Disease Identification in Papaya Plant and their Dataset

Papaya fruit which is known for its medicinal values is full of many nutrients which help human beings in fighting many ailments. The fruit yield is affected by many diseases occurring in different parts of papaya plant. These diseases when not cured at appropriate time may lead to their spread in farms and consequently affect the production adversely with huge loss to farmers. Farmers need smart techniques to identify these diseases to save time and to be accurate in classification. This paper presents the comprehensive study of several research works done in the field of disease recognition and classification in Papaya plants. Different studies have been analyzed for comparing their problem domains, algorithms used, diseases and parts of papaya plant used along with the dataset used in corresponding research. Focus is placed mainly on the datasets used for these works. Availability of dataset, size of the dataset in terms of number of images used (if any) and source of the dataset are the major parameters considered for comparation. It has been found that majority of works have been done on either leaves or fruits. Availability of adequate dataset with diseases in different parts of the papaya plant like leaf, fruit, stem etc. is the major challenge. Either the dataset in terms of number of images is small or not available in public domain for future reference.