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ARS Home » Southeast Area » Mississippi State, Mississippi » Crop Science Research Laboratory » Genetics and Sustainable Agriculture Research » Research » Publications at this Location » Publication #113291
Title: DEVELOPMENT AND IMPLEMENTATION OF LARGE-SCALE SPATIALLY VARIABLE INSECTICIDE EXPERIMENTS IN COTTON

Author
item SEAL, MICHAEL
item DUPONT, KELLY
item BETHEL, MATTHEW
item JOHNSON, JIM
item Willers, Jeffrey
item HOOD, KENNETH
item HARDWICK, JAY

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 7/19/2000
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: In support of the NASA's Commercial Remote Sensing Program, the Institute for Technology Development, Spectral Visions worked with USDA-ARS and Perthshire Farms to conduct a spatially-variable insecticide (SVI) experiment on 1023 acres of cotton in 1999. This experiment explored the role of remote sensing in precision farming to improve profits and reduce chemical application costs.Past research suggests that vibrant cotton plants, as indicated by remotely sensed imagery, provide ideal habitat for the tarnished plant bug (Heteroptera: Miridae). Remotely sensed imagery and scouting are both used to produce a SVI prescription (spray-ON or spray-OFF) applied by GPS-controlled spray-rig equipment. The experiment resulted in five SVI applications with a 30- 40% average reduction of insecticide applied and no negative impacts on yield. Building upon the 1999 results, the team designed a 2050-acre SVI experiment for the 2000- growing season at Perthshire Farms. A replicate SVI experiment will be conducted at Hardwick Farms in Newellton, LA, on 1000 acres. Development and implementation of these experiments produce many challenges throughout the season. These include efficient field scouting and sampling, timeliness of imagery collection, delivery and turnaround, SVI development and application of prescriptions, GPS and controller communica- tion problems, lead and lag times with product mixing across the boom, collection of yield data, and analysis of results.