An ontology-based decision support system for insect pest control in crops

Abstract

Agriculture provides most of the world’s food that helps to sustain and enhance human life. Diseases infections and insect pest in crops cause considerable economic losses. Diagnosing or defining the type of insect pest or disease that affects the crop is not an easy task for farmers, even more, when the diversity of insects and diseases is quite numerous. There is a need for tools focused on the knowledge management of experts capable of providing guidelines for the diagnosis and prevention of insect pests. This work presents an ontology-based decision support system for insect pest control in sugarcane, rice, soya, and cacao crops. This system takes advantage of Semantic Web technologies to represent the experts’ knowledge as well as to apply semantic reasoning to diagnose the insect pest that affects the crop. This system was evaluated to measure its efficacy regarding the diagnosis of the insect pest that affects a crop obtaining encouraging results.