Browsing by Author "Jeffrey White, Committee Co-Chair"

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    Evaluation of Realistic Yield Expectations in the North Carolina Piedmont and Coastal Plain
    (2004-11-09) Lohman, Mindy; Deanna Osmond, Committee Co-Chair; Jeffrey White, Committee Co-Chair; David Crouse, Committee Member; Randy Weisz, Committee Member
    Realistic Yield Expectations (RYE) have been developed in North Carolina to assist in site-specific farming decisions that will improve N-use efficiency and reduce N contamination of ground- and surface water, especially in the Neuse River Basin. This study was conducted to determine whether correlations exist between soil chemical properties, actual yields, soil map units, zones, and RYEs. Soil surveys of the fields were completed at an approximate scale of 1:3500 in 2002 (remapped soil map units) and compared to existing county soil surveys (original soil map units). Samples from equilateral triangle grid soil sampling were analyzed and used to map the spatial distribution of soil pH, soil P, and soil K and lime requirement. Interpolated maps were created to display the spatial distribution of the investigated soil chemical properties. To represent zones (transition zone or map unit interior), 20 m buffers centered on map unit boundaries were created in order to investigate these highly unique and variable areas. Soybean (Glycine max [L.] Merr) and wheat (Triticum aestivum L.) yield data was collected for two site-years in one Piedmont field, while wheat and corn (Zea mays L.) were sampled for one site-year in the two remaining Piedmont fields. Soybean and wheat yield data was collected for three site-years in two Coastal Plain fields. Interpolated nutrient maps showed visual correlations between soil map units and soil K values in the Coastal Plain, but no other relationships between soil chemical properties and soil map units or zones were visually apparent for either location. Yield maps showed visual relationships with soil map units in the Coastal Plain but not in the Piedmont. Various statistical models were utilized to analyze the data and the spatial covariance model was determined to be more efficient than the independent and identically distributed fixed effects model in capturing a significant proportion of the variability for tested soil chemical properties and crop yield in both locations. Remapped and original soil map units were also studied to determine their effectiveness in capturing the variability of soil chemical properties and crop yield. The remapped soil map units were more effective than the original soil map units in capturing this variability in most cases. Soil K was highly significant among the remapped soil map units in the Field 7 in the Piedmont where r2=0.82. In all locations, other investigated parameters also displayed significance, but none as highly significant as soil K in Field 7. RYEs were found to be greater than actual yields for all crops harvested in both locations.