Huang, X. 2007. Analysis of effects of soil properties, topographical variables and management practices on spatial-temporal variability of crop yields. Ph.D. Dissertation, Michigan State University, East Lansing, Michigan, USA.
Crop yields are highly variable across fields and years as a result of the complex interactions among topography, weather conditions, and management practices. Understanding the relationship between yield and these factors is a critical component of site-specific management systems.
The first study was to demonstrate the feasibility of mapping soil carbon using newly developed on-the-go near infrared spectroscopy (NIRS) measurements and Landsat Enhanced Thematic Mapper (ETM) image reflectance in a 50-ha field. Regression coefficients between measured and predicted carbon values were equal to 0.70 and 0.46 using NIRS data and ETM imagery, respectively. When topographical attributes, such as elevation, wetness index (WI), and slope were included into the regression model along with NIRS and ETM data, the regression coefficients improved to 0.81 and 0.62. The results indicated that combination of the NIRS and ETM measurements with topography is a valuable tool for accurate total carbon mapping in glacial till soils.
The second study was to identify spatial clusters from historical yield data, and relate the clusters to the underlying soil electrical conductivity (EC), and topographical attributes, and to validate whether cluster groups can be used to accurately predict yield patterns. Both EC and topographical attributes were found to be helpful in explaining yield variability. Consistently low and high yield clusters were identified. Four to five yield clusters can explain about 40% of the yield variation. Areas with lower EC and slope tended to form high yield clusters in the studied fields. The information from historical yield classification could be helpful in delineating management zones within a field.
The third study was to analyze the effects of management practices on the relationship between crop yield and topography, yield and precipitation with 10-yr corn-soybean-wheat rotation in Long Term Ecological Research site, located at Kellogg Biological Station. A nonparametric spline regression was used to characterize boundary yields, that are maximum yields, versus WI. The algorithm was also used to compare the yield difference across the range of the WI between two treatments. Management practices significantly interact with WI and influence crop yields. The interaction can also be affected by summer precipitation. The yield difference between no-till and conventional tillage was strongly influenced by WI in dry or normal year but not in wet year. The relationship between boundary yield and WI in most of the crops for most of the studied years had a convex shape. No-till and low input systems tended to produce higher maximum and average yields than conventional system at the lower WI areas. The results suggested that it is possible to maximize yield and profit by farming site-specifically based on landscape position.
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