Prediction of Corn and Tomato Plant Diseases Using Deep Learning Algorithm

Abstract

India is mainly an agricultural country. Agriculture assumes an essential part in the Indian economy. More than 70% of the country family units rely upon agriculture. Despite growth in other sectors, agriculture's overall contribution of GDP has decreased from 19.2 percent to 17 percent in 2018–19. When the yield is affected by pets like insect/ fungal/bacteria/viral diseases the efficiency of the yield is decrease. This problem can be overcome by identifying diseases. The recent advances in the deep learning made the classification accurately. Using Plant Village dataset of 5,300 images of disease and healthy plant leaves were collected. The deep learning convolutional neural network i.e., VGG16 were trained to identify the 14 disease leaves of corn and tomato. After identifying the disease an intimation message sent to farmer mobile number using telegram bot channel. Based on the study it is found that the deep learning algorithm is 86% efficiency for disease classification.