Studies on the Use of Soil Edaphic Factors for the Development of Site Specific Management Strategies for Rotylenchulus reniformis on Cotton by Scott Randall Moore A dissertation submitted to the Graduate Faculty of Auburn University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Auburn, Alabama August 4, 2012 Copyright 2012 by Scott Randall Moore Approved by Kathy S. Lawrence, Chair, Associate Professor of Plant Pathology Joseph W. Kloepper, Professor of Plant Pathology Brenda V. Ortiz, Extension Specialist Francisco J. Arriaga, Affiliate Associate Professor of Agronomy and Soils Dale Monks, Extension Specialist ii Abstract The reniform nematode, Rotylenchulus reniformis, is currently one of the most limiting factors to cotton production in the United States. With no available commercial host plant resistance, options for management of R. reniformis are limited to the use of rotations with non- hosts and the use of nematicides, each of which varies greatly in cost-savings and effectiveness. Site-specific application is used for a wide variety of agricultural practices, and successful programs for other species of nematodes in cotton, such as Meloidogyne incognita and Hoplolaimus columbus, are currently in use. The future of site-specific management for R. reniformis in cotton depends on determining which soil factors can be utilized to predict damage and the development of reliable recommendations based on this knowledge. The first half of this dissertation focuses on soil texture distribution and its effect on the cotton/R. reniformis interaction both directly and with respect to its influence on soil moisture availability. The second half focuses on utilizing soil texture to create management zones within cotton production systems for maximum yield and cost savings. Through these studies, a greater understanding of the differential effects of soil texture on the cotton/R. reniformis interaction is achieved as well as solutions for production scale management of R. reniformis in cotton. iii Acknowledgments I would like to thank my wife, Jessica, for her unending support and affection throughout my education. I would also like to thank my parents and family, which have provided lifelong encouragement. A special thanks to my graduate advisor, Dr. Kathy Lawrence, for going above and beyond in providing me with the time, environment, and support to become a well-rounded and successful scientist. To her, and all those who served on my graduate committees and in other advisory capacities throughout my education, I am forever grateful. Finally, to the faculty and staff of the following departments, research centers, and organizations, I would like to express my thanks for their support: the Department of Entomology and Plant Pathology, the Department of Agronomy, the USDA-ARS, Auburn, AL, the Auburn University Plant Science Research Center, the Tennessee Valley Research and Extension Center, the Brewton Agricultural Research Unit, KBH Farms, Huxford, AL, the Alabama Cotton Commission, and Cotton Incorporated. iv Table of Contents Abstract ......................................................................................................................................... ii Acknowledgments........................................................................................................................ iii List of Tables ............................................................................................................................... vi List of Figures ............................................................................................................................. vii Chapter 1: Rotylenchulus reniformis in Cotton: Current Methods of Management and the Future of Site-Specific Management ?????????????????????. .. 1 Chapter 2: The Effect of Soil Texture on the Interaction of Rotylenchulus reniformis and Cotton ?????????????????????????????? ? .13 Introduction .................................................................................................................... 14 Materials & Methods ...................................................................................................... 15 Results ............................................................................................................................. 18 Discussion ....................................................................................................................... 20 Chapter 3: The Effect of Soil Water Availability on the Interaction of Rotylenchulus reniformis and Cotton in Multiple Soil Types????????????????????. 30 Introduction .................................................................................................................... 31 Materials & Methods ...................................................................................................... 32 Results ............................................................................................................................. 33 Discussion ....................................................................................................................... 35 Chapter 4: Evaluation of Nematicides for the Management of Rotylenchulus reniformis Across Management Zones Created Using Soil Edaphic Factors???????????.. 40 v Introduction .................................................................................................................... 41 Materials & Methods ...................................................................................................... 42 Results ............................................................................................................................. 44 Discussion ....................................................................................................................... 46 Chapter 5: Evaluation of Nematicides for the Management of Rotylenchulus reniformis in a Field with Homogeneous Soil Characteristics ????????????????... ?. 58 Introduction .................................................................................................................... 59 Materials & Methods ...................................................................................................... 59 Results ............................................................................................................................. 61 Discussion ....................................................................................................................... 61 References ................................................................................................................................. 72 vi List of Tables Table 1: Particle size analysis and median soil particle size for each soil type. ........................ 23 Table 2: Mean R. reniformis populations at planting, 60 and 150 days after planting (DAP), plant heights at 60 and 150 DAP, and seed cotton yields (grams/plot) for each soil type and irrigation regime from 2008 ? 2010. ......................................................................................................... 24 Table 3: Volumetric water content for each soil at each of the three matric potentials. ........... 36 Table 4: Average cotton plant height, shoot fresh weight, root fresh weight, and numbers of R. reniformis per gram of cotton root for each soil at each matric potential??.. ??????. 37 Table 5: Attributes of each management zone. ......................................................................... 49 Table 6: Rotylenchulus reniformis populations per 150cm3 of soil at each of the 4 sampling dates (planting, 30 and 60 DAP, and harvest) for each nematicide treatment in each of the three management zones. ..................................................................................................................... 50 Table 7: Cotton plant heights (cm) at 60 DAP and harvest for each nematicide treatment in each of the three management zones. ????????????????????????. 53 Table 8: Cotton yield mapping data (number of bolls, weight, and corresponding position on the plant) for each nematicide treatment in each of the three management zones. .......................... 54 Table 9: Seed cotton yields (kg/ha) for each nematicide treatment in each of the three management zones. ..................................................................................................................... 57 Table 10: Rotylenchulus reniformis populations per 150cm3 of soil at each of the 3 sampling dates (planting, 30 and 60 DAP) for each nematicide treatment in 2009, 2010, & 2011. .......... 63 Table 11: Cotton yield mapping data (number of bolls, weight, and corresponding position on the plant) for each nematicide treatment in 2009, 2010, & 2011?????????????. 65 Table 12: Cotton plant heights (cm) at harvest for each nematicide treatment in 2009, 2010, & 2011............................................................................................................................................. 70 Table 13: Seed cotton yields (kg/ha) for each nematicide treatment in 2009, 2010, & 2011..... 71 vii List of Figures Figure 1: Mean R. reniformis populations per 500cm3 of soil, , and plant shoot weight: root weight ratios, , at 60 days after planting for each initial population of R. reniformis within each of the six soil types. ................................................................................................................... 26 Figure 2: Average shoot fresh weight (SFW) and root fresh weight (RFW) (g) at each initial inoculation level of R. reniformis at 60 DAP. .......................................................................... 28 Figure 3: Influence of soil particle size on harvest population densities of Rotylenchulus reniformis/150cm3 of soil in six different soil types over a three-year period. The relationship between population density of R. reniformis (Y) and median soil particle size of a soil (X) was described by the quadratic model Y = 39,571 ? 41,363x ? 69,707x2 (R2 = 0.61, P = 0.0001). Median soil particle size (MSPS) of a soil was calculated as: MSPS = ? [Percent particles of a category (coarse sand, medium sand, fine sand, very fine sand, coarse silt, fine silt, or clay) X median size of that category (1.25mm, 0.75mm, 0.175mm, 0.075mm, 0.035mm, 0.011mm, or 0.001mm)] /100. ......................................................................................................................... 29 Figure 4: Soil moisture release curves for each soil type (silt loam, very fine sandy loam, fine sandy loam, loam, sandy loam, and clay). ................................................................................. 39 1 Chapter 1 Rotylenchulus reniformis in Cotton: Current Methods of Management and the Future of Site- Specific Management Abstract The reniform nematode, Rotylenchulus reniformis, is currently one of the most limiting factors to cotton production in the United States. With no available commercial host plant resistance, options for management of R. reniformis are limited to the use of rotations with non-hosts and the use of nematicides, each of which varies greatly in cost-savings and effectiveness. Multiple research groups are currently pursuing the goal of site-specific management for R. reniformis in cotton. Site-specific application is used for a wide variety of agricultural practices, and successful programs for other species of nematodes in cotton, such as Meloidogyne incognita and Hoplolaimus columbus, are currently in use. Within this manuscript, future possibilities for the use of site-specific management for R. reniformis in cotton as well as potential limitations of current techniques are discussed. 2 Cotton, Gossypium hirsutum Linnaeus, is one of the most economically important crops in the United States. In 2010, cotton was grown in 17 states with 11 million acres devoted to cotton production valued at more than $7.3 billion (USDA-NASS, 2011). The reniform nematode, Rotylenchulus reniformis Linford & Oliveira, is a semi- endoparasite of roots that occurs in tropical and sub-tropical regions (Robinson et al., 1997) and is a major pathogen affecting U. S. cotton. Currently, R. reniformis can be found in 11 of the 17 cotton producing states and is estimated to have caused a loss of nearly 2% annually in the past decade (Blasingame et al., 2002 ? 2012). Rotylenchulus reniformis is easily introduced into cotton fields on contaminated equipment and other means of soil transport. Once there, it can be spread throughout the field by tillage and water flow (Monfort et al., 2008; Moore et al., 2011a); however, in no-till systems, R. reniformis can spread independently both horizontally and vertically (Moore et al., 2010a). Vertical distribution has been well documented at depths of up to 1.5 m (Lee et al., 2002; Moore et al., 2010a; Robinson et al., 2005a; Westphal & Smart, 2003; Westphal et al., 2004), and populations below the plow layer can greatly affect cotton yields (Newman & Stebbins, 2002; Robinson et al., 2005b). Currently, there are no commercial cotton cultivars with resistance or consistent tolerance to R. reniformis (Usery et al., 2005; Robinson, 2007). As such, management options for R. reniformis fall into two major categories: pesticides and crop rotation. There are many forms of pesticides available for the management of R. reniformis. Each varies in effectiveness and each has its limitations. Fumigants such as 1,3-dichloropropene (Telone II) and metam sodium (Vapam) are generally highly effective for management of R. reniformis (Kinloch & Rich, 2001; Koenning et al., 2007; Lawrence et al., 1990; Rich & Kinloch, 2000). They are often limited by 3 cost, high risk to applicators, special application equipment, soil texture, and temperature and moisture requirements. An assortment of granular pesticides have been proven effective for the management of R. reniformis, including aldicarb (Temik 15G) (Lawrence et al., 1990; Lawrence & McLean, 2000, Rich & Kinloch, 2000), fenamiphos (Nemacur) (Koenning et al., 2007; Lawrence et al., 1990), and terbufos (Counter) (Lawrence et al., 1990). Of the granular pesticides, aldicarb has been the most widely used in cotton production, and its continual use has resulted in reports of enhanced degradation by soil microbes thus decreasing its overall efficacy (Lawrence et al., 2005). Furthermore, the future of this pesticide is currently unknown due to the discontinuance of its production (Bayer CropScience, 2010). Similarly, fenamiphos is no longer labeled for use in the United States (EPA, 2002), and terbufos is not currently labeled for use in cotton production. Seed applied pesticides such as abamectin and thiodicarb have recently become widely used in cotton production as a part of Avicta Complete Cotton and Aeris Seed Applied System, respectively, and have been reported to provide adequate management of R. reniformis (Faske & Starr, 2006; Lawrence & Lawrence, 2007). Their protection of the root is limited (Faske & Starr, 2007) as is their ability to provide adequate protection against high populations of R. reniformis (Moore et al., 2010b). Oxamyl (Vydate C-LV) is a foliar applied pesticide that also provides adequate management of R. reniformis, often in conjunction with previously mentioned pesticides (Baird et al., 2000; Lawrence & McLean, 2000), but has been reported to be less effective in dry conditions (Koenning et al., 2007). Additional options for R. reniformis management in the form of biological organisms, such as Bacillus firmus (Poncho/VOTiVO) and Paecilomyces lilacinus 4 strain 251 (Nemout) as seed applied formulations (Castillo et al., 2011), have been reported to have efficacy against R. reniformis. Furthermore, there are multiple known nematophagous fungi with high levels of effectiveness in greenhouse studies (Wang et al., 2004; Castillo et al., 2009) that could prove useful in the future. Overall, the number of pesticides for the management of R. reniformis is decreasing, resulting in increased challenges for producers. Crop rotation to non-hosts, such as corn or peanuts or highly resistant varieties of soybean, is also an effective strategy for the management of R. reniformis. A one year rotation with corn and resistant soybean effectively increases cotton yields (Davis et al., 2003; Moore et al., 2010c); however, populations of R. reniformis quickly rebound to pre-rotational crop levels by mid-season. A two year or longer rotation with corn or resistant soybean or a one year or longer rotation with peanuts can result in R. reniformis populations remaining below current economic thresholds throughout the subsequent cotton crop (Stetina et al., 2007; Moore et al., 2010c). Many native weed species are host of R. reniformis to some degree and can confound the aforementioned positive effects of crop rotation if not properly controlled (Davis & Webster, 2005; Jones et al., 2006; Lawrence et al., 2008; Wang et al., 2003). The methods currently used to manage R. reniformis in cotton can be economically beneficial if utilized intelligently and with forethought. For a problem that is consistently increasing, further management strategies are needed. Site specific, or precision, management (SSM) is a concept that is increasingly utilized since being made possible by the integration of global positioning systems (GPS) technologies into agriculture. The use of SSM based on soil variability as a strategy to enhance the management of R. reniformis has developed into a subject of great interest in recent years. In this review, the current methods of zone delineation for SSM and their uses will be discussed along with the potential for use of known factors affecting R. 5 reniformis and its interaction with cotton. The pitfalls of SSM in regards to its use for R. reniformis management also will be addressed, as will an evaluation of the feasibility of using current methods of SSM for R. reniformis. Finally, we will determine what information is still required to facilitate a workable guideline for implementing SSM for R. reniformis. The delineation of management zones for SSM based on soil variability has been a