Intelligent Data Mining and Fusion Systems in Agriculture

Intelligent Data Mining and Fusion Systems in Agriculture presents methods of computational intelligence and data fusion that have applications in agriculture for the non-destructive testing of agricultural products and crop condition monitoring. Sections cover the combination of sensors with artificial intelligence architectures in precision agriculture, including algorithms, bio-inspired hierarchical neural maps, and novelty detection algorithms capable of detecting sudden changes in different conditions. This book offers advanced students and entry-level professionals in agricultural science and engineering, geography and geoinformation science an in-depth overview of the connection between decision-making in agricultural operations and the decision support features offered by advanced computational intelligence algorithms.

Covers crop protection, automation in agriculture, artificial intelligence in agriculture, sensing and Internet of Things (IoTs) in agricultureAddresses AI use in weed management, disease detection, yield prediction and crop productionUtilizes case studies to provide real-world insights and direction

1. Sensors in Agriculture 2. Artificial Intelligence in Agriculture 3. Utilization of Multisensors and Data Fusion in Precision Agriculture 4. Tutorial I: Weed Detection 5. Tutorial II: Disease Detection with Fusion Techniques 6. Tutorial III: Disease and Nutrient Stress Detection 7. Tutorial IV: Leaf Disease Recognition 8. Tutorial V: Yield Prediction 9. Tutorial VI: Postharvest Phenotyping 10. General Overview of the Proposed Data Mining and Fusion Techniques in Agriculture