Biography

Shital Patel, Department of Obstritics and Gynaecological Nursing, Sumandeep Nursing College, Sumandeep Vidyapeeth deemed to be University, Vadodara, Gujarat, India, patelshital512@gmail.com Plant diseases put global food security at risk bydrastically lowering agricultural productivity. Conventional diagnostic techniques mostly rely on professional eye assessment, which is subjective and timeconsuming. Deep learning (DL) [7]and machine learnin (ML) have become popular tools for automated plant disease prediction and diagnosis in recent years. High accuracy, generalization across a variety of circumstances, and the interpretability of model decisions a crucial component for agronomists and farmers to adopt remain difficult to achieve. In order to solve these issues, hybrid ensemble learning frameworks that integrate several models with explainability procedures have showed potential. This review of the literature highlights the contributions, constraints, and future directions of important advancements in explainable AI (XAI)[8] integration, hybrid frameworks targeted at agricultural improvement, and ensemble learning for plant disease prediction. Plant diseases significantly reduce agricultural productivity, endangering the world's food security