producer. Producers whose operations are small enough to allow them to know all parts intimately may benefit very little from automating information collection. Precision agriculture allows producers to reduce heterogeneity in farming operations, which permits improved profitability through reduced input expenditures, increased yields, or both. An alternative strategy to reduce heterogeneity, however, is to divide the farm into fields that are relatively homogeneous, permitting the same sorts of gains from uniform management. Producers whose operations are of a size that permits such intensity of management are unlikely to gain much from automation of information gathering and processing.

Other factors suggest the opposite—that smaller operators may gain more from precision agriculture than larger ones. The number of small farm operations is large. In 1992, 35 percent of all farm operators worked off the farm 200 or more days per year, whereas an additional 8 percent worked off the farm 100 to 199 days per year (U.S. Bureau of the Census, 1992). Automation may be more valuable to smaller, part-time producers, who operate under tight labor constraints and may otherwise be unable to increase their monitoring of field conditions. Automation may also narrow differentials in management by allowing smaller operators to access the same sophisticated strategies as larger operators. However, the current competitive advantage of some smaller operators—being able to focus on individual plants in high-value crops—may be lost when the adoption of information-intensive approaches enables larger operators to do the same.

There is similarly no clear-cut evidence that precision agriculture exhibits substantial economies of scale, so that larger operators find precision agriculture less costly on average (i.e., per acre) than smaller operators. Equipment such as variable-rate application units, GPS receivers, and computer hardware may decrease average costs because their capital costs can be spread over larger acreage. The data in Table 3-1 indicate that such economies of scale tend to be limited, however. Moreover, some smaller operators may be able to take advantage of economies of scale by hiring out themselves and their equipment for custom services. The cost of soil sampling depends on grid size, which in turn depends on the heterogeneity of soils within a field. Larger operators are more likely to have larger, more heterogeneous fields, and may thus find soil sampling more costly. Crop consultants typically charge a flat per-acre fee for their services, in which case the cost of these services does not vary with farm size.

Experience with similar information-intensive technologies fails to support the notion of a consistent size bias. As noted, the per-acre cost of scouting (a central component of IPM) is comparable to the per-acre cost of many precision agriculture technologies. The literature shows no consistent relation between farm size and the use of scouting. For example, Napit et al. (1988) examined factors influencing the use of scouting throughout the United States. They found that the value of farm sales was positively correlated with scouting on corn in Indiana, apples in New York, cotton in Texas and Mississippi, and alfalfa in the Northwest, but not correlated with scouting on soybean fields in Virginia, peanuts in

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