Abstract
Mango is one of the world’s most important fruits of the tropical and subtropical countries and cultivated extensively as a commercial fruit crop. The mango fruit crop is also cultivated in all parts of Ethiopia. Mango trees in most parts of Ethiopia are developed from seedlings and are inferior in productivity and in fruit quality. Mango tree is attacked by different insects and diseases. With an end goal to address such issues and problems it is very essential to develop knowledge-based system that can provide advice for agriculture professionals and farmers to make possible diagnosis and treatment of mango diseases.
The aim of this study was developing knowledge based system for diagnosis and treatment of mango disease. Ambo Plant Protection Research Center and Assosa plant health clinic were selected area for data collection. Purposive sampling technique was utilized to choose domain experts for knowledge acquisition. In this way, in order to develop the proposed knowledge based system an implicit and explicit knowledge utilized and acquired through interview and document analysis respectively. The knowledge acquired through document analysis and interview is modeled using decision tree. The researchers used experimental research design to developed prototype system. The experiment was conducted using rule based technique. Finally, performance testing and user acceptance evaluation were performed. The performance according to the domain expert’s evaluation is scored total of 81.8% and the user acceptance testing scored 86.29% performance. The overall performance of the system is 84.05%. The prototype system meets the objectives of the study. Updating the rules in the knowledge base of the system automatically, developing the system in local language with well designed user interface and applying other techniques are the future works of the study.
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Birhanie, W., Tegegne, T. (2019). Knowledge Based System for Diagnosis and Treatment of Mango Diseases. In: Mekuria, F., Nigussie, E., Tegegne, T. (eds) Information and Communication Technology for Development for Africa. ICT4DA 2019. Communications in Computer and Information Science, vol 1026. Springer, Cham. https://doi.org/10.1007/978-3-030-26630-1_2
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