Adoption of Site-Specific Information and Variable-Rate Technologies in Cotton Precision Farming
Probit analysis identified factors that influence the adoption of precision farming technologies by Southeastern cotton farmers. Younger, more educated farmer who operated larger farms and were optimistic about the future of precision farming were most likely to adopt site-specific information technology. The probability of adopting variable-rate input application technology was higher for younger farmers who operated larger farms, owned more of the land they farmed, were more informed about the costs and benefits of precision farming, and were optimistic about the future of precision farming. Computer use was not important, possibly because custom hiring shifts the burden of computer use to agribusiness firms.
Volume (Year): 36 (2004)
Issue (Month): 01 (April)
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- Madhu Khanna, 2001.
"Sequential Adoption of Site-Specific Technologies and its Implications for Nitrogen Productivity: A Double Selectivity Model,"
American Journal of Agricultural Economics,
Agricultural and Applied Economics Association, vol. 83(1), pages 35-51.
- Khanna, Madhu, 1999. "Sequential Adoption Of Site-Specific Technologies And Its Implications For Nitrogen Productivity: A Double Selectivity Model," 1999 Annual meeting, August 8-11, Nashville, TN 21599, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
- Roberts, Roland K. & English, Burton C. & Larson, James A. & Cochran, Rebecca L. & Goodman, W. Robert & Larkin, Sherry L. & Marra, Michele C. & Martin, Steven W. & Reeves, Jeanne M. & Shurley, W. Dona, 2002. "Precision Farming by Cotton Producers in Six Southern States: Results from the 2001 Southern Precision Farming Survey," Research Reports 91331, University of Tennessee, Department of Agricultural and Resource Economics.
- Linda Whipker & jay Akridge, 2006. "2006 Precision Agricultural Services Dealership Survey Results," Working Papers 06-10, Purdue University, College of Agriculture, Department of Agricultural Economics.
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