Agricultural Informatics and Artificial Intelligence is a comprehensive academic resource developed for undergraduate students of Agriculture and Allied Sciences. The book systematically progresses from computer fundamentals, hardware and software, memory concepts, operating systems, MS Office, databases, internet technologies and programming to ICT applications in agriculture, computer and crop simulation models, geospatial technologies, decision support systems and expert systems.

The latter part focuses on Artificial Intelligence, Machine Learning, IoT, Big Data, agricultural drones, robotics, precision agriculture, smart farming and AI-enabled applications in crop management, livestock health, pesticide application, yield prediction, weeding, harvesting, produce sorting and food processing. The book therefore connects fundamental computing knowledge with practical applications in modern digital agriculture. The book introduces students to essential computer concepts and progressively develops their understanding of digital technologies and their applications in agriculture.

Beginning with the fundamentals of computers, memory, operating systems, MS Office, internet and database technologies, the book provides a strong foundation in computing and programming. It then moves towards Information and Communication Technology (ICT) in Agriculture, computer modelling, automation, geospatial technologies, Decision Support Systems and Expert Systems.

In keeping with the emerging requirements of modern agricultural education, dedicated chapters introduce students to the fundamentals of Artificial Intelligence (AI) and its practical applications in agriculture, including areas such as precision farming, crop monitoring, disease and pest detection, agricultural decision-making, forecasting, automation and smart farming.

The book is structured to support conceptual understanding, practical learning and application-oriented education, making it useful for undergraduate students of Agriculture and allied disciplines. It also provides a foundation for students to understand the rapidly evolving Digital Agriculture, Smart Farming and AI-enabled agricultural ecosystem.

Prof. A. P. Prajapati is an Assistant Professor in the Department of Agricultural Statistics, College of Agriculture, Junagadh Agricultural University, Junagadh. He has extensive experience in teaching computer applications, agricultural informatics, statistical computing, and related courses at undergraduate and postgraduate levels. His academic and research interests include agricultural research data analysis, Python programming, data science, machine learning, artificial intelligence, and their applications in agriculture. He has contributed to the development of JOSARDA (Junagadh Agricultural University Online System for Agricultural Research Data Analysis), a web-based platform for statistical analysis of agricultural research data, and has been actively involved in teaching, research, training, development of academic resources, and statistical advisory services.

Dr. D. V. Patel is Professor and Head, Department of Agricultural Statistics, College of Agriculture, Junagadh Agricultural University, Junagadh. He has extensive experience in teaching, research, postgraduate guidance, statistical analysis of agricultural experiments, and academic administration. He has contributed significantly to strengthening the application of statistical methods and computational tools in agricultural research and education. His experience in agricultural statistics, research methodology, experimental designs, data analysis, and academic guidance has provided valuable academic and technical support in developing this book.

Chapter 1. Introduction to Computer
Chapter 2. Memory Concepts and Operating Systems
Chapter 3. Productivity Tools of M. S. Office
Chapter 4. Concept of Internet and Database Technologies
Chapter 5. Computer Programming Fundamentals
Chapter 6. Information and Communication Technology (ICT) in Agriculture
Chapter 7. Computer Models and Automation in Agriculture
Chapter 8. Geospatial Technologies, Decision Support Systems/Expert System
Chapter 9. Fundamentals of Artificial Intelligence
Chapter 10. Applications of Artificial Intelligence in Agriculture