Prospects of a multi-tiered insect resistance management program for genetically modified corn hybrids expressing toxins derived from Bacillus thuringiensis

Driven by biofuel demand, planted acreage of genetically modified corn expressing plant incorporated protectants (PIP) derived from Bacillus thuringiensis (Bt) is expected to significantly increase for the 2007 growing season.  Acreage planted to PIP expressing corn is predicted to continue to increase and account for approximately 80% of total corn plantings by 2009.  Many corn growers are likely to abandon traditional corn-soy rotations to take advantage of more profitable continuous corn plantings.  Additionally, incidence of grower non-compliance with mandated non-genetically modified corn refuge is projected to increase.  Under the Federal Insecticide Fungicide and Rodenticide Act registration’s terms and conditions for genetically modified corn expressing a PIP, seed producers are required to implement an insect resistance management (IRM) program as part of a stewardship program designed to maintain this crop.  Long-term sustainability of PIP corn relies on the validity of assumptions underlying IRM models and ability to monitor, detect and react to insect resistance when it develops.  The United States Environmental Protection Agency’s (EPA) Office of Research and Development (ORD) is currently developing a proactive multi-tiered approach to IRM that seeks to improve on existing IRM programs.  EPA-ORD is near completing a stochastic spatially explicit population genetics model for the evolution of insect resistance in temporally and spatially heterogeneous environments.  Additionally, multi-spectral satellite and hyperspectral airborne remote sensing platforms are being evaluated for their ability to locate and monitor genetically modified corn in the agricultural landscape for signs of insect pest infestation.  The current status of EPA-ORD’s approach to the new IRM monitoring program and integration of IRM models and remote sensed imagery from multi-spectral satellite and airborne hyperspectral sensors for use as inputs for a decision support tool will be discussed.