Publication

Abstract : Agriculture is one of the main sources of our economic system. If plant leaves are infected by microorganisms, it will definitely affect the production of crops and can also succumb to huge agricultural losses. It can also cause a reduction in the quality of the crops. Therefore, identification of plant and leaf diseases is very crucial. Usually, farmers use pesticides on plants to kill the bacteria which is not healthy. To detect these leaf diseases, a few techniques have already been provided. In this paper, different techniques like RGB to HSI conversion, k-means clustering, GLCM, and SVM classifiers are used. The genetic algorithm is used for calculating fitness factors and the selection of offspring and also helps to improve the quality of production. The accuracy of the classifier was found using the confusion matrix where the overall accuracy value was around 93.5%. The qualities of different leaves were also found which further can be used to produce offsprings.