AgroSmart: ML-Driven Crop and Fertilizer Recommender
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“AgroSmart: ML-Driven Crop and Fertilizer Recommender”
Authors:
Kishor Pawar1, Prof. Shubhangi Vitalkar2
1Department of MCA, Trinity Academy of Engineering, Pune, India
2Assistant Professor of MCA, Trinity Academy of Engineering, Pune, India
Abstract: Agriculture is the backbone of many economies, especially in developing countries, where farmers often rely on intuition or traditional knowledge for crop planning and fertilizer usage. Agro Smart is a machine learning-based web application designed to provide intelligent recommendations for crop selection and fertilizer usage based on environmental and soil parameters. The system uses real-world datasets and trains robust models such as Random Forest and Decision Tree classifiers to ensure accurate predictions. Users input data such as nitrogen (N), phosphorus (P), potassium (K), pH, temperature, humidity, and rainfall. Based on this, the system predicts the most suitable crop and identifies nutrient deficiencies to recommend appropriate fertilizers.
Keywords: Machine Learning, Crop Recommendation, Fertilizer Optimization, Precision Agriculture,
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