Deep Learning for Plant Disease Detection and Identification

Plant diseases pose a significant threat to farming operations and food supply chains by exposing crops to harmful pathogens, thereby affecting the livelihoods of those involved. The swift progress in deep learning (DL) has revolutionized conventional methods for detecting plant diseases, providing unmatched levels of accuracy, speed, and scalability. This chapter explores the identification of various plant diseases such as blight, rust, leaf spot, and powdery mildew. Advanced image augmentation, data balancing, and feature extraction can contribute to the resilience of the models. The implementation of automated leaf disease diagnosis using the Internet of Things, DL, and artificial intelligence sensors is being explored for enhanced analysis and detection. Data visualization through recurrent neural networks and convolutional neural networks models established excellent milestones for plant diseases, alterations with gene regulation, and ion concentration spectrum differences in tissues of plants. This chapter provides a concise draft of plant pathogen detection through modern DL techniques.