Development of Knowledge Based System for Wheat Disease Diagnosis: A Rule Based Approach

Abstract

Wheat production in Ethiopia is widely affected by diseases and attacked by a number of insect pests. Wheat disease diagnosis needs sufficient and knowledgeable agricultural experts to identify the diseases and describe the methods of treatment and protection at early stage of infestation. But, agricultural specialist assistance may not always available and accessible to every farmer when the need arises for their help. Hence, this study presents a rule based knowledge based system for wheat disease diagnosis in order to identify wheat disease timely and apply the control measures effectively. The system aims to provide a guide for research centers and development agents to facilitate the diagnostic process. To develop the system, data and knowledge are acquired from documented and non- documented sources. The acquired knowledge is modeled by using decision tree structure that represents concepts and procedures involved in the diagnosis of wheat disease. The system is developed using SWI Prolog programming language. The system has been tested and evaluated to ensure whether the performance of the system is accurate and the system is usable by research centers and development agents. The system has been registered overall performance of 87.78%. So, the developed system has potential to use as a decision tool for diagnosing and treating wheat disease.