Developing Self-Learning Knowledge Based System for Predominant Chicken Diseases Diagnosis, Prevention and Management

Abstract

Poultry diseases remain one of the major threats to poultry production worldwide. Chicken disease need to be observed intensively because of its impact on the health and quality of chicken production. Chicken disease becomes one of the problems that are very detrimental to chicken farmers. In attempt to solve this problem, knowledge based system is identified as a powerful tool with extensive potential in alleviating agricultural and medical problems. This study aims at developing knowledge base system for diagnosing, prevention and management of predominant chicken diseases. Design science research method was used to develop the prototype system. The domain experts were selected by purposive sampling technique from Jimma University College of Agriculture and Veterinary Medicine and from Kito Furdisa Poultry Farm of Jimma University for knowledge acquisition. The knowledge was acquired using both structured and unstructured interviews. The acquired knowledge was modeled and represented using decision tree and production rules (If-Then-Action). Backward chaining algorithm was used in this study. At the end performance of the system was evaluated and produced a result of 83%. In addition, user acceptance of the developed system was found to produce 83.4%. Thus, the average performance of the prototype system was 83.2%. The prototype system achieves a very good performance and meets the objectives of the study. And thus it is strongly recommended that the stake holders take part in deploying the developed system.