Section 1: Introduction to Big Data Analytics in Agriculture 1. Introduction to Traditional Data Analytics 2. Introduction to Big Data and Big Data Analytics Section II: Big Data Management and Processing 3. Agricultural Big Data -- Storage, Loading, and Application Development 4. Data Analysis Techniques for Agricultural-based Multi corpus: Scalability and Cost Perspective 5. Approaches for Big Data Processing: Applications and Challenges Section III: Big Data Analytics Algorithms 6. From Theory to Practice: The Application of Big Data and Machine Learning in Real-World Scenarios 7. Feature engineering and Model fitting for Efficient Big Data Analytics Section IV: Big Data Applications 8.
Data-Driven Approaches and AI Applications in Managing Variability for Sustainable Crop Production 9. Big Data-Driven Smart Farming: A Visualization Perspective of tracking Agricultural Productivity 10. Smart and Precise Irrigation: A Way Forward 11. Application of Mobile Collaborative Robot using Deep Learning in Precision Weed Control of Large Farms - A Brief Review 12. Machine Learning Enabled Nutrient Stress Detection and Real time Prediction 13. Performance Evaluation of Machine Learning Algorithms for Leaf Disease Detection 14. AI-Driven Smart Agriculture System for Multi-Crop Disease Detection: A Study on Potato, Tomato and Bell Pepper 15. Soil moisture estimation through machine learning and polarimetric Synthetic Aperture Radar data over high altitude agroforestry landscapes 16.
Review on the increasing role of Artificial Intelligence / Machine Learning in climate prediction 17. Impact Assessment of Climate Change Through Agricultural Big Data with Emphasis on Smart Agriculture 18. Rice Pest Detection using YOLO Machine Learning 19. Practical applications of Supply Chain Analytics in Agriculture 20. Harnessing Big Data for Agricultural Transformation in Developing Economies: Origins, Applications, and Impacts on Farmers Section V: Challenges and prospects 21. Challenges and Future Pathways for Big Data Analytics in Agriculture from an Algorithmic and Applications Perspective.