Our Story

Building the Future of
Mushroom Farming in Nepal

We are final-year Computer Engineering students at Nepal Engineering College, on a mission to transform how oyster mushroom farmers detect disease, access expertise, and grow sustainable crops.

95%
Detection Accuracy
2,744
Training Images
5
Disease Classes
3
CNN Models Tested
8+
Product Categories
Our Mission

Empowering farmers with technology they can trust

Nepal produces 8–10 tonnes of mushrooms daily, yet farmers in rural areas surrounding Pokhara, Narayanghat, and the Kathmandu Valley continue to suffer significant financial losses from undiagnosed diseases. Without access to agronomists, many resort to guesswork — leading to overuse of pesticides and avoidable crop failures.

Our platform bridges this gap. By leveraging a DenseNet Convolutional Neural Network trained on locally sourced images from farms across the Bagmati Pradesh region, we provide instant, accurate disease identification and actionable treatment recommendations — directly in farmers' hands.

Beyond detection, the platform connects farmers with certified agronomists, offers a marketplace for cultivation supplies, and serves as a channel for government subsidy information — building a complete ecosystem for modern mushroom farming in Nepal.

🔬
AI Disease Detection
Upload a photo, get a diagnosis and treatment plan in seconds.
👨‍🌾
Expert Connect
Direct messaging with certified agronomists.
🛒
Cultivation Store
Seeds, tools, PPE and more — all in one place.
📊
Government Link
Access subsidy details and agricultural support programs.
Under the Hood

Powered by Deep Learning

We trained and compared three CNN architectures — NASNet, VGG16, and DenseNet201 — on a custom dataset of 2,744 oyster mushroom images collected from farms in Sallaghari, Duwakot, Godavari, and Dhading. DenseNet emerged as the top performer with 95% accuracy across five disease categories.

🧠 DenseNet201
📐 VGG16
🔍 NASNet Mobile
🐍 Python / TensorFlow
🌐 Django
☁️ Google Colab (GPU)
🗃️ Keras ImageGenerator
📊 Class Weight Balancing
The Team

The people behind the platform

Abhishek Chalise
Abhishek Chalise
Trained VGG16 Model
Student ID: 019-313
Namuna Paudel
Namuna Paudel
Trained DenseNet Model
Student ID: 019-332
Dinesh Wasti
Dinesh Wasti
Trained NasNet Model
Student ID: 019-338
Project Supervisor
Assoc. Prof. Dinesh Dangol
Department of Computer Science & Engineering
Nepal Engineering College