Smarter Farming Through AI-Powered Vision

Fruit crops are increasingly vulnerable to diseases, pests, and unpredictable climate patterns.

Our AI-based Fruit Disease Detection system uses computer vision and machine learning to help farmers, researchers, and agronomists detect, diagnose, and respond — before it’s too late.

What We Detect:

• Leaf Disease Detection:
  • Use image classification models to identify fungal infections, blight, and discoloration in fruit tree leaves (e.g., apple, orange, mango).
  • Enables early intervention and reduces chemical overuse.
• Fruit Ripeness Detection:
  • Analyze fruit color, size, and surface texture to determine optimal ripeness.
  • Helps farmers harvest at the right time, improving fruit quality and reducing waste.
• Pest Detection:
  • Detect pests like fruit borers, aphids, or mealybugs on leaves or fruits using object detection models.
  • Prevent infestations with timely and targeted responses.
• Yield Prediction:
  • Forecast fruit yield using past harvest data, visual inputs, and environmental factors through machine learning.
  • Supports better market planning and resource allocation.

Why It Matters:

• → Reduces crop loss: with timely detection
• → Uses real image data: from your farm for high accuracy
• → Works with just a smartphone: or drone camera
• → Supports precision farming and sustainability goals

Who Benefits:

• →Fruit farmers and orchard owners
• →Agricultural research institutes
• →Agri-tech startups and consultants
• →Supply chain and export planners