cannot be developed, much of the potential of precision agriculture will not be realized.

Reliable crop models are the foundation of any attempt to construct data-driven, computer-based decision support systems that can effectively use precision data to make precision management changes, yet few such models exist. Theoretical and empirical understanding of crop yield responses to variations in nutrients and soil quality remains primitive. For example, fertilizer recommendations are based on rules of thumb, such as "one and a quarter pounds of nitrogen per acre for every bushel of yield goal for corn," even though theory and evidence indicate that crop nutrient response is nonlinear and that yield will not respond to additions of some nutrients when others are limiting (Cerrato and Blackmer, 1990; Chambers and Lichtenberg, 1996; Frank et al., 1990; Paris, 1992; Paris and Knapp, 1989). Similarly, it is well-known in principle that crop productivity and crop nutrient response depend on elements of soil quality and tilth (such as structure, texture, organic matter, and water-holding capacity), yet there exists little quantitative modeling of these factors in crop production. Pest management presents a similar picture; treatment thresholds are frequently based on rules of thumb because there are no reliable crop-pest ecosystem models. Even if rules of thumb for nutrient and pest management are based on significant experimental data, the resulting recommendations are developed on an aggregated basis that ignores the other factors that vary within fields. "[Precision agriculture] departs from current nitrogen fertilizer guidelines that were primarily developed on a regional scale. … As a result, current nitrogen recommendations may have limited application to site-specific nitrogen management." (Pan et al., 1997, p. 81). If modeled relationships can be developed that capture the effects of variation in factors that vary at the subfield level, better recommendations can be made.

Nutrients, pest management, and soil quality are obvious targets for public research because of their linkage to environmental quality. Nutrient pollution of both surface water and groundwater is a significant problem throughout the United States, and agriculture is a major contributor to nutrient pollution in many areas, such as the Great Lakes region, the Chesapeake Bay watershed, and the Mississippi drainage (where it contributes to Gulf of Mexico hypoxic zone problems). In many areas, reductions in nitrogen pollution resulting from improved nitrogen management could justify the use of variable-rate application and other precision farming methods even when reductions in fertilizer expenditures do not (Khanna and Zilberman, 1996). Public incentives, such as regulations, cost-sharing, or incentive payments, may be needed to spur adoption in such areas, if it is not otherwise profitable. Models of crop-pest interactions are important for devising improved ecologically-based pest management strategies. More judicious use of pesticides could reduce environmental damage. Investment in soil quality is a central tenet of sustainable farming systems. Models elucidating the relative contributions of the components of soil quality to crop yield could help improve the design of sustainable farming systems.

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