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Researchers are expending considerable effort to develop the technology and methodology needed to identify and map within-field management zones for site-specific farming. Much of the research has focused on the use of either a high-density geographically referenced grid of soil samples or mechanical yield sensor measurements that record geographic positions and production levels. In either case, complex spatial models are generally used to extrapolate the various soil variables and production level information across the entire field. Both procedures produce a wealth of information, however, the analysis of soil samples tend to be quite expensive and the accuracy of mechanical yield measurements does vary. This study represents an ongoing effort designed to evaluate remote sensing as a tool for determining within field management zones. Color-infrared aerial photography and multispectral videography were used in concert to map and stratify two grain sorghum fields into regions or zones of homogeneous spectral response. A limited number of soil and plant samples were acquired to characterize the biotic and edaphic conditions within each zone. Results obtained during the first year of the study indicated that multispectral video can be used to develop within field management zones. Simple univariate analysis indicated that soil pH, Ca, and Fe were important variables affecting yield. Analysis of the yield data indicated that the economic returns from 17% of the first field and 20% of the second field were insufficient to recoup planting costs. Multispectral video also proved instrumental in modeling the spatial variability of yield. A significant negative correlation (r2 greater than 0.90) was obtained between the red spectral band and crop yields for both fields. Stratification, in this case using image data, reduces the number of samples required to characterize a field by reducing the variance associated within each stratum. Image data also provided a comprehensive view of each field that maintained the spatial connectivity between sites, thus reducing the need for complex spatial modeling.
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