1 22.8082* 0.0191 78.5832* 15.4755 Week*Tillage 8 2.0318 0.0149 2.8173* 0.8208 Week*Irrigation 8 2.9894* 1.8336 1.5650 0.3381 Tillage*Irrigation 1 1.2262 0.0149 0.0119 4.2518 Week*Irrigation*Tillage 8 3.2876* 0.0948 0.3692 0.3755 i ndicates P < 0.05
52 Table 2 8. ANOVA Cotton Root Architecture. F values for treatment effects on cotton total root length (TRL) and total surface area (TSA) in 10 cm depth increments indicated by zone numbers (0 9) in 2012 and 2012. indicates P < 0.05 2011 Zone 0 Zone 1 Zone 2 Zone 3 Zone 4 Effect df TRL TSA TRL TSA TRL TSA TRL TSA TRL TSA Tillage 1 0.1134 0.0114 1.6999 0.0079 2.7012 0.3162 3.6831 2.0408 0.0523 0.4016 Date 3 0.4862 0.1369 2.0406 2.4097 2.6333 6.0325 2.2453 1.0615 3.7971 2.7640 Date*Tillage 3 0.4827 0.5442 0.5935 0.1363 0.8946 1.4217 1.0124 0.8817 0.0746 0.3849 Zone 5 Zone 6 Zone 7 Zone 8 Zone 9 Effect df Tillage 1 0.8195 1.1483 0.6096 0.6984 0.2370 0.0859 0.8038 0.8784 --Date 3 5.8884 5.2694 1.2806 1.3223 1.7072 2.3703 0.8986 0.9379 --Date*Tillage 3 0.2667 0.5402 0.7000 0.6895 0.5217 0.2723 1.1088 1.0647 --2012 Zone 0 Zone 1 Zone 2 Zone 3 Zone 4 Effect df Tillage 1 0.9349 1.9109 0.0187 0.1370 5.0834 1.5293 0.1335 0.1556 0.0555 0.0244 Date 3 9.0415* 0.9370 11.2236* 25.5163 5.9725 4.6054* 19.3116* 11.3940* 6.0615* 4.3551* Date*Tillage 3 2.3344 0.6586 0.4071 0.1803 0.2344 0.2906 0.8506 0.5733 0.4300 0.2275 Zone 5 Zone 6 Zone 7 Zone 8 Zone 9 Effect df Tillage 1 0.5353 0.7734 7.5640 4.0008 3.2934 0.2413 1.0115 1.1083 0.0078 0.2425 Date 3 3.1942 2.2371 8.8957* 4.8101* 1.5463 0.2724 1.3609 1.4651 1.5388 1.7688 Date*Tillage 3 0.5051 0.5757 5.2838* 3.6275 2.0525 0.2213 0.7800 0.7759 0.4452 0.3356
53 Figure 2 1. 2011 Soil Moisture in Peanut. Average soil moisture readings at 10 (A), 20 (B), 30 (C), 40 (D), 60 (E) and 100 (F) cm depths in peanut throughout the 2011 cropping season shown in the conventional tillage irrigated (CI), conventional tillage non irrigated (CN), the strip tillage irrig ated (SI), and the strip tillage non irrigated (SN).
56 Figure 2 2. 2011 Soil Moisture in Cotton. Average soil moisture readings at 10 (A), 20 (B), 30 (C), 40 (D), 60 (E) and 100 (F) cm depths in cotton throughout the 2011 cropping season shown in the conventional tillage irrigated (CI), conventional tillage non irrigated (CN), the strip tillage irrig ated (SI), and the strip tillage non irrigated (SN).
59 Figure 2 3. 2012 Soil Moisture in Peanut. Average soil moisture readings at 10 (A), 20 (B), 30 (C), 40 (D), 60 (E) and 100 (F) cm depths in peanut throughout the 2011 cropping season shown in the conventional tillage irrigated (CI), conventional tillage non irrigated (CN), the strip tillage irrig ated (SI), and the strip tillage non irrigated (SN).
62 Figure 2 4. 2012 Soil Moisture in Cotton. Average soil moisture readings at 10 (A), 20 (B), 30 (C), 40 (D), 60 (E) and 100 (F) cm depths in cotton throughout the 2011 cropping season shown in the conventional tillage irrigated (CI), conventional tillage non irrigated (CN), the strip tillage irrig ated (SI), and the strip tillage non irrigated (SN).
65 Figure 2 5. Soil Temperature in Peanut Soil temperature at 7.5 cm depth in peanut throughout the 2012 cropping season shown in the conventional tillage irrigated (CI), conventional tillage non irrigated (CN), the strip tillage irrigated (SI), and the strip tillage non irrigated (SN)
66 Figure 2 6. Soil Temperature i n Cotton. Soil temperature at 7.5 cm depth in cotton throughout the 2012 cropping season shown in the conventional tillage irrigated (CI), conventional tillage non irrigated (CN), the strip tillage irrigated (SI), and the strip tillage non irrigated (SN)
67 Figure 2 7. 2011 Florida 07 Flower, Peg, and Pod Counts. Flowers (A), pegs (B), and pods (C) per plant in the conventional tillage irrigated (CI), conventional tillage non irrigated (CN), the strip tillage irrigated (SI), and the strip tillage non irrigated (SN).
69 Figure 2 8. 2011 Tifguard Flower, Peg, and Pod Counts. Flowers (A), pegs (B) and pods (C) per plant in the conventional tillage irrigated (CI), conventional tillage non irrigated (CN), the strip tillage irrigated (SI), and the strip tillage non irrigated (SN).
