Quantifying adoption intensity for weed-resistance management practices and its determinants among U.S. Soybean, corn, and cotton farmers

Fengxia Dong; Paul D. Mitchell; Terrance M. Hurley; George B. Frisvold

Quantifying adoption intensity for weed-resistance management practices and its determinants among U.S. Soybean, corn, and cotton farmers

Fengxia Dong, Paul D. Mitchell, Terrance M. Hurley, George B. Frisvold

Research output: Contribution to journal › Article › peer-review

Abstract

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 herbicideresistance BMP adoption. Two-limit truncated regression results show that higher yields and a greater proportion of acres planted with Roundup ReadyR 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.

Original language	English (US)
Pages (from-to)	42-61
Number of pages	20
Journal	Journal of Agricultural and Resource Economics
Volume	41
Issue number	1
State	Published - Jan 2016

Keywords

Adoption Intensity
Best Management Practices
Common-Weight Data Envelopment Analysis
Herbicide-Resistance Management
Polychoric Non-Negative Principal Component Analysis
Weed-Resistance Management

ASJC Scopus subject areas

Animal Science and Zoology
Agronomy and Crop Science
Economics and Econometrics

Cite this

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abstract = "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 herbicideresistance BMP adoption. Two-limit truncated regression results show that higher yields and a greater proportion of acres planted with Roundup ReadyR 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.",

keywords = "Adoption Intensity, Best Management Practices, Common-Weight Data Envelopment Analysis, Herbicide-Resistance Management, Polychoric Non-Negative Principal Component Analysis, Weed-Resistance Management",

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AU - Frisvold, George B.

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AB - 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 herbicideresistance BMP adoption. Two-limit truncated regression results show that higher yields and a greater proportion of acres planted with Roundup ReadyR 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.

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Quantifying adoption intensity for weed-resistance management practices and its determinants among U.S. Soybean, corn, and cotton farmers

Abstract

Keywords

ASJC Scopus subject areas

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