This book summarizes advancements in artificial intelligence (AI) technologies, particularly for applications in plant research. It discusses agricultural applications, including AI-enabled smart agriculture and speed breeding, as well as ethical considerations of AI applications in plant sciences and agriculture. It focuses on the application of AI in omics-based plant sciences and crop breeding; digital technologies used in farming, smart agricultural practices, and basic knowledge of AI tools and applications in disease classification and detection.
This book provides information on techniques to use AI tools in plant biological research and agricultural applications. It is a solid reference for a wide range of readers, including students, researchers, lecturers, and professors in all sub-fields of plant sciences and agriculture.
Preface.
1. Artificial Intelligence for Biological Sciences: An
Overview.
2. Technical Advancements and Emerging Applications of Artificial
Intelligence in Plant Research.
3. Advances in Artificial Intelligence for
Plant Systems Biology.
4. Integrating AI with Plant Functional Genomics.
5.
Digital Plant Phenomics: Next-Generation Plant Phenotyping Based on
Artificial Intelligence.
6. Artificial Intelligence Approaches for Analyzing
and Interpreting Visual Data in Plant Biology.
7. Artificial
Intelligence-Assisted Genomic Prediction for Plant Breeding.
8. Artificial
Intelligence for Plant 3D Spatial Omics: Current Achievements and Future
Directions.
9. Artificial Intelligence-Accelerated Crop Improvement.
10.
Plant Morphology and Species Identification Based on Artificial Intelligence
Tools.
11. Artificial Intelligence for Advancing Plant Genome Editing and
Precision Breeding.
12. Artificial Intelligence Approaches in Plant Digital
Multiple Omics.
13. Uncovering Complicated Plant Biological Networks Through
the Assistance of Artificial Intelligence Tools.
14. Artificial Intelligence
for the Management of Plant Factories.
15. Simulation Intelligence Approaches
in Plant Sciences.
16. Artificial Intelligence Approaches for Uncovering
Plant-Microbial Interactions.
17. Organizing Smart Digital Agriculture Based
on Artificial Intelligence.
18. Plant Disease Diagnosis Based on Artificial
Intelligence Technologies.
19. AI-Enabled ChatGPT and Large Language Models
in Plant Research.
20. Machine Learning for Studying Plant Protein Function
and Evolution.
21. Artificial Intelligence in Omics-Assisted Crop Breeding
and Genetic Enhancement.
22. Low Carbon Transition in the Food System through
Machine Learning-Enhanced Energy Efficiency.
23. Deep Learning:
Revolutionizing Data-Driven Science in Plant Research.
24. Machine Learning
in Plant Biology: Fundamentals and Applications.
Dr. JenTsung Chen is a professor of cell biology at the National University of Kaohsiung in Taiwan. He also teaches genomics, proteomics, plant physiology, and plant biotechnology. His 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 journals to advance the exploration of multidisciplinary knowledge involving plant physiology, plant biotechnology, nanotechnology, ethnopharmacology, systems biology, and drug discovery. He serves as an editorial board member and a guest editor in several reputed journals. He published books in collaboration with international publishers on diverse topics such as drug discovery, herbal medicine, medicinal biotechnology, nanotechnology, bioengineering, plant functional genomics, plant speed breeding, CRISPRbased plant genome editing, and artificial intelligence. In 2023 and 2024, Stanford University/Elsevier included Dr. Chen in the "Worlds Top 2% Scientists.
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