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FIGURE 16.1 Maps of (a) cotton yield and (b) ECa measurements including sixty soil core sites. (Modified from Corwin, D.L., Lesch, S.M., Shouse, P.J., Soppe, R., Ayars, J.E., Agron. J., 95, 352-364, 2003. With permission.)

the sample sites from the ECa survey data. The software uses a model-based response-surface sampling strategy. The selected sites reflect the observed spatial variability in ECa while simultaneously maximizing the spatial uniformity of the sampling design across the study area. Figure 16.1b shows the spatial ECa survey data and the locations of the sixty core sites. Soil samples were collected at 0.3 m increments to a depth of 1.8 m. Soil samples were analyzed for physical and chemical properties thought to influence cotton yield including gravimetric water content (8g), bulk density (pb), pH, B, NO3-N, Cl-, electrical conductivity of the saturation extract (ECe), leaching fraction (LF), percentage clay, and saturation percentage (SP). All samples were analyzed for physical and chemical properties following the methods outlined in Agronomy Monograph No. 9 (Page et al., 1982).

16.2.4 Statistical and Spatial Analyses

Statistical analysis was conducted using SAS software (SAS, 1999). The statistical analysis consisted of three stages: (1) determination of the correlation between ECa and cotton yield using data from the sixty sites, (2) exploratory statistical analysis to identify the significant soil properties influencing cotton yield, and (3) development of a crop yield response model based on ordinary least squares regression (OLS) adjusted for spatial autocorrelation with restricted maximum likelihood. Because the location of ECa and cotton yield measurements did not exactly overlap, ordinary krig-ing was used to determine the expected cotton yield at the sixty sites.

Spatial analysis was accomplished with a geographic information system (GIS). The commercial GIS software ArcView 3.3 (ESRI 2002) was used to compile, manipulate, organize, and display all spatial data. Delineation of SSMUs was accomplished using the GIS, exploratory statistical analyses, and crop yield response model adjusted for spatial autocorrelation.

16.3 RESULTS AND DISCUSSION 16.3.1 Correlation between Crop Yield and EC

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