SIMULATION OF A PREDICTIVE MODEL FOR THE CLASSIFICATION OF BACTERIAL DISEASES AFFECTING RICE PLANT USING FUZZY LOGIC

Abstract

This project is based on Simulation of a Predictive Model for The Classification of Bacterial Diseases Affecting Rice Plant Using Fuzzy Logic. The likelihood of detecting disease sooner or before a diseased plant is symptomatic is a key outlook in this work. This project aims to apply fuzzy logic model to the classification of bacterial diseases affecting rice plant based on information about symptoms observed from part of the rice plant. In order to achieve its aim and objectives, a review of the literature was conducted in order to identify the bacterial diseases affecting rice plant in Nigeria alongside symptoms associated with the risk of the bacterial diseases. Formulate the fuzzy logic by the fuzzification of the symptoms. The fuzzy logic model was simulated using MATLAB R2018 software. The predictive model developed will provide a means of early warning signal required for averting damages caused by bacterial infection. The resulting model will reduce the damage caused by bacterial diseases which affect rice and thus mitigating waste.

This would improve the detection of related diseases affecting the rice plant thereby improving the productivity of the plant. It is recommended that the system is improved upon to increase the scope and productivity of the system.