Plant Disease Detection System Using Machine Learning Algorithm

Plant Disease Detection System Using Machine Learning Algorithm

Harshvardhan Singh1,Ankur Singh2,Mr.Raj Kumar Bharti3

B.Tech. 4th Year Students ,Department of Computer Science and Engineering ,Buddha Institute of Technology ,Gida, Gorakhpur ,Uttar Pradesh

bit21cs17@bit.ac.in1, bit21cs34@bit.ac.in2

Abstract

Plant diseases pose a significant threat to global food security, causing substantial agricultural losses. Traditional disease detection methods are labor-intensive and often unreliable. This paper presents an automated Machine Learning (ML)-based Plant Disease Detection System that leverages Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), and Random Forest (RF) for accurate disease classification using leaf images. We utilize a publicly available dataset (Plant Village) containing thousands of labeled images of healthy and diseased leaves. Our experiments demonstrate that deep learning models (CNNs) achieve 98.7% accuracy, outperforming traditional ML techniques. The proposed system includes a mobile application for real-time disease detection, enabling farmers to take timely preventive measures. This research contributes to precision agriculture by providing an efficient, scalable, and cost-effective disease detection solution.

Keywords: Plant disease detection, Machine Learning, Deep Learning, CNN, SVM, Random Forest, Precision Agriculture, Image Processing