Submitted to: Weed Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: June 1, 1996
Publication Date: 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 model for soybean 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 by 47 to 93% using the model compared to the standard herbicide treatment. Economic returns to weed control were also increased in many cases. Although weed control practices differed, the bioeconomic model generally resulted in weed control and soybean yield similar to the standard herbicide. 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 soybean and corn producers.
A bioeconomic model was tested as a decision aid for weed control in soybean at Rosemount, MN, from 1991 to 1994. The model makes recommendations for preplant incorporated and preemergence control tactics based on weed seedling densities. Weed control, soybean yield, herbicide load, and economic return with model-generated treatments were compared to standard herbicide and mechanical control systems. Effects of these treatments on weed populations and corn yield the following year were also determined. In most cases, the model-generated treatments controlled weeds as well as a standard herbicide treatment. Averaged over the 3 years, quantity of herbicide active ingredient applied was decreased by 47% with the seed bank model and 93% with the seedling model relative to a standard soil-applied herbicide treatment. However, frequency of herbicide application was not reduced. Soybean yields reflected differences in weed control and crop injury. Net economic return to weed control was increased 50% of the time using model-generated control recommendations compared with a standard herbicide treatment. Weed control treatments the previous year affected weed density in the following corn crop, but had little impact on weed control or corn yield. The bioeconomic model was responsive to differing weed populations, maintained weed control and soybean yield and often increased economic returns under the weed species and densities observed in this research.