International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Volume 8 Issue 3
May-June 2026

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Plant Disease Detection using AI

Author(s) Ms. Ananya M J, Ms. Chandana S, Ms. Dhruthi G N, Dr. Padma M C
Country India
Abstract This paper presents an AI-Based Tomato Leaf Disease Detection and Treatment Recommendation System developed to support smart agricultural practices through deep learning and computer vision techniques. The proposed system identifies tomato leaf diseases using image-based analysis and provides instant treatment recommendations for effective crop management. A MobileNetV2 deep learning model trained on the PlantVillage tomato dataset is used for disease classification, enabling accurate detection of diseases such as Early Blight, Late Blight, Mosaic Virus, and Yellow Leaf Curl Virus. The system integrates HTML, CSS, and JavaScript for the frontend interface and Node.js with Express.js for backend processing. Real-time disease prediction, severity estimation, and AI-generated treatment guidance help farmers take timely preventive measures and reduce crop loss. Experimental results demonstrate high classification accuracy and fast response time, making the system suitable for practical agricultural applications. The proposed solution highlights the potential of Artificial Intelligence in improving disease diagnosis, supporting sustainable farming, and enhancing agricultural productivity.
Keywords Tomato Leaf Disease Detection, Deep Learning, MobileNetV2, Computer Vision, Artificial Intelligence, PlantVillage Dataset, Image Classification, Smart Agriculture, Disease Prediction, Treatment Recommendation System, Precision Farming, Sustainable Agriculture.
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 8, Issue 3, May-June 2026
Published On 2026-05-26
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E-ISSN 2582-2160
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