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Title: :  LEAF DISEASE DETECTION USING MATLAB AND DEEP LEARNING
PaperId: :  26093
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 11 Issue 2 2025
DUI:    16.0415/IJARIIE-26093
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Mande Srinivasa RaoVasireddy Venkatadri Institute of Technology, Nambur, Andhra Pradesh, India
Sivalenka AashuthoshVasireddy Venkatadri Institute of Technology, Nambur, Andhra Pradesh, India
Shaik Sameer BabuVasireddy Venkatadri Institute of Technology, Nambur, Andhra Pradesh, India
Yerra Abhi RamuVasireddy Venkatadri Institute of Technology, Nambur, Andhra Pradesh, India
Ammanabrolu Sai KarthikVasireddy Venkatadri Institute of Technology, Nambur, Andhra Pradesh, India

Abstract

Electronics and Communication Engineering
Leaf disease,Convolution Neural Networks, VGG16,Detection,Deep learning
Agriculture is one of the most vital sectors for economic development, and plant diseases pose a significant threat to crop productivity. Early and accurate detection of these diseases is crucial for preventing yield loss and ensuring food security. Traditional methods of disease detection rely on manual inspection by experts, which is time-consuming, inconsistent, and often impractical for large-scale farming. In this study, we propose an automated leaf disease detection system using image processing and deep learning techniques in MATLAB. The system processes leaf images through preprocessing steps such as resizing, noise reduction, and contrast enhancement to improve feature extraction. A Convolutional Neural Network (CNN) based on the pre-trained VGG16 model is employed to classify leaves as either healthy or diseased. The diseased leaves are further categorized into specific diseases such as Powdery Mildew, Rust Disease, Bacterial Blight, and Leaf Spot Disease. The proposed approach eliminates the need for manual feature extraction, allowing the model to learn disease-specific patterns directly from images. The model is trained and tested on a diverse dataset, achieving an accuracy of over 91%. The results demonstrate that this deep learning-based system provides a fast, accurate, and reliable solution for farmers and agricultural researchers, enabling early disease detection and timely intervention. Future improvements may include real-time monitoring, integration with IoT-based systems, and the development of a mobile application for broader accessibility.

Citations

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IJARIIE Mande Srinivasa Rao, Sivalenka Aashuthosh, Shaik Sameer Babu, Yerra Abhi Ramu, and Ammanabrolu Sai Karthik. "LEAF DISEASE DETECTION USING MATLAB AND DEEP LEARNING" International Journal Of Advance Research And Innovative Ideas In Education Volume 11 Issue 2 2025 Page 1173-1177
MLA Mande Srinivasa Rao, Sivalenka Aashuthosh, Shaik Sameer Babu, Yerra Abhi Ramu, and Ammanabrolu Sai Karthik. "LEAF DISEASE DETECTION USING MATLAB AND DEEP LEARNING." International Journal Of Advance Research And Innovative Ideas In Education 11.2(2025) : 1173-1177.
APA Mande Srinivasa Rao, Sivalenka Aashuthosh, Shaik Sameer Babu, Yerra Abhi Ramu, & Ammanabrolu Sai Karthik. (2025). LEAF DISEASE DETECTION USING MATLAB AND DEEP LEARNING. International Journal Of Advance Research And Innovative Ideas In Education, 11(2), 1173-1177.
Chicago Mande Srinivasa Rao, Sivalenka Aashuthosh, Shaik Sameer Babu, Yerra Abhi Ramu, and Ammanabrolu Sai Karthik. "LEAF DISEASE DETECTION USING MATLAB AND DEEP LEARNING." International Journal Of Advance Research And Innovative Ideas In Education 11, no. 2 (2025) : 1173-1177.
Oxford Mande Srinivasa Rao, Sivalenka Aashuthosh, Shaik Sameer Babu, Yerra Abhi Ramu, and Ammanabrolu Sai Karthik. 'LEAF DISEASE DETECTION USING MATLAB AND DEEP LEARNING', International Journal Of Advance Research And Innovative Ideas In Education, vol. 11, no. 2, 2025, p. 1173-1177. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/LEAF_DISEASE_DETECTION_USING_MATLAB_AND_DEEP_LEARNING_ijariie26093.pdf (Accessed : ).
Harvard Mande Srinivasa Rao, Sivalenka Aashuthosh, Shaik Sameer Babu, Yerra Abhi Ramu, and Ammanabrolu Sai Karthik. (2025) 'LEAF DISEASE DETECTION USING MATLAB AND DEEP LEARNING', International Journal Of Advance Research And Innovative Ideas In Education, 11(2), pp. 1173-1177IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/LEAF_DISEASE_DETECTION_USING_MATLAB_AND_DEEP_LEARNING_ijariie26093.pdf (Accessed : )
IEEE Mande Srinivasa Rao, Sivalenka Aashuthosh, Shaik Sameer Babu, Yerra Abhi Ramu, and Ammanabrolu Sai Karthik, "LEAF DISEASE DETECTION USING MATLAB AND DEEP LEARNING," International Journal Of Advance Research And Innovative Ideas In Education, vol. 11, no. 2, pp. 1173-1177, Mar-App 2025. [Online]. Available: https://ijariie.com/AdminUploadPdf/LEAF_DISEASE_DETECTION_USING_MATLAB_AND_DEEP_LEARNING_ijariie26093.pdf [Accessed : ].
Turabian Mande Srinivasa Rao, Sivalenka Aashuthosh, Shaik Sameer Babu, Yerra Abhi Ramu, and Ammanabrolu Sai Karthik. "LEAF DISEASE DETECTION USING MATLAB AND DEEP LEARNING." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 11 number 2 ().
Vancouver Mande Srinivasa Rao, Sivalenka Aashuthosh, Shaik Sameer Babu, Yerra Abhi Ramu, and Ammanabrolu Sai Karthik. LEAF DISEASE DETECTION USING MATLAB AND DEEP LEARNING. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2025 [Cited : ]; 11(2) : 1173-1177. Available from: https://ijariie.com/AdminUploadPdf/LEAF_DISEASE_DETECTION_USING_MATLAB_AND_DEEP_LEARNING_ijariie26093.pdf
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