• Sanika Ashok Jadhav
• Meghana R. Khare
• Snehal S. Patil
• Vrushali M. Magdum
• Nisha N. Jadhav

Grapes are one of the most economically significant fruit crops globally, widely cultivated for fresh consumption and wine production. However, grapevine diseases such as downy mildew, black rot, and powdery mildew present serious threats to yield and crop quality. Traditional methods of disease identification rely heavily on manual inspection and expert knowledge, which are time-consuming, error-prone, and inaccessible to many small-scale farmers. The proposed project, Plant Defender, aims to address this problem by developing a web-based grape leaf disease prediction system using machine learning. It employs Support Vector Machine (SVM) classification and image processing techniques—specifically color histograms in HSV color space—for disease identification. The system allows users to upload images of grape leaves via a user-friendly interface built with React.js, which are then analyzed by a Flask-based backend. In addition to identifying the disease, the system also provides treatment recommendations to assist farmers in taking appropriate action. With high prediction accuracy and minimal computational requirements, Plant Defender offers a scalable and accessible solution to empower grape growers and support sustainable agriculture practices.

Grape Leaf Disease, Plant Disease Detection, Support Vector Machine (SVM), Image Processing, Smart Agriculture, Machine Learning, HSV Color Histogram, Flask, React.js, Precision Farming.

"Plant Defender: A Machine Learning-Based Approach for Real-Time Grape Leaf Disease Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 6, page no.g652-g657, June-2025, Available :http://www.jetir.org/papers/JETIR2506682.pdf

"Plant Defender: A Machine Learning-Based Approach for Real-Time Grape Leaf Disease Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 6, page no. ppg652-g657, June-2025, Available at : http://www.jetir.org/papers/JETIR2506682.pdf