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Quantifying Adoption Intensity for Weed-Resistance Management Practices and Its Determinants among US Soybean, Corn, and Cotton Farmers

机译:量化美国大豆,玉米和棉农抗除草剂管理措施的采用强度及其决定因素

摘要

Using data envelopment analysis with principal components, we calculate an adoption-intensity index for herbicide-resistance best management practices (BMPs). Empirical results for over 1,100 farmers in twenty-two U.S. states suggest that many farmers could improve their herbicide resistance BMP adoption. Two-limit truncated regression results show that higher yields and a greater proportion of acres planted with Roundup Ready (R) seeds motivate weed BMP adoption. While soybean and corn farmers have lower adoption intensity than cotton farmers, farmer educational attainment and greater concern for herbicide effectiveness and for human and environmental safety are found to help increase the adoption of weed BMPs.
机译:使用具有主要成分的数据包络分析,我们计算了除草剂抗性最佳管理实践(BMP)的采用强度指数。美国22个州的1,100多名农民的经验结果表明,许多农民可以提高他们对除草剂抗性BMP的采用。两次极限截短的回归结果表明,使用Roundup Ready(R)种子种植的更高产量和更大比例的英亩促使杂草采用BMP。尽管大豆和玉米农民的收养强度低于棉农,但农民的受教育程度以及对除草剂有效性以及对人类和环境安全的更大关注被发现有助于增加杂草BMP的采用。

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