Detection and Control of Disease Affecting Cash Crops with YOLO model

Cash crops are vital for farmer livelihood and national economy, but are perpetually threatened by pathogens that can cause catastrophic yield losses. The works in this comparison leverage the real-time object detection capabilities of the YOLO (You Only Look Once) model to provide automated, rapid, and accurate identification of crop disease symptoms from visual crop data acquired with drones, robots, or smartphone imagery. The impact of deploying such technology is transformative, enabling early and precise disease detection that facilitates timely, targeted interventions. These efforts seek to move agricultural practice away from broad-spectrum pesticide application towards precision agriculture. They minimize chemical usage, reduce environmental impact, and protect crop yields. Advancing research in this direction ensures crops safety, which directly supports the economic stability of farmers and bolsters the resilience of the agricultural supply chain against biotic stresses.