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Full Description
Cutting-Edge Agri-Technologies for Next-Generation Farming explores how emerging innovations such as nanotechnology, genome editing, artificial intelligence, precision agriculture, and smart sensing systems are reshaping modern food production. Bringing together insights from leading global experts, this volume presents interdisciplinary perspectives on improving crop productivity, enhancing resource-use efficiency, and strengthening resilience to climate change. It offers a holistic roadmap for developing sustainable, technology-driven farming systems that balance economic viability with environmental stewardship. Designed for researchers, policymakers, students, and industry professionals, this book serves as a comprehensive reference for advancing the future of agriculture through science-based innovation.
Contents
Preface. Section I: General 1. Nanotechnology and AI in Next-Generation Agriculture. Section II: Novel Nanotechnologies for Shaping Farming 2. Nanomaterials in Agriculture: Enhancing Soil Health and Plant Growth. 3. Seed Nanopriming for Sustainable Crop Production. 4. Emerging Nanopesticides: Opportunities and Challenges. 5. Nanofertilizers for Sustainable Agriculture: Limitations and Future Trends. 6. Next-Generation Farming: Crop Monitoring with Nanosensor Technologies. 7. Nanobiotechnology for the Management of Plant Diseases. 8. Nanotechnology for Plant Growth Promotion and Stress Tolerance. Section III: CRISPR-Cas9 Technology 9. CRISPR-Cas9 Editing Technology: Concept, Applications, and Prospects for Agriculture. 10. Genome Editing in Cereal Crops Using CRISPR-Cas9 Technology. 11. Genome Editing of Horticultural Crops Using CRISPR/Cas for Enhanced Improvement. 12. Opportunities and Challenges of CRISPR/Cas Systems in Crop Breeding. Section IV: Artificial Intelligence Technology 13. Introduction to the Application of Artificial Intelligence-based Solutions in Agriculture. 14. Deep Learning for Crop Improvement. 15. Precision Farming and Decision Support Systems, Utilizing Convolutional Networks for Plant Detection. 16. Leveraging Artificial Intelligence for the Detection, Monitoring, and Forecasting of Plant Diseases. 17. Application of AI in Identification of Pests and Weeds. 18. Ethical and Social Implications of AI in Agriculture. Index. Editors' Biography.
