Advance Machine Learning Techniques Used for Detecting and Classification of Disease in Plants: A Review

Abstract

Today one of the major threats for agriculture sector is the crop disease that causes big losses to the farmers. In India where maximum share of population, which is around 70% of the total, is indulged in agriculture for its livelihood. Consequently, agriculture has big role to play in Indian economy. Major concern of a farmer has always been the health of his crop. With the growth of crop plants can get viral, fungal or bacterial infection which can spread in large area of farms. To overcome and control this spread of infection farmers need expert advice so that right kind and correct amount of antibacterial, antiviral or antifungal spray can be done in farms. Earlier this process was manual but now by using various machine learning and deep learning techniques this process of detecting and classifying plant disease has been automatized. Various models have been developed by many researchers for plant disease detection and classification process. Aim of this paper is to review these models so that their potential and significance can be conveyed to agriculture sector.