An automated crop assessment method based upon a photo-diode array sensor and a micro-computer analyzer is examined. This method exploits the visual damage patterns, from biological infestations, found on the leaves of the crop. Current techniques take a leaf sample along a field diagonal for laboratory analysis, after a problem is determined. This method, because of its reliance upon the farmer visually detecting crop damage, gives pathogens a change to become established. Once established, the extensive use of expansive wide area fungicides, herbicides, and pesticides is required to eradicate the pathogen. The fungus Verticillium Albo-atrum will be used because of its well-documented effects on leaves and its ease-of-handling. Objectivess are (1) to determine the ability of an automated sensor to detect Verticillium Albo-atrum, (2) to determine the automated sensors' resolution requirements; and (3) to determine the sensors performance in relation to human beings.
