Aggregation of yield monitor data for potential applications in Precision farming

摘要

This study analyzes the effects of aggregation and yield classification for corn, soybean, and wheat yields so that resulting management maps, based on crop yields, reflect the spatial heterogeneity within fields at a scale that may be appropriate for crop management. The spatially explicit yield values obtained from yield monitor data were aggregated into various resolution scales, and standard deviations within each cell and within each resolution were determined. The results indicated that aggregation had minimal effects on summarizing land areas, drastically reduced the number of data values, and did not compromise the information contained in the original data. Differences between original and aggregated crop yields were generally less than 0.2 t/ha and the standard deviations within cell resolutions rarely exceeded 0.7 t/ha. Based on crop yields alone, 0.4 hectare grids with yield classifications of 8-10 percent of the average yield for each crop were found to be appropriate for the creation of unique management areas in the three fields studied.