Black Measles Disease Identification in Grape Plant (Vitis vinifera) Using Deep Learning
Kirti Kirti, Navin Rajpal, Jyotsna Yadav
Abstract
The most common diseases found in plants are the fungi infections/diseases. One of the common fungal diseases is Esca (Black Measles) which is found in the Grape Plants and can be easily identified as brown streaking lesions on any part of the leaf. The affected leaves can dry off completely and fall off from the plant prematurely which eventually results in death of the plant. In this work, an improved technique based on Deep Learning algorithm for identifying Esca Black measles in GrapeVines is proposed. The proposed method yields better performance and accuracy in detecting the disease, than past Machine Learning based approaches. Grape Plant dataset from PlantVillage Database is used for the work. The dataset contains total 1807 images (healthy and diseased). ResNet 50 architecture of Deep Neaural Network in combination with Transfer Learning and Fine Tuning was used to compute the results. The proposed system provides an accuracy of more than 97% and performed better than the existing approaches which are based on feature extraction methods.