Overview

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 agriculture, greenhouse management and strategies for stress-smart and sustainable precision agriculture. This book offers an ideal reference for readers in a range of research fields in plant biology, plant pathology, and agricultural crop sciences. It is designed to be an inspiration for new ideas and future experiments to advance the progress of stress-smart and sustainable agriculture.

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9781836991106

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Dr. Jen-Tsung Chen is a professor of cell biology at the National University of Kaohsiung in Taiwan. He teaches cell biology, genomics, proteomics, plant physiology, and plant biotechnology. Dr. Chen's research interests include bioactive compounds, chromatography techniques, plant molecular biology, plant biotechnology, bioinformatics, and systems pharmacology. He is an active editor of academic books and international journals to advance the exploration of multidisciplinary knowledge involving plant physiology, plant biotechnology, nanotechnology, materials science, ethnopharmacology, and systems biology. He serves as an associate editor, editorial board member, and guest editor in reputed journals. Dr. Chen has published books in collaboration with international publishers and is currently handling book projects on diverse topics, including AI technologies, drug discovery, drug development, herbal medicine, medicinal biotechnology, nanotechnology, bioengineering, plant functional genomics, plant speed breeding, epigenetics, functional RNAs, and CRISPR-based genome editing. Dr. Chen is a productive author in academic publications and was recognized as one of the World's Top 2% Scientists between 2023 to 2025 by Elsevier and Stanford University. Dr. Chen received the Springer Nature Editor of Distinction Award in 2025.

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