Buch, Englisch, 596 Seiten, Format (B × H): 191 mm x 235 mm
Enhancing Crop-Water Productivity and Soil Health
Buch, Englisch, 596 Seiten, Format (B × H): 191 mm x 235 mm
ISBN: 978-1-041-37139-7
Verlag: Taylor & Francis Ltd
This book examines artificial intelligence applications in smart fertilization and soil health management for sustainable agriculture. It covers AI-driven approaches including machine learning models, robotics, and decision support systems for nutrient optimization, and also:
- Offers Comprehensive coverage of artificial intelligence applications in smart fertilization including machine learning models, robotics, and AI-powered decision support systems for nutrient optimization and sustainable agriculture.
- Examination of AI integration with Internet of Things (IoT), smart sensors, remote sensing, Geographic Information Systems (GIS), cloud computing, and blockchain technologies for precision fertilizer application and soil health monitoring.
- Addresses climate-smart agriculture strategies including drought resilience, carbon footprint mitigation, and AI-optimized fertilizer application for environmental sustainability and resource conservation.
- Discusses big data analytics and geospatial AI for mapping soil fertility, water productivity, and site-specific nutrient management in crop production systems.
- Covers AI-enabled fertigation systems, real-time soil moisture and nutrient monitoring, and data-driven strategies for reducing fertilizer runoff and preventing soil degradation
This title has been co-published with Elite Publishing House. T&F does not sell or distribute the print versions in India.
Zielgruppe
Academic, Postgraduate, and Undergraduate Advanced
Autoren/Hrsg.
Fachgebiete
- Geowissenschaften Geologie Bodenkunde, Sedimentologie
- Geowissenschaften Umweltwissenschaften Umweltwissenschaften
- Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Naturwissenschaften Agrarwissenschaften Agrarwissenschaften Nachhaltige Landwirtschaft
- Naturwissenschaften Agrarwissenschaften Ackerbaukunde, Pflanzenbau
- Geowissenschaften Geologie GIS, Geoinformatik
Weitere Infos & Material
Preface. About the Authors. Introduction. 1. AI-Driven Smart Fertilization and Its Significance for Sustainable Agriculture 2. Enhancing Soil Health through AI-Based Nutrient Monitoring 3. Robotics in Precision Fertilizer Application 4. Machine Learning Models for Fertilizer Optimization 5. AI and IoT in Smart Fertigation Systems 6. Big Data Analytics for Soil Health and Water Use Efficiency 7. AI-Powered Decision Support Systems for Fertilization 8. Smart Sensors and AI in Real-Time Soil Nutrient Monitoring 9. AI and Remote Sensing for Fertilizer and Water Management 10. Harnessing AI to Promote Balanced Fertilization and Soil Health 11. Smart Fertilizer Blending and Customization Through AI Algorithms 12. AI in Site-Specific Nutrient Management for Crops 13. Remote Sensing and GIS for AI-Based Fertilizer Planning 14. Data-Driven AI Strategies for Reducing Fertilizer Runoff 15. Carbon Footprint of Fertilizer Use: AI for Mitigation Strategies 16. Drought Resilience and AI-Optimized Fertilizer Application 17. Cloud Computing and AI in Fertilizer and Water Resource Planning 18. AI and Blockchain for Transparent and Efficient Fertilization 19. AI-Driven Smart Fertilization for Climate-Smart Agriculture 20. Real-Time AI Monitoring of Soil Moisture and Nutrient Levels 21. AI-Enabled Fertigation Systems for Maximizing Water-Nutrient Synergy 22. AI-Based Risk Assessment in Over-Fertilization and Soil Degradation 23. Geospatial AI in Mapping Soil Fertility and Water Productivity 24. AI-Powered Digital Agriculture Platforms for Smart Fertilization 25. Advancements in AI and Nano-Fertilizers for Sustainable Farming. References