71 Fi gure 2 9. 2012 Florida 07 Flower, Peg, and Pod Counts. Flowers (A), pegs (B) and pods (C) per plant in the conventional tillage irrigated (CI), conventional tillage non irrigated (CN), the strip tillage irrigated (SI), and the strip tillage non irrigated ( SN).
73 Figure 2 10. 2012 Tifguard Flower, Peg, and Pod Counts. Flowers (A), pegs (B) and pods (C) per plant in the conventional tillage irrigated (CI), conventional tillage non irrigated (CN), the strip tillage irrigated (SI), and the strip tillage non irrigated (SN).
75 Figure 2 11. Leaf Area Index Peanut. Leaf area index in 2011 (A) and 2012 (B) for peanut cultivar Florida 07 in the conventional tillage irrigated (CI), conventional tillage non irrigated (CN), the strip tillage irrigated (SI), and the strip tillage non irrigated (SN)
76 Figure 2 12. Leaf Area Index Cotton Leaf area index separated by cultivar shown in cultivar Phytogen 499 in 2011 and 2012 (A,B) and Phytogen 375 in 2012 (C) in conventional tillage irrigated (CI), conventional tillage non irrigated (CN), the strip tillage irrigated (SI), and the strip tillage non irrigated (SN).
78 Figure 2 13. Average Nitrate and Potassium 2011 and 2012. Cotton nitrate (A) and potassium (B) content averaged across tillage and irrigation treatments in 2011 and 2012.
79 Figure 2 14. Cotton Petiole Potassium 2011 and 2012 Potassium levels in cotton in 2011(A) and 2012 (B) in cul tivar Phytogen 499 in the conventional tillage irrigated (CI), conventional tillage non irrigated (CN), the strip tillage irrigated (SI), and the strip tillage non irrigated (SN).
80 Figure 2 15. TRL and TSA Cotton 2011. Total root length (A) and total root surface area (B) for cotton in 2011.
81 Figure 2 16. TRL and TSA Cotton 2012. Total root length (A) and total root surface area (B) for cotton in 2012.
82 Figure 2 17. Figure 2 17. Rooting Profile Cotton 2011. Total root length in mm (TRL) down the profile of the soil where each zone is a 10 cm increment. Graphs show measurements at 52 (A), 92 (B), 123 (C) DAP.
84 Figure 2 18. Rooting Profile Cotton 2012. Total root length (TRL) down the profile of the soil where each zone is a 10 cm increment. Graphs show measurements at 38 (A), 59 (B), 80 (C), 100 (D), 114 (E) DAP.
87 CHAPTER 3 AN INVESTIGATION OF THE RELATIONSHIP BETWEEN SOIL WATER CONTENT AND SAP FLOW IN COTTON UNDER IRRIGATED AND NON IRRIGATED CONDITIONS Summary Efficient irrigation scheduling is a key component to sustainable production strategies for cotton. Soil based measurements have been tested and implemented in commercial irrigation decision systems but may be inadequate to precisely reflect crop water use. The purpose of the current study was to quantify the relationship between volumetric soil water content (as measured with capacitance soil moisture sensors) and cotton water use. The study was conducted in 2012 at the Plant Science Research and Education Unit in Citra, Flor ida in both irrigated and rain fed conditions. The design of the experiment was a complete randomized block with irrigation being the main treatment. The c otton cultivar Phytogen 375WRF was planted on 17 April 2012 and sap flow and soil moisture measuremen ts were logged continuously from 30 June until 30 July during the peak water use period for the crop. Sap flow rates were adjusted for leaf area and summed by day to calculate total daily water use (TDWU). Soil moisture was measured at 20 and 60 cm depths to determine the depth of active water uptake in the crop. Linear and quadratic regression analyses were made between average daily soil moisture content and plant TDWU. Our analyses showed a significant quadratic relationship for non irrigated cotton TDWU with soil moisture at 60 cm only. This relationship indicates that plant water use is related more specifically to certain depths (probably reflecting root architecture) and that scheduling irrigation using the appropriate depth is critical. The lack of a relationship in the irrigated plots may have reflected an excess water receipt of these plots due to high precipitation during the
88 measurement period. This preliminary data provides guidance for the use of soil moisture sensors in scheduling irrigation in southeastern U.S. cotton production and indicates that there is a direct relationship with crop water use and soil moisture at appropriate soil depths. Introduction Cotton is an efficient user of water compared to other crops and has the potential to perf orm well even under water deficit (Ackerson & Krieg, 1977). However, t he sandy, drought prone soils in some parts of the southeast ern U.S. challenge the water use efficiency of cotton, especially in years when rainf all is inconsistent or reduced. This make s irrigation application beneficial or even essential during more drought prone years. However, to efficiently apply irrigation to meet crop demand, it is preferable to monitor soil moisture conditions to aid in irrigation scheduling decisions. It is the refore important for growers and researchers to understand how soil moisture is related to crop water use responses during changes in the soil moisture environment. There are a variety of irrigation scheduling techniques from checkbook metho ds (Lundstrom and Stegman, 1988 ), evapotranspiration (ET) estimations (Wright and Jensen, 1978) to crop modeling methods (George et al., 2000) ; but many irrigation decision systems now rely solely on soil moisture estimations to determine crop water use. Typically, a soil moisture threshold in terms of volumetric water content or soil matric potential is determined and soil moisture is monitored through the season so that when levels fall below the threshold irrigation is applied (Campbell and Campbell, 1982). The mo st common me asure of soil moisture has been soil matric potential (SMP) and SMP sensors for irrigation scheduling have been shown to be effective for many crops including vegetable s (Thompson et al., 2007) and field crops such as cotton and
