Relationship of Corn and Soybean Yield to Soil and Terrain Properties

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Abstract
Farmers will be better able to implement site‐specific management practices when they understand the causes of spatial and temporal variability of corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] yield in their fields. Our objectives were to determine if a data set containing 20 soil and terrain variables could explain spatial yield variability better than a subset of seven more easily measured variables and to determine whether the relative importance of factors in explaining yield variability differed between corn and soybean or between wet and dry years. Yield data were collected for 11 yr in a 16‐ha field in central Iowa. Soil and terrain variables measured included: A horizon depth, carbonate depth, pH, coarse sand, sand, silt, clay, organic C, N, Fe, K, P, and Zn; and seven easily measured variables: electrical conductivity, soil color, elevation, slope, profile curvature, plan curvature, and depression depth. Factor analysis of the variables followed by regression of yield on the resulting factors showed that the 20‐variable set explained more of the spatial variation in yield than the subset of seven variables. Further, the analysis of the 20‐variable data set showed that soybean yield was affected more by pH, more by closed depressions in wet years, and less by curvature in dry years than corn yield. Similarly, yield was negatively affected by closed depressions and lower landscape positions in wet years, whereas these factors had either no effect or a positive effect in dry years. Alternately, curvature had a negative effect in dry years and no effect in wet years.
Funding Information
  • School of Global Policy and Strategy, University of California, San Diego
  • Instituto Científico Pfizer

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