This project integrates soil microbiome analysis, IoT-based environmental sensing, and machine learning to enable early detection of root diseases in crops like tomato, potato, and cucumber. By combining Dna/qPCR pathogen identification with real-time data on moisture, temperature, and pH, the system predicts disease risk before visible symptoms appear. Farmers receive timely alerts through a mobile app or dashboard, helping them take preventive action and reduce yield losses by 20–30%.
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