AI in Plant Science and Precision Agriculture
CRC Press (Verlag)
978-1-032-88989-4 (ISBN)
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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.
Dr. Jen‑Tsung 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, CRISPR‑based plant genome editing, and artificial intelligence. In 2023 and 2024, Stanford University/Elsevier included Dr. Chen in the "World’s Top 2% Scientists.
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.
| Erscheint lt. Verlag | 19.3.2026 |
|---|---|
| Zusatzinfo | 40 Tables, black and white; 16 Line drawings, black and white; 36 Halftones, black and white; 52 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 210 x 280 mm |
| Themenwelt | Naturwissenschaften ► Biologie ► Botanik |
| Technik ► Umwelttechnik / Biotechnologie | |
| Weitere Fachgebiete ► Land- / Forstwirtschaft / Fischerei | |
| ISBN-10 | 1-032-88989-6 / 1032889896 |
| ISBN-13 | 978-1-032-88989-4 / 9781032889894 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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