Sustainable Farming through Machine Learning, Kartoniert / Broschiert
Sustainable Farming through Machine Learning
- Enhancing Productivity and Efficiency
(soweit verfügbar beim Lieferanten)
- Herausgeber:
- Suneeta Satpathy, Bijay Kumar Paikaray, Ming Yang
- Verlag:
- Taylor & Francis Ltd (Sales), 07/2026
- Einband:
- Kartoniert / Broschiert
- Sprache:
- Englisch
- ISBN-13:
- 9781032777504
- Artikelnummer:
- 12818969
- Umfang:
- 282 Seiten
- Gewicht:
- 427 g
- Maße:
- 234 x 156 mm
- Stärke:
- 16 mm
- Erscheinungstermin:
- 20.7.2026
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
Klappentext
This book explores the transformative potential of machine learning (ML) technologies in agriculture. It delves into specific applications, such as crop monitoring, disease detection, and livestock management, demonstrating how artificial intelligence / machine learning (AI/ML) can optimize resource management and improve overall productivity in farming practices.
Sustainable Farming through Machine Learning: Enhancing Productivity and Efficiencyprovides an in-depth overview of AI and ML concepts relevant to the agricultural industry. It discusses the challenges faced by the agricultural sector and how AI/ML can address them. The authors highlight the use of AI/ML algorithms for plant disease and pest detection and examine the role of AI/ML in supply chain management and demand forecasting in agriculture. It includes an examination of the integration of AI/ML with agricultural robotics for automation and efficiency. The authors also cover applications in livestock management, including feed formulation and disease detection; they also explore the use of AI/ML for behavior analysis and welfare assessment in livestock. Finally, the authors also explore the ethical and social implications of using such technologies.
This book can be used as a textbook for students in agricultural engineering, precision farming, and smart agriculture. It can also be a reference book for practicing professionals in machine learning, and deep learning working on sustainable agriculture applications.
Biografie (Ming Yang)
Dr. Ming Yang is Senior Environmental Economist at an international organization based in Washington, D.C. Prior to joining the organization, he worked for four years as Energy and Environment Economist and Energy Technology Economist for the International Energy Agency of the OECD in Paris. Before that, he was Energy Adviser and Climate Change Specialist for two years at the Asian Development Bank. Dr Yang is good at quantitative analysis in issues related to economics, engineering, technology and climate change. In 1986, he undertook a feasibility study with MARKAL model on China s Three Gorges Power Plant. In 1994, he simulated negotiation process by using EFOM model. In 2007, with the IEA's ETP model (the new version of MARKAL) he designed two scenarios for IEA s Energy Technology Perspectives 2008. Over the past two decades, he has about 100 articles published in journals and conference proceedings. He significantly contributed to quantitative analysis and writing of four books on energy and climate change that were published in the Asian Development Bank and the International Energy Agency. Ming holds a Ph.D. in energy economics and planning from the Asian Institute of Technology in Bangkok jointly with l'Institut d'Economie et de Politique de l'Energie (IEPE), Université des Sciences Sociales, Grenoble, France.
