International Journal of Research and Innovation in Applied Science (IJRIAS)
Deep Learning-Based Wheat Disease Detection and Classification System Using Convolutional Neural Networks
Published December 19, 2025 • Vol. 10, Issue 11, pp. 954–962Open Access
DOI: 10.51584/IJRIAS.2025.101100090
Abstract
Wheat, one of the major crops in the world, is vulnerable to many diseases that cause tremendous yield and quality loss. This paper proposes a deep learning method for the automatic detection and classification of wheat diseases based on a Convolutional Neural Network (CNN). We respond to the imperative of early and precise identification of diseases in wheat crops in order to reduce agricultural losses.The system learned on a data set of more than 14,000 wheat leaf images corresponding to 15 classes of various rusts, blights, insects, and normal leaves. Our suggested CNN model reached a training accuracy of 97.02% and validation accuracy of 91.00%. The model design uses data augmentation strategies and dropout regularization to promote generalization as well as avoid overfitting
Keywords: Wheat Disease Detection, Deep Learning, Convolutional Neural Network (CNN), Agricultural Technology
| Journal | International Journal of Research and Innovation in Applied Science (IJRIAS) |
|---|---|
| ISSN | 2454-6194 |
| Volume / Issue | Volume 10, Issue 11 |
| Pages | 954–962 |
| Publication date | December 19, 2025 |
| DOI | 10.51584/IJRIAS.2025.101100090 |
| Publisher | RSIS International |
| License | Open Access |
How to cite this article
Ms. Drashti Shah, Mr. Dhruv Chauhan, & Dr Mahasweta Joshi (2025). Deep Learning-Based Wheat Disease Detection and Classification System Using Convolutional Neural Networks. International Journal of Research and Innovation in Applied Science (IJRIAS), 10(11), 954-962. https://doi.org/10.51584/IJRIAS.2025.101100090
BibTeX
@article{Ms2025,
title = {Deep Learning-Based Wheat Disease Detection and Classification System Using Convolutional Neural Networks},
author = {Ms. Drashti Shah and Mr. Dhruv Chauhan and Dr Mahasweta Joshi},
journal = {International Journal of Research and Innovation in Applied Science (IJRIAS)},
volume = {10},
number = {11},
pages = {954--962},
year = {2025},
doi = {10.51584/IJRIAS.2025.101100090},
publisher = {RSIS International}
}