PROFITABILITY OF VARIABLE RATE PHOSPHORUS IN A TWO CROP ROTATION
Jennie S. Hughes Popp and
Terry Griffin ()
No 21806, 2000 Annual meeting, July 30-August 2, Tampa, FL from American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association)
In the Midwest, the adoption of precision farming technologies began in the early 1990s. Research has produced profiles of early adopters, evaluated adoption trends and has identified factors that influence the adoption and profitability of precision farming. Importantly, this information is available to producers, who are interested in precision farming issues. In addition, the Midwest regional agricultural industry, strong promoters of precision farming technologies, has gained the confidence of farmers who now rely on them heavily for information on farming technologies. Precision farming in Arkansas, however, is still in its infancy. Adoption levels lag far behind those in the Midwest. Two reasons for this lag have been offered. First, some suggest that much of what is believed about the technologies in the state is based on hearsay or the results of small single farm case study analyses. Because these beliefs have not been rigorously substantiated with extensive empirical evidence it has not been possible to truly assess the status of adoption, to predict potential adoption trends, or to adequately advise farmers in a decision to include precision farming in their farm management plan. Second, others suggest that agricultural industry has not taken an active role in the promotion and sale of precision farming equipment and services. Without local availability, all the research in the world will not lead to adoption of technology in the state. The objective of this paper is to provide critical information to Arkansas agricultural producers, industry and extension with answers regarding 1) the current status of precision farming 2) the amount, source and effectiveness of precision farming promotion and 3) the potential future of precision farming in Arkansas. In the Spring of 1999, three groups, early adopters of precision farming technologies (EA), Cooperative Extension Service personnel (CES) and agricultural industry personnel (AI), were surveyed to ascertain the realities and perceptions of precision farming in Arkansas. The surveys included questions related to characteristics of early adopters, factors encouraging and hindering adoption, and the roles of CES and AI in the promotion of precision farming within Arkansas. The survey response rate was over 60 percent. To build profiles of Arkansas EA to compare responses regarding sources of precision farming information across all three groups three statistical tools were used to test hypotheses regarding factors which influence adoption. The surveys revealed that Arkansas EA are young, educated, computer using, experienced farmers controlling relatively large farms predominantly devoted to rice and soybean. These farmers currently employ yield and soil mapping, as well as VRT and GIS technologies in their operations. While many reasons (such as decreased costs, improved yields, and improved management capabilities) have been cited as factors that can encourage adoption, there are still any number of reasons why many Arkansas farmers have not yet adopted these technologies, including, technical difficulties, expense and unproven profitability. In addition, AI representatives see themselves as promoters of precision farming technologies in Arkansas while EA have cited instances of a lack of available equipment and also stated that they turn to CES rather than AI for farming information because they believe this is an unbiased source of information. The authors conclude that both reasons offered for the lag in adoption are likely and hope that these insights provide both the CES and AI representatives with information to help them focus their research and outreach activities so that more Arkansas producers can make informed decisions about precision farming.
Keywords: Crop; Production/Industries (search for similar items in EconPapers)
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