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THE ROLE OF SPECTRAL IMAGERY FOR MONITORING & MODELING TRANSGENIC CROP-PEST INTERACTIONS
GLASER, J. A. THE ROLE OF SPECTRAL IMAGERY FOR MONITORING & MODELING TRANSGENIC CROP-PEST INTERACTIONS. Presented at Ecological Modeling for NASA Applied Sciences Workshop, Monterey, CA, March 30 - April 01, 2005.
To inform the public.
Crops bioengineered to contain toxins derived from Bacillus thuringensis (Bt) are under regulatory scrutiny by USEPA under the FIFRA legislation. The agency has declared these crops to be "in the public good" based on the reduced use of pesticides required for management of these crops. Hence they are environmental assets that are valued for crop protection having significant human health and ecological protection features. From a sustainability perspective, it is important to protect these crops so that society can enjoy long useful lifetimes for these new forms of biotechnology. The major threat to extended lifetimes is the development of resistance toward the crop in pest populations for which the crop protects. Detection and monitoring of resistance development becomes crucial to avoid any premature crop loss due to pest resistance. Research efforts leading to the development of new detection technology and standardization of more established detection technology are important to the ability to sample for resistance at the field level. The US crop acreage for Bt corn is about 25+ million acres. Any realistic attempt to sample such a large area for pest resistance is difficult and probably beyond the cost that can be economically endured for resistance management. A new approach to this problem that uses spectral imagery is outlined. Simulation models for pest resistance prediction have been used to portray possible lifetime for these crops and to develop management options to lengthen their useful lifetimes. Verification and validation of the predictive strengths of the models are important to the understanding the utility of these models to assist bioengineered crop management. Spatially explicit models can be enhanced with the incorporation of digital imagery features of the agroecosystem landscape. It is anticipated that these different research elements will be assembled into decision support systems and tools that will enhance the management of transgenic crops. The research program designed to achieve these objectives is built from internal EPA research alliances and external NASA & USDA supported research.