This edited volume explores the transformative impact of Artificial Intelligence on agriculture, a sector critical to economic development and global food security. As modern agriculture is undergoing a paradigm shift by integrating advanced technologies such as AI, robotics, computer vision, the Internet of Things (IoT), and data analytics across various farming processes, this volume aims to enhance productivity and sustainability.
The role of AI in agriculture holds vast potential for increasing yields, optimizing resource allocation, and minimizing environmental impact. By utilizing data-driven insights, farmers can make informed decisions on key factors like irrigation, crop management, and livestock care, driving a future of sustainable farming that supports global food security. The widespread adoption of AI is set to revolutionize the industry, creating a resilient agricultural ecosystem. This book provides an in-depth analysis of AI applications across sub-domains such as crops, livestock, fisheries and related data issues. It features real-world case studies and explores key technological areas, including computer vision, remote sensing, large language models, natural language processing, IoT, and machine learning. Grouped into three sections(i) AI in Agriculture Management and Precision Farming, (ii) AI in Livestock and Fisheries Management and (iii) Sustainable Practices, Open Data Ecosystem and Policy Issues the book highlights how AI is reshaping the future of agriculture, fostering a smarter and more sustainable agricultural ecosystem.
This volume is essential for researchers, students, and professionals in agricultural studies and related fields. It offers valuable insights for farmers and extension workers seeking to adopt innovative technologies.
Section
1. AI in Agriculture Management and Precision Farming.
Chapter
1. AgriNet-Light: Unlocking the Power of Lightweight AI models for
Agriculture.
Chapter
2. AI-Enabled UGV and UAVs in Row-Crop Production
Agriculture.
Chapter
3. e-Crop based smart farming for another boom in
agricultural production.
Chapter
4. Computer Vision-based Object Detection
for High Throughput Plant Phenotyping.
Chapter
5. Deep Learning models for
crop protection: A case study of wheat.
Chapter
6. AI-DISC: An Intelligent
Tool for Disease and Pests Detection in Crops.
Chapter
7. Deep
Learning-Based Computer Vision Methods for Smart Weed Identification.-
Chapter
8. Digital Entomology: Revolutionizing Biodiversity Management in
Indian Agriculture.
Chapter
9. IoT and AI integrated Robots for Site
Specific Weed Management.- Section 2: AI in Livestock and Fisheries
Management.
Chapter
10. Leveraging Artificial Intelligence for the
Advancement of Animal Sciences: Innovations, Applications, and Impacts.-
Chapter
11. SHRIA: Natural Language Processing based Chatbot Application for
Effective Livestock Management.
Chapter
12. AI-DISA: An Artificial
Intelligence-based Disease Identification System for Livestock Health
Management.
Chapter
13. AI/ML in molecular epidemiology of transboundary
infectious animal virus with special reference to Foot-and-mouth Disease.-
Chapter
14. Artificial Intelligence for the Blue Revolution: Advancing
Fisheries and Aquaculture Management.- Section 3: Sustainable Practices, Open
Data Ecosystem and Policy Issues.
Chapter
15. Recent Advances in Deep
Learning with Applications in Data Fusion and Agriculture.
Chapter
16.
Leveraging Artificial Intelligence for Agricultural Knowledge Dissemination:
The Krishi-Mantrana Question Answering System.
Chapter
17. Large Language
Models in Agriculture: From Theory to Practice.
Chapter
18. Upscaling
Digital Agriculture in India: Strategies for Wider Adoption.
Dr. Alka Arora is working as Professor (Computer Applications) and Principal Scientist at ICAR-Indian Agricultural Statistics Research Institute (IASRI). She has 27+ years of diversified experience in agricultural research, education, and extension activities. Her specialization in computer science, includes artificial intelligence, deep learning, image analysis, web application development, databases, and emerging technologies. She has contributed significantly towards strengthening of agricultural informatics through designing and implementing number of e-governance applications, web applications and mobile applications operational at National level. She has guided many doctoral and post graduate students. She was associated in Editing of two books and Editor for Special Issue of Journal of Indian Society of Agricultural Statistics on AI Applications in Agriculture. She has an extensive record of research publications and has delivered numerous invited talks in International/National conferences/workshops.
Dr. Sudeep Marwaha is Former Head and Professor, ICAR-Indian Agricultural Statistics Research Institute (IASRI) and has 25+ years of experience in research, teaching, training, and extension. He has led 20+ IT initiatives, including World Bankfunded projects, and served as PI for major projects like the Education Portal, NAHEP, RAES, and AI-based maize disease advisory systems. He has developed 50+ online systems and mobile apps, benefiting agricultural universities, KVKs, and millions of farmers, with several securing copyrights. His expertise spans knowledge-based systems, ontologies, deep learning, and intelligent agricultural applications, including AI tools for crop and livestock disease identification. He has organized numerous national training programs and published 50+ research papers in reputed journals and conferences. He has mentored numerous research students (MSc/PhD) in the discipline of Computer Applications.
Dr. Rajni Jain is a seasoned researcher and academic specializing in the application of computer science in agriculture. Holding a Ph.D. from Jawaharlal Nehru University, she currently serves as a Principal Scientist at ICAR-National Institute of Agricultural Economics and Policy Research (NIAP), India. Dr. Jain has three books and a special issue on Artificial Intelligence applications in agriculture for a reputed journal, contributing significantly to scholarly discourse in the field. She has also organized numerous special sessions at national and international conferences, fostering collaboration and knowledge exchange on AI in agriculture. Her research interests include AI based models, decision support systems, crop planning models, and agricultural information systems, with notable contributions to data mining techniques, productivity analysis, and ICT applications in agriculture. With over two decades of research and academic experience, Dr. Jain has published extensively and guided postgraduate and doctorate students in Computer Applications at ICAR-IARI. Her dedication to advancing agricultural innovation through Artificial Intelligence is evident in her multifaceted roles as a researcher, editor, and facilitator of knowledge dissemination in the agricultural community.
Dr. Rajender Parsad is Former Director, ICAR-Indian Agricultural Statistics Research Institute, New Delhi. He is a distinguished expert in Agricultural Statistics and statistical computing, celebrated for his substantial research contributions both nationally and internationally. His work spans theoretical and applied aspects, with a focus on advanced statistical techniques for agricultural research. A key advocate for human resource development, , he has introduced modern experimental designs and analytical tools within the National Agricultural Research and Education System. He has made significant contributions in developing portals for online learning, e-advisory, service-oriented computing and centralized research data repository. Throughout his career, he has received numerous awards and honors for his outstanding achievements, including prestigious accolades like the National Award in Statistics in Honor of Professor CR Rao, Gold Icon Award in Open Data Championship Category from Govt. of India in 2020 for ICAR-Research Data Management Initiative and recognition as Fellow of the National Academy of Agricultural Sciences, Recognition and Young Scientist Award. He has been consultant to International Center for Agricultural Research in the Dry Areas (ICARDA). He is also popularly called as Data Man of ICAR. He had chaired several National Level Committees. He is an author of 200+ research papers in 50 peer-reviewed international and national journals, with over 175 co-authors. He has also contributed to 2 books, 2 electronic books (edited), 2 research monographs, 22 book chapters including on Data Science, Artificial Intelligence in Agriculture & Digital Agriculture, 26 technical reports, 12 R Packages, 07 SAS Macros for Customized Analysis; 10 Conference Proceedings as Edited Book and 07 Special issues of research journals as Guest Editor. He has mentored numerous research students and holds various editorial positions, underscoring his lasting impact on Statistical Sciences.
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