An economic evaluation of site-specific herbicide application

An economic evaluation of site-specific herbicide application The objective of this study was to determine if site-specific application of postemergence herbicide was economically viable with current technologies. This objective was accomplished by: developing an algorithm that determined the economic optimal postemergence herbicide rate; creating models to determine the impact that postemergence herbicide rate has on yield; and determining whether site-specific application of postemergence herbicide has greater net returns than those from a uniform application of postemergence herbicide. Weed species identification and population counts were done on a regular grid in five fields across Kansas. A decision algorithm was developed to determine the economic optimal rate of postemergence herbicide for each grid cell. The site-specific herbicide rate and four standard herbicide rates [0, 0.5, 0.75, and full (1×) label rate] were applied according to a split-plot design. Weed population observations made three weeks after application showed that the site-specific treatment controlled the weeds present in the fields. Production functions developed to determine whether postemergence herbicide rate had an impact on yield showed that it had a positive, yet statistically insignificant, effect on yield. The difference in estimated net returns between applications of site-specific rate and uniform full-label rate covered all of the costs associated with site-specific application of postemergence herbicide. The margin between the estimated net returns for site-specific and uniform application of the economic optimal rate covered only a portion of the costs associated with site-specific application of postemergence herbicide. Precision Agriculture Springer Journals

An economic evaluation of site-specific herbicide application

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Kluwer Academic Publishers-Plenum Publishers
Copyright © 2006 by Springer Science+Business Media, LLC
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
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