Published online by Cambridge University Press: 12 June 2017
Based on six years of data from a field experiment near Pullman, WA, a bioeconomic decision model was developed to annually estimate the optimal post-emergence herbicide types and rates to control multiple weed species in winter wheat under various tillage systems and crop rotations. The model name, PALWEED:WHEAT, signifies a Washington-Idaho Palouse region weed management model for winter wheat The model consists of linear preharvest weed density functions, a nonlinear yield response function, and a profit function. Preharvest weed density functions were estimated for four weed groups: summer annual grasses, winter annual grasses, summer annual broadleaves, and winter annual broadleaves. A single aggregated weed competition index was developed from the four density functions for use functions for use in the yield model. A yield model containing a logistic damage function performed better than a model containing a rectangular hyperbolic damage function. Herbicides were grouped into three categories: preplant nonselective, postemergence broadleaf, and postemergence grass. PALWEED:WHEAT was applied to average conditions of the 6-yr experiment to predict herbicide treatments that maximized profit. In comparison to average treatment rates in the 6-yr experiment, the bioeconomic decision model recommended less postemergence herbicide. The weed management recommendations of PALWEED:WHEAT behaved as expected by agronomic and economic theory in response to changes in assumed weed populations, herbicide costs, crop prices, and possible restrictions on herbicide application rates.
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