89 rice (Vellidis et al., 2008; Kukal et al., 2005) In particular, Irrigator Pro for cotton, a commonly used irrigation scheduling system for cotton in the southeast (www.ars.usda.gov), utilizes gypsum block sensors for scheduling irrigation. However, in all of the irrig ation scheduling systems utilizing measurements of soil moisture or matric potential the identification of ac curate thresholds is essential. I f soil moisture thresholds used for irrigation decisions are too high, the potential for improving water use effi ciency is removed. The key to optimizing wa ter use efficiency would be to e nsure there was an accurate match between soil moisture measurement and actual crop water use. Despite the heavy reliance on soil moisture sensors for triggering irrigation, few st udies have investigated and quantified the direct measure of soil moisture with crop water use during the growing season to verify that soil moisture is an adequate surrogate for indicating crop water need. Further, determining which soil depth represents the zone of active root activity and, thus is the most appropriate for soil moisture monitoring, is often not known and little studied. To better understand the relationship between soil moisture and actual plant water use, a comparison between soil moist ure dynamics and direct measurements of plant water use is needed. To measure water use on an individual plant, the heat pulse method can be used (Baker and van Bavel, 2006 ). The heat pulse method is able to calculate the flow of sap through the stem using an insulated collar containing a heating strip with two thermocouple s on either side. The temperature difference between the thermocouples is measured several times per second as well as the amount of time between the exertion of the heat pulse and the r eturn of the sap to its initial temperature. These calculations, indexed to a stem diameter provide a direct
90 calculation of stem sap flow from a given plant (Smith and Allen, 1996). Cohen et al., (1988) demonstrated that the heat pulse method can be effectively used on cotton and Lascano (2000) demonstrated that sap flow measurements can be more effective for irrigation scheduling in cotton than ET replacement models. Identification of the appropriate soil depths to monitor for irrigation sche duling is also essential to matching sap flow with measurements of soil moisture. However, information about basic root architecture would be needed to accomplish this. Studies rarely relate root architecture to both direct and indirect measurements of cr op water use ( Taylor and Klepper, 1974; Lascano and van Bavel, 1984) Therefore, what is needed to justify the use of soil moisture monitoring for cotton irrigation scheduling is a simultaneous measurement of soil moisture at varying depths and sap flow, combined with quantification of rooting architecture over time. To address this research need, o ur objective in this study was to correlate measurements of soil moisture at two depths that are likely active zones of water uptake for southeastern cotton (2 0 and 60 cm) with daily sap flow during the mid to late season, a period representing peak water use in the crop. Further, root growth and architecture were quantified and related back to patterns of soil moisture and water uptake rates that were observed. This information could then be used to confirm the utility of soil moisture sensors for scheduling irrigation in southeastern cotton. Materials and Methods Field Preparation and Crop Maintenance Field plots were established at the University of Florid
91 on a Sparr fine sand (loamy, siliceous, subactive, hyperthermic Grossarenic Paleudults). Field trials were conducted in 2012 using the c otton cultivar Phytogen 375 planted on 16 April 2012 with an intrarow seed spacing of 13.1 seed m 1 The design of the experiment consisted of a randomized complete block design with tw o treatments ( irrigation and no irrigation ) and three replications (plots) Individual plots consisted of eight rows spaced 0.91 m apart and 19.8 m in length. Within each plot, minirhizotron tubes and soil moisture sensors were installed in the row. For measurement of sap flow, t welve reps (plants) within each treatment were spl it across the 3 replications for both irrigated and non irrigated plots within the experimental area. Plant and Soil Measurements Soil moisture measurements at 20 and 60 cm depths were logged once per hour using EC 5 soil moisture sensors (Decagon Devices, Inc.; www.decagon.com ). For analysis, hourly soil moisture readings were averaged by day. To measure sap flow, the Flow 32 1K system from Dynamax was used (www.dynamax.com). Theory and methodology of operation are described in Smith and Allen (1996). Twen ty four sap flow collars where installed on individual plants (12 in irrigated and 12 in non irrigated plots) and measurements were logged at 15 minute intervals. Sap flow measurements encompassed 30 June 2012 until 30 July 2012. Due to equipment failures only 6 plants from irrigated plots and 9 plants from non irrigated plots were used for analysis. Following removal of the sap flow equipment, total leaf area from each plant was measured with a leaf area meter (Model 3100, LI COR Biosciences ; www.licor.com ) and leaf area values were used to normalize sap flow rates on a leaf area basis. Flow rates were summed over a 24 hour period ( by day ) for total daily water use values (TDWU) that were used to relate to average daily soil moisture.