topic of research for decades. A management zone can be defined as a sub-region of a field that expresses a homogeneous combination of yield limiting factors for which a single rate of a specific crop input is appropriate (Doerge, 1999). The development of management zones requires the use of some form of geostatistical analysis. There are many different methods of geostatistical analysis, both descriptive and predictive, that can be used alone or in combination, depending on the situation. Descriptive methods of geostatistical analysis allow for the detection and quantification of the major scales of spatial variability (Goovaerts, 1998). Examples of such descriptive methods include the experimental correlogram, which plots the estimated correlation coefficients of one variable as a function of the separation distance, and the experimental semivariogram, which plots the semivariances of ordered data versus distance (Goovaerts, 1998). Predictive methods are utilized in the estimation of soil properties at un-sampled places between or near collected data points. Examples of predictive methods of geostatistical analysis include ordinary kriging, which estimates the value of an un-sampled location as a linear combination of neighboring observations, and factorial kriging, which estimates and maps different sources of spatial variability identified by experimental semivariograms (Wackernagel 1988, 1995; Goovaerts, 1992). Prescription maps began development based on soil type (Carr et al., 1991) or topography (Fiez et al., 1994). Further research has developed prescription maps on a collection 6 of characteristics including soil type, soil color, topography, yield, aerial photos, and producer experience (Ostergaard, 1997; Fleming et al., 2004). The use of soil apparent electrical conductivity (EC) has become one of the most frequently used methods of management zone delineation based on soil variability. Apparent electrical conductivity has been found to correlate highly with soil texture (Williams & Hoey, 1987). It also relates closely with a variety of other characteristics including: cation exchange capacity and exchangeable Ca and Mg (McBride et al., 1990), water content (Kachanoski et al., 1988), soil organic C (Jaynes, 1996), herbicide behavior in soil (Jaynes et al., 1994), depth to clay pans (Kitchen et al., 1999), and crop yield (Sudduth et al., 1995; Heermann et al., 1999). The geostatistical analysis of soil properties and the subsequent delineation of management zones have proven effective in a variety of situations worldwide. Casa & Castrignano (2008) demonstrated the spatial relationships between soil and crop variables of durum wheat in Italy. Rab et al. (2009) utilized geostatistical modeling of plant-available water capacity and related soil properties to delineate management zones for the enhancement of grain yields in Australia. Liu et al. (2006) explored the possibilities of combining ordinary kriging with soil map-delineation to enhance the interpolation of soil properties in a paddy rice/sugarcane rotation in Taiwan. Lopez-Lozano et al. (2010) successfully linked leaf area index with soil properties for precision management of abiotic stress of corn in Spain. In the U. S., management zones based on soil characteristics have been used to predict grain yields (Fraisse et al., 2001) and determine the risk of iron chlorosis in maize (Kyaw et al., 2008). The use of geostatistical analysis and management zone delineation also has recently been developed for the management of the Columbia lance nematode (Hoplolaimus columbus), the root-knot nematode (Meloidogyne incognita), and the ring nematode (Criconemella spp.) 7 (Khalilian et al., 2001; Khalilian et al., 2002; Khalilian et al., 2003; Monfort et al., 2007; Ortiz et al., 2007; Ortiz et al., 2008; Wolcott et al., 2004; Wolcott et al., 2005). Khalilian et al. (2003) reported a 5% yield increase using either variable rate aldicarb or 1,3-dichloropropene for Columbia lance management with a 34% and 78% reduction of input, respectively. Monfort et al. (2007) observed that the combination of the initial populations of root-knot nematodes and the sand content of the soil explained 65%, 86%, and 83% of the variation in cotton yield over a three-year period, respectively. Similarly, Ortiz et al. (2007) observed that a model of root-knot nematode risk of a field over a specific threshold value could be produced through logistic regression using soil electrical conductivity as a predictor variable. Furthermore, it was determined that the use of variable rate application of nematicides could be effectively employed to manage root-knot nematodes in cotton (Ortiz et al., 2008). Although there are several successful examples of site-specific management of nematodes, there are studies that address certain pitfalls of this technique. Wyse-Pester et al. (2002) conducted a study to determine the scale of sampling required to obtain correlated observations of density in order to reduce sampling costs for three species of nematodes on corn. The results of the study indicated that correlations between nematode density and soil attributes were inconsistent between field and species, and thus the cost of sampling was not reduced. Similarly, Evans et al. (2002) found that coarse sampling grids, which are required to make SSM a commercially viable option for the management of potato cyst nematodes (Globodera pallida and G. rostochiensis), are likely to produce misleading population distribution maps resulting in yield penalties. Farias et al. (2002) were able to construct an accurate distribution model of R. reniformis within a cotton field; however, the number of sampling points used (64 points within a 48 x 32 m area) would be cost prohibitive in a commercial setting. In a study assessing 8 sampling grid size for variable rate application of nematicides for the management of R. reniformis, Ellis et al. (2004) found that fewer rate changes occurred with increasing grid size. This relationship has one of two possible consequences. The first is increased input of nematicides where they are not needed, which would result in a cost penalty. The second consequence would be not applying nematicides where needed, which would result in a yield penalty. Technological pitfalls are also a possibility in the development of site-specific management. Choosing the correct analysis of spatial data is vital to producing accurate prescription maps. In a study of the accuracy of interpolating elevation data, a measurement commonly used in conjunction with EC for management zone delineation, Weng (2006) determined that accuracy was subject to a number of interpolation parameters that may significantly improve or worsen the accuracy. Similarly, it has been reported that apparent soil electrical conductivity is affected by soil transient properties such as volumetric soil water content and exhibits large changes throughout the season (McCutcheon et al., 2006). Factors such as these can result in unreliable data and must be considered during management zone creation. To create management zones within a field for R. reniformis, the factors of influence must first be characterized through quantitative research and then the data can subsequently developed into a useable form. As was discussed earlier, soil texture distribution can be easily measured within a field by utilizing soil apparent electrical conductivity and has been used in management strategies for other species of nematodes. Consequently, this factor has been investigated as a starting point for zone delineation for R. reniformis. While R. reniformis is known to exist and cause damage in a wide variety of soil types (Gazaway & McLean, 2003), 9 some research has suggested that R. reniformis is more prevalent in fine-textured soils (Robinson et al., 1987; Starr et al., 1993; Monfort et al., 2008). Other research on the effects of soil type on R. reniformis populations has suggested that the productivity of the soil, not specifically soil texture, is the driving force behind population development (Koenning et al., 1996; Herring et al., 2010) as well as response to nematicides (Overstreet et al., 2007, 2011, & 2012). Another consideration for zone delineation is initial populations of R. reniformis and economic damage threshold values. More often than not, management decisions and subsequently economic threshold values are based on post-harvest nematode sampling. Although little is known about the overwinter survivorship of R. reniformis, it has been observed that overwinter survivorship was lowest in areas of high sand content and increased with increasing clay content (Still & Kirkpatrick, 2006). Studies of overwinter survivorship on Meloidogyne incognita have suggested that population density and cultural practices have the greatest impact on overwinter survivorship (Ferris, 1985). Studies have shown that R. reniformis populations are adversely affected by post-harvest conventional tillage compared to non-tillage and ridge tillage (Cabanillas, et al., 1999). Economic thresholds are established based on the relationships between the degree of control and cost and nematode densities and crop value (Ferris, 1978). Current thresholds are established on a state-by state basis, but it has recently been suggested that different economic thresholds be considered based on soil type and productivity (Moore et al., 2011b). Studies exploring the possibilities of SSM and variable rate nematicide applications for R. reniformis have been conducted in recent years. Variable rate application based on populations of R. reniformis have been conducted with the fumigant nematicides 1,3- dichloropropene and metam sodium with promising results (Lawrence et al., 2002; Ellis et al., 10 2005). Farias et al. (2002) created a risk-benefit analysis for the treatment of R. reniformis in a Brazilian cotton field by utilizing geostatistical methods to interpolate population distribution over short distances (4-6 m). Another tool in development is the use of remotely sensed hyperspectral data to detect stress levels in cotton. Doshi et al. (2010) conducted a study comparing hyperspectral reflectance of cotton plants grown in microplots to R. reniformis populations in the plant rhizosphere and determined that this method could accurately estimate R. reniformis populations affecting the cotton plant. The use of remote sensing to detect cotton plant stress due to issues with subsurface drip irrigation has also illustrated this tool?s ability to detect differences in cotton response to stress in field settings (Fulton et al., 2008). The successful use of site-specific management for R. reniformis on cotton is dependent on the resolution of several issues. The first and most important issue is to what spatial scale (single field, soil region, state, etc.) can general recommendations be developed and be reliable? Second, what parameters, or combination of parameters, will provide the most accurate measure of economic risk and subsequent usefulness in management zone creation? Third, can the two aforementioned issues be resolved in a manner which will result in a method that is easily adaptable for producers and will provide them with cost savings? The issue of the size of the spatial scale upon which to separate recommendations includes two major considerations. R. reniformis is known to have geographical variation with respect to reproduction, pathogenicity, morphometrics, temperature effects on embryogenesis, and genetics (Agudelo et al., 2001; Agudelo et al., 2005; Arias et al., 2009; Leach et al., 2009; McGawley et al., 2010), some of which vary within a single state. A second consideration is the diversity of soils within regions and states. For example, Alabama has six major soil areas where cotton is produced, each with quite different characteristics and levels of in-field variability. It is 11 also well known that certain soils, such as those found in the Mississippi River Delta region, support far greater populations of R. reniformis in comparison to the soils found in the Coastal Plain region of the Southeast, yet the amount of yield loss in each region is similar. The second issue is which parameters provide the best indicators of economic risk and subsequent usefulness in management zone creation? As was detailed earlier, soil texture distribution has been studied quite extensively in relation to predicting which location in a field is more favorable to R. reniformis reproduction. While this technique has been used successfully for other species of plant-parasitic nematodes, the success of R. reniformis to reproduce and cause damage in a wide variety of soil textural distributions renders this method much less useful. Economic threshold level of R. reniformis is another parameter to be considered. Potential soil productivity has been shown to affect this relationship (Moore et al., 2011a) as well as the possibilities of additional stress due to the lack of water throughout the growing season (Moore et al., 2011c). The use of yield maps from previous years, if they exist, is another strong possibility for guidance of zone creation. Massey et al. (2008) determined that utilizing yield maps to assess profitability of corn, soybean, and grain sorghum based on field features and input costs could provide producers with information to assess management options. Can SSM for R. reniformis on cotton become an easily adaptable and cost-saving tool for cotton producers? The answer depends on two major issues; spatial scale and zone creation parameters. Spatial scale and zone creation parameters are currently a focal point of research throughout areas affected by R. reniformis. Furthermore, many of the techniques for site-specific management are used for a variety of other issues and could be easily adapted with the correct guidelines. The identification of parameters to quantify economic risk and the understanding of 12 how these parameters will differ over geographical areas will determine if SSM can enable cotton producers to gain an economic advantage over R. reniformis. 13 Chapter 2 The Effect of Soil Texture on the Interaction of Rotylenchulus reniformis and Cotton Abstract The reniform nematode, Rotylenchulus reniformis, is the most damaging nematode pathogen of cotton in Alabama. The use of soil texture is currently being explored as a basis for the development of economic thresholds and management zones within a field. Trials to determine the reproductive potential of R. reniformis as influenced by soil type and irrigation were conducted in both microplot and greenhouse settings in 2008 ? 2010. Irrigation was found to have a significant effect on R. reniformis population in only isolated cases early in the growing season. However, plant parameters were significantly increased by irrigation throughout the growing season. Populations of R. reniformis were significantly influenced by soil texture and exhibited a general decrease with increasing median soil particle size. Early season cotton development was significantly affected by increasing R. reniformis populations, with plant shoot weight/root weight ratios increasing at low R. reniformis populations and declining with increasing R. reniformis populations. Soil texture in combination with other soil properties can be a useful tool for developing management strategies for R. reniformis on cotton. 14 Introduction Site-specific management of the reniform nematode, Rotylenchulus reniformis Linford & Oliveira is a developing management strategy for cotton (Gossypium hirsutum Linnaeus) growers. This strategy has been successfully employed for other species of nematode such as the southern root-knot (Meloidogyne incognita, Kofoid & White) and Columbia lance nematodes (Hoplolaimus columbus Sher) by delineating management zones based on various soil edaphic factors and assigning a risk level to each zone. However, for the reniform nematode, which soil characteristic, or combination of characteristics, constitutes a higher or lower risk is not well defined. One such factor, soil texture, is often used as a starting point for zone delineation for current nematode management. A basic particle size distribution can be determined using apparent soil electrical conductivity and, along with factors such as elevation and slope, be used to create management zones within a field. The use of particle size distribution has been shown to be effective in assessing risk for both the southern root-knot and Columbia lance nematode. Both species exhibit a strong preference to soils with high sand content (Koenning et al. 1996; Lewis and Smith 1976), and as such zone delineation using soil texture as a main factor is highly useful. Alternatively, a 1990 survey of 11 states to determine the agronomic significance of the reniform nematode found no consistent relationship between the reniform nematode?s presence and soil texture, soil pH, rainfall, or irrigation regime (Heald and Robinson 1990). Subsequently, the reniform nematode has been observed to prefer soils with less than 40% sand content (Starr et al. 1993); with moderate clay + silt percentages (28%) (Koenning et al. 1996); and with silt percentages ranging from 54 ? 60% (Monfort et al. 2008). Within Alabama, the reniform nematode is known to exist above current economic thresholds in a wide variety of soils 15 (Gazaway and McLean 2003), and although populations are generally observed to be higher in finer texture soils, the impact of these differing populations on cotton yield is difficult to compare due to environmental factors. In order to further our understanding of the effects of soil texture on the reniform/cotton relationship either for management zone delineation or to make management recommendations based on nematode population, a comparison of soils unbiased by environmental factors must be conducted. As such, the objectives of the trials presented here were to evaluate six different soil types representative of the major agronomic regions of Alabama to determine 1) population potential of R. reniformis under irrigated and non-irrigated conditions and subsequent effects on cotton yield; and 2) the effects of increasing initial populations of R. reniformis on early season cotton growth. Materials and Methods Two trials were conducted during 2008 ? 