Abstract—In Southeast Asia, durian is affectionately called
the king of fruit. Durian is the most popular crop planted in
eastern and southern of Thailand. The total crop is around
600,000 tons per year; among this, 500,000 tons of the total
production were exported worldwide. In Thailand, the
knowledge of durian production is based on experience from
generation to generation, especially the knowledge of durian
pests and diseases control. This paper presents the ontology
knowledge based for durian pests and diseases retrieval system.
The major contributions of the system consist of 1) the stored
knowledge of durian pests and diseases and 2) the diagnosis of
durian diseases and the suggestions for the treatments. The
ontology knowledge consists of 8 main classes: 1) diseases, 2)
pests, 3) cultivars, 4) symptoms of bunch, 5) leaf area
symptoms, 6) symptoms of the branches and trunk, 7)
symptoms of fruit, and 8) symptoms of root and growth. The
experimental results yielded 100% of precision, 88.33% of
recall, and 93.8% of overall performance.
Index Terms—Ontology, semantic web, durian cultivars, durian pests, durian diseases, information retrieval.
Porawat Visutsak is with the Department of Computer and Information Science, Faculty of Applied Science, KMUTNB, Bangkok, Thailand (email: firstname.lastname@example.org).
Cite: Porawat Visutsak, "Ontology-Based Semantic Retrieval for Durian Pests and Diseases Control System," International Journal of Machine Learning and Computing vol. 11, no. 1, pp. 92-97, 2021.Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).