The concept of using information about variability to manage specific sites in a field is not new. Farmers of ancient times were keen observers of crop performance and recognized benefits from spreading different amounts of manure and liming materials on different kinds of soils (Kellogg, 1957). In the 1620s, colonists observed site-specific fertilizer practices of Indian farmers who placed fish directly at the roots of each corn plant. In 1929, researchers Bauer and Linsley suggested marking a field in 3-foot pace intervals in the north-south and east-west directions to determine field position for variable application of limestone materials (Goering, 1993). Today's information technologies have the potential to generate more sophisticated assessments and responses to within-field heterogeneity and variation in soil fertility.
Uniformity trials have been used to study soil heterogeneity by simply planting a crop that was uniformly managed throughout the growing season. The field was divided into small segments and crop yield was measured on each segment. Crop yield variability among segments was the measure of varying levels of soil fertility in the field. Crop yields obtained from a uniformity trial were plotted on a map, and field segments having similar yields were connected by smooth lines. These yield maps were interpreted as soil fertility contour maps. LeClerg et al. (1962) made two general conclusions from these early uniformity trials:
Soil fertility variations are not distributed randomly but are to some degree systematic; that is, contiguous field segments are more likely to be alike than are segments separated by some distance.
Soil fertility is seldom distributed so systematically that it can be described by a mathematical formula.
A common strategy in soil fertility management is to match fertilizer inputs with crop needs. The goals of this mass balance approach are to increase nutrient uptake efficiency and minimize fertilizer losses. Fertilizer rate recommendations for immobile nutrients (i.e., phosphorus, potassium, and zinc) are based almost entirely on soil test levels calibrated for a specific crop, soil type, and climate. Nitrogen fertilizer rates are based on estimates of yield potential (average or spatial) with corrections or credits for nitrogen in soil profile, legume, manure, and soil organic matter sources. Recently, producers have been encouraged to adjust timing of fertilizer applications to reduce environmental risks. For example, nitrogen losses due to leaching can be reduced by minimizing the time between application and plant uptake (Killorn et al., 1995). Conventional approaches to soil testing based on averages are inadequate for characterizing temporal and spatial variation of soil properties.
The most widely used precision agriculture technique is probably the management of soil nutrients and pH. Precision management of soil nutrients can increase profit in two ways. The first is improved crediting of residual nutrients