Discusses soil, agriculture, and ecosystem modeling using artificial intelligence technologies for fostering smart sustainable agricultural practices. It provides insight into sustainable agriculture, crop protection and management, soil carbon sequestration, and ecology preservation.
Discusses soil, agriculture, and ecosystem modeling using artificial intelligence technologies for fostering smart sustainable agricultural practices. It provides insight into sustainable agriculture, crop protection and management, soil carbon sequestration, and ecology preservation.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Owais Bashir, PhD, is working in the Department of Soil Science at Sher-e-Kashmir University of Agricultural Sciences and Technology, India. He is involved in research in soil pedology, climate change, machine learning, and soil health. The author of more than 10 research articles, two book chapters and one book, Dr. Bashir has presented at and participated in conferences, seminars, workshops, and symposiums and serves as an editorial board member and reviewer for reputed international journals. He has received many awards for his work in the science of soil analysis. Khalid Rehman Hakeem, PhD, is Professor at King Abdulaziz University, Saudi Arabia. He has more than 10 years of teaching and research experience in plant eco-physiology, biotechnology and molecular biology, medicinal plants, plant-microbe-soil interactions, as well as in environmental studies. He has received several fellowships and is involved with several government-funded research projects. To date, Dr. Hakeem has authored and edited more than 80 books and published more than 220 research papers and book chapters. He serves as an editorial board member and reviewer for several international scientific journals and is on the advisory board of Cambridge Scholars Publishing. Surinder S. Kukal, PhD, has worked in the field of agricultural water management at Punjab Agricultural University, India, where he has been Professor of Soil Conservation, Additional Director of Research, and Dean of Faculty of Agriculture. He has more than 350 research publications to his credit, including 150 research papers in international and national journals. Dr. Kukal has been a visiting scientist at CSIRO, Australia, and has delivered and led lectures in USA, Australia, China, Thailand, Serbia, Singapore, and Pakistan. Dr. Kukal has several awards and honors to his credit. Razeef Mohd, PhD, is a Machine Learning and Artificial Intelligence Expert at Sher-e-Kashmir University of Agriculture Sciences and Technology, India. He has more than eight years of teaching and research experience. He has published many research papers in international journals and has presented papers at IEEE conferences and science congresses.
Inhaltsangabe
1. State-of-the Art Modeling in Soil and Ecosystem Services under the Current Scenario 2. Predicting and Modeling of Soil Organic Carbon in Various Land Uses 3. Modeling for Soil Processes, Soil Quality, and Soil Biodiversity from an Agricultural and Ecosystem Perspective 4. Holistic Approach and New Assessment Techniques for Modeling Soil Erosion under Changing Climatic Conditions 5. Deep Learning-Based Approach for Disease Detection in the Changing Global Ecosystem 6. Deep Learning Approach for Detecting, Classifying, and Managing Insect Pests of Various Crops 7. A Systemic Machine Learning Approach for Fruit Yield Estimation under Changing Global Climatic Conditions 8. Current Trends and Future Perspectives for Modeling Agronomic Crops and Improving Intercropping in Climate Change Scenarios: A Review 9. Novel Disruptive Technology Innovations for Smart Sustainable Agricultural Practices
1. State-of-the Art Modeling in Soil and Ecosystem Services under the Current Scenario 2. Predicting and Modeling of Soil Organic Carbon in Various Land Uses 3. Modeling for Soil Processes, Soil Quality, and Soil Biodiversity from an Agricultural and Ecosystem Perspective 4. Holistic Approach and New Assessment Techniques for Modeling Soil Erosion under Changing Climatic Conditions 5. Deep Learning-Based Approach for Disease Detection in the Changing Global Ecosystem 6. Deep Learning Approach for Detecting, Classifying, and Managing Insect Pests of Various Crops 7. A Systemic Machine Learning Approach for Fruit Yield Estimation under Changing Global Climatic Conditions 8. Current Trends and Future Perspectives for Modeling Agronomic Crops and Improving Intercropping in Climate Change Scenarios: A Review 9. Novel Disruptive Technology Innovations for Smart Sustainable Agricultural Practices
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