Kenneth W. Paxton

A Binary Logit Estimation of Factors Affecting Adoption of GPS Guidance Systems by Cotton Producers

Binary logit analysis was used to identify the factors influencing adoption of Global Positioning System (GPS) guidance systems by cotton farmers in 11 Mid-south and Southeastern states. Results indicate that adoption was more likely by those who had already adopted other precision-farming practices and had used computers for farm management. In addition, younger and more affluent farmers were more likely to adopt. Farmers with larger farms and with relatively high yields were also more likely to adopt. Education was not a significant factor in a farmer’s decision to adopt GPS guidance systems.

Factors affecting farmer adoption of remotely sensed imagery for precision management in cotton production

This research evaluated the factors that influenced cotton (Gossypium hirsutum L.) producers to adopt remote sensing for variable-rate application of inputs. A logit model estimated with data from a 2005 mail survey of cotton producers in 11 southern USA states was used to evaluate the adoption of remote sensing. The most frequently made management decisions using remote sensing were the application of plant growth regulators, the identification of drainage problems and the management of harvest aids. A producer who was younger, more highly educated and had a larger farm with irrigated cotton was more likely to adopt remote sensing. In addition, farmers who used portable computers in fields and produced their own map-based prescriptions had a greater probability of using remote sensing. The results suggest that value-added map-making services from imagery providers greatly increased the likelihood of a farmer being a user of remote sensing.

Intensity of Precision Agriculture Technology Adoption by Cotton Producers

Many studies on the adoption of precision technologies have generally used logit models to explain the adoption behavior of individuals. This study investigates factors affecting the intensity of precision agriculture technologies adopted by cotton farmers. Particular attention is given to the role of spatial yield variability on the number of precision farming technologies adopted, using a count data estimation procedure and farm-level data. Results indicate that farmers with more within-field yield variability adopted a higher number of precision agriculture technologies. Younger and better educated producers and the number of precision agriculture technologies used were significantly correlated. Finally, farmers using computers for management decisions also adopted a higher number of precision agriculture technologies.

Grid soil sampling adoption and abandonment in cotton production

Technology adoption in precision agriculture has received considerable attention, while abandonment has received little. Survey data are now available to evaluate adoption and abandonment decisions. Understanding the factors motivating technology adoption and abandonment has implications for educational efforts directed toward improving the efficiency of production inputs and for research and development to improve the value of precision agriculture technologies. The objective of this research was to identify factors motivating the adoption and abandonment of grid soil sampling in precision cotton production. These decisions were evaluated assuming a random utility model. Data were obtained from a 2005 survey of cotton producers in 11 Southeastern states in the USA. Results from limited dependent variable regressions indicate that younger producers who farmed more cotton area, owned more of their cropland, planted larger amounts of non-cotton area, used a computer for farm management and used a Personal Digital Assistant (PDA) in the field were more likely to adopt grid soil sampling for cotton precision farming. Results also suggest that producers with more cotton area who owned livestock and adopted management zone soil sampling were more likely to abandon grid soil sampling, while those who used a PDA in the field, used grid soil sampling for more years and followed up grid soil sampling with variable-rate fertilizer application were less likely to abandon grid soil sampling for cotton production.

Factors Influencing Farmer Adoption of Portable Computers for Site-Specific Management: A Case Study for Cotton Production

Personal digital assistants (PDA) and handheld global positioning systems (GPS) have become increasingly important in cotton production but little is known about their use. This research analyzed the adoption of PDA/handheld GPS devices in cotton production. A younger farmer who used a computer in farm management and had a positive perception of Extension had a greater likelihood of adopting the devices. In addition, farmers who used complementary remote sensing, plant mapping, and grid soil sampling information were more likely to use PDA/handheld GPS devices. Finally, the COTMAN in-field decision support program from Extension also positively impacted adoption.

IRRIGATION AND POTENTIAL DIVERSIFICATION BENEFITS IN HUMID CLIMATES

Income variability and means for managing risk continue to receive much attention in farm management research. In this paper, irrigation is presented as a risk-management strategy that offers potential diversification benefits. Potential diversification opportunities largely result from a wider range of enterprise production activities. A portfolio analysis of dryland and irrigated farm scenarios indicates that income stabilizing and diversification effects of irrigation substantially modify the risk-return position of a typical farm in northeast Louisiana. Safety-first considerations along with Target MOTAD programming procedures also are used to evaluate the impact of irrigation on the farms financial performance.

Changes in Producers' Perceptions of Within-Field Yield Variability after Adoption of Cotton Yield Monitors

This article investigates how information from cotton yield monitors influences the perceptions of within-field yield variability of cotton producers. Using yield distribution modeling techniques and survey data from cotton producers in 11 southeastern states, we find that cotton farmers who responded to the survey tend to underestimate within-field yield variability (by approximately 5–18%) when not using site-specific yield monitor information. Results further indicate that surveyed cotton farmers who responded to a specific question about yield monitors place a value of approximately

Precision Farming by Cotton Producers in Twelve Southern States: Results from the 2009 Southern Cotton Precision Farming Survey

20/acre/year (on average) on the additional information about within-field yield variability that the yield monitor technology provides.