92 Differenc es in overall TDWU between irrigated and non irrigated plots were analyzed using Generalized Linear Models and linear and quadratic regressions using JMP 9.0 software (SAS Institute Inc., Cary, NC).To determine if a relationship existed between soil moistu re content and sap flow, linear and quadratic polynomial regressions related average daily soil moisture content (cm 3 cm 3 ) with TDWU, the sum of daily sap flow per unit leaf area (g cm 2 ). Root architecture was measured using a minirhizotron camera syste m (Bartz Technology Corp; www.bartztechnology.com ) which allows in situ non de structive measurements of roots throughout the growing seas on. The technology uses acrylic access tubes inserted within and parallel to a crop row at a 45 degree angle from the plane of the soil. Within two weeks after planting, 12 mini rhizotron tubes were installed into irrigated and non irrigated cotton plots A camera was inserted into each tube and root images were taken at every 13. 5 mm along the top surface of the tube on 6 and 26 July 2012, representing the beginning and end of the measurement period, respectively. These images were then analyzed using Win Rhizo Tron software (Regent Instruments Inc; www.regentinstruments.com) which quantified rooting depth, root length, and root surface area. Individual root image analyses were grouped into 10 zones (0 9), each zone encompassing consecutive 10 cm depth sections beginning at the surface of the soil. Results and Discussion The total rainfall during th e measurement period w as 53 cm. Irrigated plots were irrigated twice during this period, 30 June and 7 July, 2012 with 1.9 cm each time. However, previous to the measurement period, rainfall totaled 58.8 cm and irrigated plots received an additional 15.24 cm of irrigation ( Figu re 3 1 )
93 TDWU varied between irrigated and non irrigated treatments for the 31 day period with an average TDWU of 0.41 g cm 2 under irrigation and 0.50 g cm 2 without irrigation (p value = 0.0149) ( Figure 3 2 ). These totals were similar to others documented in the literature for cotton (Isoda and Wang, 2002) that recorded s ums ranging from 0.40 to 0.90 g cm 2 during a 4 day measurement period Overall, TDWU ranged from 0.22 to 0.89 g cm 2 but tended to decrease over the 30 day measurement period as the crop was maturing ( Figure 3 2) The average daily soil volumetric water content over the 30 day measurement period at the 20 and 60 cm depth s was greater in the irrigated treatment (p value < 0.001) than in the non irrigated treatment. At 20 cm, soil moisture in the irrigated plots was 12.0 compared to 8.7% in the non irrigated treatment ; while at the 60 cm depth, soil volumetric water content under irrigation was 9.6 compared to 7.4% in the non irrigated treatment ( Figure 3 3 ). These numbers are w ithin the general range of unsaturated soil water content values (5 10%) that have been documented in a similar Florida soil (Obreza et al., 1997). When TDWU and average daily soil moisture were regressed, no linear relationships were found for irrigated or non irrigated sap flow at either 20 or 60 cm soil depths However, a significant quadratic relationship was found between TDWU in non irrigated plots and soil moisture values at the 60 cm depth ( Figure 3 4 ; Table 3 1). This relationship indicates that soil moisture at particular depths (in this case 60 cm) can be directly related to crop water use. The lack of relationship between TDWU and soil moisture (at either depth) for irrigated plots is somewhat surprising because the daily soil moisture patterns were similar for both irrigated and non irrigated plots and differed only in magnitude ( Figure 3 2). The lack of a significant relationship between TDWU
94 and soil moisture in the irrigated plots could represent a moisture content in these plots that was ab ove plant water need, such that additional moisture had no effect on TDWU. Whereas, in the non irrigated plots, soil moisture availability may have reached levels below crop water requirement, such that TDWU was able to respond to increases in soil moistu re. This is supported by the shape of the relationship between TDWU and soil moisture: a negative quadratic shape ( Figure 3 4 ). If this explanation is correct, the overall relationship shows that TDWU increases nearly linearly with soil moisture up to a th reshold of 8.5 9% VWC (Figure 3 5); beyond which TDWU drops off and decreases dramatically. This indicates that TDWU increases with increasing VWC up to a threshold and then no longer responds to increases in soil moisture. This is similar to the situation when cotton experiences water deficit stress : osmotic adjustment will occur and transpiration will decrease (Oosterhuis and Wullschlegger, 1987). However, in the current study, TDWU may decrease because of excess water availability in the profile. Howe ver, the overall quadratic shape of the relationship between TDWU and average daily soil moisture is driven almost exclusively by the last five points at the highest soil moisture levels. In the absence of these points, the relationship is solely linear. These last five points represent points collected during the last five days of measurement It was visually noted that the crop during this period was significantly senesced due to the impact of a developing fungal disease combined with acute nutrient def iciencies. Therefore, the dramatic drop in TDWU for these points may not be indicative of true crop water requirement but more related to the overall rapid maturing and senescence of the crop under suboptimal conditions If these last five
9 5 points are remo ved, the relationship is significantly linear (p value < 0.001 R 2 = 0.542 ) ( Figure 3 5). It is a lso important to note that the relationship between TDWU and soil moistu re occurred at the 60 cm depth. This would be expected based on the root architecture, where increase d total root length was present at deeper depths (zones 5 7; p values < 0.001) in the non irrigated plants during the study period (Table 3 2 and Figure 3 6 ). The data in the current study show that in north central Florida environment s soil moisture at a relatively shallow depth (20 cm) has a limited direct relationship with cotton water use, and therefore, little utility for scheduling irrigation This may be due to a lack of significant root proliferation and thus active water uptake in this region. This result agrees with other research including the study by Burke and Upchurch (1995) which showed that non irrigated cotton had greater root length density at deeper depths (70 120 cm) than irrigated plants There is some evi dence of a relationship between soil moisture content and root proliferation (Taylor and Klepper, 1974). Further research could focus on monitoring TDWU and soil moisture at additional depths These findings have important implications for the study of cotton water u se as well as irrigation management. Some have noted that the value of using soil moisture readings for irrigation scheduling is limited and that evaporative changes in the plant respond directly to changes in plant water status in different portions of th e plant, changes which may not be related to changes in bulk soil moisture (Jones, 2004; Thompson et al., 2007). Jones (2004) also claims that the water status of the plant relies not only on soil moisture but the resistances to water flow that occurs at t he interface between the soil the root and within the plant. Since plant water use may act
96 independently of soil moisture, using soil moisture as a surrogate for irrigation scheduling may be problematic in some cases. Some studies have shown the validity of using sap flow by itself for irrigation scheduling. Eastham and Gray conducted a study on sap flow in irrigated and non irrigated grapevines (1998) and found that plant sap flow was sensitive to changes in timing and amounts of water applied Similarly others have found validity in the use of sap flow to detect differences between flow rates of irrigated and non irrigated woody plants, showing that sap flow is a good indicator of plant water status (Ameglio et al., 1999; Ginestar et al., 1998; Giorio an d Giorio, 2003; Remorini and Massai, 2003). Each of these studies note the validity of using sap flow for irrigation scheduling but there are no examples of replicated studies testing the application of this method in the field. Additionally, the applicati on of sap flow technology, especially in the case of cotton, would be cost prohibitive for commercial production, as well as technically difficult. Therefore, it is essential to validate the relationship b etween soil moisture and sap flow and to identify t he appropriate soil depths to monitor soil moisture for irrigation scheduling. Knowledge about this relationship could determine the success or failure of irrigation scheduling systems utilizing soil moisture sensors and could prove to be essential for im proving cotton irrigation scheduling efficiency in the southeast.