2010 in six different soil types from the major field crop cultivated regions of Alabama to evaluate the effect of soil particle size on 1) the reproductive potential of the reniform nematode on cotton over a three-year period from a standardized initial population under both irrigated and non-irrigated conditions; and 2) the reproductive potential of the reniform nematode on cotton and its effects on early season cotton development from differing initial populations. The soil types used in the trials were Decatur silt loam (18-49-33 S-S-C, 1.0% OM, pH = 5.5), Hartsells fine sandy loam (66-21-13 S-S-C, 2.7% OM, pH = 5.4), Vaiden clay (9-53-38 S-S-C, 3.8% OM, pH = 6.1), Lloyd loam (38-35-27 S-S-C, 2.0% OM, pH = 5.5), Dothan sandy loam (82-11-7 S-S-C 0.6% OM, pH = 5.9), and Ruston very fine sandy loam (64-21-15 S-S-C, 1.6% OM, pH = 5.8). Soils were collected from the plow layer (top 12 ? 15 cm) of the soil in cultivated fields free of plant parasitic nematodes. Soils were analyzed for nutrient and pH levels and maintained according to standard recommendations set 16 by the Auburn University Soil Testing Laboratory (Adams et al., 1994). Both trials were conducted at the Auburn University Plant Science Research Center in Auburn, AL. Microplot Trial: The first trial was conducted from 2008 ? 2010 in 4,400 cm3 outdoor microplots arranged in a completely randomized 6 x 2 factorial design replicated 5 times with the first factor designated as soil type and the second factor designated as irrigation. Pots were planted each season with DP161B2RF cotton. Immediately after planting in 2008, 5,000 vermiform life stage R. reniformis nematodes were pipetted into to each pot in 10 ml of water into the seed row. Irrigation was added by hand watering the irrigated pots twice a day throughout the season to maintain adequate moisture availability. Cotton plants were evaluated at 60 and 150 days after planting (DAP) for height, and the cotton was hand-picked as bolls matured (120 - 150 DAP) and weighed. The R. reniformis nematode populations were evaluated at planting, 60, and 150 DAP by taking four 2.5 x 12 cm core samples from each pot. The four samples were homogenized and the nematodes extracted by combined gravity screening/sucrose centrifugation and enumerated. Eggs were extracted by agitating the root system on an orbital shaker at 150 rpm for 4 minutes in a 0.6% sodium hypochlorite (NaOCl) solution and collected on a 25 ?m screen. Greenhouse Trial: The second set of trials to determine reproductive potential with varying initial nematode populations were conducted in 2010 using 500 cm3 polystyrene pots placed in the greenhouse. The tests were arranged in a randomized complete block design with four replicates and repeated twice. At planting, six levels of reniform nematodes were added to the designated pots: 0, 500, 1000, 2000, 5000, and 10000 vermiform life stages were pipetted into each pot in 2 ml of water. Pots were planted with DP161B2RF cotton seed. Plant parameters measured included plant height at 30 and 60 DAP as well as root and shoot fresh 17 weight at 60 DAP. Shoot/root ratios indicating plant development were calculated by dividing the shoot fresh weight by the root fresh weight. Reniform nematode populations were extracted and enumerated at 60 DAP using the previously described methods. Particle Size Analysis: Analysis of soil particle size distribution was conducted using the nested sieving (2.0 ? 0.02 mm fraction) and pipette method (< 0.02 mm fraction) (Gee and Bauder, 1994). Median soil particle size (MSPS) of a soil was calculated as: MSPS = ? [Percent particles of each category (coarse sand, medium sand, fine sand, very fine sand, coarse silt, fine silt, or clay) X median size of that category (1.25mm, 0.75mm, 0.175mm, 0.075mm, 0.035mm, 0.011mm, or 0.001mm)] / 100. Full particle size analysis and median soil particle size for each soil are presented in Table 1. Data were analyzed utilizing analysis of variance (ANOVA) within the GLIMMIX procedure or by linear regression within the REG procedure of SAS, version 9.2 (SAS Institute, Cary, NC). Treatment means were determined from the PDIFF option with LSMEANS, where P < 0.05 was required to be significant. Interactions between the treatment factors of soil and irrigation were not statistically significant for the microplot trials, and data were not analyzed separately. There were also no significant effects of year for the microplot trials, and thus the data for all three years was combined. Soil was a significant factor for the greenhouse trials; therefore, data for each soil type were analyzed separately. Mean populations or R. reniformis and shoot:root ratios at 60 DAP were plotted against initial populations of R. reniformis. Mean final populations (Pf) of R. reniformis were plotted against median soil particle size, and graphics were generated using Microsoft EXCEL. 18 Results Microplot Trial: A soil type by irrigation interaction was not observed for nematode counts, plant heights, or seed cotton yields (Table 2). Irrigation did increase mean populations of R. reniformis. Irrigated pots averaged 45% higher R. reniformis populations at 60 DAP and were significantly higher in the silt loam and sandy loam soils. Irrigated pots averaged 50% higher R. reniformis populations at 150 DAP. The overwintering nematode populations were influenced by irrigation; averaging more than double the R. reniformis populations at cotton planting the following season and supporting significantly higher initial populations in the clay and silt loam soils. Soil type also influenced R. reniformis populations. Between soil types, the silt loam soil averaged the highest R. reniformis populations at each sampling date in both irrigated and non- irrigated pots, respectively. The fine sandy loam soil followed the silt loam soil as the best soil for R. reniformis population densities over the three years. Initial, mid-season, and final population densities were consistently lower in the clay soil without irrigation. Plant parameters were primarily affected by irrigation (Table 2). Plants were significantly shorter in the non-irrigated pots within each soil type at 60 DAP with the exception of the clay soil. The reduction of plant height in the silt loam through the sandy loam soil types averaged 5.35 cm with a range of 4.77 to 6.39 cm. Only the clay soil supported plant growth equally when infested with R. reniformis in the irrigated and non-irrigated systems. However, plant heights had equilibrated between all soils at cotton harvest. Seed cotton yields in R. reniformis infested soils were influenced by irrigation (Table 2). Seed cotton yields were significantly higher in the irrigated pots containing the silt loam, the very fine sandy loam, and the sandy loam soils compared to the non-irrigated pots. Irrigation 19 increased yields by 68% in these soils. The irrigated silt loam soil produced the highest yield compared to all soil types. This soil also supported the highest nematode populations throughout the season. No interactions between soil type or nematode populations and seed cotton yield were observed in this trial. Greenhouse Trial: Cotton growth response to increasing initial populations (Pi) of R. reniformis was similar for all six soil types tested (Fig. 1). In each case, both shoot and root weight decreased at lowest inoculation level (Pi = 500) compared to the Pi=0; however, the decrease in root weight was double in magnitude compared to the decrease in shoot weight resulting in higher shoot weight to root weight ratios (Fig 2). As R. reniformis populations increased (Pi = 1,000 ? 2,000), root weights steadily increased and at Pi = 10,000 averaged 41% higher compared to the root weights in the Pi= 500 treatment (not shown). Inversely, after increasing back to levels at Pi = 2,000 that were similar to the Pi = 0 control, shoot weights decreased with increasing nematode populations resulting in descending shoot weight to root weight ratios. These shoot to root weight ratios were significantly lower at Pi = 10,000 in the silt loam soil, Pi = 1,000 ? 10,000 in the loam soil, and Pi = 5,000 ? 10,000 in the sandy loam when compared to the Pi = 0 control. Final R. reniformis populations (Pf) in the soil increased significantly with increasing Pi. The clay soil supported the highest R. reniformis populations, while the very fine sandy loam supported the lowest. Particle Size Analysis: The effect on soil particle size distribution on average final nematode populations (Pf) for both the microplot and greenhouse trials is shown in Figure 3. A quadratic relationship between final R. reniformis population density of a soil and the median particle size of a soil provided an acceptable fit (R2 = 0.61, P = 0.0001), with the most favorable median particle size for R. reniformis population development within these trials being 20 approximately 0.04 mm. In general, as the median soil particle size of a soil increased from 0.04 mm in the clay soil to > 0.30 mm in the very fine sandy loam and sandy loam soils, R. reniformis populations decreased. Although the initial classifications for the very fine sandy loam (64-21-15 S-S-C) and fine sandy loam (66- 21-13 S-S-C) used in our trial are very similar, a complete particle size analysis reveals the MSPS of the fine sandy loam (0.165 mm) is less than half that of the very fine sandy loam (0.336 mm). Consequently, R. reniformis populations within the fine sandy loam were more than 5x those in the very fine sandy loam. Thus the closer the median particle size of the soil is to 0.04 mm the greater the R. reniformis population development within these trials. Discussion ?Of soil characteristics, texture is one of the most important. It influences many other properties of great significance to land use and management? (Brown 1990). Although within these trials and many others (Heald and Robinson 1990; Robinson et al. 1987; Starr et al. 1993; Koenning et al. 1996) R. reniformis has been shown to prefer soils with a smaller soil particle size distribution, the range at which this preference exists is still very wide. Additionally, R. reniformis has been reported to cause economic damage to cotton in a wide variety of soil types (Gazaway and McLean 2003). Within these trials, R. reniformis was shown to illicit similar plant responses in a wide variety of soils at far different population densities. The results suggests that even if R. reniformis prefers, or will reach higher population densities within, a certain soil the damage very well may be no greater than in a soil that is less preferential. Other qualities of a soil that are dictated by soil texture such as water holding capacity, nutrient availability, etc., may offer a beneficial growing environment to the cotton plant in a similar fashion as they provide benefit to the nematode. 21 The results from the microplot trials indicated that although the availability of water generally increased R. reniformis populations, in only the silt loam and sandy loam at 60 DAP were these increases significant. In the case of the silt loam soil, the irrigated pots produced the highest yields even in the presence of the highest nematode populations. However, in the non- irrigated pots, the silt loam again had the highest nematode populations but produced the lowest yields. Although this study did not address the differences of cotton yields in comparison to a nematode free control, the general trend suggests that the interaction of water and nematode stress is an important factor influencing cotton yield. The growth patterns exhibited by the cotton in our greenhouse trials are consistent with previous findings on the differential effects of low and high R. reniformis populations on cotton. Koenning et al. (1996) reported that their findings suggested low Pi of R. reniformis may enhance plant maturity while high R. reniformis Pi may delay plant maturity. Although our trial focused on early season cotton growth, the effects of Pi produced a marked effect on cotton development. The use of MSPS may lead to a better understanding of how soil particle size distribution of a soil can be used to predict R. reniformis population potential compared to previous methods. While our results are comparable to those previously mentioned (Starr et al. 1993; Koenning et al. 1996; Monfort et al. 2008) in that R. reniformis does prefer or possibly has an advantage in finer textured soils, the use of generic soil series information or basic particle size analysis (S-S- C) may not always be sufficient. Within this trial, the use of a basic particle size analysis for the very fine sandy loam and sandy loam suggests that those two soils should similarly affect R. reniformis populations. However, using a more in depth particle size analysis and MSPS revealed that they were in fact very different. This is not to suggest that MSPS explains all of the 22 variability. Rather that it is another tool which could provide meaningful information in the attempt to develop management strategies for R. reniformis. Rotylenchulus reniformis is a widely adapted pathogen in cotton production regions and is known to cause economic damage in many environmental conditions. Our results suggest that R. reniformis will cause comparable yield declines in a wide range of soil types even though population densities differ significantly. Additionally, the interaction of water stress and R. reniformis may be a more significant factor than water stress alone. Using soil texture to create management zones within a field is certainly a useful tool for site-specific management of R. reniformis. However, the properties of the soil in each zone, yield potential, the risk of water stress, and initial R. reniformis population must be considered and used to develop an economic threshold and management plan for each zone. 23 Table 1: Particle size analysis and median soil particle size for each soil type. Soil Particle Size z Coarse Sand Medium Sand Fine Sand Very Fine Sand Coarse Silt Fine Silt Clay 0.5 ? 2.0 mm 0.25 ? 0.50 mm 0.10 ? 0.25 mm 0.05 ? 0.10 mm 0.02 ? 0.05 mm 0.002 ? 0.02 mm < 0.002 mm MSPS (mm) y Clay 1.06 1.14 2.12 5.14 8.78 43.85 37.92 0.038 Silt Loam 2.08 2.45 7.53 5.52 8.61 40.30 33.50 0.070 Loam 6.84 8.78 15.06 7.33 3.98 30.57 27.44 0.188 Very Fine Sandy Loam 8.43 23.96 23.98 7.93 4.47 16.12 15.11 0.336 Fine Sandy Loam 1.29 7.44 45.66 11.85 5.98 15.44 12.35 0.165 Sandy Loam 8.27 29.76 34.59 9.60 2.73 8.30 6.75 0.396 z Values are percent of particle size present for each soil. y Median soil particle size calculated as (MSPS) = ? [Percent particles of each category X median size of each category] / 100. 24 Table 2: Mean R. reniformis populations at planting, 60 and 150 days after planting (DAP), plant heights at 60 and 150 DAP, and seed cotton yields (grams/plot) for each soil type and irrigation regime from 2008 ? 2010. Rotylenchulus reniformis / 150 cm3 Plant height (cm) Soil Irrigation Planting 60 DAP 150 DAP 60 DAP 150 DAP Yield (g) z Clay Yes 865 b y 1379 bc 1978 bcd 29.28 abcde 47.31 abc 37.06 abc No 278 c 699 c 1011 d 27.92 bcde 45.32 bcd 29.77 bcd Silt Loam Yes 2233 a 2433 a 3404 a 31.25 ab 45.21 bcd 43.65 a No 950 bc 1661 b 2427 ab 24.86 e 45.19 bcd 22.3 d Loam Yes 657 bc 1058 bcd 2092 bc 30.10 abcd 47.27 abc 33.76 abc No 355 bc 908 bcd 1089 cd 25.33 e 42.39 cd 33.98 abc Very Fine Sandy Loam Yes 935 bc 1085 bcd 1414 bcd 30.35 ab 46.36 bcd 36.01 abc No 595 bc 653 c 1357 bcd 25.37 de 40.75 d 21.57 d Fine Sandy Loam Yes 1151 b 1321 bc 1628 bcd 32.94 a 49.78 ab 31.46 bcd No 479 bc 1020 bcd 1116 cd 27.64 bcde 47.74 abc 28.98 cd Sandy Loam Yes 579 bc 618 c 1567 bcd 31.21 ab 52.84 a 41.07 ab No 471 bc 545 d 1283 cd 25.88 cde 48.36 ab 28.95 cd P-value Soil 0.2973 0.0061 0.8425 0.7653 0.0586 0.8033 Irrigation 0.0051 0.0196 0.1679 0.0002 0.0260 0.0010 Soil*Irrigation 0.6035 0.8530 0.3757 0.8049 0.8502 0.1445 25 z Means in the same column followed by the same letter do not differ significantly (P < 0.05) according to differences in least squares means. 26 Clay Silt Loam Very Fine Sandy Loam Loam R. re nif ormis pe r 500 cm 3 soil Root: Shoot Ra tio Initial R. reniformis Inoculation Level per 500cm3 soil y = -4E-05x + 1.8453 R? = 0.589 y = 8.0915x + 6061.9 R? = 0.9567 y = 3.8252x + 21582 R? = 0.5239 y = -8E-05x + 1.4516 R? = 0.8922 y = -7E-05x + 1.3193 R? = 0.7432 y = 6.6529x + 16721 R? = 0.7817 y = 8E-06x + 1.0213 R? = 0.0273 y = 0.8119x + 3773.3 R? = 0.4329 27 Figure 1. Mean R. reniformis populations per 500cm3 of soil, , and plant shoot weight: root weight ratios, , at 60 days after planting for each initial population of R. reniformis within each of the six soil types. Fine Sandy Loam Sandy Loam R. re nif ormis pe r 500 cm 3 soil Root: Shoot R ati o Initial R. reniformis Inoculation Level per 500cm3 soil y = -3E-05x + 1.4778 R? = 0.3396 y = 6.3727x + 1861.3 R? = 0.9862 y = 3.3523x + 6876.7 R? = 0.8692 y = -4E-05x + 1.1769 R? = 0.8513 28 Figure 2. Average shoot fresh weight (SFW) and root fresh weight (RFW) (g) at each initial inoculation level of R. reniformis at 60 DAP. R. reniformis Initial Population/500cm3 Gr ams 29 Figure 3. Influence of soil particle size on end of the year cotton harvest population densities of Rotylenchulus reniformis/150cm3 of soil in six different soil types over a three-year period. The relationship between population density of R. reniformis (Y) and median soil particle size of a soil (X) was described by the quadratic model Y = 39,571 ? 41,363x ? 