Adoption of Best Management Practices to Control Weed Resistance by Corn, Cotton, and Soybean Growers

Abstract

This study examined adoption of 10 best management practices (BMPs) to control weed resistance to herbicides using data from a survey of more than 1,000 US corn, cotton, and soybean growers. Count-data models were estimated to explain the total number of BMPs frequently practiced. Ordered-probit regressions were used to explain the frequency of individual BMP adoption. Growers practicing a greater number of BMPs frequently had more education, but less farming experience; grew cotton; expected higher yields relative to the county average; and farmed in counties with a lower coefficient of variation (CV) for yield of their primary crop. Yield expectations and variability were significant predictors of adoption of individual BMPs. Most growers frequently adopted the same seven BMPs. Extension efforts may be more effective if they targeted the three practices with low adoption rates. Counties with a high-yield CV would be areas to look for low BMP adoption.