Knowledge systems development in U.S. agriculture

Abstract Knowledge engineering involves simulating the problem solving logic of a human expert, group of experts, or a constructed “expert process.” It is the integration of assimilated information as knowledge with data. This is, in fact, the procedure used in human decision making. The potential capabilities for knowledge engineering to help solve ill-structured agricultural problems where information and data are incomplete has excited many scientists. However, knowledge engineering is in its infancy and is not ready for widespread, economically viable application to commercial agriculture. The state of the art for developing and using agricultural knowledge-based decision support “expert” systems is discussed; representative examples depicting areas that are most promising are presented, and specific examples from the authors' experiences are given. These are followed by comments on commercialization, pitfalls, needed developments, and prognosis.