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United States Department of Agriculture

Agricultural Research Service

Research Project: DEVELOPMENT OF PRECISION AGRICULTURE SYSTEMS IN COTTON PRODUCTION

Location: Genetics and Precision Agriculture Research

Title: Geographical approaches for integrated pest management of arthropods in forestry and row crops

Authors
item Willers, Jeffrey
item Riggins, John -

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: December 2, 2009
Publication Date: July 1, 2010
Citation: Willers, J.L., Riggins, J.J. 2010. Geographical approaches for integrated pest management of arthropods in forestry and row crops. In: Oerke, E.C., Gerhards, R., Menz, G., Sikora, R.A., editors. Precision Crop Protection - the Challenge and Use of Heterogeneity. New York, NY: Springer. p. 183-202.

Interpretive Summary: Remote sensing technology offers the forest and row crop entomologist new opportunities to approach Integrated Pest Management issues. The technology leads to innovative analyses of forest and row crop ecosystems because of spatial and spectral resolutions of these sensors near 4m x 4m pixels or smaller. The availability of these resolutions at this scale leads to innovative changes in sampling for insects. We describe the basic concepts of how to alter sampling methods for forest and row crop insect pests if remote sensing information is available.

Technical Abstract: With the proper technology and access to geographical information, it is more important to spend time on developing an excellent classification scheme of a remotely sensed attribute of crop and forest vigor rather than spending large amounts of time collecting many samples of insect counts. The ability to define zones from remote sensing images of crop or forest systems is essential for controlling the sample variability of insect counts by sampling them from more homogenous plant populations. Perspectives on defining zones from remote sensing information including an examination of their relationships to other sample attributes not measurable by remote sensing techniques are discussed.

Last Modified: 9/23/2014
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