Abstract
The development of expert systems in agriculture consists of many steps such as problem definition, selection of experts, audience considerations, knowledge representation, coding, testing, and feedback. The problem definition and selection of experts for the problem domain are the foundation of a working system. Audience definition, economics and goal setting are areas that must be documented before knowledge engineering. Knowledge representation methods and system conceptual layout are the next level of development. The use of the user feedback and field testing data to improve the system are often overlooked. Benefits of expert systems for on farm decision making include education, efficiency, and adaption to changing regulations. Many aspects of agricultural expert systems are similar to traditional expert systems; yet special problem inherent in agriculture make the development interesting and challenging.
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