Deep Learning

The burgeoning fields of plant science and agriculture are undergoing a profound transformation driven by the advent of deep learning. This powerful subset of artificial intelligence is enabling researchers to extract unprecedented insights from increasingly large and complex biological datasets, ushering in an era of data-driven discovery and application. This chapter provides a comprehensive review of how deep learning is revolutionizing various aspects of plant research, from high-throughput phenotyping and accurate disease detection to precise yield prediction and insightful genomic analysis. It delves into the specific deep learning architectures and techniques being employed, the types of data utilized, and the tangible impacts on accelerating scientific understanding and developing sustainable agricultural practices. Furthermore, we critically examine the current challenges faced in integrating deep learning into plant science workflows and explore promising future directions that will continue to shape the landscape of plant research in the years to come.