An Exploration of Contagion Infection in Citrus Plant with Augmented Data using ConvNet

Citrus is widely cultivated and consumed fruit across the global. It gains its popularity from its nutritional benefits. Citrus fruit has gained its international trading due to freshly consumed, processed products, oil production and other by-products. Citrus production is cut short mainly due its diseases. Identifying the diseases at early stage and stepping forward to cure them is vital role in improving the production. Automated disease identification cuts down the manual effort and also improves the efficiency in identification. With various degrees of accuracy, both machine learning and deep learning algorithms have been successful in identifying citrus leaf and fruit diseases. This research study proposes a novel disease classification method using CNN and also provides a comparative study with models like SVM, k-means clustering, ANN and CNN for disease identification.