69,707x2 (R2 = 0.61, P = 0.0001). Median soil particle size (MSPS) of a soil was calculated as: MSPS = ? [Percent particles of a category (coarse sand, medium sand, fine sand, very fine sand, coarse silt, fine silt, or clay) X median size of that category (1.25mm, 0.75mm, 0.175mm, 0.075mm, 0.035mm, 0.011mm, or 0.001mm)] /100. mm Roty lenc hulus reniformis 30 Chapter 3 The Effect of Soil Water Availability on the Interaction of Rotylenchulus reniformis and Cotton in Multiple Soil Types Abstract A trial to determine the effect of water availability on the interaction of Rotylenchulus reniformis and early season cotton growth was conducted in 2011. The trial was a 6x3x2 factorial design with six different soils (clay, silt loam, loam, very fine sandy loam, fine sandy loam, sandy loam), three different soil moisture potentials (-0.33 bar, - 1.00 bar, - 3.00 bar), and R. reniformis present or absent. At 30 days after planting (DAP), each plot was evaluated for R. reniformis density per gram of root and plant growth parameters. Water availability affected both R. reniformis populations and plant growth; however, the effects were different dependent on soil type. The density of R. reniformis per gram of root was significantly higher (P < 0.05) at ? 3 bar in the fine sandy loam soil compared to ? 0.33 bar. Conversely, R. reniformis density per gram of root in the sandy loam soil was significantly lower at ? 3 bar compared to the other soil moisture potentials. All other soils supported comparable R. reniformis populations at each of the three moisture potentials. Plant growth exhibited a general increase with increasing water availability, and plants free of R. reniformis were, on average, numerically taller and had higher weights compared to those with R. reniformis. Although there were no significant differences in plant growth between nematode present/absent plots, when compared to the nematode free control, all soils presented a general trend of decreasing plant growth with increasing moisture availability in the presence of R. reniformis. 31 Introduction The reniform nematode, Rotylenchulus reniformis, is the most damaging nematode pathogen of cotton in Alabama. Currently, site-specific strategies are being explored for the economic management of this pathogen. One of the many factors to consider when creating management zones is the potential of water stress. Moore et al. (2011c) reported that nematicides to control the reniform nematode resulted in a greater yield increase of cotton where the average seasonal volumetric water content of the soil was the lowest. The root-knot nematode (Meloidogyne incognita) can affect the maximum rate and cumulative amount of water flow within a cotton plant (Kirkpatrick et al., 1995) and the interaction of the root-knot nematode and water stress has been observed to negatively impact components of leaf water potential, leaf temperature, transpiration, and stomatal resistance of cotton (Kirkpatrick et al., 1991). Similarly, the interaction of root-knot nematodes and water stress was observed to negatively impact tobacco yields at both low and high water availability (Wheeler, et al., 1991). A study of the response of soybean in soybean cyst nematode (Heterodera glycines) infested soil at differing moisture potentials concluded that providing adequate moisture during the growing season may limit yield reductions caused by the soybean cyst nematode (Johnson, et al., 1994). The objective of this trial is to determine the effect of the reniform nematode on cotton crown at varying soil moisture potentials and how this effect may vary within a range of soil types. 32 Materials and Methods A trial to determine the effects of soil moisture availability and Rotylenchulus reniformis on cotton in six different soil types was conducted in 2011 at the Auburn University Plant Science Research Center, Auburn, AL. The trial was arranged in a completely randomized 6x3x2 factorial design (6 soils, 3 moisture potentials, with and without R. reniformis) with four replicates. The soil types used in the trials were Decatur silt loam (18-49-33 S-S-C, 1.0% OM, pH = 5.5), Hartsells fine sandy loam (66-21-13 S-S-C, 2.7% OM, pH = 5.4), Vaiden clay (9-53- 38 S-S-C, 3.8% OM, pH = 6.1), Lloyd loam (38-35-27 S-S-C, 2.0% OM, pH = 5.5), Dothan sandy loam (82-11-7 S-S-C 0.6% OM, pH = 5.9), and Ruston very fine sandy loam (64-21-15 S- S-C, 1.6% OM, pH = 5.8). Soils were collected from the plow layer (top 15 cm) of the soil in cultivated fields free of plant parasitic nematodes. Soils were analyzed for nutrient and pH levels and maintained according to standard recommendations set by the Alabama Cooperative Extension System. Three matric potentials, or plant available water, were determined for each soil type by creating a moisture release curve (Figure 4) and selecting the volumetric water content for each soil at matric potentials of -3.0, -1.0, and -0.33 MPa (Table 3), where -3.0 is the least amount of available water and -0.33 is nearing field capacity. Volumetric water content (VWC, m3/m3), or the fraction of total volume of soil that is occupied by the water contained in the soil, for each pot was monitored throughout the trial with EC-5 soil moisture sensors and logged with EM-50 dataloggers (Decagon Devices, Pullman, WA). Pots were maintained at the desired volumetric water content with a ? inch drip irrigation system controlled by a Rain Bird SST Series Automatic Sprinkler Timer (Rain Bird Corporation). One thousand cubic centimeter polystyrene pots were planted with DP161B2RF cotton and 10,000 vermiform life stages of R. reniformis were added to the designated pots in 5 mL of 33 water. Cotton plants were evaluated at 30 days after planting (DAP) for height, shoot fresh weight and root fresh weight. Populations of R. reniformis were appraised at 30 DAP by combined gravity screening/sucrose centrifugation and enumerated. Eggs were extracted by agitating the root system on an orbital shaker at 150 rpm for 4 minutes in a 0.6% sodium hypochlorite (NaOCl) solution and collected on a 25 ?m screen. Nutrient content of the leaves and petioles of the cotton plants was conducted at the Auburn University Soil Testing Center in Auburn, AL. Plant material was dry-ashed in a muffle furnace at 500?C for eight hours and digested using a 1N nitric acid and 1N hydrochloric acid solution. The resulting solution was subsequently filtered and analyzed for nutrient content by Inductively Coupled Plasma Emission Spectroscopy using a Varian Vista-MPX Radial Spectrometer. Data were analyzed using analysis of variance (ANOVA) within the GLIMMIX procedure of SAS, version 9.2 (SAS Institute, Cary, NC). Treatment means were determined from the PDIFF option with LSMEANS, were P < 0.05 was required to be significant. There was a significant effect of soil type and as such each soil type was analyzed separately. Treatment means (with or without nematodes) for plant parameters were compared directly within each matric potential for each soil type. Mean numbers of R. reniformis per gram of root were compared between matric potentials within each soil type. Results Differences in water availability at -3.0, -1.0, and -0.33 MPa in these six soil types had little overall impact on nematode populations produced in one generation within this trial. No significant differences in the numbers of R. reniformis per gram of root were observed in the clay, silt loam, loam or very fine sandy loam at any of the three matric potentials (Table 4). Density of R. reniformis per gram of root was significantly higher at the -3.0 MPa matric 34 potential compared to the -0.33 MPa matric potential in the fine sandy loam soil; however were significantly lower at -3.0 MPa matric compared to the other two matric potentials in the sandy loam soil. Plant parameters exhibited a noticeable difference between soils due to the effects of soil moisture and nematode presence. The difference in average plant height between nematode present/absent pots was affected very little by water availability in the clay, silt loam, loam and very fine sandy loam. At each of the three matric potentials, -3.0, -1.0, and -0.33 MPa, the nematode absent pots produced 18, 17 and 20% taller plants in the clay soil compared to the nematode present pots, 13, 15 and 17% taller in the silt loam, 25, 25, and 25% taller in the loam, and 6, 11, and 10% taller in the very fine sandy loam, respectively. Conversely, in the sandy loam soil, plants at the -3.0 MPa moisture potential were taller in the nematode present pots by 13%. As more water became available at the -1.0 and -0.33 MPa matric potentials, the nematode absent pots had increased plant heights by 12 and 14% in the fine sandy loam and 2 and 26% in the sandy loam. Differences in average shoot fresh weight were higher in the nematode absent pots at all matric potentials in the clay, silt loam, and loam soils by an average of nearly 27%. However, in the very fine sandy loam, the fine sandy loam, and the sandy loam soils, the nematode present pots had increased average shoot fresh weight at the -3.0 MPa matric potential by 7, 14 and 48%, respectively. As with the plant heights, as more water became available at the -1.0 and -0.33 MPa matric potentials, the nematode absent pots had increased shoot fresh weight compared with the nematode present pots. Concentration of nutrients in the cotton leaves and petioles showed no significant differences or trends in this trial (results not shown). 35 Discussion The presence of R. reniformis within this trial caused early season cotton growth to exhibit a slight decline in overall plant growth as water became more available. However, the differences observed between soils suggests that water available to the plant may not have as much of an effect on R. reniformis as volumetric water content of a soil. For example, VWC at -3.0 MPa for the silt loam was 0.33 m3/m3 while for the sandy loam was 0.04 m3/m3. Although the plant available water is the same, the amount of water within the soil pores or the continuity of the water particles within the soil is not necessarily equal. Further study on the season-long effects of soil moisture availability is needed to determine the how these differences will affect cotton yields. 36 Table 3. Volumetric water content for each soil at each of the three matric potentials. MPa Clay Silt Loam Loam Very Fine Sandy Loam Fine Sandy Loam Sandy Loam Volumetric Water Content (m3/m3) - 0.33 0.33 0.33 0.33 0.18 0.23 0.1 - 1.00 0.25 0.26 0.26 0.13 0.18 0.06 - 3.00 0.19 0.22 0.22 0.10 0.09 0.04 37 Table 4: Average cotton plant height, shoot fresh weight, root fresh weight, and numbers of R. reniformis per gram of cotton root for each soil at each matric potential. Soil MPa Nematodes Plant Height (cm) 95% Confidence Interval Shoot Fresh Weight (g) 95% Confidence Interval R. reniformis/ gram root 95% Confidence Interval Clay -3.00 Yes 9.8 ns* (7.8, 11.8) 3.2 ns (1.9, 5.1) 4257 a** (1174.0, 15438.2) No 12.0 (10.0, 14.0) 4.3 (2.4, 7.2) NA NA -1.00 Yes 13.3 (9.0, 17.7) 5.1 (3.0, 7.2) 3783 a (1043.1, 13718.5) No 16.1 (12.3, 19.8) 6.0 (3.9, 8.1) NA NA -0.33 Yes 14.5 (10.8, 18.2) 5.8 (2.8, 8.7) 7994 a (2204.4, 28986.9) No 18.2 (14.5, 21.9) 8.2 (5.2, 11.2) NA NA Silt Loam -3.00 Yes 15.1 (11.5, 18.5) 5.0 (2.3, 7.6) 21772 a (10624.3, 44613.9) No 17.3 (13.4, 21.2) 7.4 (4.5, 10.4) NA NA -1.00 Yes 17.6 (11.4, 23.8) 6.5 (1.4, 11.6) 18275 a (8918.7, 37447.8) No 20.6 (14.4, 26.8) 9.2 (4.1, 14.3) NA NA -0.33 Yes 17.7 (11.0, 24.4) 5.6 (1.9, 9.3) 15992 a (5852.4, 24575.4) No 21.4 (14.8, 28.1) 7.4 (3.7, 11.2) NA NA Loam -3.00 Yes 7.0 (6.0, 8.0) 1.1 (0.83, 1.33) 20906 a (10201.6, 42843.1) No 9.3 (7.9, 10.3) 1.4 (1.15, 1.65) NA NA -1.00 Yes 7.1 (4.4, 9.7) 1.2 (0.6, 1.7) 20821 a (10159.9, 42667.8) No 9.5 (8.4, 13.7) 1.7 (1.1, 2.2) NA NA -0.33 Yes 7.1 (5.0, 9.1) 1.2 (0.6, 1.8) 22071 a (10750.4, 45147.9) No 9.5 (6.5, 10.5) 1.8 (1.2, 2.4) NA NA Very Fine Sandy Loam -3.00 Yes 11.8 (8.4, 15.1) 4.2 (2.5, 5.9) 5619 a (3613.0, 7625.3) No 12.6 (9.2, 15.9) 4.0 (2.3, 5.7) NA NA -1.00 Yes 15.8 (12.6, 19.0) 5.7 (3.6, 7.8) 4268 a (2261.5, 6273.7) No 17.8 (14.6, 21.0) 5.6 (3.5, 7.7) NA NA -0.33 Yes 18.1 (14.9, 21.3) 7.2 (5.3, 9.0) 3941 a (1934.8, 5947.0) No 20.1 (16.9, 23.3) 8.7 (6.9, 10.6) NA NA Fine Sandy Loam -3.00 Yes 16.2 (10.9, 21.5) 9.1 (3.0, 15.2) 4755 a (2983.9, 7577.2) No 16.1 (10.8, 21.4) 8.0 (1.9, 14.1) NA NA -1.00 Yes 27.4 (20.6, 34.2) 19.8 (13.4, 25.9) 4113 ab (2581.2, 6554.4) No 31.3 (24.4, 38.1) 22.5 (16.2, 28.7) NA NA -0.33 Yes 26.8 (22.8, 30.8) 19.6 (14.6, 24.5) 2384 b (1495.9, 3798.6) No 31.1 (27.2, 35.1) 25.6 (20.6, 30.6) NA NA 38 Soil Matric Nematodes Plant Height (cm) 95% Confidence Interval Shoot Fresh Weight (g) 95% Confidence Interval R.reniformis/ gram root 95% Confidence Interval Sandy Loam -3.00 Yes 9.4 (5.9, 12.8) 3.1 (1.8, 4.4) 4371 b (2616.5, 7302.0) No 8.3 (4.8, 11.7) 2.1 (0.8, 3.4) NA NA -1.00 Yes 11.4 (6.7, 16.0) 3.6 (1.6, 5.7) 9939 a (5949.7, 16604.0) No 11.6 (6.9, 16.2) 3.7 (1.6, 5.7) NA NA -0.33 Yes 12.1 (8.3, 15.9) 4.4 (3.1, 5.7) 14256 a (8533.0, 23813.3) No 16.4 (12.6, 20.2) 6.5 (5.2, 7.8) NA NA *Means for plant parameters are compared directly within each matric potential within each soil type and means followed by the same letter do not differ significantly. ** Means for R. reniformis populations are compared between matric potentials within each soil type and means followed by the same letter do not differ significantly. 39 Figure 4. Soil moisture release curves for each soil type (silt loam, very fine sandy loam, fine sandy loam, loam, sandy loam, and clay). Matr ic Pot enti al ( MP a) Volumetric Water Content 40 Chapter 4 Evaluation of Nematicides for the Management of Rotylenchulus reniformis Across Management Zones Created Using Soil Edaphic Factors Abstract Site specific management of Rotylenchulus reniformis utilizing management zones delineated by soil attributes is an emerging practice in Southeastern cotton production. A trial to determine differential effects of soil attributes used for management zone delineation on nematicide efficacy was conducted from 2009 ? 2011 in a 26 hectare field in the coastal plain of Alabama. Zones were delineated using apparent soil electrical conductivity (EC) and elevation. The nematicides 1, 3-dichloropropene, aldicarb, and Avicta Complete Pak seed treatment exhibited increased yields in the zones where EC values and seasonal moisture were the lowest. The foliar nematicide Oxamyl exhibited reduced efficacy in the management zone where moisture was most limiting. The knowledge of how these nematicides perform across management zones will allow producers to make a more informed decision when choosing nematicides for site specific management of Rotylenchulus reniformis. 41 Introduction The reniform nematode, Rotylenchulus reniformis Linford & Oliveira, is a major pathogen affecting U. S. cotton. Currently, R. reniformis can be found in 11 of the 17 cotton producing states and is estimated to have caused a loss of nearly 2% annually in the past decade (Blasingame et al., 2002 ? 2012). The presence of R. reniformis has been confirmed in at least 30 of the 59 cotton producing counties in Alabama and is responsible for annual yield losses of nearly 7 percent resulting in an estimated $14 million economic loss. Current management strategies rely heavily on chemical nematicides. The most common examples include fumigants such as 1, 3-dichloropropene (Telone II?), granular such as aldicarb (Temik 15G?), seed treatments such as abamectin (Avicta Complete Pak?) or thiodicarb (Aeris Seed Applied System?) and foliar sprays such as oxamyl (Vydate C-LV?). Site-specific management of nematodes is an emerging practice that has been proven useful for a number of nematode species including the Columbia lance nematode (Hoplolaimus columbus), the root-knot nematode (Meloidogyne incognita), and the ring nematode (Criconemella spp.) (Khalilian et al., 2001, 2002, 2003; Monfort et al., 2007; Ortiz et al., 2007, 2008; Wolcott et al., 2004, 2005). Recent studies suggest that nematicide efficacy improves with decreasing electrical conductivity values (Overstreet et al. 2012). These techniques are developed based on soil characteristics such as apparent electrical conductivity and terrain attributes and are primarily for the usage of the fumigant nematicide 1, 3-dichloropropene. Site- specific management techniques for Rotylenchulus reniformis in cotton based on management zones delineated from soil attributes is currently a topic of interest throughout the cotton growing regions. The objective of this research was to determine the relative efficacy of nematicides, 42 alone and in combination, over three management zones delineated by apparent soil electrical conductivity, elevation, and initial nematode populations. Materials and Methods A trial to determine the efficacy of multiple rates of nematicides, alone and in combination, in management zones delineated by soil electrical conductivity and elevation was conducted in 2009-2011 in a 26 hectare field in Escambia County, Alabama (lat, long = 31.073475?, -87.538682?). Continuous apparent soil electrical conductivity and elevation data were collected using a Veris 3100 sensor (Veris Technologies, Inc, Salina, KS) connected to a real-time kinematic (RTK) Trimble GPS receiver mounted to the tractor. The data collected was analyzed using the Mahalanobis distance technique within Management Zone Analyst software (USDA-ARS) to determine the optimal number of management zones (Table 5). Three management zones were chosen and have the following attributes. Management zone 1: Highest sand content, lowest EC, elevation, and seasonal VWC, second highest average nematode population. This zone contains moderately productive soil with adequate moisture. Management zone 2: Highest clay content, EC, and average nematode population, second highest seasonal VWC, average elevation the same as management zone 3. Soils within this zone are considered highly productive agricultural soils. Management zone 3: Highest silt content and seasonal VWC. Second highest EC and average elevation the same as management zone 2. Lowest average nematode population. Soils within this zone considered very productive, but are prone to flooding. Nine nematicide treatments were selected for evaluation and compared to an untreated (no nematicide) control. All seeds received a base insecticide, thiomethoxam (Cruiser?), and fungicide, azoxystrobin + fludioxanil + mefenoxam (Dynasty CST?). Three rates of 1, 3- 43 dichloropropene (Telone II?), 42, 28, and 14 L/ha, were applied 30-cm deep to selected rows 14 days prior to planting during the strip-till operation. Two rates of aldicarb (Temik 15G?), 3.9 and 7.8 kg/ha, were applied at planting as an in-furrow granular. The seed treatment abamectin (Avicta Complete Pak?) was applied to the seed and planted alone and in combination with aldicarb at 3.9 kg/ha, aldicarb 3.9 kg/ha + oxamyl (Vydate C-LV?) 1.2 L/ha, and oxamyl 1.2 L/ha. Oxamyl was applied as a foliar spray at 45 days after planting (DAP) at a volume of 94 L/ha. All treatments were applied in 6-row strips (5.5 m) through each management zone. Five replicates, 15.25 m in length, were established within each zone for sampling. Nematode population densities were evaluated at planting, 30 and 60 DAP, and at harvest by taking 10, 2.5 x 15 cm soil cores from the center two rows of each plot. The soil cores were homogenized and a 150cm3 subsample was taken for analysis. Nematodes were extracted from the soil by combined gravity screening and sucrose (specific gravity 1.13) centrifugation and enumerated. Plant heights were evaluated at 60 DAP and harvest by measuring 3 random plants from each plot. At harvest, cotton plants were collected from 1 m of row for plant mapping. Total number of bolls produced per plant and respective fruiting positions of the bolls were recorded. Seed cotton was removed from each fruiting position, dried at 80?C for 48 hours, and weights were recorded. All plots were mechanically harvested at approximately 150 DAP. Data were statistically analyzed by SAS (SAS Institute, Inc) using generalized linear models. Means were compared by Dunnett?s Test, with the untreated with no nematicide control as the reference group with alpha = 0.10. 