97 Table 3 1. Relationship Between Soil Moisture and Sap Flow.Listed below are the R 2 values for quadratic regressions made between soil volumetric water content and sap flow. Treatment Value 20 cm 60cm Irrigated R 2 0.083634 0.172355 equation y = 0.096 + 0.028x 0.015(x 12.0417) 2 y = 0.198 + 0.067x 0.061(x 9.554) 2 Non Irrigated R 2 0.122493 0.356712 equation y = 0.607 0.003x 0.048(x 8.673) 2 y = 0.075 + 0.092x 0.119(x 7.396) 2 p value < 0.05
98 Table 3 2. ANOVA of Root Analyses. F values of analyses of the effect of irrigation on total root length (TRL) and total surface area (TSA) near the beginning of the measurement period (7/06/2012) and end of the measurement period (7/26/2012). Values are separated by zones (0 9) which encompass a 10 cm region of the rooting profile. 7/06/2012 Zone 0 Zone 1 Zone 2 Zone 3 Zone 4 Effect df TRL TSA TRL TSA TRL TSA TRL TSA TRL TSA Irrigation 1 4.8951 3.9939 4678.599* 204.4222* 30.5174* 13.9916 0.1781 0.3163 0.1125 0.2474 Zone 5 Zone 6 Zone 7 Zone 8 Zone 9 Irrigation 1 73.9832* 31.6747* 15.7674 21.7827* 0.1905 3.2319 0.0116 0.0127 0.5499 0.3416 7/26/2012 Zone 0 Zone 1 Zone 2 Zone 3 Zone 4 Irrigation 1 3.2829 2.5795 93.5614* 270.8946* 45.4918* 18.3476 0.0508 0.3376 0.0572 0.1935 Zone 5 Zone 6 Zone 7 Zone 8 Zone 9 Irrigation 1 78.1563* 25.2871* 14.0159 23.2646 3.6886 3.1048 0.0059 0.0073 0.0494 0.0165
99 Figure 3 1. Rainfall and Irrigation Distribution. Amounts of rainfall and irrigation received during the cropping season where the box outlines the period of soil moisture and sap flow were measured.
100 Figure 3 2. Cotton Total Daily Water Use. Total daily water use in units of grams per cm2 leaf area.
101 Figure 3 3. Soil Moisture. Soil volumetric water content shown in irrigated 20 and 60 cm depths (I 20; I 60) and non irrigated 20 and 60 cm depths (N 20; N 60).
102 Figure 3 4. Polynomial Regression of TDWU with Soil Moisture. Summed daily sap flow response to volumetric soil moisture content at 60 cm from 30 June 2012 through 30 July 2012.
103 Figure 3 5. Linear Regression of TDWU with Soil Moisture. Summed daily sap flow response to volumetric soil moisture content at 60 cm from 30 June 2012 through 30 July 2012. Five points where soil moisture was over 8.5% were removed.
104 Figure 3 6. C otton Rooting Profile. Total root length (TRL) near the beginning of the measurement period (7/06/2012; A) and end of the measurement period (7/26/2012; B). Values are separated by zones (0 9) which encompass a 10 cm region of the rooting profile.
105 LIST OF REFERENCES Ameglio T, Archer P, Cohen M, Valancogne C, Daudet F, Dayau S, and Cruiziat P. 1999. Significance and limits in the use of predawn leaf water potential for tree irrigation. Plant and Soil 207:155 167. Arshad MA, Franzluebbers AJ, Azooz RH. 1999. Components of surface soil structure under conventional and no tillage in northwestern Canada. Soil and Tilla ge Res. 53 :41 47 Baker JM and van Bavel CHM. 2006. Measurement of mass flow of water in the stems of herbaceous plants. Plant, Ce ll and Env.10:777 782. Baldwin JA and Hook J. 1998. Reduced tillage systems for peanut production in georgia. Proc. Am. Peanut Res. Ed. Soc. 30:48. Ball RA, Oosterhuis DM, Mauromoustakos A. Growth dynamics of the cotton plant during water deficit stress. A gron. J 86:788 795 Bauer PJ, Fortnum BA, Frederick JR. 2010. Cotton responses to tillage and rotation during the turn of the century drought. Agron J 102 :1145 8. Black CR, Tang DY, Ong CK, Solon A, Simmonds LP. 1985. Effects of soil moisture stress on the water relations and water use of groundnut stands. New Phytologist 100:313 328. Blevins RL, Cook D, Phillips SH, Phillips RE. 1971. Influence of no tillage on soil moisture. Agron. J. 63:593 596. Brandenburg RL, Herbert DA, Sullivan GA, Naderman GC, and W right FS. 1998. The impact of tillage practices on thrips injury of peanut in north carolina and virginia. Peanut Sci. 25:27 31. Brown SM, Whitwell T, Touchton JT, Burmester CH. 1985. Conservation tillage systems for cotton production. Agron. J. 49: 1256 12 60 Burke JJ, and Upchurch DR. 1995. Cotton rooting patterns in relation to soil temperatures and the thermal kinetic window. Agron. J. 87:1210 1216. Busschler WJ and Bauer PJ. 2003. Soil strength, cotton root growth and lint yield in a southeastern usa co astal loamy sand. Soil and Tillage Research 74:151 159. Campbell GS and Campbell MD. 1982. Irrigation scheduling using soil moisture measurements: theory and practice. Advances in Irrigation 1:25 42. Cassman KG, Kerby TA, Roberts BA, Bryant DC, and Higashi SL. 1990. Potassium effects on lint yield and fiber quality of acala cotton. Crop Sci. 30:672 677.
