🌾 Smart Crop & Fertilizer Recommendation System

A smart AI-based system that recommends the best crop and required fertilizer using soil and environmental data.

📌 Problem Statement

Farmers often apply fertilizers without knowing exact soil nutrient requirements, leading to low yield and soil damage.

💡 Solution

This system uses Machine Learning (Random Forest) to:

• Recommend the most suitable crop
• Suggest required fertilizers (Urea, DAP, MOP) based on soil nutrients

⚙️ Input Parameters

• Nitrogen (N)
• Phosphorus (P)
• Potassium (K)
• Temperature
• Humidity
• Soil pH
• Rainfall

🧠 Technologies Used

• Python
• Google Colab
• Scikit-learn
• Random Forest Algorithm
• GitHub

📊 Dataset

• Crop_recommendation.csv
• Contains soil and weather parameters with crop labels

🔄 Working Flow

1. User enters soil and weather values
2. ML model predicts best crop
3. System checks nutrient deficiency
4. Fertilizer recommendation is generated

▶️ Example Output

Recommended Crop: Pomegranate Fertilizer Advice: Nitrogen is low → Add Urea | Phosphorus is low → Add DAP

📁 Project Files

• Smart_Crop_Fertilizer_Recommendation_System.ipynb
• Crop_recommendation.csv
• README.md
• LICENSE

📜 License

This project is licensed under the MIT License.

👤 Author

Shaurya Mehta & Diantha Kanchan