44 Results Populations of R. reniformis were similar within each management zone at planting for all nematicide plots with the exception of the 1, 3-dichloropropene applied in management zones 1 and 2 (Table 6). The 1, 3-dichloropropene pre-plant treatments (28 and 42 L/ha) significantly lowered the at plant populations of R. reniformis compared to the untreated control. At 30 DAP, R. reniformis populations remained 50% lower than the untreated control in the plots that received the high rate of 1, 3-dichloropropene (42 L/ha) in management zone 1. All other nematicide treatments within zone 1 supported similar nematode numbers. In management zone 2, six of the nine nematicide applications reduced R. reniformis populations at 30 DAP. The mid and high rates (28 and 42 L/ha) of 1, 3-dichloropropene continued to suppress R. reniformis populations below the untreated control at 30 DAP. The at-plant applications of aldicarb at both rates (3.9 and 7.8 kg/ha) significantly lowered R. reniformis populations. The seed treatment Avicta Complete Pak with and without the low rate of aldicarb applied at plant also lowered the 30 DAP populations, however significantly so in only one out of two applications (pre-Oxamyl application). All nematicide treatments in management zone 3 reduced the first generation of R. reniformis populations. The plots that received the pre-plant treatments of 1, 3-dichloropropene at resulted in significantly lower R. reniformis population levels at 30 DAP. The Avicta Complete Pak seed treatment, as in management zone 2, produced significantly lower R. reniformis populations in 1 out of 2 applications (pre-Oxamyl application). Rotylenchulus reniformis populations taken at 60 DAP and at harvest found no significant reduction in nematode populations for any nematicide treatment in any zone. Average populations within each zone, as at planting, were highest in management zone 2, followed by management zone 1 and management zone 3. 45 Cotton plant heights were significantly increased by 1, 3-dichloropropene application in management zones 1 and 2 (Table 7). At 60 DAP, all rates of 1, 3-dichloropropene significantly increased plant heights compared to the untreated control in management zone 1, and the high rate (42 L/ha) significantly increased cotton plant height in management zone 2. At harvest, cotton plant heights for the mid and high rate of 1, 3-dichloropropene (28 and 42 L/ha) remained significantly taller than the untreated control, as did the high rate treatment (42 L/ha) in management zone 2. Cotton yield mapping data illustrates the plant yield potential as affected by nematicide. Boll weight and retention was significantly increased by the mid and high rates of 1, 3- dichloropropene as well as the high rate of aldicarb. A significant increase in 1st position boll weight was observed by the mid rate of 1, 3-dichloropropene (28 L/ha) in both management zones 2 and 3 (Table 8), while the number of 1st position bolls was similar. The weight of the first position bolls was increased but the retention of these bolls, or their numbers was not affected. The mid rate of 1, 3-dichloropropene (28 L/ha) produced significantly more 2nd position bolls in management zone 2 compared to the untreated control, though no significant increase in boll weight was observed. Thus the retention of the 2nd position bolls was increased by the nematicide application. The high rate of 1, 3-dichloropropene (42 L/ha) increased the number and weight of 3rd position bolls in management zone 1 compared to the untreated control; thus retention and boll weight were increased by nematicide. The mid rate of 1, 3- dichloropropene (28 L/ha) and the high rate of aldicarb (7.8 kg/ha) produced significantly heavier 3rd position bolls in comparison to the untreated control in management zone 3. The application of 1, 3-dichloropropene increased seed cotton yields at all rates in all three management zones (Table 9). The mid rate (28 L/ha) was the highest yielding treatment 46 across all management zones, and significantly greater than the untreated control in management zones 1 and 3. The low rate (14 L/ha) also produced higher seed cotton yields in management zone 3. The low rate of aldicarb (3.9 kg/ha), or the insecticide rate, did not increase seed cotton yields in comparison to the untreated control in management zones 1 and 2 which had the higher nematode numbers at planting; however, the high rate (7.8 kg/ha), or the nematicide rate, did increase yields in all management zones 1, 2, and 3 by 24, 2, and 6%, respectively. Avicta Complete Pak seed cotton yield was 17% greater in management zone 3 under minimal nematode pressure. The combination of Avicta Complete Pak and the low rate of aldicarb (3.9 kg/ha) at plant increased seed cotton yields by 18, 11, and 5%, respectively, in all management zones. The combination of Avicta Complete Pak and Oxamyl increased seed cotton yields by 12 and 8% in management zones 2 and 3, respectively. Average increase in seed cotton yields over the untreated control by all nematicides was 8.1, 7.0, and 7.1% in management zones 1, 2 and 3. Discussion The two factors utilized for zone delineation, apparent soil electrical conductivity and elevation, have proven extremely useful not only for nematode management (Khalilian et al., 2001, 2002, 2003; Monfort et al., 2007; Ortiz et al., 2007, 2008, Wolcott et al., 2004, 2005), but also for detecting areas with commonalities in soil productivity (Heermann et al., 1999; Jaynes, 1996; Kachanoski et al., 1988; McBride et al., 1990; Sudduth et al., 1995). Management zone 2 produced the highest average seed cotton yield despite having higher seasonal populations of R. reniformis. This observation is consistent with our previous findings (Moore et al., 2011) in which the effects of R. reniformis on cotton growth were related to soil productivity rather than population density. The nematicides applied within this trial did not exhibit any major differences in efficacy that could be attributed solely to the soil attributes utilized for 47 management zone delineation, specifically EC and elevation. However when taking into consideration the zones with near or above threshold nematode populations (1,000/150cm3), zones 1 and 2, the yield increases were numerically higher in the zone with a lower EC value, zone 1. This observation of increasing nematicides efficacy with decreasing EC values agrees with those reported by Overstreet et al., 2012. Differences in soil apparent electrical conductivity also can be used to predict spatial differences in soil water content (Kachanoski et al., 1988) which can influence the efficacy of certain nematicides (Koenning et al., 2007).The addition of oxamyl to the seed treatment Avicta Complete Pak increased yields in management zones 2 and 3, but provided no benefit in management zone 1, which had the lowest seasonal VWC. This observation is consistent with the finding of Koenning et al. (2007) in which oxamyl was reported to be less effective in dry conditions. Each of the other nematicides appeared to perform to their well documented standards. The 1, 3-dichloropropene treatments were able to effectively reduce nematode populations and increase yields as expected within each zone (Kinloch & Rich, 2001; Koenning et al., 2007; Lawrence et al., 1990; Rich and Kinloch, 2000). The high rate of aldicarb lowered nematode populations at 30 DAP and increased seed cotton yields within each zone, while the low rate provided a yield increase in management zone 3 under minimal nematode pressure. Similar nematode number reductions have been reported (Lawrence et al., 1990; Lawrence & McLean, 2000, Rich & Kinloch, 2000). The Avicta Complete Pak, much like the low rate of aldicarb, proved beneficial under lownematode populations in management zone 3 (Faske and Starr, 2006; Lawrence and Lawrence, 2007); however, when paired with a low rate of aldicarb, was able to reduce nematode numbers and increase seed cotton yields. 48 Management zone delineation by soil attributes provides cotton producers with valuable information that can be used to effectively manage Rotylenchulus reniformis. By creating management zones, the areas of the field with a potential for high productivity or specific in- season stress can be identified. When this knowledge is combined with nematode populations, management decisions can then be made to achieve maximized yields with minimal input. 49 Table 5. Attributes of each management zone. Management Zone Sand Silt Clay OM EC Elevation Average Seasonal VWC % % % % mS/m meters % 1 59 31 10 1.5 3.5 86.1 12.55 2 48 22 30 1.5 6.8 88.1 15.01 3 32 57 11 2.0 4.2 88.1 18.41 50 Table 6. Rotylenchulus reniformis populations per 150cm3 of soil at each of the 4 sampling dates (planting, 30 and 60 DAP, and harvest) for each nematicide treatment in each of the three management zones as compared to the untreated control. R. reniformis /150cm3 of soil at plant Treatment and Rate Management zone 1 Management zone 2 Management zone 3 Mean 90% CL Dunnett?s P z Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Untreated Control 734.8 (467.1, 1155.9) 1212.7 (770.5, 1908.7) 24.1 (9.0, 65.0) 1, 3-dichloropropene 42.0 L/ha 323.7 (205.8, 509.2) 0.0359 256.2 (162.8, 403.3) <0.0001 28.6 (10.6, 76.9) 0.8416 1, 3-dichloropropene 28.0 L/ha 385.1 (244.8, 605.8) 0.0972 525.6 (333.9, 827.3) 0.0326 26.1 (9.7, 70.2) 0.9268 1, 3-dichloropropene 14.0 L/ha 422.9 (268.9, 665.3) 0.1556 740.3 (470.4, 1165.3) 0.2049 20.8 (7.7, 56.1) 0.8626 Aldicarb 3.9 kg/ha 430.9 (273.9, 677.8) 0.1700 954.3 (606.3, 1502.1) 0.5373 22.0 (8.2, 59.2) 0.9128 Aldicarb 7.8 kg/ha 619.3 (393.7, 974.2) 0.6592 881.0 (559.8, 1386.7) 0.4109 22.1 (8.2, 59.6) 0.9191 Avicta Complete Pak 576.6 (366.6, 907.1) 0.5320 691.2 (439.1, 1087.9) 0.1490 20.8 (7.7, 56.1) 0.8626 Avicta Complete Pak + Aldicarb 3.9 kg/ha 453.5 (288.3, 713.4) 0.2144 1021.7 (649.1, 1608.1) 0.6589 19.9 (7.4, 53.6) 0.8204 Avicta Complete Pak + Oxamyl 1.26 L/ha 842.0 (535.3, 1324.5) 0.7252 856.5 (544.1, 1348.0) 0.3709 35.1 (13.0, 94.4) 0.6589 Avicta Complete Pak + Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 957.7 (599.2, 1530.6) 0.5022 643.8 (409.0, 1013.3) 0.1044 43.7 (16.2, 117.7) 0.4837 51 Table 6 (continued) R. reniformis /150cm3 of soil 30 DAP Treatment and Rate Management zone 1 Management zone 2 Management zone 3 Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Untreated Control 711.9 (449.8, 1126.8) 2923.4 (2277.4, 3753.0) 105.4 (91.2, 121.8) 1, 3-dichloropropene 42.0 L/ha 356.2 (225.1, 563.8) 0.0796 976.5 (760.7, 1253.6) <0.0001 77.1 (66.7, 89.1) 0.0124 1, 3-dichloropropene 28.0 L/ha 438.3 (276.9, 693.5) 0.2180 1382.7 (1077.2, 1775.1) 0.0006 80.7 (69.9, 93.3) 0.0325 1, 3-dichloropropene 14.0 L/ha 570.3 (360.4, 902.6) 0.5725 2100.6 (1636.3, 2696.5) 0.1235 77.1 (66.7, 89.1) 0.0124 Aldicarb 3.9 kg/ha 379.4 (239.7, 600.4) 0.1106 1797.2 (1400.1, 2307.2) 0.0241 88.6 (76.7, 102.4) 0.1626 Aldicarb 7.8 kg/ha 483.1 (305.3, 764.6) 0.3244 1557.3 (1213.2, 1999.2) 0.0037 92.8 (80.3, 107.2) 0.3052 Avicta Complete Pak 768.3 (485.5, 1216.0) 0.8461 2213.2 (1724.0, 2841.0) 0.1941 97.3 (84.2, 112.4) 0.5182 Avicta Complete Pak + Aldicarb 3.9 kg/ha 545.7 (344.8, 863.6) 0.4988 1749.5 (1362.8, 2245.8) 0.0174 95.3 (82.5, 110.1) 0.4152 Avicta Complete Pak + Oxamyl 1.26 L/ha 712.5 (450.2, 1127.7) 0.9983 1955.3 (1523.1, 2509.9) 0.0614 129.5 (112.0, 149.6) 0.0977 Avicta Complete Pak + Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 584.9 (363.7, 940.7) 0.6231 2246.9 (1750.2, 2884.2) 0.2192 95.4 (82.5, 110.2) 0.4192 R. reniformis /150cm3 of soil 60 DAP Treatment and Rate Management zone 1 Management zone 2 Management zone 3 Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Untreated Control 801.5 (449.1, 1430.5) 674.2 (399.6, 1137.7) 40.2 (15.3, 105.6) 1, 3-dichloropropene 42.0 L/ha 751.7 (421.2, 1341.7) 0.8971 486.7 (288.4, 821.2) 0.4669 56.8 (21.6, 149.2) 0.6755 1, 3-dichloropropene 28.0 L/ha 678.0 (379.9, 1210.2) 0.7358 607.1 (359.8, 1024.3) 0.8146 28.0 (10.7, 73.6) 0.6633 1, 3-dichloropropene 14.0 L/ha 854.7 (478.9, 1525.4) 0.8969 639.1 (378.8, 1078.5) 0.9048 29.9 (11.4, 78.7) 0.7224 Aldicarb 3.9 kg/ha 499.8 (280.1, 892.1) 0.3415 816.4 (483.8, 1377.5) 0.6693 33.3 (12.7, 87.6) 0.8211 Aldicarb 7.8 kg/ha 576.8 (316.7, 1050.6) 0.5145 785.6 (465.6, 1325.6) 0.7328 29.4 (11.2, 77.2) 0.7045 Avicta Complete Pak 769.2 (431.0, 1372.8) 0.9338 1054.7 (625.0, 1779.5) 0.3184 44.4 (16.9, 116.6) 0.9046 Avicta Complete Pak + Aldicarb 3.9 kg/ha 549.9 (308.1, 981.4) 0.4476 644.7 (382.1, 1087.9) 0.9203 31.2 (11.9, 82.0) 0.7605 Avicta Complete Pak + Oxamyl 1.26 L/ha 636.3 (356.4, 1135.6) 0.6414 1089.9 (634.2, 1873.0) 0.2928 69.8 (26.5, 183.4) 0.5046 Avicta Complete Pak + Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 911.6 (500.5, 1660.4) 0.7986 797.3 (472.5, 1345.2) 0.7082 32.8 (12.5, 86.3) 0.8071 52 Table 6 (continued) R. reniformis /150cm3 of soil at harvest Treatment and Rate Management zone 1 Management zone 2 Management zone 3 Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Untreated Control 451.3 (253.2, 804.3) 1498.5 (828.3, 2710.8) 147.6 (98.0, 222.1) 1, 3-dichloropropene 42.0 L/ha 607.8 (341.0, 1083.1) 0.5465 993.3 (549.1, 1796.9) 0.4171 123.2 (81.9, 185.5) 0.6057 1, 3-dichloropropene 28.0 L/ha 704.4 (395.2, 1255.4) 0.3676 940.5 (519.9, 1701.4) 0.3583 88.6 (58.8, 133.3) 0.1459 1, 3-dichloropropene 14.0 L/ha 479.4 (269.0, 854.4) 0.9026 1401.5 (774.7, 2535.4) 0.8948 97.0 (64.5, 146.1) 0.2315 Aldicarb 3.9 kg/ha 899.5 (504.7, 1603.1) 0.1642 794.5 (439.2, 1437.3) 0.2117 134.5 (89.4, 202.5) 0.7912 Aldicarb 7.8 kg/ha 768.5 (431.2, 1369.6) 0.2819 1094.9 (605.2, 1980.7) 0.5355 110.4 (73.3, 166.1) 0.4061 Avicta Complete Pak 583.1 (327.2, 1039.3) 0.6035 943.1 (521.3, 1706.2) 0.3612 127.4 (84.6, 191.8) 0.6742 Avicta Complete Pak + Aldicarb 3.9 kg/ha 688.0 (386.0, 1226.1) 0.3934 468.2 (424.7, 1389.8) 0.1287 130.7 (86.9, 196.8) 0.7288 Avicta Complete Pak + Oxamyl 1.26 L/ha 652.9 (366.3, 1163.6) 0.4546 775.0 (428.4, 1401.9) 0.1945 235.3 (156.3, 354.2) 0.1836 Avicta Complete Pak + Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 417.6 (227.1, 767.9) 0.8782 621.4 (343.5, 1124.2) 0.1844 172.9 (114.9, 260.3) 0.6501 Z Probability of being significantly different (P<0.10) than the control (untreated control). 53 Table 7. Cotton plant heights (cm) at 60 DAP and harvest for each nematicide treatment in each of the three management zones. Plant height (cm) 60 DAP Treatment and Rate Management zone 1 Management zone 2 Management zone 3 Mean 90% CL Dunnett?s P z Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Untreated Control 56.1 (45.9, 66.3) 58.4 (47.7, 69.0) 84.7 (69.3, 100.1) 1, 3-dichloropropene 42.0 L/ha 82.1 (71.9, 92.4) 0.0034 77.9 (67.2, 88.6) 0.0341 94.0 (78.6, 109.4) 0.4821 1, 3-dichloropropene 28.0 L/ha 76.6 (66.4, 86.8) 0.0200 72.4 (61.7, 53.1) 0.1253 88.7 (73.3, 104.1) 0.7618 1, 3-dichloropropene 14.0 L/ha 72.5 (62.3, 82.8) 0.0614 70.9 (60.2, 81.5) 0.1731 86.0 (70.6, 101.5) 0.9189 Aldicarb 3.9 kg/ha 60.8 (50.5, 71.0) 0.5931 63.4 (52.7, 74.1) 0.5807 88.0 (72.6, 103.4) 0.8018 Aldicarb 7.8 kg/ha 63.0 (52.8, 73.2) 0.4295 67.7 (57.0, 78.4) 0.3092 83.3 (67.9, 98.7) 0.9151 Avicta Complete Pak 56.5 (46.3, 66.7) 0.9619 63.6 (52.9, 74.3) 0.5661 84.4 (69.0, 99.9) 0.9845 Avicta Complete Pak + Aldicarb 3.9 kg/ha 62.2 (51.9, 72.4) 0.4868 69.8 (59.1, 80.5) 0.2119 85.6 (70.2, 101.0) 0.9495 Avicta Complete Pak + Oxamyl 1.26 L/ha 56.3 (46.1, 66.5) 0.9788 57.7 (47.0, 68.4) 0.9439 74.0 (58.5, 89.4) 0.4150 Avicta Complete Pak + Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 63.5 (53.3, 73.7) 0.3972 63.3 (52.6, 74.0) 0.5870 80.3 (64.9, 95.7) 0.7366 Plant height (cm) at harvest Treatment and Rate Management zone 1 Management zone 2 Management zone 3 Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Untreated Control 87.6 (75.9, 99.3) 93.8 (83.1, 104.5) 105.0 (95.0, 114.9) 1, 3-dichloropropene 42.0 L/ha 114.0 (102.4, 125.7) 0.0093 109.5 (98.8, 120.2) 0.0872 112.8 (102.9, 122.7) 0.3569 1, 3-dichloropropene 28.0 L/ha 109.1 (97.4, 120.8) 0.0331 108.1 (97.4, 118.8) 0.1184 110.4 (100.4, 120.3) 0.5251 1, 3-dichloropropene 14.0 L/ha 101.9 (90.3, 113.6) 0.1522 105.2 (94.5, 115.9) 0.2104 110.3 (100.4, 120.3) 0.5287 Aldicarb 3.9 kg/ha 91.1 (79.5, 102.8) 0.7210 99.3 (88.6, 110.0) 0.5455 110.8 (100.9, 120.8) 0.4903 Aldicarb 7.8 kg/ha 97.3 (85.6, 109.0) 0.3298 106.1 (95.4, 116.8) 0.1779 109.1 (99.1, 119.0) 0.6298 Avicta Complete Pak 90.7 (79.1, 102.4) 0.7527 103.1 (92.4, 113.8) 0.3057 110.1 (100.2, 120.1) 0.5420 Avicta Complete Pak + Aldicarb 3.9 kg/ha 103.7 (92.0, 115.3) 0.1088 101.6 (90.9, 112.3) 0.3917 108.8 (98.9, 118.8) 0.6481 Avicta Complete Pak + Oxamyl 1.26 L/ha 96.5 (84.8, 108.2) 0.3723 96.2 (85.5, 106.9) 0.7912 105.8 (95.9, 115.8) 0.9198 Avicta Complete Pak + Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 101.0 (89.4, 112.7) 0.1788 99.5 (88.8, 110.2) 0.5316 105.6 (95.6, 115.5) 0.9448 Z Probability of being significantly different (P<0.10) than the control (untreated control). 