• Geeta devi
• Harjinder Kaur

Plant diseases are a major challenge in modern agriculture because they can reduce crop productivity, quality, and economic returns. Traditional plant disease identification generally depends on visual inspection by farmers or agricultural experts, which can be time-consuming, subjective, and difficult to apply over large agricultural areas. This study proposes a deep learning-based plant disease detection framework integrated with Explainable Artificial Intelligence (XAI). The proposed system analyses plant leaf images and automatically classifies them into healthy and disease categories. A Convolutional Neural Network (CNN) or transfer-learning-based architecture can be employed to learn discriminative visual characteristics such as colour variation, lesions, spots, texture, and changes in leaf structure. Image preprocessing, resizing, normalization, data augmentation, model training, and performance evaluation are incorporated into the proposed methodology. To improve transparency, Grad-CAM is applied to generate visual explanations showing the regions of the leaf that contribute most strongly to the model's prediction. Unlike a conventional black-box classifier, the proposed approach provides both a disease prediction and an interpretable visual explanation. The framework is evaluated using accuracy, precision, recall, F1-score, and confusion matrix analysis. The integration of deep learning and XAI can support more transparent and trustworthy computer-vision-based agricultural disease diagnosis and can provide a foundation for future mobile and smart-farming applications.

Plant Disease Detection, Deep Learning, Convolutional Neural Network, Transfer Learning, Explainable AI, Grad-CAM, Image Classification, Precision Agriculture, Computer Vision.

"Plant Disease Detection Using Deep Learning with Explainable Artificial Intelligence", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 9, page no.c184-c195, September-2026, Available :http://www.jetir.org/papers/JETIR2609222.pdf

"Plant Disease Detection Using Deep Learning with Explainable Artificial Intelligence", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 9, page no. ppc184-c195, September-2026, Available at : http://www.jetir.org/papers/JETIR2609222.pdf