Site-Specific Herbicide Decision Model to Maximize Profit in Winter Wheat

Abstract

A user-friendly computerized agricultural herbicide decision model has been developed for selecting profitable site-specific herbicide applications in winter wheat. The model is based on 6 years of field research in southeastern Washington State, USA. The model calibrates herbicide applications to management unit weed densities, soil organic matter, soil moisture, and preceding management, as well as to expected input and output prices. The model increased broadleaf herbicide rates by an average 0.65 of label rates compared to the recommendations by farmers and weed science professionals, but cut the more expensive grass herbicides by an average 0.56 of label rates. The model increased average projected profitability, excluding model application costs, by 65% compared to four other criteria for determining application rates. The profitability increase relative to local farmers was 19%. Both the model and the cooperating farmers properly chose to use no grass herbicides on the study sites, but the weed science experts chose to use up to 1.0 of label rates. The estimated payoff from using the model substantially exceeded the cost of weed scouting and other information collection. Determining economically optimal sampling and management units is an important challenge for the adoption of precision agriculture models like the one developed in this study.