Prototype Knowledge Based System for Land Suitability Prediction for Coffee Production in Afaan Oromoo

Abstract

Agriculture is one of the world’s most important activities that support human life. It includes crop production, horticulture, agricultural engineering, forestry, animal husbandry and fishery science. Among crop production, coffee production is paramount because millions of small producers rely on coffee for living in various countries. However, factors such as selecting suitable land for coffee plantation affects coffee production. In Ethiopia, 25% of foreign exchange is from coffee, of which more than 64% comes from Oromia Regional State. The main objective of this study was to develop a prototype knowledge based system for land suitability prediction for coffee production in Afaan Oromoo. To develop the proposed system, experimental research design was used. The study sites were Ministry of Agriculture, Jimma University College of Agriculture and Veterinary Medicine, Gomma and Mana Agricultural Offices. Data was collected from study sites using systematic sampling technique. Moreover, interview and document analysis were employed as data collection methods. Visual prolog v7.3 software was used for the systemdevelopment. As a result, the developed system can help professionals, land managers, investors and farmers to identify suitable land for coffee production because it can categorize the suitability of land for coffee plantation into high, moderate or marginally suitable in Afaan Oromoo, an official language of Oromia Regional State. The system can contribute significantly to increase coffee production and quality and thus we recommend the implementation of this system.