106 Cohen Y, Fuchs M, Falkenflug V, and Moreshet S. 1988. Calibrated heat pulse method for determining water uptake in co tton. Crop Sci. 80:398 402. Colvin DL, Brecke BJ, and Whitty EB. 1988. Tillage variables for peanut production. Peanut Sci. 15: 94 97. Coker DL, Oosterhuis DM, and Brown RS. 2009. Cotton yield response to soil and foliar applied potassium as influenced by irrigation. J. of Cotton Sci. 13:1 10. [CTIC] Conservation tillage Information Center. 2002. Tillage type definitions [online]. http://www.ctic.purdue.edu (1 October 2012). Dao TH. 1993. Tillage and winter wheat residue management effects on water infiltra tion and storage. Soil Sci. Soc. Journal 57:1586 1595 Dwyer LM, Ma BL, Stewart DW, Hayhoe HN, Balchin D, Culley JLB, McGovern M. 1996. Root mass distribution under conventional and conservation tillage. Canadian Journal of Soil Science 76:23 28. Eastham J and Gray S. 1998. A preliminary evaluation of the suitability of sap flow sensors for use in scheduling vineyard irrigation. Am. J. Enol. Vitic. 49:171 176. Endale DM, Schomberg HH, Fisher DS, Jenkins MB, Sharpe RR, and Cabrera ML. 2008. No till corn prod uctivity in a southeastern united states ultisol amended with poultry litter. Agron. J. 100: 1401 1408. [FAO] Food and Agriculture Organization of the United Nations. 1998. Crop evapotranspiration: guidelines for computing crop water requirements. p. 111. Franzluebbers AJ. 2002. Soil organic matter stratification ratio as an indicator of soil qual ity. Soil and Tillage Res. 66 :95 106 Gantzer CJ and Blake GR. 1978. Physical characteristics of le sueur clay loam soil following no till and conventional tillage. Agron. J. 70 :853 857. George BA, Shende SA and Raghuwanshi NS. 2000. Development and testing of an irrigation scheduling model. Agric. Water Mgmt. 46:121 136. Ginestar C, Eastham J, Gray S, and Il and P. 2003. Use of sap flow sensors to schedule vineyard irrigation. i. effects of post veraison water deficits on water relations, vine growth, and yield of shiraz grapevines. Am. J. Enol. Vitic. 49:413 420. Giorio P and Giorio G. Sap flow of several oli ve trees estimated with the heat pulse technique by continuous monitoring of a single gauge. Env. and Exp. Botany 49:9 20. Graven LM and Carter PR. 1991. Seed quality effect on corn performance under conventional and no tilla ge systems. J. Prod. Agric. 4: 366 373.
107 Guin G and Mauney JR. 1984. Fruiting of cotton.ii. effects of plant moisture status and active boll load on boll retention. Agron. J. 76:94 98. Halvorson AD, Mosier AR, Reule CA, and Bausch WC. 2006. Nitrogen and tillage effects on irrigated conti nuous corn yields. Agron. J. 98: 63 71. Hammel JE. 1995. Long term tillage and crop rotation effects on winter wheat production in northern idaho. Agron. J. 87: 16 22. Hilfiker RE and Lowery B. 1988. Effect of conservation tillage systems on corn root growth Soil and Tillage Research 12:269 283. Howell, 1996Howell, T.A., 1996. Irrigation scheduling research and its impact on water use. In: Camp, C.R., Sadler, E.J., Yoder, R.E. (Eds.), Proceedings of the International Conference on Evapotranspiration and Irr igation Scheduling, San Antonio, TX, USA, 3 6 November 1995, ASAE, pp. 21 33. Hsu HH, Lancaster JD, and Jones WF. 1978. Potassium concentration in leaf blades and petioles as affected by potassium fertilization and stage of maturity of cotton. Com. in Soil Sci. and Plant Anal. 9:265 277. Hurt CA, Brandenburg RL, Jordan DL, Royals BM, Johnson PD. 2006. Interactions of tillage with management practices designed to minimize tomato spotted wilt of peanut (arachis hypogaea l.). Peanut Sci. 33:83 89 Hutson SS, B arber NL, Kenny JF, Linsey KS, Lumia DS, and Maupin MA. Estimated use of water in the united states in 2000. US Geological Survey Circular 1268. Ishaq M, Ibrahim M, and Lal R. 2001. Tillage effect on nutrient uptake by wheat and cotton as influenced by fer tilizer rate. Soil and Tillage Research 62:41 53. Isoda A and Wang P. 2002. Leaf temperature and transpiration of field grown cotton and soybean under arid and humid conditions. Plant Prod. Sci. 5:224 228. Johnson MD and Lowery B. 1985. Effect of three con servation tillage practices on soil temperature and thermal properties. Journal Soil Science Society of America 49 :1547 15 52. Johnson IR and Thornley JHM. 1985. Temperature dependence of plant and crop processes. Ann. Bot. 55:1 24. Jones HG. 2003. Irriga tion scheduling: advantages and pitfalls of plant based methods. J. of Exp. Botany 407:2427 2436. Jones HG. 2007. Monitoring plant and soil water status: established and novel methods revisited and their relevance to studies of drought tolerance. J of Exp. Botany 58: 119 130.
