Rice Disease

Rice diseases pose a significant threat to global food security, causing substantial yield losses and impacting millions reliant on rice as a staple crop. Current research focuses on developing rapid and accurate disease detection methods, primarily employing computer vision techniques such as convolutional neural networks (CNNs), including lightweight architectures like EfficientNet and MobileNet, and incorporating multispectral imaging to enhance diagnostic capabilities. These advancements aim to improve early disease detection, enabling timely interventions and minimizing crop damage, ultimately contributing to more efficient and sustainable rice production.