Bundled Adoption of Precision Agriculture Technologies by Cotton Producers

This research analyzes the adoption patterns among cotton farmers for remote sensing, yield monitors, soil testing, soil electrical conductivity, and other precision agriculture technologies using a Multiple Indicator Multiple Causation regression model. Adoption patterns are analyzed using principle component analysis to determine natural technology groupings. Identified bundles are regressed on farm structure and operator characteristics. The propensity to adopt technology bundles was greater for producers managing relatively larger operations who used a variety of information sources to learn about precision farming, irrigated cotton, practiced crop rotation, and participated in working land conservation programs.


Issue Date:
2015-05
Publication Type:
Journal Article
PURL Identifier:
http://purl.umn.edu/206599
Published in:
Journal of Agricultural and Resource Economics, Volume 40, Number 2
Page range:
325-345
Total Pages:
21




 Record created 2017-04-01, last modified 2017-11-22

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