Enhancing Paddy Leaf Disease Detection and Classification Through Advanced AI Techniques

Abstract

Rice (Oryza sativa) is the third highest produced crop in the world. Rice is a newlinestaple food for over one-fifth of the global population, providing a rich source of calories. newlineAgriculture has a major role in feeding the global population, with paddy being one of newlinethe most significant crops for ensuring food security. Paddy crops are highly susceptible newlineto various diseases that can severely impact yield, quality and farmers livelihoods. newlinePathogens such as bacteria, fungi and viruses can cause diseases in plants that drastically newlineaffects the harvest. To avoid the losses and achieve more yields on crops, it is necessary newlineto diagnose the diseases as early as possible. According to the Food and Agriculture newlineOrganisation (FAO), these diseases can cause yield losses ranging from 10% to 30% in newlinepaddy crops. Agricultural officers or external specialists must manually inspect and newlineprovide corrective measures for this problem. Still, due to lack of resources, other experts newlineare unable to visit the field on a regular basis. A study by the Indian Council of Agriculture newlineResearch (ICAR) estimated that disease caused by bacteria, fungus, viruses and other newlineenvironmental factors causes annual yield losses of around 15% to 20% in paddy crops newline