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- Author or Editor: P.H. Heinemann x
- HortScience x
Apple orchards are highly diversified and complex ecological and economic systems. Production is affected by a wide range of insects, diseases, weeds, and mammalian pests. The incidence of these pests is often dependant upon climatological effects; and the microclimate within orchards. An expert system, a form of artificial intelligence, has been developed and commercially released to apple growers that utilizes weather data to make recommendations regarding production decisions. Users of the system are instructed on how to establish a weather station, and to collect, and input weather data from the farm. The information is utilized to calculate disease infection periods and pesticide residues to arrive at a control recommendation. Other weather dependant modules include the scheduling of trickle irrigation as well as water application rates during a frost. An interactive demonstration of the system will be presented to the group.
Research is described on the development of an automated inspection system which uses digital images and artificial intelligence techniques. Procedures have been developed for evaluating size, shape, and color of apples, potatoes, and mushrooms. Current emphasis is being placed on developing algorithms for detection of surface defects. A major effort will also be expended toward the development of an overall “quality” score for automated inspection of fruit and vegetables. The automated results are compared with those obtained using conventional manual inspection methods. Apples, potatoes, and mushrooms are the primary crops being inspected although the algorithms and techniques are applicable to many different fruits and vegetables. Color and monochromatic image processing components in “MS-DOS” and “Macintosh” computers are being used in this study.