Spatio-temporal analysis of yield variability for a corn-soybean field in Iowa

Spatio-temporal analyses of yield variability are required to delineate areas of stable yield patterns for application of precision farming techniques. Spatial structure and temporal stability patterns were studied using 19951997 yield data for a 25-ha field located near Story City, Iowa. Corn was grown during 1995-1996, and soybean in 1997. The yield data were collected on nine east-west transects, consisting of 25 yield blocks per transect. The two components of yield variability, i.e., large-scale variation (trend) and small-scale variation, were studied using median polishing technique and variography, respectively. The trend surface, obtained from median polishing, accounted for the large-scale deterministic structure induced by treatments and landscape effects. After removal of trend from yield data, the resulting yield residuals were used to analyze the small-scale stochastic variability using variography. The variogram analysis showed strong spatial structure for the yield residuals. The spatial correlation lengths were found to vary from about 40 m for corn to about 90 m for soybean. The range parameter of the variograms showed a significant correlation coefficient of –0.95 with the cumulative growing season rainfall. The total variance of 1995 corn yield was partitioned as 56% trend, 37% small-scale stochastic structure, and 7% as an interaction of both. Yield variance of 1996 corn was about 80% trend and 20% small-scale stochastic structure. Contrary to corn years, the total yield variance for soybean in 1997 was partitioned as about 25% trend and about 75% small-scale stochastic structure. The significant negative correlation of range with rainfall shows that small-scale variability may be controlled by factors induced directly or indirectly by rainfall. More years of data are required to substantiate these relationships. The lack of temporal stability in large-scale and small-scale variation suggest that longer duration yield data analyses are required to understand and quantify the impact of various climatic, and management factors and their interaction with soil properties on delineation of areas under consistent yield patterns before applying variable rate technology.