Relationship of Corn and Soybean Yield to Soil and Terrain Properties

Abstract

yield data collected over many years in the same field and a larger set of measured soil and terrain variables Farmers will be better able to implement site-specific management would have a better chance of accomplishing this goal. practices when they understand the causes of spatial and temporal variability of corn (Zea mays L.) and soybean [Glycine max (L.) Data collection and analysis, however, are costly and Merr.] yield in their fields. Our objectives were to determine if a data labor-intensive, and questions remain about the kind set containing 20 soil and terrain variables could explain spatial yield and amount of data that are needed to adequately unvariability better than a subset of seven more easily measured variables derstand spatial yield patterns. Additionally, it is unclear and to determine whether the relative importance of factors in exwhether different variables should be measured for soyplaining yield variability differed between corn and soybean or bebean and corn or for wet and dry years. tween wet and dry years. Yield data were collected for 11 yr in a 16-ha Growing season precipitation often interacts with terfield in central Iowa. Soil and terrain variables measured included: A rain attributes and soil properties to influence crop yield horizon depth, carbonate depth, pH, coarse sand, sand, silt, clay, (Timlin et al., 1998; Jaynes et al., 2002; Kaspar et al., organic C, N, Fe, K, P, and Zn; and seven easily measured variables: 2003). In years with below average rainfall, field areas electrical conductivity, soil color, elevation, slope, profile curvature,higher on a hillslope with greater slopes and convex plan curvature, and depression depth. Factor analysis of the variables followed by regression of yield on the resulting factors showed that curvatures usually have less available water and lower the 20-variable set explained more of the spatial variation in yield than yield than areas lower on the hillslope, with lesser slopes the subset of seven variables. Further, the analysis of the 20-variable and concave curvatures (Ciha, 1984; Halvorson and data set showed that soybean yield was affected more by pH, more Doll, 1991; Afyuni et al., 1993;Timlin et al., 1998; Jaynes by closed depressions in wet years, and less by curvature in dry years Kaspar et al., 2003). Similarly, eroded soils, than corn yield. Similarly, yield was negatively affected by closed which commonly have substantial slopes, convex curvadepressions and lower landscape positions in wet years, whereas these tures, and shallow topsoils (Pennock and de Jong, 1987; factors had either no effect or a positive effect in dry years. Alternately, Lindstrom et al., 1992), show a greater yield decline curvature had a negative effect in dry years and no effect in wet years.

Spatial Relation of Apparent Soil Electrical Conductivity with Crop Yields and Soil Properties at Different Topographic Positions in a Small Agricultural Watershed

“…Dry years showed no differences at various topographic positions. Many studies have shown yearly differences in crop yields due to topography [18,19,[43][44][45][46]. In agreement with our results, Muñoz et al [44] also reported that topography had major influence on corn yields during the year with higher precipitation.…”

“…Thelemann et al [48] observed that higher water retention for longer periods of time resulted in lower corn grain and stover yields at depositional and flat areas, whereas well drained summit positions had the highest yields as these slope positions drained earlier. Depression areas can accumulate water in turn they can impact corn and soybean yields and significant difference in yield can be observed during wet and dry years of precipitation in these areas [46]. Depth to B horizon can play an important role in regulating yields at different topographic positions.…”

Spatial and temporal variability of crop yield and some Rhodic Hapludox properties under no-tillage

“…In the northern area there was a certain tendency of higher yields, as observed for hyacinth bean 2002, (2002) and Kaspar et al (2004) point out that the higher the number of harvests monitored in the same area, the more precise and easier is the definition of differentiated land management zones. This corroborates the results reported here, since five of the seven harvests analyzed indicated the northern area as high-yield management zone.…”

Categorical Analysis of Spatial Variability in Economic Yield Response of Corn to Nitrogen Fertilization

“…Elev. tend to have higher yield levels in years with above-average rainfall (Kaspar et al, 2004). Including corn grain yield from the previous growing seasons as a covariate in the autologistic models provided no improvements in predicting economic YR in all fi elds (data not shown).…”