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E-grāmata: Agri-Tech Approaches for Nutrients and Irrigation Water Management

Edited by (MCAET, Akbarpur, India), Edited by (CRDT, IIT Delhi, India), Edited by (AIT, Thailand)
  • Formāts: 406 pages
  • Izdošanas datums: 03-Jun-2024
  • Izdevniecība: CRC Press
  • Valoda: eng
  • ISBN-13: 9781040021408
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Agri-Tech Approaches for Nutrients and Irrigation Water ManagementPalielināt

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"This book includes concept, state-of-the-art methodologies, and techniques used in soil nutrients and irrigation water management. It covers soil moisture flow, nutrient dynamics, crop water estimation techniques, approaches to improve crop water productivity and soil health, crop simulation modeling, remote sensing/GIS applications in irrigation water management. Agri-technologies, climate-resilient agriculture, and advances in big data/machine learning techniques are explained. Precision farming techniques and their environmental/economic impacts are included. Features: Discusses applications of agri-techniques in agriculture and water sciences. Provides comprehensive review on irrigation water management. Covers application of machine learning, big data analysis, IoT, metagenomics, and modeling approaches for nutrients and water management. Reviews practice and the future of agriculture water and nutrients management. Explores crop simulation, climate change and its impact on agriculture. This book is aimed at researchers and graduate students in agriculture, water resources, environmental, and irrigation engineering"--

This book includes concepts, methodologies, and techniques used in soil nutrients and irrigation water management with regional and global prospects. This book accommodates up-to-date approaches to agricultural technologies along with future directions and compiles a wide range of articles ranging from soil moisture flow, nutrient dynamics, crop water estimation techniques, approaches to improve crop water productivity and soil health, crop simulation modeling, and remote sensing/GIS applications. The book also includes chapters on climate-resilient agriculture, advances in big data and machine-learning techniques, IoT, plasma technology, seed priming, and precision farming techniques and their environmental/economic impacts.

Features:


• Discusses applications sustainable technologies for soil nutrients and irrigation water management at multi-scale.
• Covers application of remote sensing/GIS, big data and machine learning, IoT, plasma technology, seed priming, and precision farming techniques for nutrients and water management.
• Reviews concepts, methodologies, and techniques being used in soil nutrients and irrigation water management.
• Provides up-to-date information as well as future directions in the field of nutrients and agricultural water management.

This book is aimed at researchers and graduate students in agriculture, water resources, environment, and irrigation engineering.



This book includes concept, state-of-the-art methodologies, techniques used in soil nutrients and irrigation water management. It covers soil moisture flow, nutrient dynamics, crop water estimation techniques, crop water productivity, soil health, crop simulation modeling, and remote sensing/GIS applications in irrigation water management.

Chapter
1. AI for Sustainable Agriculture in the Face of Climate Change.
Chapter
2. Development of a Modeling Approach for Agriculture Crop Type Classification Aiming at Large-Scale Precision Agriculture by Synergistic Utilization of Fused Sentinel-1 and Sentinel-2 Datasets with UAV Datasets.
Chapter
3. IoT and Smart Sensor Applications in Nutrient and Irrigation Water Management.
Chapter
4. Assessing Nutrient Variability Across Irrigation Management Zones Using Unsupervised Learning and Mixed Models.
Chapter
5. Comparative Study on Estimation of Sediment Yield Index Using GIS and Remote Sensing for Soil Erosion Prediction.
Chapter
6. Soil Moisture Flows Modeling for Micro-Irrigation and Nutrient Load Management.
Chapter
7. Applications of Remote Sensing and GIS Techniques in the Monitoring of Ecosystem Services.
Chapter
8. Evaluation of Machine Learning Algorithms in Soil Water Content Prediction at Multiple Depths.
Chapter
9. Artificial Intelligence Application in Database Management for SCADA Systems.
Chapter
10. Entropy-Weighted-Multi-Criteria Decision-Making (E-MCDM) Approach for Erosion Area Prioritization: Case Study of a Himalayan River Basin.
Chapter
11. Role of Urea Super Granule (USG) Applicator in Efficient Management of Nitrogen Fertilizer: Case Study of Rice Farming in Bangladesh.
Chapter
12. AI as Improved Agri-Tech Approach for Better Nutrients and Proper Irrigation Water Management: A Comparative Study.
Chapter
13. Plasma Technology: An Emerging Tool for Sustainable Agriculture.
Chapter
14. Application of Metaheuristic Optimizations for Unconfined Aquifer Parameter Estimation to Improve Irrigation Water Management.
Chapter
15. Application of Remote Sensing, GIS, and AI Techniques in the Agricultural Sector.
Chapter
16. Flood Modeling Using the AHP Method in a GIS Environment of the Iril River Catchment, Manipur, India.
Chapter
17. Agricultural Drought Modelling Through Drought Indices in the Thoubal District, Manipur, India.
Chapter
18. Seed Priming: Potential Nutrient Management Tool for Improving Crop Productivity Under Abiotic Stress.
Chapter
19. Protected Cultivation: Microclimate-Based Agriculture Under Greenhouse.
Chapter
20. Estimation of Groundwater Fluctuation and NDVI Using Geospatial Techniques for Chandigarh City, India.
Chapter
21. Holistic Approach for Prediction of Total Nitrogen Based on Machine-Learning Techniques.
Chapter
22. Resource Conservation Technologies for Sustainable Management of Soil, Water and Energy in Modern Agriculture.

Shivam Gupta is an Assistant Professor in the Department of Irrigation and Drainage Engineering, Mahamaya College of Agricultural Engineering and Technology, Acharya Narendra Dev University of Agriculture and Technology, Ayodhya, Uttar Pradesh.

Sushil Kumar Himanshu is an Assistant Professor in the Department of Food, Agriculture and Bio-resources, School of Environment, Resources and Development, Asian Institute of Technology (AIT), Pathum Thani, Thailand.

Pankaj Kumar Gupta is a Ramanujan fellow, at the Indian Institute of Technology (IIT) Delhi, India. He is also an adjunct assistant professor at the University of Waterloo, Canada.
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