1*Research Scholar, Computer Science and Engineering Institute of Engineering and Technology, Srinivas University, Mangalore. Assistant Professor, GFGC Honnali. Email: surekha.bijapur@gmail.com (Corresponding Author)
2Associate Professor, Computer Science and Engineering Institute of Engineering and Technology, Srinivas University, Mangalore.
3Research Scholar, Computer Science and Engineering Institute of Engineering and Technology, Srinivas University, Mangalore. Assistant Professor GSC, Hassan University
4Associate Professor, CSE, Jain Institute of Technology, Davangere.
5Associate Professor, EEE, Jain Institute of Technology, Davangere.
Background: Mango and banana are major commercial crops with worldwide importance, providing nutritional and economic sustainability. But leaf diseases pose a threat to their growth and productivity. Effective disease management is necessary to avoid losses. In this research, we present an automated system for identifying and classifying banana and mango leaves infected by diseases using a Deep Learning (DL) approach.
Methodology: The proposed method utilizes a CNN that has been trained on a large and diverse dataset of leaf images representing different stages of various diseases at different resolutions. The proposed method is expected to provide accurate identification between different common diseases such as Bacterial Canker, Powdery Mildew, Anthracnose, Gall Midge, and Sooty Mould. By leveraging learned visual features, the proposed system provides a valuable tool for early detection and effective pest control measures in commercial farming.
Results: Beside proposing a pesticide to control the diseases observed in both bananas and mangoes, the proposed work utilizes a hybrid feature extraction technique, image segmentation, and classification algorithms to improve the efficiency of the disease identification process. With an accuracy of 95.5% for banana and 96.0% for mango leaf disease identification, the proposed hybrid model proved its applicability for real-time agricultural applications.
Keywords- Mango and banana leaf, leaf disease detection, deep learning, image segmentation, feature extraction.
How to cite this article: Bijapur S, Krishna JV, Sheela NS, Meghana GR, Chetan HR. Smart Agriculture: Deep Learning-Powered Disease Recognition in Mango and Banana Leaves. Int J Drug Deliv Technol. 2026;16(13s): 1053-1061. DOI: 10.25258/ijddt.16.13s.116
Source of support: Nil.
Conflict of interest: None