54 Table 8. Cotton yield mapping parameters (number of bolls, weight, and corresponding position on the plant) for each nematicide treatment in each of the three management zones. 1st Position Bolls Treatment and Rate Management zone 1 Management zone 2 Management zone 3 Mean 90% CL Dunnett?sP z Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Untreated Control 10.3 (8.4, 12.3) 10.6 (8.6, 12.5) 9.8 (8.6, 11.0) 1, 3-dichloropropene 42.0 L/ha 10.4 (8.5, 12.4) 0.9467 12.0 (10.1, 14.0) 0.3844 8.8 (7.7, 10.0) 0.3159 1, 3-dichloropropene 28.0 L/ha 12.1 (10.1, 14.1) 0.2911 12.8 (10.8, 14.7) 0.1893 12.0 (10.8, 13.2) 0.0368 1, 3-dichloropropene 14.0 L/ha 10.7 (8.7, 12.7) 0.8254 11.5 (9.5, 13.4) 0.5919 10.2 (9.0, 11.4) 0.7205 Aldicarb 3.9 kg/ha 8.8 (6.8, 10.7) 0.3553 11.2 (9.2, 13.1) 0.7207 9.9 (8.7, 11.1) 0.9151 Aldicarb 7.8 kg/ha 11.2 (9.3, 13.2) 0.5967 11.1 (9.1, 13.0) 0.7709 9.8 (8.6, 11.0) 1.0000 Avicta Complete Pak 10.3 (8.3, 12.3) 0.9829 9.8 (7.9, 11.8) 0.6394 9.8 (8.6, 11.0) 1.0000 Avicta Complete Pak + Aldicarb 3.9 kg/ha 11 (9.1, 13.0) 0.6747 11.5 (9.6, 13.5) 0.5762 9.4 (8.2, 10.6) 0.6923 Avicta Complete Pak + Oxamyl 1.26 L/ha 10.7 (8.8, 12.7) 0.8082 12.0 (10.1, 14.0) 0.3844 10.9 (9.6, 12.1) 0.3169 Avicta Complete Pak + Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 9.8 (7.8, 11.7) 0.7412 9.1 (7.2, 11.1) 0.3848 10.0 (8.8, 11.2) 0.8295 Weight of 1st Position Bolls (g) Treatment and Rate Management zone 1 Management zone 2 Management zone 3 Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Untreated Control 120.9 (93.1, 148.7) 116.5 (88.5, 144.5) 120.2 (102.0, 138.5) 1, 3-dichloropropene 42.0 L/ha 123.1 (95.3, 150.9) 0.9252 143.4 (115.5, 171.4) 0.2605 121.0 (102.7, 139.2) 0.9637 1, 3-dichloropropene 28.0 L/ha 151.1 (123.4, 178.9) 0.2038 159.3 (131.3, 187.3) 0.0756 148.0 (129.8, 166.3) 0.0766 1, 3-dichloropropene 14.0 L/ha 128.0 (100.2, 155.8) 0.7645 139.4 (111.4, 167.4) 0.3387 134.5 (116.3, 152.7) 0.3609 Aldicarb 3.9 kg/ha 110.8 (83.0, 138.5) 0.6686 136.7 (108.7, 164.7) 0.3986 120.9 (102.7, 139.2) 0.9642 Aldicarb 7.8 kg/ha 137.7 (109.9, 165.5) 0.4781 132.7 (104.7, 160.6) 0.4990 124.6 (106.4, 142.9) 0.7771 Avicta Complete Pak 114.2 (86.4, 142.0) 0.7768 120.9 (92.9, 148.9) 0.8539 129.8 (111.6, 148.1) 0.5371 Avicta Complete Pak + Aldicarb 3.9 kg/ha 144.8 (117.0, 172.6) 0.3143 139.4 (111.5, 167.4) 0.3377 124.4 (106.2, 142.7) 0.7874 Avicta Complete Pak + Oxamyl 1.26 L/ha 122.4 (94.6, 150.2) 0.9494 148.3 (120.3, 176.3) 0.1850 137.9 (119.6, 156.1) 0.2588 Avicta Complete Pak + Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 114.6 (86.8, 142.4) 0.7897 122.4 (84.4, 150.3) 0.8062 129.7 (111.4, 147.9) 0.5449 55 Table 8 (continued) 2nd Position Bolls Treatment and Rate Management zone 1 Management zone 2 Management zone 3 Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Untreated Control 3.7 (2.4, 5.0) 5.1 (3.5, 6.7) 4.7 (3.8, 5.5) 1, 3-dichloropropene 42.0 L/ha 5.4 (4.1, 6.7) 0.1281 5.6 (4.1, 7.2) 0.7002 4.8 (4.0, 5.6) 0.8775 1, 3-dichloropropene 28.0 L/ha 5.7 (4.4, 7.0) 0.0697 5.4 (3.9, 7.0) 0.8038 4.6 (3.8, 5.4) 0.9153 1, 3-dichloropropene 14.0 L/ha 3.5 (2.2, 4.8) 0.8684 4.4 (2.8, 6.0) 0.6025 4.9 (4.1, 5.7) 0.7556 Aldicarb 3.9 kg/ha 3.4 (2.1, 4.8) 0.8155 4.2 (2.6, 5.7) 0.4766 4.8 (4.0, 5.6) 0.8775 Aldicarb 7.8 kg/ha 4.9 (3.6, 6.2) 0.2735 4.5 (2.9, 6.1) 0.6605 5.0 (4.1, 5.8) 0.6752 Avicta Complete Pak 3.5 (2.1, 4.8) 0.8163 4.4 (2.8, 6.0) 0.5841 4.9 (4.1, 5.8) 0.7150 Avicta Complete Pak + Aldicarb 3.9 kg/ha 4.1 (2.8, 5.4) 0.7147 4.6 (3.0, 6.2) 0.7008 4.7 (3.8, 5.5) 1.0000 Avicta Complete Pak + Oxamyl 1.26 L/ha 3.7 (2.4, 5.0) 0.9734 4.1 (2.5, 5.7) 0.4598 4.8 (4.0, 5.6) 0.8775 Avicta Complete Pak + Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 4.1 (2.8, 5.4) 0.7139 5.0 (3.5, 6.6) 0.9561 3.9 (3.1, 4.8) 0.2954 Weight of 2nd Position Bolls (g) Treatment and Rate Management zone 1 Management zone 2 Management zone 3 Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Untreated Control 45.6 (28.8, 62.4) 58.1 (39.0, 77.2) 53.8 (42.8, 64.7) 1, 3-dichloropropene 42.0 L/ha 58.6 (41.8, 75.4) 0.3663 62.9 (43.8, 82.0) 0.7687 62.6 (51.7, 73.5) 0.3441 1, 3-dichloropropene 28.0 L/ha 63.8 (47.0, 80.6) 0.2059 65.4 (46.3, 84.5) 0.6529 54.1 (43.1, 65.0) 0.9748 1, 3-dichloropropene 14.0 L/ha 39.2 (22.3, 56.0) 0.6520 45.0 (25.9, 64.1) 0.4237 62.2 (51.3, 73.1) 0.3660 Aldicarb 3.9 kg/ha 37.2 (20.4, 54.0) 0.5571 45.5 (26.4, 64.6) 0.4396 61.4 (50.5, 72.3) 0.4133 Aldicarb 7.8 kg/ha 61.0 (44.2, 77.8) 0.2842 46.2 (27.1, 65.3) 0.4677 61.9 (51.0, 72.8) 0.3827 Avicta Complete Pak 37.6 (20.8, 54.5) 0.5782 46.7 (27.6, 65.8) 0.4847 61.9 (51.0, 72.8) 0.3827 Avicta Complete Pak + Aldicarb 3.9 kg/ha 49.4 (32.6, 66.2) 0.7923 51.1 (31.9, 70.2) 0.6669 58.8 (47.9, 69.8) 0.5849 Avicta Complete Pak + Oxamyl 1.26 L/ha 37.8 (21.0, 54.6) 0.5854 46.1 (27.0, 65.2) 0.4638 56.3 (45.4, 67.3) 0.7818 Avicta Complete Pak + Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 39.8 (22.9, 56.6) 0.6829 54.5 (35.3, 73.6) 0.8242 45.1 (34.2, 56.1) 0.3555 56 Table 8 (continued) 3rd Position Bolls Treatment and Rate Management zone 1 Management zone 2 Management zone 3 Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Untreated Control 0.1 (0.04, 0.6) 0.2 (0.04, 0.8) 0.2 (0.04, 0.5) 1, 3-dichloropropene 42.0 L/ha 1.3 (0.3, 5.2) 0.0674 0.2 (0.04, 0.8) 1.0000 0.3 (0.1, 1.2) 0.4425 1, 3-dichloropropene 28.0 L/ha 0.3 (0.07, 1.2) 0.5494 0.3 (0.07, 1.3) 0.7478 0.8 (0.2, 2.8) 0.1262 1, 3-dichloropropene 14.0 L/ha 0.1 (0.04, 0.6) 1.0000 0.3 (0.07, 1.3) 0.7478 0.3 (0.1, 1.2) 0.5205 Aldicarb 3.9 kg/ha 0.1 (0.04, 0.6) 1.0000 0.3 (0.07, 1.3) 0.7478 0.3 (0.1, 1.2) 0.5516 Aldicarb 7.8 kg/ha 0.8 (0.2, 3.2) 0.1534 0.4 (0.09, 1.8) 0.5755 1.5 (0.4, 5.3) 0.0342 Avicta Complete Pak 0.1 (0.04, 0.6) 1.0000 0.9 (0.2, 3.8) 0.2445 0.2 (0.04, 0.5) 0.7885 Avicta Complete Pak + Aldicarb 3.9 kg/ha 0.4 (0.1, 1.6) 0.4039 0.5 (0.1, 2.3) 0.4396 0.6 (0.2, 2.1) 0.1983 Avicta Complete Pak + Oxamyl 1.26 L/ha 0.3 (0.07, 1.2) 0.6462 0.2 (0.04, 0.8) 1.0000 0.2 (0.04, 0.5) 0.8286 Avicta Complete Pak + Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 0.1 (0.04, 0.6) 1.0000 0.2 (0.04, 0.8) 1.0000 0.4 (0.1, 1.4) 0.3542 Z Probability of being significantly different (P<0.10) than the control (untreated control). Weight of 3rd Position Bolls (g) Treatment and Rate Management zone 1 Management zone 2 Management zone 3 Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Untreated Control 0.5 (0.06, 3.3) 0.7 (0.1, 5.4) 0.4 (0.1, 2.1) 1, 3-dichloropropene 42.0 L/ha 13.1 (1.8, 93.4) 0.0475 0.7 (0.1, 5.4) 1.0000 3.0 (0.5, 17.8) 0.1605 1, 3-dichloropropene 28.0 L/ha 1.3 (0.2, 9.3) 0.5303 1.5 (0.2, 11.9) 0.6499 5.1 (0.9, 30.1) 0.0815 1, 3-dichloropropene 14.0 L/ha 0.2 (0.02, 1.1) 0.5300 1.3 (0.2, 10.4) 0.7028 1.6 (0.3, 9.4) 0.3220 Aldicarb 3.9 kg/ha 0.4 (0.06, 3.1) 0.9699 1.3 (0.2, 10.4) 0.7028 1.2 (0.2, 7.2) 0.4140 Aldicarb 7.8 kg/ha 7.0 (1.0, 49.7) 0.1062 2.3 (0.3, 18.4) 0.4858 12.7 (2.1, 74.9) 0.0204 Avicta Complete Pak 0.3 (0.05, 2.4) 0.8641 5.1 (0.6, 41.3) 0.2516 1.4 (0.2, 8.4) 0.3603 Avicta Complete Pak + Aldicarb 3.9 kg/ha 2.3 (0.3, 16.3) 0.3377 3.0 (0.4, 24.6) 0.3900 4.2 (0.7, 25.0) 0.1050 Avicta Complete Pak + Oxamyl 1.26 L/ha 1.0 (0.2, 7.4) 0.6214 0.9 (0.1, 7.2) 0.8653 0.8 (0.1, 4.7) 0.5948 Avicta Complete Pak + Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 0.3 (0.04, 1.9) 0.7372 0.7 (0.1, 5.4) 1.0000 2.6 (0.4, 15.1) 0.1944 57 Table 9. Seed cotton yields (kg/ha) for each nematicide treatment in each of the three management zones. Seed Cotton Yields (kg/ha) Treatment and Rate Management zone 1 Management zone 2 Management zone 3 Mean 90% CL Dunnett?s P z Mean 90% CL Dunnett?s P Mean 90% CL Dunnett?s P Untreated Control 2118.2 (1611.8, 2624.6) 2333.1 (1799.7, 2866.6) 2247.3 (1925.0, 2529.6) 1, 3-dichloropropene 42.0 L/ha 2379.6 (1873.3, 2886.1) 0.5452 2673.8 (2140.4, 3207.3) 0.4546 2319.7 (2017.3, 2622.0) 0.2585 1, 3-dichloropropene 28.0 L/ha 2854.7 (2348.2, 3361.1) 0.0909 2933.0 (2399.5, 3466.4) 0.1896 2596.4 (2294.1, 2898.9) 0.0716 1, 3-dichloropropene 14.0 L/ha 2261.7 (1755.4, 2768.2) 0.9196 2437.8 (1904.3, 2971.2) 0.8181 2564.5 (2262.2, 2866.9) 0.0927 Aldicarb 3.9 kg/ha 1878.3 (1372.0, 2384.8) 0.5789 2300.2 (1766.8, 2833.6) 0.9422 2351.9 (2049.6, 2654.4) 0.3844 Aldicarb 7.8 kg/ha 2621.4 (2115.1, 3127.8) 0.2457 2380.1 (1846.6, 2913.4) 0.9179 2366.5 (2064.1, 2668.8) 0.1906 Avicta Complete Pak 2052.8 (1546.3, 2559.1) 0.7017 2258.9 (1725.5, 2792.4) 0.8704 2487.5 (2185.1, 2789.9) 0.1648 Avicta Complete Pak + Aldicarb 3.9 kg/ha 2508.1 (2001.7, 3014.6) 0.3676 2579.3 (2045.9, 3112.8) 0.5886 2341.6 (2039.3, 2644.0) 0.4066 Avicta Complete Pak + Oxamyl 1.26 L/ha 2084.0 (1577.7, 2590.4) 0.9369 2614.6 (2081.1, 3148.0) 0.5365 2398.9 (2096.6, 2701.2) 0.2936 Avicta Complete Pak + Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 1960.2 (1453.7, 2466.5) 0.7144 2393.3 (1759.8, 2826.8) 0.9302 2269.9 (1940.4, 2545.2) 0.6541 Z Probability of being significantly different (P<0.10) than the control (untreated control). 58 Chapter 5 Evaluation of Nematicides for the Management of Rotylenchulus reniformis in a Field with Homogeneous Soil Characteristics Abstract The reniform nematode, Rotylenchulus reniformis, is currently the most damage cotton pathogen in Alabama. A trial to determine the efficacy of nematicides currently under consideration for use in site-specific management systems was conducted in a field with homogeneous soil characteristics from 2009 ? 2011 to compare with observations from fields of highly variable soil characteristics. The nematicides aldicarb (2 rates), oxamyl, and the seed treatment Aeris? were evaluated alone and in combination against an untreated control for efficacy against R. reniformis. Although no significant increases were observed compared to the untreated control, all nematicides numerically increased seed cotton yield in at least one of three seasons with the exceptions of Aeris + oxamyl and aldicarb at the low rate. When compared to results of studies in variable soil types, these results suggest that variable rate nematicide programs in homogeneous soils is of much less importance for management of R. reniformis. 59 Introduction The reniform nematode, Rotylenchulus reniformis Linford & Oliveira, is a major pathogen affecting U. S. cotton. Currently, R. reniformis can be found in 11 of the 17 cotton producing states and is estimated to have caused an annual loss of nearly 2% (Blasingame et al., 2002 ? 2012). Much research is currently focusing on developing site-specific management strategies for R. reniformis by constructing prescription application maps based on variability in soil characteristics. Results of these efforts have shown that nematicide efficacy and yield benefit increase with decreasing electrical conductivity values and accompanying soil productivity and moisture holding capabilities (Moore et al., 2011; Overstreet et al., 2012). The objective of this trial was to determine the efficacy of commonly used nematicides, alone and in combination, and use the resulting data for comparison against similar trials in fields with highly variable soils. Materials and Methods A trial to determine the efficacy of multiple rates of nematicides, alone and in combination, in a field with homogeneous soil characteristics was conducted in 2009-2011 at the Tennessee Valley Research and Extension Center near Belle Mina, Alabama. The soil was a Decatur silt loam, (fine, kaolinitic, thermic, Rhodic Paleudults: 23% sand, 49% silt, 28% clay; 1% organic matter; pH 6.2). Homogeneity was confirmed by collecting continuous apparent soil electrical conductivity (EC) and elevation data using a Veris 3100 sensor (Veris Technologies, Inc, Salina, KS) connected to a real-time kinematic (RTK) Trimble GPS receiver mounted to the tractor. The data collected was analyzed using the Mahalanobis distance technique within Management Zone Analyst software (USDA-ARS) resulting in one zone with an average EC and elevation of 9.82 60 mS/m and 186.5 m, respectively. Rotylenchulus reniformis populations initially averaged 696 per 150 cm3 of soil across with a range of 425 to 850 across the 3.5 ha field in the spring of 2009. Nematicide treatments in 2009 included the Aeris Seed Applied System? (thiodicarb + imidacloprid) (ASAS), ASAS + aldicarb (Temik 15G?) 3.9 kg/ha, ASAS + aldicarb 5.6 kg/ha, and ASAS + aldicarb 5.6 kg/ha + oxamyl (Vydate C-LV?) 1.26 L/ha. Nematicide treatments were expanded in 2010 and 2011 to include an untreated control, ASAS + oxamyl 1.26 L/ha, aldicarb 3.9 kg/ha, aldicarb 5.6 kg/ha, aldicarb 3.9 kg/ha + oxamyl 1.26 L/ha, and aldicarb 5.6 kg/ha + oxamyl 1.26 L/ha. All seeds received a base fungicide treatment of triadimenol, thiram, and metalaxyl and the insecticide imidacloprid was added to treatments not including ASAS. Aldicarb was applied at planting as an in-furrow granular while oxamyl was applied as a foliar spray at 45 days after planting (45 DAP). Plots were 8 rows with the nematicides applied to the center 4 rows. In 2009 plots were 55 m long, while in 2010 and 2011 plots were 27.5 m long. Nematode population densities were evaluated at planting, 30 and 60 DAP, and at harvest by taking 10, 2.5 x 15 cm soil cores from the center two rows of each plot. The soil cores were homogenized and a 150cm3 subsample was taken for analysis. Nematodes were extracted from the soil by combined gravity screening and sucrose (specific gravity 1.13) centrifugation and enumerated. At harvest, cotton plants were collected from 1 m of row for plant mapping and height evaluation. Total number of bolls produced per plant and respective fruiting positions of the bolls were recorded. Seed cotton was removed from each fruiting position, dried at 80?C for 48 hours, and weights were recorded. All plots were mechanically harvested at approximately 150 DAP. Data were analyzed using analysis of variance (ANOVA) within the GLIMMIX procedure of SAS, version 9.2 (SAS Institute, Cary, NC). Means were compared by Dunnett?s 61 Test, with the ASAS treatment as the reference group in 2009, and the untreated control as the reference group in 2010 and 2011. Results In 2011, the addition of oxamyl to the ASAS significantly lowered R. reniformis populations at 60 DAP (Table 10). All other nematicide treatments were comparable to either the ASAS in 2009 or the untreated control in 2010 and 2011. Similarly, plant heights and yield mapping parameters at harvest were not significantly affected by nematicide treatment (Tables 11 & 12) with one exception. The combination of ASAS + aldicarb 5.6 kg/ha + oxamyl 1.26 L/ha significantly increased number and weight of first position bolls in 2011 compared to the untreated control (Table 11). Seed cotton yield, although not significantly affected by nematicide treatment, was numerically higher compared to the respective controls in at least one year for all treatments with the exceptions of ASAS + oxamyl 1.26 L/ha and aldicarb 3.9 kg/ha (Table 13). Discussion The results of this study show that in a field with little variability of soil characteristics, the choice of which nematicide to use is of much less importance than in a field with high soil variability. All nematicides within this trial were comparable and performed as previously observed (Koenning, et al., 2007; Lawrence et al., 1990; Lawrence & McLean, 2000; Lawrence & Lawrence, 2007; Rich & Kinloch, 2000). The populations of R. reniformis within this trial were very near current economic threshold levels for Alabama (1,000/150cm3). Differences in efficacy may have been more pronounced had the populations been higher, especially for the low rate of aldicarb or the seed treatment alone. When compared to studies of fields with high 62 variability, producers with fields of homogeneous soil characteristics can focus on R. reniformis levels alone rather than how that level will affect their cotton in a specific soil type. 63 Table 10. Rotylenchulus reniformis populations per 150cm3 of soil at each of the 3 sampling dates (planting, 30 and 60 DAP) for each nematicide treatment in 2009, 2010, & 2011. 