Intelligent Disease Detection System for Early Blight of Tomato Using Foldscope: A Pilot Study

摘要

Early disease identification plays an inevitable role in modern agricultural fields to mitigate huge production losses. This paper presents a method to identify the pathogen of Alternaria solani, causing early blight fungal disease in tomato leaves, using foldscope and machine learning algorithms. Foldscope is a paper microscope invented by Manu Prakash and his team. It is the remedy for bulky and expensive conventional microscope. The foldscope can be attached with high resolution mobile phone for obtaining magnified images. The images of Alternaria solani were captured using the above mentioned set up. Then the captured images were classified using various machine learning algorithms. The quadratic Support Vector Machine (SVM) classifier shows the highest classification accuracy of 89% in prediction phase when compared to other machine learning algorithms.