A Logit Analysis of Precision Farming Technology Adoption in Tennessee

Data from a survey of County Agricultural Extension Agents and the Census of Agriculture were use to develop logit regression models to estimate the probabilities of farmers adopting four precision farming technologies in Tennessee counties. County characteristics associated with adoption were owned versus rented land, land in large farms relative to total land in farms, the value of crop sales per acre, total cropland, numbers of fulland part-owner farmers, and cropland relative to total land in farms. Agribusiness firms could use the estimated probabilities to identify counties with favorable characteristics for adoption of their precision farming services. A Logit Analysis Precision Farming Technology Adoption in Tennessee Farm fields have numerous areas that differ from one another with respect to soil type, topography, microclimate, and other factors that influence crop yields (Carr et al.; Hannah, Harlan, and Lewis; Hibbard et al.; Malzer et al.; Sawyer; Spratt and McIver). The concept of precision farming employs information about the heterogeneous makeup of farm fields for making management choices. Precision farming does not use a single technology to generate information for decision making but a whole set of information technologies (Swinton and Lowenber-DeBoer). These technologies include: (a) diagnostic and data management technologies which generate and organize data that describe field variability, (b) technologies capable of attaching spatial coordinates to the data, and (c) variable rate application equipment that allows farmers to apply inputs using the information about field variability (Nowak; Khanna, Epouhe, and Hornbaker). More precise placement of inputs with precision farming may increase farm profits and may reduce adverse environmental consequences of crop production (Kitchen et al.; Koo and Williams; Sawyer; Watkins, Lu, and Huang). However, the key to farmer adoption of site-specific farming is the profitability of the technology (Daberkow; Reetz, and Fixen; Roberts, English, and Mahajanashetti; Sawyer). Available information on where precision farming practices have been adopted is primarily for a few higher value crops such as sugar beets and for several crops grown in the Midwestern United States (Daberkow and McBride; Khanna, Epouhe, and Hornbaker; Franzen; Surjandari and Batte). Little information currently exists on where precision farming practices have been adopted in the Southern United States. Crops in the Southern United States are generally produced in fields known to have a high degree of variability in soil type, topography, soil moisture and other factors affecting crop production. In addition, high value crops specific to the region such as cotton, rice, tobacco, and peanuts require extensive use of chemicals such as fertilizers, insecticides, herbicides, and defoliants. Precision farming technologies hold great promise for these high-value, high-input southern crops. 2 A March 1999 survey of Tennessee Agricultural Extension Agents identified 284 producers using some form of precision farming technology in 38 of Tennessee’s 95 counties (English, Roberts, and Sleigh). Yield monitors were used in 34 counties; grid soil sampling was practiced in 28 counties; and variable rate application of fertilizer and/or lime was practiced in 18 counties. An April-May 1999 survey of firms providing precision farming services to Tennessee farmers found that 170 farmers received grid soil sampling services and 88 producers received variable rate application of fertilizer and/or lime services from the 23 responding firms (Roberts, English, and Sleigh). The number of Tennessee producers using grid soil sampling and variable rate fertilizer and/or lime application was less than 0.5% of the total number of farms harvesting crop acreage and less than 1% of the number of farms with sales over $10,000 in Tennessee (U.S. Department of Agriculture). Even though the number of farms using precision farming technology in Tennessee was low relative to other areas, firms supplying these services expected the demand for precision farming services to grow rapidly over the next 5 years. Because of anticipated growth in demand, firms providing precision farming services are interested in knowing where in Tennessee to offer these services with the largest likelihood of finding new clients. The objective of this research was to identify factors that influence the geographic location of precision farming technology adoption in Tennessee. Methods Analytical Framework The location of precision farming technology adoption can be analyzed in the same way as other technology investment decisions. A farmer’s decision to investment in precision farming technology is related to maximization of expected net farm income over time, which depends on factors influencing costs and revenues in a geographic area. Assume the probability of precision farming technology adoption by farmers in a geographic area depends on a set of locational characteristics that affect costs