GourNet: A CNN-Based Model for Mango Leaf Disease Detection

2026-04-30

AI Summary

This study addresses the critical challenge of early and accurate identification of mango leaf diseases, which severely threaten crop yield and fruit quality. To this end, the authors propose GourNet, a lightweight convolutional neural network with only 680,000 parameters, enhanced through tailored image preprocessing and data augmentation strategies to significantly improve generalization. Evaluated on the MangoLeafBD dataset encompassing eight distinct disease classes, GourNet achieves a classification accuracy of 97%, demonstrating an effective balance between high diagnostic precision and computational efficiency. The proposed approach offers a practical solution for intelligent disease diagnosis in agricultural settings with limited computational resources.

Abstract

Mango cultivation is crucial in the agricultural sector, significantly contributing to economic development and food security. However, diseases affecting mango leaves can significantly reduce both the production and overall fruit grade. Detecting leaf diseases at an early stage with precision is key to effective disease prevention and sustaining crop productivity. In this paper, we introduce a "deep learning" model named "GourNet", which leverages "Convolutional Neural Networks" to identify infections in mango leaves. We utilize the "MangoLeafBD" (MBD) dataset to train and assess the effectiveness of the presented model. The MBD dataset contains seven disease classes and a Healthy class, making a total of eight classes. To enhance model performance, the images are preprocessed through steps like resizing, rescaling, and data augmentation prior to training. To properly evaluate the model, the dataset is separated into 80% for training, with the remaining 20% equally split between validation and testing. Our model uses only 683,656 total parameters and achieves a classification accuracy of 97%. This research's source code can be found at: https://github.com/ekramalam/GourNet-Repo.

Problem

• mango leaf disease
• early detection
• precision diagnosis
• crop productivity
• disease prevention

Innovation

• GourNet
• Convolutional Neural Networks
• Mango leaf disease detection
• Lightweight deep learning
• Data augmentation