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Factors Influencing the Timing of Precision Agriculture Technology Adoption in Southern U.S. Cotton Production
1D. M. Lambert, 1J. A. Larson, 1B. C. English, 2R. M. Rejesus, 2M. C. Marra, 3A. K. Mishra, 4C. Wang, 1P. Watcharaanantapong, 1R. K. Roberts, 1M. Velandia
1. The University of Tennessee
2. North Carolina State University
3. Louisiana State University
4. Texas Tech University

Technology innovators in cotton production adopted precision agriculture (PA) technologies soon after they became commercially available, while others adopted these technologies in later years after evaluating the success of the innovators. The timing of technology adoption is influenced by farmers’ ability to bear risk, and innovators are more risk tolerant compared with laggards. The diffusion of PA technologies over time is related to factors such as farm size, education, land ownership and the availability of PA information. The factors influencing cotton farmers’ adoption of PA technologies sooner than later are important in helping anticipate technology diffusion over time. Thus, the objective of this research was to identify factors influencing Southern cotton farmers’ decisions to adopt yield monitoring (YMR), grid soil sampling (GSS), management zone soil sampling (MSS), remote sensing (RMS), and soil survey maps (SSM) at different points in time. Data for cotton farmers in 12 states were obtained from a Cotton Incorporated survey conducted in 2009 for the 2008 crop. Tobit models were used to evaluate the factors influencing the timing of adoption. The numbers of years a farmer had used each of the PA technologies were used as dependent variables. Independent variables hypothesized to influence the timing of adoption included farm characteristics, farmer characteristics, farmer perceptions, PA information sources, adoption of other PA technologies, and regional characteristics. Farm size, lint yield, computer use, education level, and adoption of other PA technologies, among others, influenced cotton farmers to adopt these technologies sooner than later. The results can provide information to cotton farmers for making technology adoption decisions now and in the future; decision that may help them improve input efficiency, increase profit and decrease negative environment impacts. The results will help researchers put PF technology adoption and diffusion into a historical perspective for future research.

Keyword: Precision Agriculture, Timing, Technology Adoption, Diffusion Curve