108 Jones JN, Moody JE, and Lillard JH. 1969. Effects of tillage, no tillage, and mulch on soil water and plant growth. Agron. J. 61 :719 721. Karamanos AJ, Bilalis D, Sidiras N. 2004. Effects of reduced tillage and fertlization practice s on soil characteristics, plant water status, growth and yield of upland cotton. Journal of Agronomy and Crop Sci. 190: 262 276. Katsvairo TW, Wright DL, Marois JJ, Hartzog DL, Rich JR and Wiatrak PJ. 2006. Sod livestock integration into the peanut cotton rotation. Agron. J. 98:1156 1171. Katsvairo TW, Wright DL, Marois JJ, Hartzog DL, Balkcom KB, Wiatrak PP, and Rich JR. 2007. Cotton roots, earthworms, and infiltration characteristics in sod peanut cotton cropping systems. Agron. J. 99: 390 398. Kerby TA an d Adams F. 1985. Potassium nutrition of cotton. Potassium in Agriculture. American Society of Agronomy Meeting: 843 860. review and synthesis of re cent research. Food Policy 3 2 :25 48. Kukal SS, Hira GS and Sidhu AS. 2005. Soil matric potential based irrigation scheduling to rice (oryza sativa). Irrigation Sci. 23:153 159. Lamb MC, Davidson Jr. JI, Childre JW, and Martin Jr. NR. 1997. Comparison of peanut yield, quality and net returns between nonirrigated and irrigated production. Peanut Sci. 24:97 101. Lamb MC, Masters MH, Rowland D, Sorenson RB, Zhu H, Blankenship RD, and Butts CL. 2004. Impact of sprinkler irrigation amount and rotation on peanut yield. Peanut Sci. 31:108 113 Langdale GW, Wilson RL, and Bruce RR. 1990. Cropping frequencies to sustain long term conservation tillage sys tems. Soil Sci. Soc. Am. J. 54: 193 198. Lascano RJ. 2000. A general system to measure and calculate daily crop water use. Agron. J. 92:821 832. Lascano RJ, Baumhardt RL, and Hicks SK. 1994. Soil and plant water evaporation from strip tilled cotton: measurement and simulation. Agron. J. 86: 987 994 Lascano RJ and Baumhardt RL. 1996. Effects of crop residue on soil and plant water evaporation in a d ryland cotton system. Theoreti cal and Applied Climatology 54: 69 84. Lascano RJ and Van Bavel CHM. 1984. Root water uptake and soil water distribution: test of an availability concept. Soil Sci. Soc. Am. J. 48:233 237.
109 Lindstrom and Onstad. 1984. Influence of tillage systems on soil physical parameters and infiltration after planting. J of Soil and Water Cons. 39 :149 152. Loison R, Rowland D, Faircloth W, Marois JJ, Wright DL and George S. 2012. Cattle grazing affects cotton root dimensions and yield in a b ahiagrass based crop rotation. Online. Crop management doi:10.1094/CM 2012 0925 02 RS. Lundstrom DR and Stegman EC. 1988. Irrigation scheduling by the checkbook method. Bull. AE 792(rev.) North Dakota State Univ. Ext. Serv., Fargo. MacKenzie AJ, Spencer WF, Stockinger KR, and Krantz BA. 1963. Seasonal nitrate nitrogen content of cotton petioles as affected by nitrogen application and its relationship to yield. Agron. J. 55:55 59. Marois JJ and Wright DL. 2003. Effect of tillage system, phorat e, and cultivar on tomato spotted wilt of peanut. Agron. J. 95:386 389. Masters MH and Lamb MC. 2003. Economic feasibility of limiting irrigation on cotton in southwest Georgia. Proceedings of 2003 Beltwide Cotton Conferences, Nashville,TN 421 427. Meisner CA and Karnok KJ. 1992. Peanut root response to drought stress. Agron. J. 84:159 165. Miguez FE and Bollero GA. 2005. Review of corn yield response under winter cover cropping systems using meta analytic methods. Crop Sci. 45:2318 2329. Mitchell JP, Munk DS, Prys B, Klonsky KK, Wroble JF, DeMoura RL. 2006. Conservation tillage production systems compared in san joaquin valley cotton California Agriculture 60: 140 145. Newell RL and Wilhelm WW. 1987. Conservation tillage and irrigation effects on corn root development. Agron. J. 79:160 165. Nyajatawa EZ, Reddy KC, and Mays DA. 2000. Tillage, cover cropping, and poultry litter effects on cotton:ii. growth and yield parameters. Agron. J. 92:1000 1007. Obreza TA, Pitts DJ, Parson LR, Wheaton TA, and Morgan KT. 1997. Soil water holding characteristic affects citrus irrigation scheduling strategy. Proc. Fl. State Hort. Soc. 110:36 39. Olson TC and Schoeberl LS. 1970. Corn yields, soil temperature, and water use with four tillage methods in the western corn belt. A gron. J. 62: 229 232. Oosterhuis DM and Wullschleger SD. 1987. Osmotic adjustment in cotton (gossypium hirsutum l.) leaves and roots in response to water stress. Plant Phys. 84:1154 1157.
