🌾 AgroAdvisor

AgroAdvisor is a machine learning and deep learning-based website that assists farmers and agricultural professionals by recommending the best crop to grow, appropriate fertilizers, and detecting plant diseases using computer vision.

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📊 Data Sources

• Crop Recommendation Dataset
• Plant Diseases Dataset

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💻 Features & How to Use

🚜 Crop Recommendation

Enter:

• N-P-K values (Nitrogen-Phosphorous-Potassium) — Refer to this guide
• State and City

🔔 Note: Use commonly known cities. Some remote areas may not be supported by the OpenWeatherMap API.

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🌿 Fertilizer Suggestion

Provide:

• Soil nutrients
• Target crop

The model will suggest adjustments in fertilizer usage based on nutrient excess or deficiency.

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🦠 Disease Detection

Upload:

• A leaf image of the crop

The system detects:

• Crop type
• Health status (Healthy/Diseased)
• Disease name and treatment suggestions

Supported Crops

• Apple
• Blueberry
• Cherry
• Corn
• Grape
• Pepper
• Orange
• Peach
• Potato
• Soybean
• Strawberry
• Tomato
• Squash
• Raspberry

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🛠️ Run Locally

Requirements:

• git
• Anaconda or Miniconda

Step 1: Clone the Repository

git clone https://github.com/xHarshit/AgroAdvisor.git
cd AgroAdvisor

Step 2: Set Up Environment

conda create -n agroadvisor python=3.6.12
conda activate agroadvisor
pip install -r requirements.txt

Step 3: Launch the App

python app.py

Then, open the URL shown in your terminal (usually http://127.0.0.1:5000).

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🖼️ Screenshots

1. Homepage

2. Our Services

3. Crop Recommendation Input

4. Recommended Crop Output

5. Disease Detection Upload

6. Diagnosis and Treatment Info

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📈 Future Improvements

• Expand disease support to more crops
• Add regional language support
• Integrate real-time weather-based decision-making
• IoT integration for smart soil monitoring

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🪪 License

This project is licensed under the MIT License. See the LICENSE file for details.