Deep Learning for Plant Disease Detection

Description

This research chapter explores into the burgeoning field of deep learning and its transformative application in detecting plant diseases, a critical challenge in agriculture. With the global population escalating, ensuring crop health and productivity is paramount for food security. Deep learning, an advanced artificial intelligence technique, offers a novel approach … This research chapter explores into the burgeoning field of deep learning and its transformative application in detecting plant diseases, a critical challenge in agriculture. With the global population escalating, ensuring crop health and productivity is paramount for food security. Deep learning, an advanced artificial intelligence technique, offers a novel approach to identifying plant diseases with unparalleled accuracy and speed. Deep learning has been successfully applied to detect various plant diseases, including apple scab and apple rot, cassava mosaic and brown streak diseases, grapevine powdery mildew, banana Fusarium wilt (Panama disease), and early blight in tomatoes. Through a comprehensive review of the literature, this study elucidates the principles of deep learning, focusing on Convolutional Neural Networks (CNNs) for image-based disease detection. It examines various case studies where deep learning models have been successfully implemented, showcasing significant improvements in detection rates and reduction in false positives. The chapter also addresses the challenges faced in data collection, model training, and the need for computational resources, proposing innovative solutions such as data augmentation and transfer learning to enhance model efficacy. Additionally, it explores future directions, including the integration of deep learning with other technological advancements like drones and IoT devices for real-time monitoring and diagnosis. This research underscores the potential of deep learning in revolutionizing plant disease detection, contributing to sustainable agriculture practices and ensuring food security in the face of growing environmental challenges. Read More