A SURVEY OF MACHINE LEARNING ALGORITHMS FOR DISEASE CLASSIFICATION IN CROPS AND PLANTS
Mini Rani
M.tech, CSE Dept. RIMT University, Mandi Gobindgarh, Punjab, India , IN
Rupinder Kaur
M.tech, CSE Dept. RIMT University, Mandi Gobindgarh, Punjab, India , IN
Keywords: Machine Learning, Agricultural disease detection, Classification, Agricultural science, Algorithms.
Abstract
In the plants, fruits, and vegetables, the problem of infections can lead to the reduction in quantity and quality of the products. This infection can further affect the human health when they consume those infected products in their food intakes. Thus, it is important to detect the infections/diseases in the early stages so that the agriculture products can maintain the quality of the products. Previously, the farmers were using the approach of monitoring the crops continuously for any disease identification. This method was too time consuming and requires a lot of efforts from the farmer’s side. So, in recent years, researchers focused on this area and tried to improve the work using the machine learning. A number of algorithms and techniques were developed for machine learning to detect the disease on crops, fruits, and vegetables. The techniques used image processing, segmentation, and classification as their backend to achieve the desired goal. This paper presents the detailed review of recent machine learning algorithms that were applied to agriculture products to detect the diseases and infections and achieves great success. This paper also presents the techniques based on detection of diseases, their methodology, and achieved efficiency by previous researches till now
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