Smart Agriculture : Artificial Intelligence for Sustainable Food Systems / Krishnankutty, Radhakrishnan Edayileveetil (EDT)/ Kumar, Ajay (EDT)/ Soni, Kallamparambil Balakrishnan (EDT)

Smart Agriculture : Artificial Intelligence for Sustainable Food Systems

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予約

Smart Agriculture : Artificial Intelligence for Sustainable Food Systems

Krishnankutty, Radhakrishnan Edayileveetil (EDT)/ Kumar, Ajay (EDT)/ Soni, Kallamparambil Balakrishnan (EDT)

ウェブストア価格 ¥49,249（本体¥44,772）
Springer Verlag, Singapore（2026/05発売）
外貨定価 US$ 219.99
ポイント 447pt

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製本 Hardcover:ハードカバー版／ページ数 262 p.
言語 ENG
商品コード 9789819587841

Full Description

This book provides deeper understanding into the framework of artificial intelligence (AI) based applications in agriculture. It starts with discussing the basics and history of AI, and then delves into identifying the opportunities of AI intervention at various stages of agricultural practices. AI and its subset, machine learning, present an outstanding tool for analyzing, understanding and identifying data patters in farming. This book thus discusses the complete potential of computational intelligence techniques for enhancing crop productivity and yield. Main topics in the book include use of AI in soil health monitoring, irrigation systems, evaluation of crop nutrients, intelligent spraying of biofertilizers and plant disease management. It also outlays the legal and ethical aspect of integrating AI into agriculture.

This book is suitable for scientists, academicians, industrialists and professionals involved in agriculture extension programs, plant sciences, environmental sciences and agricultural biotechnology.

.- Chapter 1: AI Tools, Techniques and Technologies in Agriculture
.- Chapter 2: Opportunities for AI interventions at various stages of agricultural practices
.- Chapter 3: Use of AI in Crop Health Monitoring
.- Chapter 4: One More Step towards Sustainable Development Goals (SDG): Internet of Things (IoT) based Smarter Irrigation Systems
.- Chapter 5: Scope of AI in Future Farming
.- Chapter 6: Strategies for Strengthening Biosecurity in Indian Agriculture
.- Chapter 7: Plant Disease Management through Artificial Intelligence Tools
.- Chapter 8: Microbiomes in weed and post-harvest management
.- Chapter 9: Unlocking the potential of algal-mediated nanoparticles in plant science: synthesis, challenges, and applications
.- Chapter 10:Integrated metagenomic insight into microbial dye degradation
.- Chapter 11:Current trends in Agriculture Research based on AI and Machine Learning
.- Chapter 12:Applications of ai in future farming
.- Chapter 13:Genotyping advancements for mitigating biotic stress induced damage in wheat.