Spatial analyses to evaluate multi-crop yield stability for a field

This paper proposes that yield stability patterns exist for multiple crops planted on the same land area over a period of years that growers can use to their advantage in planning crop management strategies using precision agriculture technologies. This study examines the relationship of soil elevation, slope, aspect and curvature to crop yield stability using a digital elevation model of the study area derived from a precise light detection and ranging (LIDAR) image of the farming area and surroundings. Three crop years of cotton and two crop years of corn yields were used to evaluate this hypothesis. The interpolation methods of Inverse Distance Weighted (IDW), simple Kriging and Natural Neighbor found in ESRI's ARCGIS were used to produce crop yield maps. These methods were also compared in the analysis. Simple Kriging gave the best R2 estimates of yield as a function of elevation, slope, curvature and aspect. When the SAS FastCluster procedure was used to group yield points together using topographical features, the resulting regression analyses R2 values of yield as a function of elevation, aspect, curvature and slope by cluster number were improved.