Multi-criteria Agriculture Recommendation System using Machine Learning for Crop and Fertilizesrs Prediction.

Agriculture plays an essential role in the economies of developing countries such as India and contributes significantly to gross domestic product (GDP). The escalation population has led upsurge food demand. Numerous challenges selection crops, fertilizers, pesticides without considering various parameters like types soil, water requirement, temperature conditions, profitability analysis crops for a particular region may lead degradation quality crop, yield profitability. With advancement Computational technologies, researchers are working on recommending according soil condition, market along with fertilizers recommendation, disease identification, pesticide recommendation. Through this research, we propose machine learning-based crop fertilizer recommendation algorithm called AgriRec. We have utilized properties, level, farm size, minimum support price design learning model which predicts different seasons. Further, another mechanism that processes properties/details envisage combination fertilizer(s) given pair crop. Our is tested 5000 land samples Gujarat 24 it successfully recommends 95.85% accuracy 92.11% 4 times better performance compared existing benchmark approaches.