The Future of Plant Health: A Vision for Genetically-Inspired Image Processing and Deep Learning for Sustainable Crop Protection

Plant disease detection is a critical agricultural management aspect affecting crop yields and food security. Plant diseases significantly threaten global agriculture, leading to substantial economic losses and food security concerns. For efficient disease control and crop protection, plant diseases must be promptly identified and monitored. The novel application of genetic algorithms and image segmentation methods to plant disease detection is the subject of this study. Genetic algorithms, which draw inspiration from natural selection, have demonstrated potential for improving feature selection and parameter tuning, among other elements of illness detection systems. On the other hand, early intervention is made possible by the accurate identification of disease-affected areas in plant through the use of image segmentation. The survey explores integrating these methods for plant disease detection, addressing challenges like environmental factors and data quality. This review is a valuable resource for researchers, practitioners, and policymakers in agriculture for effective plant disease management.