• Ramata Mosissa Gichila

Abstract: Coffee is one of the most important traded commodities in the Ethiopia. This means Coffee production and marketing are the means of livelihood for millions of households in Ethiopia. Coffee’s global value chains are quickly transforming because of shifts in demands and an increasing emphasis on product differentiation in importing countries. The aim of this research is to develop knowledge based system for coffee disease diagnosis and treatment that assists agriculture experts, development agents and whole the community to make timely decisions. The knowledge of coffee diagnosis was represented using production rule as if-then rules and implemented using swi prolog programming tool. Coffee diagnosis knowledge based system reasons using backward chaining inference mechanism. The inference engine identifies a type of coffee diseases as goals and checks the symptoms of coffee diseases caused by particular pathogens to diagnose the possible coffee disease and provide description and treatment knowledge determine its applicability in the domain area, the prototype Coffee has been evaluated by the domain experts through visual interaction based on the criteria of easiness to use, time efficiency, accuracy in diagnosing coffee diseases diagnosis and providing description and treatments. According to the evaluation through visual interaction 83.33% system performance is obtained.

Agriculture, Coffee, disease, KBS, AI

"Developing Knowledge Based System prototype for Coffee Disease Diagnosis and Treatment", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.319-324, June 2019, Available :http://www.jetir.org/papers/JETIR1907E47.pdf

"Developing Knowledge Based System prototype for Coffee Disease Diagnosis and Treatment", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp319-324, June 2019, Available at : http://www.jetir.org/papers/JETIR1907E47.pdf