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AI-Driven Plant Science: Advancing Crop Performance Through Omics Integration and Physiology

Editat de Osamah Shihab Albahrey, Jameel R. Al-Obaidi
en Limba Engleză Paperback – feb 2027
AI-Driven Plant Science: Advancing Crop Performance Through Omics Integration and Physiology offers cutting-edge insights into the rapidly evolving fields of precision agriculture, Artificial Intelligence, plant biotechnology and genetic engineering, and bioinformatics. With a strong focus on applications in smart agriculture, crop improvement, and environmental adaptation, it bridges the gap between advanced research and practical implementation. The rapid advancements in AI and biotechnology have created both opportunities and complexities for the agricultural sector. This book fills a critical gap in the existing literature by providing a multidisciplinary resource that integrates AI, biotechnology, and agricultural science. While there are numerous resources on plant biology and AI individually, few works explore their synergistic potential in depth. This book offers actionable insights into how AI can revolutionize crop physiology, stress tolerance, and plant-based research. It also highlights the challenges and ethical considerations of integrating AI into agricultural practices, ensuring a balanced and forward-thinking perspective. AI-Driven Plant Science: Advancing Crop Performance Through Omics Integration and Physiology provides a definitive guide for researchers, industry professionals, and students seeking to understand and apply AI in plant science and crop production.

  • Integrates AI concepts with real-world case studies and actionable insights
  • Presents a broad and comprehensive exploration of AI application in plant science and crop breeding
  • Leverages emerging technologies in an applied approach
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Specificații

ISBN-13: 9780443451607
ISBN-10: 0443451605
Pagini: 285
Dimensiuni: 152 x 229 mm
Editura: ELSEVIER SCIENCE

Cuprins

Part 1: Foundations of AI in Plant Omics
1. The Future of Agriculture: AI Meets Plant Sciences
2. AI Fundamentals for Plant Research: Concepts and Applications
3. AI-Driven Systems Biology: Connecting Data for Plant Research

Part 2: Genomics, Breeding, and Epigenetics
4. Decoding Plant Genomes: AI in Sequencing and Annotation
5. AI-Assisted Breeding for Climate-Resilient Crops
6. Epigenetics and AI: Unlocking Gene Regulation in Plants

Part 3: Transcriptomics, Proteomics, and Metabolomics
7. Deep Learning in Plant Transcriptomics: Understanding Gene Expression Dynamics
8. AI in Plant Stress Biology: Predicting Adaptive Responses to Abiotic Stress
9. AI in Plant Proteomics: Mapping Protein Functions and Interactions
10. Metabolomics and AI: Pathways to Discovery
11. AI in Plant Pathology: Disease Resistance, Pest Control, and Weed Management
12. High-Throughput Phenotyping: AI in Action
13. AI for Sustainable Agriculture

Part 4: Future Directions and Ethical Considerations
14. Synthetic Biology and AI: Shaping the Future of Plant Biotechnology
15. Ethical, Regulatory, and Data Security Challenges in AI-Driven Plant Research