Ai-Driven Plant Science

Advancing Crop Performance Through Omics Integration and Physiology
Erscheinungsjahr 2027
ISBN: 978-0-443-45160-7
Verlag: Elsevier Science

Buch, Englisch, 285 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 449 g

AI-Driven Plant Science traces the convergence between plant biology and artificial intelligence, connecting molecular data to breeding decisions and breeding decisions to sustainable outcomes. It opens with the genomic and epigenetic foundations of crop improvement, looking at how AI-based sequencing tools speed up genome annotation and how predictive models help identify which breeding lines are worth pursuing for climate resilience. The narrative then moves into the layers of gene expression and function, following the flow of biological information through transcriptomics, proteomics, and metabolomics, supported by bioinformatics pipelines built to handle that scale of data, and showing how integrative approaches are beginning to explain why two plants with near-identical genomes can respond so differently under the same stress.
From the lab, the book moves to the field where AI supports disease and pest management, high-throughput phenotyping, and sustainable agricultural practice, translating molecular insight into decisions that affect real crops under real environmental pressures. A closing section looks ahead to synthetic biology's role in plant biotechnology, alongside the ethical, regulatory, and data-security questions that accompany these technologies' expanding presence in agricultural research.
With contributions from specialist groups across Asia, the Middle East, and Europe, the volume offers a coherent perspective for researchers, industry professionals, and students seeking to understand how computational methods are changing the questions plant science can ask, and the speed at which it can answer them.

Autoren/Hrsg.

Al-Obaidi, Jameel R.

Albahrey, Osamah Shihab

Fachgebiete

• Naturwissenschaften Biowissenschaften Biowissenschaften Genetik und Genomik (nichtmedizinisch)
• Naturwissenschaften Agrarwissenschaften Ackerbaukunde, Pflanzenbau
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
• Technische Wissenschaften Technik Allgemein Technik: Allgemeines
• Naturwissenschaften Agrarwissenschaften Agrarwissenschaften
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Primärer Sektor

Inhaltsverzeichnis

Part 1: Foundations of AI in plant science
1. The future of agriculture: AI meets plant science
2. AI-driven systems biology: connecting data for plant research

Part 2: Genomics, breeding, and epigenetics
3. Decoding plant genomes: AI in sequencing and annotation
4. AI-assisted breeding for climate-resilient crops
5. Epigenetics and AI: understanding gene regulation in plants

Part 3: Transcriptomics, proteomics, and metabolomics
6. Deep learning in plant transcriptomics: understanding gene expression dynamics
7. AI in plant proteomics: mapping protein functions and interactions
8. Metabolomics and AI: pathways to discovery
9. AI in plant pathology: disease resistance, pest control, and weed management
10. High-throughput phenotyping: applications of AI
11. AI for sustainable agriculture

Part 4: Future directions and ethical considerations
12. Synthetic biology and AI: shaping the future of plant biotechnology
13. Ethical, regulatory, and data-security challenges in AI-driven plant research

Über Autor(innen)

Al-Obaidi, Jameel R.
Jameel R. Al-Obaidi obtained his PhD in molecular biology from the University of Malaya, Malaysia. He then worked at the National Institutes of Biotechnology, Ministry of Science, Technology and Innovation, Malaysia, first as a senior research officer and later as research director. He is currently a senior lecturer in the Department of Biology, Faculty of Science and Mathematics, at Universiti Pendidikan Sultan Idris. Dr. Al-Obaidi's research interests span molecular biology, proteomics, protein markers, metabolomics, bioinformatics, plant disease, and edible mushroom research. He has published widely in peer-reviewed journals and contributed to several books, and has received local and international grants supporting his involvement in national and international research projects. Dr. Al-Obaidi serves as an editor for PLOS ONE, BMC Molecular and Cell Biology, PeerJ, and the Journal of Tropical Medicine, and reviews for several other high-impact international scientific journals.

Albahrey, Osamah Shihab
Osamah Shihab Albahrey is an accomplished academic and researcher specializing in artificial intelligence, with a focus on decision support systems, machine learning, deep learning, and multicriteria decision-making. Dr. Albahrey currently serves as a Course Coordinator and Lecturer at various Australian institutions, including the Australian Technical & Management College (affiliated with Western Sydney University and Federation University), the Victorian Institute of Technology, and the Melbourne Institute of Technology. He is also a Research Fellow at the National Energy University in Malaysia, contributing to advanced research in fuzzy multi-criteria decision analysis techniques for energy studies. He earned his PhD in artificial intelligence from Sultan Idris Education University in Malaysia, a master's in computer science and communication from the Arts, Sciences and Technology University in Lebanon, and a bachelor's in computer science from Al-Turath University College in Iraq. Dr. Albahrey has published extensively in leading journals indexed in the Web of Science, covering topics from trustworthy AI models to healthcare informatics and energy system integration. His editorial contributions include peer review for leading international journals and academic editorship at several prestigious publications.