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Title: GPS/GIS FOR WEED MAPPING IN ROW-CROP PRODUCTION

Author
item Hanks, James
item Bryson, Charles

Submitted to: Proceedings of Southern Weed Science Society
Publication Type: Abstract Only
Publication Acceptance Date: 1/28/2001
Publication Date: 1/28/2001
Citation: Hanks, J.E., Bryson, C.T. 2001. Gps/gis for weed mapping in row-crop production. Proceedings of Southern Weed Science Society. 54:194-195.

Interpretive Summary: Abstract only.

Technical Abstract: Studies were conducted in cotton and soybean fields as part of the Mississippi Delta Management Systems Evaluation Area (MDMSEA) project with crops grown under conservation-tillage production practices, on rows spaced 38" apart. The total acreage in the project included approximately 125 acres of cotton and 100 acres of soybeans. Data collection points were setup in a 200 ft. by 200 ft. grid pattern. Field boundaries and data collection points were geo-referenced with a Starlink Model DNAV 212 GPS interfaced with a Rockwell Vision Computer Display (VCD) mounted on an ATV. Geo-referenced data were processed and maps generated using Vision GIS software. Data collection points for the second year were setup in the field by downloading the geo-referenced data and navigating to each point. Weed counts by specie were collected at each geo-referenced point throughout the growing seasons in 1997 and 1998. Data were processed in the GIS software, which allowed maps to be generated by field, crop, weed specie or any combination. GPS/GIS systems are excellent tools for collecting, storing and presenting field data. The geo-referenced data allowed information to be viewed in relation to the field boundary, making it easy to visually see variations within a field. Data and/or maps can be downloaded to the VCD allowing navigation to specific points of interest. The GIS processed data can also be used to generate prescription application maps that provide properly equipped spray applicators with required information to apply herbicides only where weeds were present or vary herbicides depending on the concentration of weeds. Although these technologies provide significant advances for weed control, methods of collecting data must be improved to fully utilize their utmost benefit.