AI-enhanced Plant Omics

This book presents methods for the application or integration of AI tools (including machine learning, deep learning, and generative AI) with plant omics approaches (including functional genomics, transcriptomics, proteomics, metabolomics, epigenomics, and other omics systems) and proposes AI-based strategies for crops resistant to diverse biotic and abiotic stressors and even complicated or multiple stress conditions. It aims to advance the construction of digital plant omics to assist future breeding for developing stress-resilient crops with high-yield and high-quality traits. The book is meant as a reference and a guide to AI technologies and is designed for students and researchers to efficiently overview these critical topics of plant science and technology and thus inspire ideas of future experiments. This book is the first to provide a comprehensive summary of AI-based strategies for constructing digital plant omics involving functional genomics, transcriptomics, proteomics, metabolomics, and epigenomics for developing digital plant biology at single-cell and spatial resolution. The book: Presents ways to apply AI approaches for advancing plant omics Summarizes AI-enhanced plant functional genomics Includes current achievements in developing stress-resilient crops Is essential reading for researchers and graduate students of crop science using omics methodologies