Demonstrating the Feasibility of Cover Crops in Managing Corn Insect Pests of the Great Plains
North Central Agricultural Research Laboratory
Project Number: 3080-21220-006-04
Interagency Reimbursable Agreement
Start Date: Sep 01, 2013
End Date: Aug 31, 2016
The overall objective of this research is to develop and implement conservation biological control using vegetation diversity and natural enemies as a reliable and practical tool for corn farmers of the Great Plains Region. To accomplish this, a multidisciplinary systems approach has been adopted that focuses on corn insect pests. The system will examine the multitrophic interplay that drives how the diverse soil- and foliar-dwelling natural enemy communities and vegetational diversity (in the form of winter cover crops) interact to reduce pest damage, and improve the profitability of corn production relative to current, pesticide-intensive management strategies. To maximize relevancy, this research will be conducted across a linear transect of farmers spanning four states throughout the western Corn Belt. Specific objectives of this project are:
1. Determine how increasing diversity in winter vegetation affects natural enemy biodiversity, their impacts on pests, and the economics of crop production in the Northern Great Plains.
Apply cost-benefit analysis to determine the agronomic and economic feasibility of using cover crops as a pest management tool relative to prevailing pest management approaches across multiple locations.
Experimental sites will be established in ND, SD, NE, and KS in a RCBD comparing two treatments in four replicates. The treatments will be conventional corn preceded by winter cover crops versus Bt corn preceded by bare soil. Insects will be monitored at each site over the season using soil cores, quadrat samples, and whole plant counts. Root damage and stalk tunneling will be recorded for each plot, as will yield. And economic model will be developed that compares the relative profitability of these two pest management systems. A logic model has been created to disseminate the research results to end users.