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ARS Home » Midwest Area » Morris, Minnesota » Soil Management Research » Research » Publications at this Location » Publication #59058

Title: WEED EMERGENCE MODELING FOR A BIOECONOMIC WEED/CROP MANAGEMENT EXPERT SYSTEM

Author
item Forcella, Frank
item BARBOUR, JAMES - UNIVERSITY OF MINNESOTA
item ORIADE, C - UNIVERSITY OF MINNESOTA
item KING, R - UNIVERSITY OF MINNESOTA
item Buhler, Douglas - Doug

Submitted to: Clean Water Clean Environment 21st Century Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 3/8/1995
Publication Date: N/A
Citation: N/A

Interpretive Summary: Models are being developed that simulate seed dormancy and seedling emergence for weed species important to the Corn Belt. These models permit accurate prediction of weed densities on a daily basis in crops. The models can be used as submodels in larger Bioeconomic Weed/Crop Management Decision Aids prior to crop planting or during crop development to improve the process by which weed control decisions are made. Use of such models in field tests resulted in substantial reductions in herbicide use, large decreases in weed control costs, and profit increases of at least $20/acre compared to standard farming practices. These models also were used to simulate weed control costs in sections of fields to explore the economic feasibility of site-specific weed management. Modest increases in profit were associated with site-specific weed management recommendations.

Technical Abstract: Mechanistic and real-time models were developed that predict seed dormancy, seed germination, and seedling emergence from the soil surface for several species of weeds important to Midwest agriculture. These models have been used successfully in maize and soybean to determine the optimal timing for cultural weed control treatments, replacing herbicides in some situations. The models also have been used as important components in the on-going development of a bioeconomic weed management expert system known as WEEDSIM. This expert system attempts to optimize weed management through minimizing weed control costs and maximizing net returns to producers. Multi-year field validation of WEEDSIM clearly shows that objective control decisions, based on weed biology and management economics, reduce herbicide use by half and increase net returns to producers.