2009 Treatment and Rate Plant 30 DAP 60 DAP Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Aeris Seed Applied System 425.9 (86.4, 1128.3) 656.9 (317.4, 1359.3) 1112.3 (559.8, 2209.9) Aeris Seed Applied System + Aldicarb 3.9 kg/ha 840.6 (293.6, 2064.5) 0.3211 1116.6 (539.6, 2310.5) 0.3812 1439.6 (724.5, 2860.1) 0.6491 Aeris Seed Applied System + Aldicarb 5.6 kg/ha 845.5 (241.2, 2095.9) 0.3551 1169.5 (565.2, 2419.9) 0.3421 2268.1 (1141.5, 4506.6) 0.2184 Aeris Seed Applied System + Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 668.8 (205.9, 1626.6) 0.6572 895.8 (432.9, 1853.6) 0.6057 2248.9 (1131.8, 4468.5) 0.2237 2010 Treatment and Rate Plant 30 DAP 60 DAP Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Untreated Control 1030.8 (457.6, 2322.3) 143.8 (59.6, 346.7) 634.8 (240.6, 1675.2) Aeris Seed Applied System 729.2 (360.9, 1473.4) 0.5882 215.0 (89.2, 518.5) 0.5874 689.2 (261.2, 1818.7) 0.9197 Aeris Seed Applied System + Aldicarb 3.9 kg/ha 964.5 (477.3, 1948.9) 0.9170 200.1 (83.0, 482.5) 0.6556 659.2 (249.8, 1739.8) 0.9630 Aeris Seed Applied System + Aldicarb 5.6 kg/ha 1066.2 (527.7, 2154.3) 0.9578 125.6 (52.1, 303.0) 0.8555 547.4 (207.4, 1444.3) 0.8557 Aeris Seed Applied System + Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 355.8 (176.1, 718.9) 0.1033 233.9 (97.0, 564.0) 0.5122 1299.1 (492.3, 3428.2) 0.3828 Aeris Seed Applied System + Oxamyl 1.26 L/ha 408.7 (202.3, 825.9) 0.1543 361.6 (149.9, 872.0) 0.2183 681.9 (258.4, 1799.6) 0.9300 Aldicarb 3.9 kg/ha 1692.9 (837.8, 3420.7) 0.4391 115.5 (47.9, 278.6) 0.7675 987.7 (374.3, 2606.6) 0.5886 Aldicarb 5.6 kg/ha 980.9 (485.5, 1982.1) 0.9380 140.7 (58.3, 339.3) 0.9765 1083.4 (410.6, 2858.9) 0.5136 Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 741.7 (367.1, 1498.8) 0.6067 101.7 (42.2, 245.2) 0.6400 984.7 (373.2, 2598.5) 0.5912 Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 514 (254.4, 1038.6) 0.2802 246.7 (102.3, 594.9) 0.4674 361.6 (137.0, 954.2) 0.4917 64 Table 10 (continued) 2011 Treatment and Rate Plant 30 DAP 60 DAP Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Untreated Control 1648.5 (838.4, 3241.2) 759.8 (289.3, 1995.8) 531.4 (320.5, 881.1) Aeris Seed Applied System 686.5 (349.1, 1349.8) 0.1304 615.6 (234.3, 1617.0) 0.7954 406.7 (345.3, 674.2) 0.5301 Aeris Seed Applied System + Aldicarb 3.9 kg/ha 1078.6 (548.6, 2120.7) 0.4573 1174.6 (447.2, 3085.3) 0.5922 463.5 (279.6, 768.5) 0.7477 Aeris Seed Applied System + Aldicarb 5.6 kg/ha 1427.1 (725.8, 2806.0) 0.7997 676.5 (257.5, 1776.9) 0.8861 582.8 (351.5, 966.3) 0.8281 Aeris Seed Applied System + Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 1321.6 (672.2, 2598.5) 0.6977 698.6 (266.0, 1835.0) 0.9175 283.0 (170.7, 469.1) 0.1451 Aeris Seed Applied System + Oxamyl 1.26 L/ha 1090.9 (554.9, 2145.0) 0.4694 2328.5 (886.5, 6116.2) 0.1742 143.8 (86.7, 238.4) 0.0042 Aldicarb 3.9 kg/ha 1344.4 (683.8, 2643.3) 0.7199 645.4 (245.7, 1695.3) 0.8406 664.9 (401.0, 1102.4) 0.5988 Aldicarb 5.6 kg/ha 751.6 (382.3, 1477.8) 0.1735 759.8 (289.3, 1995.8) 1.0000 556.9 (335.9, 923.2) 0.9125 Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 1452.9 (738.9, 1856.6) 0.8241 1937.4 (737.5, 5088.8) 0.2539 865.4 (522.0, 1434.8) 0.2563 Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 988.3 (502.7, 1943.4) 0.3711 1255.5 (478.0, 3297.8) 0.5373 304.1 (183.4, 504.1) 0.1950 65 Table 11: Cotton yield mapping data (number of bolls, weight, and corresponding position on the plant) for each nematicide treatment in 2009, 2010, & 2011. 2009 Treatment and Rate Total 1st Position Bolls Total 2nd Position Bolls Total 3rd Position Bolls Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Aeris Seed Applied System 14.0 (11.9, 16.1) 7.3 (5.8, 8.8) 2.7 (1.3, 4.1) Aeris Seed Applied System + Aldicarb 3.9 kg/ha 15.1 (12.9, 17.2) 0.5475 7.9 (6.4, 9.4) 0.6272 5.0 (3.6, 6.4) 0.0639 Aeris Seed Applied System + Aldicarb 5.6 kg/ha 15.6 (13.5, 17.7) 0.3704 7.8 (6.3, 9.3) 0.6657 3.9 (2.5, 5.3) 0.3344 Aeris Seed Applied System + Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 16.1 (14.0, 18.3) 0.2369 8.9 (7.4, 10.4) 0.2052 4.4 (3.0, 5.8) 0.1627 2009 Treatment and Rate Total Weight 1st Position Bolls (g) Total Weight 2nd Position Bolls (g) Total Weight 3rd Position Bolls (g) Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Aeris Seed Applied System 197.6 (169.4, 230.5) 89.0 (69.1, 114.6) 35.5 (13.6, 57.4) Aeris Seed Applied System + Aldicarb 3.9 kg/ha 216.1 (185.2, 252.1) 0.4829 107.9 (83.8, 138.9) 0.3624 62.0 (40.1, 83.9) 0.1538 Aeris Seed Applied System + Aldicarb 5.6 kg/ha 216.2 (185.3, 252.2) 0.4801 105.9 (82.3, 136.4) 0.4083 63.7 (41.8, 85.6) 0.1313 Aeris Seed Applied System + Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 215.5 (184.7, 251.4) 0.4960 108.0 (83.9, 139.1) 0.3587 57.8 (35.9, 79.7) 0.2265 66 Table 11 (continued) 2010 Treatment and Rate Total 1st Position Bolls Total 2nd Position Bolls Total 3rd Position Bolls Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Untreated Control 27.25 (23.21, 31.29) 11.75 (9.10, 14.40) 3.30 (1.70, 4.80) Aeris Seed Applied System 29.75 (25.71, 33.79) 0.4634 11.00 (8.35, 13.65) 0.7360 3.00 (1.50, 4.50) 0.8436 Aeris Seed Applied System + Aldicarb 3.9 kg/ha 24.25 (20.21, 28.29) 0.3797 10.00 (7.35, 12.65) 0.4337 1.00 (-0.05, 2.50) 0.0835 Aeris Seed Applied System + Aldicarb 5.6 kg/ha 30.00 (25.96, 34.04) 0.4203 11.50 (8.85, 14.15) 0.9106 2.00 (0.50, 3.50) 0.3277 Aeris Seed Applied System + Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 25.75 (21.71, 29.79) 0.6589 9.75 (7.10, 12.40) 0.3716 1.80 (0.20, 3.30) 0.2418 Aeris Seed Applied System + Oxamyl 1.26 L/ha 32.25 (28.21, 36.29) 0.1478 10.25 (7.60, 12.90) 0.5016 3.80 (2.20, 5.30) 0.6936 Aldicarb 3.9 kg/ha 27.75 (23.71, 31.79) 0.8829 11.25 (8.60, 13.90) 0.8222 4.00 (2.50, 5.50) 0.5550 Aldicarb 5.6 kg/ha 27.00 (22.96, 31.04) 0.9412 10.25 (7.60, 12.90) 0.5016 4.30 (2.70, 5.80) 0.4325 Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 28.00 (23.96, 32.04) 0.8252 11.50 (8.85, 14.15) 0.9106 2.30 (0.70, 3.80) 0.4323 Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 24.50 (20.46, 28.54) 0.4202 9.00 (6.35, 11.65) 0.2220 1.50 (-0.10, 3.00) 0.1739 67 Table 11 (continued) 2010 Treatment and Rate Total Weight 1st Position Bolls (g) Total Weight 2nd Position Bolls (g) Total Weight 3rd Position Bolls (g) Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Untreated Control 123.83 (105.86, 141.80) 48.90 (38.26, 59.53) 11.30 (5.40, 17.30) Aeris Seed Applied System 127.50 (109.53, 145.47) 0.8080 45.62 (34.98, 56.25) 0.7139 11.40 (5.50, 17.30) 0.9968 Aeris Seed Applied System + Aldicarb 3.9 kg/ha 111.96 (93.99, 129.93) 0.4340 43.14 (35.51, 53.78) 0.5212 4.80 (-1.10, 10.70) 0.1921 Aeris Seed Applied System + Aldicarb 5.6 kg/ha 135.88 (117.91, 153.84) 0.4274 46.85 (36.22, 57.78) 0.8193 6.00 (0.10, 11.90) 0.2828 Aeris Seed Applied System + Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 119.40 (101.43, 137.36) 0.7692 42.15 (31.51, 52.78) 0.4522 5.70 (-0.20, 11.60) 0.2579 Aeris Seed Applied System + Oxamyl 1.26 L/ha 136.82 (118.85, 154.78) 0.3925 49.04 (38.41, 59.68) 0.9871 12.90 (7.00, 18.80) 0.7551 Aldicarb 3.9 kg/ha 123.65 (105.68, 141.62) 0.9905 47.13 (36.49, 57.76) 0.8430 15.40 (9.50, 21.30) 0.4167 Aldicarb 5.6 kg/ha 118.25 (100.28, 136.21) 0.7118 43.96 (33.32, 54.59) 0.5815 16.40 (10.40, 22.30) 0.3175 Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 121.06 (103.09, 139.03) 0.8544 43.85 (33.21, 54.48) 0.5732 8.20 (2.30, 14.10) 0.5229 Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 96.53 78.56, 114.49) 0.0782 35.44 (24.80, 46.07) 0.1393 4.40 (-1.50, 10.30) 0.1676 68 Table 11 (continued) 2011 Treatment and Rate Total 1st Position Bolls Total 2nd Position Bolls Total 3rd Position Bolls Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Untreated Control 24.50 (22.27, 26.73) 7.50 (5.36, 9.64) 3.50 (2.10, 4.90) Aeris Seed Applied System 24.75 (22.52, 26.98) 0.8937 10.00 (7.86, 12.14) 0.1706 4.00 (2.60, 5.40) 0.6783 Aeris Seed Applied System + Aldicarb 3.9 kg/ha 26.50 (24.27, 28.73) 0.2896 8.25 (6.11, 10.39) 0.6766 1.50 (0.10, 2.90) 0.1042 Aeris Seed Applied System + Aldicarb 5.6 kg/ha 25.50 (23.27, 27.73) 0.5938 12.00 (9.86, 14.14) 0.0170 4.00 (2.60, 5.40) 0.6783 Aeris Seed Applied System + Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 28.00 (25.77, 30.23) 0.0689 9.00 (6.86, 11.14) 0.4064 3.00 (1.60, 4.40) 0.6784 Aeris Seed Applied System + Oxamyl 1.26 L/ha 22.00 (19.77, 24.23) 0.1879 8.25 (6.11, 10.39) 0.6766 2.00 (0.60, 3.40) 0.2186 Aldicarb 3.9 kg/ha 23.50 (21.27, 25.73) 0.5938 6.50 (4.36, 8.64) 0.5786 1.00 (-0.40, 2.40) 0.0448 Aldicarb 5.6 kg/ha 27.25 (25.02, 29.48) 0.1487 8.00 (5.86, 10.14) 0.7808 1.00 (-0.40, 2.40) 0.0448 Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 26.50 (24.27, 28.73) 0.2896 10.00 (7.86, 12.14) 0.1706 3.30 (1.80, 4.70) 0.8355 Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 27.00 (24.77, 29.23) 0.1879 9.75 (7.61, 11.89) 0.2161 1.30 (-0.20, 2.70) 0.0692 69 Table 11 (continued) 2011 Treatment and Rate Total Weight 1st Position Bolls (g) Total Weight 2nd Position Bolls (g) Total Weight 3rd Position Bolls (g) Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Untreated Control 100.50 (88.87, 112.13) 26.50 (16.84, 36.16) 8.00 (3.60, 12.40) Aeris Seed Applied System 109.25 (97.62, 120.88) 0.3738 39.00 (29.34, 48.66) 0.1308 11.30 (6.90, 15.60) 0.3794 Aeris Seed Applied System + Aldicarb 3.9 kg/ha 108.75 (97.12, 120.38) 0.4014 30.50 (20.84, 40.16) 0.6227 4.00 (-0.40, 8.40) 0.2809 Aeris Seed Applied System + Aldicarb 5.6 kg/ha 104.50 (92.87, 116.13) 0.6828 36.50 (26.84, 46.16) 0.2236 8.80 (4.40, 13.10) 0.8383 Aeris Seed Applied System + Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 123.25 (111.62, 134.88) 0.0257 36.50 (26.84, 46.16) 0.2236 8.30 (3.90, 12.60) 0.9457 Aeris Seed Applied System + Oxamyl 1.26 L/ha 95.50 (83.87, 107.13) 0.6098 24.50 (14.84, 34.16) 0.8054 4.30 (-0.10, 8.60) 0.3115 Aldicarb 3.9 kg/ha 100.75 (89.12, 112.38) 0.9796 23.25 (13.59, 32.91) 0.6891 3.80 (-0.60, 8.10) 0.2526 Aldicarb 5.6 kg/ha 115.00 (103.37, 126.63) 0.1451 33.50 (23.84, 43.16) 0.3913 2.30 (-2.10, 6.60) 0.1250 Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 105.25 (93.62, 116.88) 0.6277 35.00 (25.34, 44.66) 0.2992 6.50 (2.10, 10.90) 0.6834 Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 110.00 (98.37, 121.63) 0.3349 33.00 (25.34, 44.66) 0.4256 1.80 (-2.60, 6.10) 0.0965 70 Table 12. Cotton plant heights (cm) at harvest for each nematicide treatment in 2009, 2010, & 2011. Treatment and Rate 2009 2010 2011 Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Untreated Control 94.3 (84.6, 99.6) 95.8 (86.0, 105.6) Aeris Seed Applied System 111.6 (106.7, 116.6) 92.1 (82.5, 97.6) 0.7253 106.4 (96.6, 116.2) 0.2051 Aeris Seed Applied System + Aldicarb 3.9 kg/ha 116.7 (111.8, 121.7) 0.2187 90.1 (84.6, 99.6) 0.5045 101.3 (91.5, 111.1) 0.5060 Aeris Seed Applied System + Aldicarb 5.6 kg/ha 111.5 (106.5, 116.4) 0.9739 92.1 (86.0, 101.1) 0.7253 101.7 (91.9, 111.5) 0.4808 Aeris Seed Applied System + Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 114.4 (109.5, 119.4) 0.4950 93.6 (83.1, 98.1) 0.9067 102.1 (92.3, 111.9) 0.4503 Aeris Seed Applied System + Oxamyl 1.26 L/ha NA* NA NA 90.6 (86.8, 101.8) 0.5589 91.9 (82.1, 101.7) 0.6352 Aldicarb 3.9 kg/ha NA NA NA 90.0 (82.4, 97.5) 0.4940 98.7 (88.9, 108.5) 0.7312 Aldicarb 5.6 kg/ha NA NA NA 92.3 (84.8, 99.8) 0.7505 107.1 (97.3, 116.9) 0.1788 Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha NA NA NA 90.5 (83.0, 98.0) 0.5478 100.1 (90.7, 110.3) 0.5722 Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha NA NA NA 86.7 (79.2, 94.2) 0.2335 105.4 (95.6, 115.2) 0.2501 * Treatments were not applied in 2009. 71 Table 13: Seed cotton yields (kg/ha) for each nematicide treatment in 2009, 2010, & 2011. Treatment and Rate 2009 2010 2011 Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Mean 95% CL Dunnett?s P Untreated Control 2853.1 (2490.0, 3216.2) 2336.3 (1857.2, 2815.4) Aeris Seed Applied System 2510.4 (2306.1, 2714.8) 2959.8 (2959.8, 2596.7) 0.7268 2757.5 (2278.4, 3236.6) 0.2998 Aeris Seed Applied System + Aldicarb 3.9 kg/ha 2323.5 (2119.1, 2527.8) 0.2752 2921.4 (2558.3, 3284.5) 0.8231 2562.0 (2082.9, 3041.2) 0.5759 Aeris Seed Applied System + Aldicarb 5.6 kg/ha 2559.6 (2355.3, 2763.9) 0.7703 2922.1 (2559.0, 3285.2) 0.8213 2410.8 (1931.7, 2889.9) 0.8532 Aeris Seed Applied System + Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 2608.4 (2404.1, 2812.7) 0.5623 3181.7 (2818.6, 3544.8) 0.2861 2523.9 (2044.8, 3003.0) 0.6418 Aeris Seed Applied System + Oxamyl 1.26 L/ha 2775.1 (2412.0, 3138.2) 0.7983 2151.0 (1671.9, 2630.1) 0.6460 Aldicarb 3.9 kg/ha 2830.3 (2467.2, 3193.4) 0.9404 2013.9 (1534.8, 2493.0) 0.4257 Aldicarb 5.6 kg/ha 2743.9 (2380.8, 3107.0) 0.7206 2796.9 (2317.7, 3276.0) 0.2577 Aldicarb 3.9 kg/ha + Oxamyl 1.26 L/ha 2850.9 (2487.8, 3214.0) 0.9941 2553.0 (2073.9, 3032.1) 0.5912 Aldicarb 5.6 kg/ha + Oxamyl 1.26 L/ha 2869.5 (2506.4, 3232.6) 0.9572 2843.1 (2363.9, 3322.2) 0.2140 72 References Adams, J. F., C.C. Mitchell, and H.H. Bryant. 1994. Soil test fertilizer recommendations for Alabama crops. Ala. Agric. Exp. Sta. Dep. Ser. No. 178. Auburn University, AL. Agudelo, P., R. T. Robbins, and J. M. Stewart. 2001. Morphometric variation of reniform nematode geographic populations from cotton-growing regions in the United States. Arkansas Agricultural Experiment Station, Research Series 497:87-91. http://arkansasagnews.uark.edu/1292.htm Agudelo, P., R. T. Robbins, and J. M. Stewart, A. Szalanski. 2005. Intraspecific variability of Rotylenchulus reniformis from cotton-growing regions in the United States. Journal of Nematology 37:105-114. Arias, R. S., S. R. Stetina, J. L. Tonos, J. A. Scheffler, and B. E. Scheffler. 2009. Microsatellites reveal genetic diversity in Rotylenchulus reniformis populations. Journal of Nematology 411:46-156. Baird, R. E., J. R. Rich, R. G. McDaniel, and B. G. Mullinix. 2000. Effects of nematicides on Rotylenchulus reniformis in cotton. Nematologia Mediterranea 28:83-88. Bayer CropScience. 2010. Bayer CropScience plans to discontinue aldicarb by 2014. Bayer CropScience 2010-0423E. http://www.bayercropscience.com/bcsweb/cropprotection.nsf/id/EN_20100816/$file/201 0-0423e.pdf Blasingame, D., and M. V. Patel. 2002. Cotton disease loss estimate committee report. Proceedings of the Beltwide Cotton Conferences, 2002. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm 73 Blasingame, D., and M. V. Patel. 2003. Cotton disease loss estimate committee report. Proceedings of the Beltwide Cotton Conferences, 2003 Pp. 252-253. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Blasingame, D., and M. V. Patel. 2004. Cotton disease loss estimate committee report. Proceedings of the Beltwide Cotton Conferences, 2004 Pp. 459-450. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Blasingame, D., and M. V. Patel. 2005. Cotton disease loss estimate committee report. Proceedings of the Beltwide Cotton Conferences, 2005 Pp. 259-262. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Blasingame, D. 2006. Cotton disease loss estimate committee report. Proceedings of the Beltwide Cotton Conferences, 2006 Pp. 155-157. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Blasingame, D., J. C. Banks, P. D. Colyer, R. M. Davis, W. S. Gazaway, N. Goldburg, R. C. Kemerait, T. L. Kirkpatrick, S. R. Koenning, J. Muller, M. A. Newman, M. Olsen, P. M. Phipps, G. L. Sciumbato, R. Sprenkel, J. E. Woodward, A. Wrather, M. V. Patel. 2008. Cotton disease loss estimate committee report. Proceedings of the Beltwide Cotton Conferences, 2008 Pp. 294-297. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Blasingame, D., W. Gazaway, K. Lawrence, A. Wrather, M. Olsen, N. Goldberg, T. Kirkpatrick, S. Koenning, M. Davis, J. C. Banks, R. K. Sprenkel, J. Muller, R. Kemerait, M. Newman, P. Colyer, J. Woodward, G. Scuimbato, P. Phipps. 2009. Cotton disease loss estimate committee report. Proceedings of the Beltwide Cotton Conferences, 2009 Pp. 94-96. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm 74 Blasingame, D., M. V. Patel, K. Lawrence, W. Gazaway, M. Olsen, T. Kirkpatrick, S. Monfort, M. Davis, J. Marios, R. Kemerait, P. Colyer, G. Scuimbato, G. Lawrence, A. Wrather, N. Goldberg, S. Koenning, J. T. Pitts, J. Muller, M. Newman, J. Woodward, T. Wheeler, P. Phipps. 2010. Cotton disease loss estimate committee report. Proceedings of the Beltwide Cotton Conferences, 2010 Pp. 237-240. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Blasingame, D., and M. V. Patel. 2011. Cotton disease loss estimate committee report. Proceedings of the Beltwide Cotton Conferences, 2011 Pp. 306-308. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Blasingame, D., and M. V. Patel. 2012. Cotton disease loss estimate committee report. Proceedings of the Beltwide Cotton Conferences, 2012 Pp. 341-344. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Brown, R. B. 1990. Soil Texture. University of Florida IFAS Extension Publication #SL29. Cabanillas, H. E., J. M. Bradford, and J. R. Smart. 1999. Effect of tillage system, soil type, crop stand, and crop sequence on reniform nematodes after harvest. Nematropica 29:137-146. Carr, P. M., G. R. Carlson, J. S. Jacobsen, G. A. Nielsen, and E. O. Slogles. 1991. Farming soils, not fields: A strategy for increasing fertilizer profitability. Journal of Production Agriculture 4:57-61. Casa, R., and A. Castrignano. 2008. Analysis of spatial relationships between soil and crop variables in a durum wheat field using a multivariate geostatistical approach. European Journal of Agronomy 28:331-342. 75 Castillo, J. D., K. S. Lawrence, and E. van Santen. 2009. Efficacy of Arthrobotrys dactyloides, Dactylaria brochopaga, Fusarium oxysporium, and Paecilomyces lilacinus for biocontrol of reniform nematode (Rotylenchulus reniformis). Proceedings of the Beltwide Cotton Conferences, 2009 Pp. 144-150. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Castillo, J. D., K. S. Lawrence, and J. W. Kloepper. 2011. Evaluation of Bacillus firmus (Votivo?) and Paecilomyces lilacinus strain 251 (Nemout?) for the biocontrol of reniform nematode Rotylenchulus reniformis. Proceedings of the Beltwide Cotton Conferences, 2011 Pp. 242-246. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Davis, R. F., S. R. Koenning, R. C. Kemerait, T. D. Cummings, and W. D. Shurley. 2003. Rotylenchulus reniformis management in cotton with crop rotation. Journal of Nematology 35:58-64. Davis, R. F., and T. M. Webster. 2005. Relative status of selected weeds and crops for Meloidogyne incognita and Rotylenchulus reniformis. The Journal of Cotton Science 9:41-46. Doerge, T. 1999. Defining management zones for precision farming. Crop Insight. Vol. 8 No. 21. Pioneer Hybrids, Johnston, IA. Doshi, R. A., R. L. King, and G. W. Lawrence. 2010. Classification of Rotylenchulus reniformis numbers in cotton using remotely sensed hyperspectral data on self-organizing maps. Journal of Nematology 42:179-193. Ellis, G. R., G. W. Lawrence, S. Samson, W. A. Givens, and K. S. Lawrence. 2004. Variable rate nematicides applications on cotton for reniform nematode management. Journal of Nematology 36:316. 76 Ellis, G. R., G. W. Lawrence, S. A. Samson, and W. A. Givens. 2005. Variable rate applications of Telone II on cotton for reniform nematode management. 2005. Proceedings of the Beltwide Cotton Conferences, 2005 Pp. 195-196. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Environmental Protection Agency. 2002. Iterim re-registration eligibility decision (IRED) fenamiphos. EPA 738-R-02-004. http://www.epa.gov/REDs/fenamiphos_ired.pdf Evans, K., R. M. Webster, P. D. Halford, A. D. Barker, and M. D. Russell. 2002. Site-specific management of nematodes: Pitfalls and practicalities. Journal of Nematology 34:194- 199. Farias, P. R. S., X. Sanchez-Vila, J. C. Barbosa, S. R. Vieira, L. C. C. B. Ferraz, and J. Solis- Delfin. 