graphs from remotely sensed vegetation indexes has the potential to better inform growers of the approaching harvest date. Within the field, relative differences in the vegetation index can show whether a crop is developing uniformly at any one time or over the growing season. The aerial image shown is a computer enhanced green vegetation map of a 140-acre cantaloupe field. Ten meter resolution aerial images of the field have been acquired eight times over the summer. Data collected from sites with varying levels of crop growth have been extracted from the images to show the pattern of their development (see graphs Changes in Crop Growth). The graphs illustrate how seasonal progression in crop canopy growth can be tracked for five sites that initially are at different growth performance levels (i.e., 20 percent initial greenness). Changes in the growth rates of each site are seen clearly as are changes in the relative ranking late in the season of sites at 80 percent and 60 percent initial greenness. The crop relative growth rate declines when the growth shifts to fruit production. Superimposed on the crop development graphs are key dates showing the relationship between crop condition and management decisions. Seasonal changes in plant cover and biomass can be linked to predictions of future crop growth, harvest timing, and yield estimates. When these kinds of data are used in a crop production model it can assist in farm management decisions. This capability will be important in irrigated agriculture as producers could manipulate water inputs or fertilizers to advance or slow down crop maturity. The ability to follow changes in crop development for specific field locations is an emerging area of precision agriculture.

Precision agriculture strategies attempt to adjust field practices to accommodate known variability of important factors. As practiced today, precision agriculture is primarily based on a few parameters, such as soil nutrients or weed maps. Understanding the impact of multivariate interactions is a challenge to both producers, consultants, and scientists. The amount and complexity of available information has increased at a phenomenal rate. Growers will have access to large databases, but the ability to extract useful information will have to be developed. Agriculturists may find themselves uncertain about what information to use and how it can add value to production systems.

Systems Approach

Crops are integrators of the biophysical environment within a field. Crops express their genetic potential and reaction to local soil, pest, and climatic conditions



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