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Title: FIELD EVALUATION OF A BIOECONOMIC MODEL FOR WEED MANAGEMENT IN CORN (ZEA MAYS)

Author
item Buhler, Douglas - Doug
item KING, ROBERT - UNIVERSITY OF MINNESOTA
item SWINTON, SCOTT - MICHIGAN STATE UNIVERSITY
item GUNSOLUS, JEFFERY - UNIVERSITY OF MINNESOTA
item Forcella, Frank

Submitted to: Weed Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/1/1996
Publication Date: N/A
Citation: N/A

Interpretive Summary: Recent public concern over environmental pollution from the application of pesticides has stimulated discussion and research on methods to reduce herbicide use in corn and soybean production. Decision-support models are beginning to provide tools to improve farm profits while holding the promise of reducing herbicide use. Bioeconomic models integrate biological processes of weed-crop interactions with economic factors to provide farmers with more complete information to guide weed control decisions. While several decision-support models have been developed, field testing has been limited. The goal of our research was to evaluate a bioeconomic weed management models for corn under field conditions in terms of weed control, herbicide use, crop yields, and economic returns. Results of our research indicated that model-generated treatments controlled weeds as well as a herbicide treatment commonly used by farmers. Herbicide use was decreased using the model compared to the standard herbicide treatment. While the model reduced herbicide use, economic returns to weed control were not increased. Although weed control practices differed, the bioeconomic model generally resulted in weed control and corn yield similar to the standard herbicide treatment. The bioeconomic model showed potential to control weeds with less herbicide and at a lower cost to farmers. Further research will continue the development of the model to make it useful to corn and soybean producers.

Technical Abstract: A bioeconomic weed management computer model was tested as a decision aid for weed control in corn from 1991 to 1994. The model makes recommendations for preemergence control tactics based on the weed seed content of the soil and postemergence decisions based on weed seedling densities. Weed control, corn yield, herbicide load, and economic returns with model-generated treatments were compared to standard herbicide and mechanical control systems. Effects of these treatments on weed populations and soybean yield the following year were also determined. In most cases, the model-generated treatments controlled weeds as well as the standard herbicide treatment. Herbicide use decreased by 27% with the seed bank model and 68% with the seedling model relative to the standard herbicide treatment. In one year, seed bank model treatments did not control weeds as well as the standard herbicide or seedling model treatments. Corn yields reflected differences in weed control. Net economic return to weed control was not increased by using model-generated control recommendations. Weed control treatments the previous year impacted weed density in the following soybean crop. In 2 of 3 years, these differences did not alter weed control or soybean yield. Although tactics differed, the bioeconomic model generally resulted in weed control and corn yield similar to the standard herbicide. The model was responsive to differing weed populations, but did not greatly alter economic returns under the weed species and densities in this research.