Deep Learning in Plant Science and Agricultural Biotechnology

This book introduces the fundamentals of deep learning models and their current applications in a diverse range of subtopics in plant sciences and agriculture.Areas covered include: functional genomics, multiple omics, stress physiology, plant disease diagnosis, plant—microbe interactions, and high—throughput technologies (phenotyping and synthetic biology).Deep—learning models are also being used in developing pest and weed control strategies, the use of unmanned aerial vehicles in agricul...