No abstract

A total of 289 studies of returns to agricultural R&D were compiled and these provide 1821 estimates of rates of return. After removing statistical outliers and incomplete observations, across the remaining 1128 observations the estimated annual rates of return averaged 65 per cent overall ö 80 per cent for research only, 80 per cent for extension only, and 47 per cent for research and extension combined. These averages reveal little meaningful information from a large body of literature, which provides rate-of-return estimates that are often not directly comparable. This study was aimed at trying to account for the di¡erences. Several features of the methods used by research evaluators matter, in particular assumptions about lag lengths and the nature of the research-induced supply shift.

No abstract

Probit analysis identified factors that influence the adoption of precision farming technologies by Southeastern cotton farmers. Younger, more educated farmers 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.

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.