A knowledge-based expert system for planning and design of agroforestry systems

Abstract

Computer-based Expert Systems that use knowledge, facts, and reasoning techniques to solve problems, normally requiring the abilities of human experts, are increasingly being used in many activities. The United Nations University (UNU) Agroforestry Expert System (AES) is a first attempt to apply this technique to agroforestry. UNU-AES is a prototype Knowledge-Based Expert System (KBES) designed to support land-use (agricultural, forestry, etc.) officials, research scientists, farmers, and individuals interested in maximizing benefits gained from applying agroforestry management techniques in developing countries. This prototype addresses the options for alley cropping, a promising agroforestry technology which has potential applicability when used under defined conditions in the tropics and subtropics. Alley cropping involves the planting of crops in alleys or interspaces between repeatedly pruned hedgerows of fast-growing, preferably leguminous, woody perennials. The primary benefits from this technique include nutrient enrichment, soil improvement, and erosion control. UNU-AES, which is the first known attempt at the application of expert system procedures in the field of agroforestry, uses a total of 235 decision rules to develop its recommendations. With the inclusion of more climatic and socio-economic data and improved advisory recommendations, UNU-AES can be expanded to provide advice on alley cropping in more diverse geographical and ecological conditions and eventually address other agroforestry techniques.