A Study on Leaf Disease Detection Using Machine Learning

India is an agricultural nation, hence the rate of crop output there is cause for concern. Lower crop yields result in higher food prices and a hunger problem for people. Deep learning models so seek to raise crop yield rates and decrease plant disease infections. They might even help farmers with technology in the process. Food security may be compromised by a number of diseases that significantly reduce agricultural output. Accurately detecting plant ailments is so essential and crucial. The subjective, labor-intensive laboratory testing and visual observation that characterize conventional classification systems have many disadvantages. Plant pathologists use optical methods to observe diseased leaves in plants in order to diagnose illnesses in plants, which is the current acknowledged method. This is so that most plant diseases may be identified by their outward symptoms. The difficulty of the disease diagnosis process when done manually plus the fact that the pathologist's skill level determines how successful the diagnosis will be making this a good problem for computer-aided diagnostic systems. Plant diseases cause an annual loss of thirty-five percent of India's crop yield. Due to inadequate lab equipment and comprehension, early plant disease identification is still challenging. Our study delves into the potential use of computer vision methods for early and scalable detection of plant diseases. When productivity is prioritized over the ecological effects of input resources, the environment deteriorates. Pesticides and fertilizers are the primary source of production expenses and environmental degradation. By keeping a check on leaf area, leaf disease, and chlorophyll content, it is possible to effectively utilize that contribution. Different diseases that harm plants through their leaves can have a detrimental effect on agricultural productivity and lead to losses in money. Reduction of both the amount and quality crucial accelerating plant growth increasing crop harvests. It can be challenging for researchers and farmers alike to recognize diseases in plant leaves. Both the economy and public health are negatively impacted by the pesticides that farmers now use on their crops. To identify these plant diseases, a few approaches applied. In this paper we studied a number of plant diseases and new techniques for diagnosing them.