2002. Using geostatistical analysis to evaluate the presence of Rotylenchulus reniformis in cotton crops in Brazil: Economic implications. Journal of Nematology 34:232-238. Faske, T. R., and J. L. Starr. 2006. Sensitivity of Meloidogyne incognita and Rotylenchulus reniformis to abamectin. Journal of Nematology 38:240-244. Faske, T. R., and J. L. Starr. 2007. Cotton root protection from plant-parasitic nematodes by abamectin-treated seed. Journal of Nematology 39:27-30. Ferris, H. 1978. Nematode economic thresholds: Derivation, requirements, and theoretical considerations. Journal of Nematology 10:341-350. Ferris, H. 1985. Density-dependant nematode seasonal multiplication rates and overwinter survivorship: a critical point model. Journal of Nematology 17:93-100. Fiez, T. E., B. C. Miller, and W. L. Pan. 1994. Assessment of spatially variable nitrogen fertilizer management in winter wheat. Journal of Production Agriculture 7:86-93. 77 Fleming, K. L., D. F. Heermann, and D. G. Westfall. 2004. Evaluating soil color with farmer input and apparent soil electrical conductivity for management zone delineation. Agronomy Journal 96:1581-1587. Fraisse, C. W., K. A. Sudduth, and N. R. Kitchen. 2001. Delineation of site-specific management zones by unsupervised classification of topographic attributes and soil electrical conductivity. Transactions of the American Society of Agricultural Engineers 44:155- 166. Fulton, J. P., J. N. Shaw, D. Sullivan, M. P. Dougherty, and C. Brodbeck. 2008. Use of remote sensed thermal imagery for in-season stress detection and site-specific management of cotton. Alabama Agricultural Experiment Station Research Report Series No. 32:26-27. http://www.ag.auburn.edu/aaes/communications/researchreports/07cottonrr.pdf Gazaway, W. S., and K. S. McLean, 2003. Plant pathology and nematology: A survey of plant- parasitic nematodes associated with cotton in Alabama. J. Cot. Sci. 7:1-7. Gee, G. W., Bauder, J. W. 1994. Particle size analysis. In Methods of Soil Analysis, Part 1. Physical and Mineralogical Methods. A. Klute, ed. SSSA Book Series: 5. SSSA, Madison, WI. Goovaerts, P. 1992. Factorial kriging analysis: a useful tool for exploring the structure of multivariate geostatistics. Geoderma 62:93-107. Goovaerts, P. 1998. Goestatistical tools for characterizing the spatial variability of microbiological and physic-chemical soil properties. Biology and Fertility of Soils 27:315-334. Heald, C. M., Robinson, A. F. 1990. Survey of current distribution of Rotylenchulus reniformis in the United States. J. Nem. 22:695-699. 1990. 78 Heermann, D. F., J. Hoeting, H. R. Duke, D. G. Westfall, G. W. Buckleiter, P. Westra, F. B. Peairs, and K. L. Fleming. 1999. Interdisciplinary irrigated precision farming team research. Pp. 212-230. in J. V. Stafford (ed.) Precision Agriculture ?99. Vol. 1. Soil and crop factors: Location, sensing, and sampling. Oxford, UK. Herring, S. L., S. R. Koenning, and J. L. Heitman. 2010. Impact of Rotylenchulus reniformis on cotton yield as affected by soil texture and irrigation. Journal of Nematology 42:319- 323. Jaynes, D. B., J. M. Novak, T. B. Moorman, and C. M. Cambardella. 1994. Estimating herbicide partition coefficients from electromagnetic induction measurements. Journal of Environmental Quality 24:26-41. Jaynes, D. B. 1996. Improved soil mapping using electromagnetic induction surveys. Pp. 169- 179. Proceedings of the 3rd International Conference on Site-Specific Management for Agricultural Systems. ASA, CSSA, and SSSA, Madison, WI. Johnson, A. B., H. D. Scott, and R. D. Riggs. 1994. Response of soybean in cyst nematode- infested soils at three soil-water regimes. Journal of Nematology 26:329-335. Jones, J. R., K. S. Lawrence, and G. W. Lawrence. 2006. Evaluation of winter cover crops in cotton cropping for management of Rotylenchulus reniformis. Nematropica 36:53-66. Kachanoski, R. G., E. G. Gregorich, and I. J. Van Wesenbeck. 1988. Estimating spatial variations of soil water content using noncontacting electromagnetic inductive methods. Canadian Journal of Soil Science 68:715-722. Khalilian, A., J. D. Mueller, Y. J. Han, and F. J. Wolak. 2001. Predicting cotton nematodes distribution utilizing soil electrical conductivity. Proceedings of the Beltwide Cotton Conferences, 2001 Pp. 146-148. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm 79 Khalilian, A., J. Mueller, S. Lewis, and Y. Han. 2002. Relationship of Columbia lance and root- knot nematodes to soil type. Proceedings of the Beltwide Cotton Conferences, 2002. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Khalilian, A., J. D. Mueller, and Y. J. Han. 2003. Performance of variable rate nematicides application systems. Proceedings of the Beltwide Cotton Conferences, 2003 Pp. 578-582. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Kinloch, R. A., and J. R. Rich. 2001. Management of root-knot and reniform nematodes in ultra- narrow row cotton with 1,3-dichloropropene. Journal of Nematology 33:311-313. Kirkpatrick, T. L., D. M. Oosterhuis, and S. D. Wullschleger. 1991. Interaction of Meloidogyne incognita and water stress on two cotton cultivars. Journal of Nematology 23:462-467. Kirkpatrick, T. L., M. W. van Iersel, and D. M. Oosterhuis. 1995. Influence of Meloidogyne incognita on the water relations of cotton grown in microplots. Journal of Nematology 27:465-471. Kitchen, N. R., K. A. Sudduth, and S. T. Drummond. 1999. Soil electrical conductivity as a crop productivity measure for clay pan soils. Journal of Production Agriculture 12:607-617. Koenning, S. R., S. A. Walters, and K. R. Barker. 1996. Impact of soil texture on the reproductive and damage potentials of Rotylenchulus reniformis and Meloidogyne incognita on cotton. Journal of Nematology 28:527-536. Koenning, S. R., D. E. Morrison, and K. L. Edmisten. 2007. Relative efficacy of selected nematicides for management of Rotylenchulus reniformis in cotton. Nematropica 37:227- 235. 80 Kyaw, T., R. B. Ferguson, V. I. Adamchuk, D. B. Marx, D. D. Tarkalson, and D. L. McCallister. 2008. Delineating site-specific management zones for pH-induced iron chlorosis. Precision Agriculture 9:71-84. Lawrence, G. W., K. S. McLean, W. E. Batson, D. Miller, and J. C. Borbon. 1990. Response of Rotylenchulus reniformis to nematicides applications on cotton. Journal of Nematology 22:707-711. Lawrence, G. W., and K. S. McLean. 2000. Effect of foliar applications of oxamyl with aldicarb for the management of Rotylenchulus reniformis on cotton. Journal of Nematology 32:542-549. Lawrence, G. W., K. S. McLean, W. A. Givens, R. K. Mehrle, H. K. Lee, and A. T. Kelley. 2002. Reniform nematode management on cotton with VRT and site specific applications. Proceedings of the Beltwide Cotton Conferences, 2002. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Lawrence, K. S., Y. Feng, G. W. Lawrence, C. H. Burmester, and S. H. Norwood. 2005. Accelerated degradation of aldicarb and its metabolites in cotton field soils. Journal of Nematology 37:190?197. Lawrence, K. S., and G. W. Lawrence. 2007. Performance of the new nematicides seed treatments on cotton. Proceedings of the Beltwide Cotton Conferences, 2007 Pp. 602- 605. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Lawrence, K. S., A. J. Price, G. W. Lawrence, J. R. Jones, and J. R. Akridge. 2008. Weed hosts for Rotylenchulus reniformis in cotton fields rotated with corn in the southeast United States. Nematropica 38:13-22. 81 Leach, M., P. Agudelo, and P. Gerard. 2009. Effect of temperature on the embryogenesis of geographic populations of Rotylenchulus reniformis. Journal of Nematology 41:23-27. Lee, H. K., G. W. Lawrence, A. T. Kelley, and K. S. McLean. 2002. Horizontal and vertical distribution of Rotylenchulus reniformis in a Mississippi cotton field. Proceedings of the Beltwide Cotton Conferences, 2002. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Lewis, S. A., Smith, F. H. 1976. Host plant distribution and ecological associations of Hoplolaimus columbus. Journal of Nematology 8:264?270. Liu, T., K. Juang, and D. Lee. 2006. Interpolating soil properties using kriging combined with categorical information of soil maps. Soil Science Society of America Journal 70:1200- 1209. Lopez-Lozano, R., M. A. Casterad, and J. Herrero. 2010. Site-specific management units in a commercial maize plot delineated using very high resolution remote sensing and soil properties mapping. Computers and Electronics in Agriculture 73:219-229. Massey, R. E., D. B Myers, N. R. Kitchen, and K. A. Sudduth. 2008. Profitability maps as an input for site-specific management decision making. Agronomy Journal 100:52-59. McBride, R. A., A. M. Gordon, and S. C. Shrive. 1990. Estimating forest soil quality from terrain measurements of apparent electrical conductivity. Soil Science Society of America Journal 54:290-293. McCutcheon, M. C., H. J. Farahani, J. D. Stednick, G. W. Buchleiter, and T. R. Green. 2006. Effect of soil water on apparent soil electrical conductivity and texture relationships in a dryland field. Biosystems Engineering 94:19-32. 82 McGawley, E. C., M. J. Pontif, and C. Overstreet. 2010. Variation in reproduction and pathogenicity of geographic isolates of Rotylenchulus reniformis on cotton. Nematropica 40:275-288. Monfort, W. S., T. L. Kirkpatrick, C. S. Rothrock, and A. Mauromoustakos. 2007. Potential for site-specific management of Meloidogyne incognita in cotton using soil textural zones. Journal of Nematology 39(1):1-8. Monfort, W. S., T. L. Kirkpatrick, and A. Mauromoustakos. 2008. Spread of Rotylenchulus reniformis in an Arkansas cotton field over a four-year period. Journal of Nematology 40:162-166. Moore, S. R., K. S. Lawrence, F. J. Arriaga, C. H. Burmester, and E. van Santen. 2010a. Natural migration of R. reniformis in a no-till cotton system. Journal of Nematology 42:307-312. Moore, S. R., K. S. Lawrence, B. V. Ortiz, J. N. Shaw, and J. Fulton. 2010b. Evaluation of nematicides for the management of Rotylenchulus reniformis across management zones created using soil electrical conductivity. Phytopathology 100:S86. Moore, S. R., W. S. Gazaway, K. S. Lawrence, B. Goodman, and J. R. Akridge. 2010c. Value of rotational crops for profit increase and reniform nematode suppression with and without a nematicides in Alabama. Proceedings of the Beltwide Cotton Conferences, 2010 Pp. 260-268. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Moore, S. R., K. S. Lawrence, F. J. Arriaga, C. H. Burmester, and E. van Santen. 2011a. Influence of water movement and root growth in the downward dispersion of Rotylenchulus reniformis. Nematropica 41:75-81. 83 Moore, S. R., and K. S. Lawrence. 2011b. Effects of soil type on the reproductive potential of Rotylenchulus reniformis on cotton. Proceedings of the Beltwide Cotton Conferences, 2011 Pp. 235-240. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Moore, S. R., K. S. Lawrence, B. Ortiz, J. Shaw, and J. Fulton. 2011c. Evaluation of the effects of soil moisture on the damage potential of Rotylenchulus reniformis on cotton. Phytopathology 101:S123 Newman, M. A., and T. C. Stebbins. 2002. Recovery of reniform nematodes at various soil depths in cotton. Proceedings of the Beltwide Cotton Conferences, 2002. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Ortiz, B. V., D. Sullivan, C. Perry, and G. Vellidis. 2007. Geostatistical analysis of the spatial variability of cotton-parasitic nematodes and the factors favoring its occurrence. Proceedings of the Beltwide Cotton Conferences, 2007 Pp. 920-928. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Ortiz, B. V., C. Perry, D. Sullivan, R. Kemerait, A. R. Ziehl, R. Davis, G. Vellidis, and K. Rucker. 2008. Cotton yield response to variable rate nematicides according to risk zones. Proceedings of the Beltwide Cotton Conferences, 2008 Pp. 573-582. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Ostergaard, H. G. S. 1997. Agronomic consequences of variable N fertilization. Pp. 315-320. in J. V. Stafford (ed.) Precision Agriculture ?97. Vol. 1. Spatial variability in soil and crop. Oxford, UK. Overstreet, C., E. Burris, D. R. Cook, E. C. McGawley, B. Padgett, and M. Wolcott. 2007. Telone II fumigation. Proceedings of the Beltwide Cotton Conferences, 2007 Pp. 587- 597. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm 84 Overstreet, C., R. Barbosa, D. Burns, R. L. Frazier, E. C. McGawley, G. B. Padgett, and M.C. Wolcott. 2011. Using electrical conductivity to determine nematode management zones in alluvial soils of the mid-South. Proceedings of the Beltwide Cotton Conferences, 2011 Pp. 252-258. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Overstreet, C., E. C. McGawley, D. Burns, R. L. Frazier, and R. Barbosa. 2012. The influence of apparent electrical conductivity of the soil on nematicides in cotton. Proceedings of the Beltwide Cotton Conferences, 2012 Pp. 288-292. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Rab, M. A., P. D. Fisher, R. D. Armstrong, M. Abuzar, N. J. Robinson, and S. Chandra. 2009. Advances in precision agriculture in south-eastern Australia. IV. Spatial variability in plant-available water capacity of soil and its relationship with yield in site-specific management zones. Crop & Pasture Science 60:885-900. Rich, J. R., and R. A. Kinloch. 2000. Influence of aldicarb and 1,3-dichloropropene applications on cotton yield and Rotylenchulus reniformis post-harvest populations. Nematropica 30:47-53. Robinson, A. F., C. M. Heald, S. L. Flanagan, w. H. Thames, and J. Amador. 1987. Geographical distributions of Rotylenchulus reniformis, Meloidogyne incognita, and Tylenchulus semipenetrans in the Lower Rio Grande Valley as related to soil texture and land use. Annals of Applied Nematology (Journal of Nematology 19, Supplement) 1: 20-25. Robinson, A. F., R. N. Inserra, E. P. Caswell-Chen, N. Vovlas, and A. Troccoli. 1997. Rotylenchulus species: identification, distribution, host ranges, and crop plant resistance. Nematropica 27:127-180. 85 Robinson, A. F., C. G. Cook, A. Westphal, and J. M. Bradford. 2005a. Rotylenchulus reniformis below plow depth suppresses cotton yield and root growth. Journal of Nematology 37:285-291. Robinson, A. F., R. Akridge, J. M. Bradford, C. G. Cook, W. S. Gazaway, T. L. Kirkpatrick, G. W. Lawrence, G. Lee, E. C. McGawley, C. Overstreet, B. Padgett, R. Rodriguez-Kabana, A. Westphal, and L. D. Young. 2005b. Vertical distribution of Rotylenchulus reniformis in cotton fields. Journal of Nematology 37:265-271. Robinson, A. F. 2007. Reniform in U.S. cotton: when, where, why, and some remedies. Annual Review of Phytopathology 45:263-288. Starr, J. L., C. M. Heald, A. F. Robinson, R. G. Smith, and J. P. Krausz. 1993. Meloidogyne incognita and Rotylenchulus reniformis and associated soil textures from some cotton production areas of Texas. Journal of Nematology 25:895-899. Stetina, S. R., L. D. Young, W. T. Pettigrew, and H. A. Bruns. 2007. Effect of corn-cotton rotations on reniform nematode populations and crop yield. Nematropica 37:237-248. Still, J. A., and T. L. Kirkpatrick. 2006. Ecology and over-wintering ability of Rotylenchulus reniformis on cotton in Arkansas. Research Series 552. Summaries of Arkansas Cotton Research 2006. http://arkansasagnews.uark.edu/1993.htm Sudduth, K. A., D. F. Hughes, and S. T. Drummond. 1995. Electromagnetic induction sensing as an indicator of productivity on claypan soils. Pp. 671-681. Proceedings of the 2nd International Conference on Site-Specific Management for Agricultural Systems. ASA, Madison, WI. United States Department of Agriculture, National Agricultural Statistical Service. 2011. www.nass.usda.gov 86 Usery, S. R., K. S. Lawrence, G. W. Lawrence, and C. H. Burmester. 2005. Evaluation of cotton cultivars for resistance and tolerance to Rotylenchulus reniformis. Nematropica 35:121- 133. Wackernagel, H. 1988. Geostatistical techniques for interpreting multivariate spatial information. Pp, 393-409. in: Chung, C. F., A. Fabbri. G, R. Sinding-Larsen. (eds) Quantitative analysis of mineral and energy resources. Reidel, Dordrecht. Wackernagel, H. 1995. Multivariate geostatistics: and introduction with applications. Springer, Berlin Heidelberg New York. Wang, K. H., B. S. Sipes, and D. P. Schmitt. 2003. Intercropping cover crops with pineapple for the management of Rotylenchulus reniformis. Journal of Nematology 35:39-47. Wang, K., R. D. Riggs, and D. Crippen. 2004. Suppresion of Rotylenchulus reniformis on cotton by the nematophagous fungus ARF. Journal of Nematology 36(2):186-191. Weng Q. 2006. An evaluation of spatial interpolation accuracy of elevation data. Pp. 805-824 in Progress in spatial data handling. Riedl, A., W. Kainz,, G. A. Elmes eds. Springer Berlin Heidelberg. Westphal, A., and J. R. Smart. 2003. Depth distribution of Rotylenchulus reniformis under different tillage and crop sequence systems. Phytopathology 93:1182-1189. Westphal, A., A. F. Robinson, A. W. Scott, Jr., and J. B. Santini. 2004. Depth distribution of Rotylenchulus reniformis under crops of different host status and after fumigation. Nematology 6:97-107. Wheeler, T. A., K. R. Barker, and S. M. Schneider. 1991. Yield-loss models for tobacco infected with Meloidogyne incognita as affected by soil moisture. Journal of Nematology 23:365- 371. 87 Williams, B. G., and D. Hoey. 1987. The use of electromagnetic induction to detect spatial variability of the salt and clay content of soils. Australian Journal of Soil Research 25:21- 27. Wolcott, M. C., C. Overstreet, B. Padgett, and E. Burris. 2004. Using soil electrical conductivity to denote potential nematode management zones. Proceedings of the Beltwide Cotton Conferences, 2004 Pp. 349-353. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Wolcott, M. C. Overstreet, E. Burris, D. Cook, D. Sullivan, G. B. Padgett, and R. Goodson. 2005. Evaluating cotton nematicides response across soil electrical conductivity zones using remote sensing. Proceedings of the Beltwide Cotton Conferences, 2005 Pp. 215- 220. National Cotton Council of America. Online. http:/www.cotton.org/beltwide/proceedings.htm Wyse-Pester, D. Y., L. J. Wiles, and P. Westra. 2002. The potential for mapping nematode distributions for site-specific management. Journal of Nematology 34:80-87.