110 Pettigrew WT, and Jones MA. 2001. Cotton growth under no till production in the lower Mississippi river valley alluvial flood plain. Agron. J. 93: 1398 1404. Pietola LM. 2005. Root growth dynamics of spring cereals with discontinuation of mouldboard ploughing. S oil and Tillage Research 80: 103 114. Rasse DP and Smucker AJM. 1998. Root recolonization of previous root channels in corn and alfalfa rotations. Plant and Soil 204:203 212. Remorini D and Massai Rossano. 2003. Comparison of water status indicators for young peach trees. Irrigation Sci. 22:39 46. Rowland DL, Faircloth WH, and Butts CL. 2007. Effects of irrigation method and tillage regime on peanut (arachis hypogaea l.) reproductive processes. Peanut Sci. 34: 85 95. Rowland DL, Faircloth W, Payton P. 2008. Rooting d ynamics associated with minimal tillage in the semi arid peanut production region of west texas. 30th Southern Conservation Tillage Conference for Sustainable Agriculture. www.ag.auburn.edu Ruhl JB. 2009. Water wars, eastern style: divvying up the Apalach icola chattahoochee flint river basin. Journal of Contemporary Water Research and Eduction 131:47 54. Smith DM and Allen SJ. 1996. Measurment of sap flow in plant stems. J. of Exp. Bot. 47:1833 1844. Stevens WE, Johnson JR, Varco JJ, and Parkman J. 1992. T illage and winter cover management effects on fruiting and yield of cotton. Journal of Production Agriculture 5 :570 575. Sullivan DG, Truman CC, and Schomberg HH. 2007. Potential impact of conservation tillage on conservin g water resources in Georgia. J. o f Soil and Water Cons. 62 :145 152. Shear GM and Moschler WW. 1969. Continuous corn by the no tillage and conventional tillage methods: a six year comparison. Agron. J. 61: 524 526 Smiley RW and Wilkins DE. 1993. Annual spring barley growth, yield, and root rot in high and low residue till age systems. J. Prod. Agric. 6: 270 275 Taylor HM and Klepper B. 1974. Water relations of cotton. i. root growth and water use as related to top growth and soil water content. Agron. J. 66:584 588. Thierfelder C and Wall P C. 2009. Effects of conservation agriculture techniques on infiltration and soil water content in Zambia and Zimbabwe. So il and Tillage Res. 105: 217 227.
111 Thompson RB, Gallardo M, Valdez LC, and Fernandez. 2007. Using plant water status to define threshold values for irrigation management of vegetable crops using soil moisture sensors. Agric. Water Mgmt. 88:147 158. Tollner EW, Hargrove WL and Langdale ,GW. 1984. Influence of conventional and no till practices on soil physical properties i n the southern pied mont. Soil and Water Cons. 39: 73 76. Tubbs RS and Gallaher RN. 2005. Conservation tillage and herbicide management in tow peanut cultivars. Agron. J. 97:500 504 Unger PW. 1991. Infiltration on simulated rainfall: tillage system and crop residue effects. Agron. J. 56 :283 289 USDA National Agricultural Statistics Service (NASS). (June 2012). National statistics for peanuts/cotton. www.nass.usda.gov USDA. 2009. State level data. 2007 Census of Agriculture. State Vol. 1, Ch. 2. Van den Putte A, Govers G, Di els J, Gillijns K, and Demuzere M. 2010. Assessing the effect of soil tillage on crop growth: a meta regression analysis on european crop yields under conservation agriculture. Euro J. of Agron. 33: 231 241. Vara Prasad PV, Craufurd PQ, and Summerfield RJ. 1999. Sensitivity of peanut to timing of heat stress during reproduc tive development. Crop Sci. 39: 1352 1357. Vara Prasad PV, Craufurd PQ, and Summerfield RJ. 2000. Effect of high air and soil temperature on dry matter production, pod yield, and yield components of gr oundnut. Plant and Soil 222: 231 239. Vellidis G, Tucker M, Perry C, Kvien C and Bednarz C. 2008. A real time wireless smart sensor array for sched uling irrigation. Computers and Electronics in Agric. 61:44 50. Wagger MG and Denton HP. 1992. Crop and tillage rotations: grain yield, residue cover, and soil water. Soil Science Soc iety of America J. 56: 1233 1237 Wiatrak PJ, Wright DL, Marois JJ, Koziar a W, Pudelko JA. 2005. Tillage and nitrogen application impact on cotton following wheat. Agron. J. 97: 288 293. Wright DM and Porter FS. 1991. Early leafspot of peanuts: effect of conservational tillage practices on disease development. Peanut Sci. 18: 76 7 9. Wright DM and Porter FS. 1995. Conservational tillage and cultivar influence on peanut production. Peanut Sci. 22: 120 124.
112 Wright DM, Marois J, Katsvairo T, Wiatrak P and Rich J. 2004. Value of perennial grasses in conservation cropping systems. Proceedings of 26 th Annual Conservation Tillage Conference, Auburn, Alabama 135 142. Wright JL and Jensen ME. 1978. Development and evaluation of evapotranspiration models for irrigation scheduling. Trans. of the ASAE 21: 88 91, 96. Zhai R, Kachanoski RG andVoroney RP. 1990. Tillage effects on the spatial and temporal variations of soil water. Soil Science Society of America Journal 54:186 192. Zhao D, Wright DL, and Marois JJ. 2009. Peanut yield and grade responses to timing of bahiagrass termination and tillage in a sod based crop rotation. Peanut Sci. 36: 196 203.
113 BIOGRAPHICAL SKETCH Joshua Thompson grew up near Jacksonville, Florida and after graduating Providence School in 2007, began attending the University of No rth Florida in Jacksonville. After completing two years there, he transferred to the University of Florida in Gainesville and in 2010 received a Bachelor of Science degree in p lan t s cience with a focus in a anuary of 2011 a t the University of Florida in a gronomy. Upon graduation in December of 2012, Joshua will take a position as the Regional Integrated Pest Management Extension Agent in Jackson County, Florida.