A review of various existing approaches in disease detection of various plants and vegetables is done in order to find which algorithm works better and provides higher accuracy and this can be made using various models of machine learning.
India is a country that is highly dependent upon agriculture but the sad truth is many plants are being wasted due to an inexpert approach towards their growth. The various diseases in plants lead to their insufficient growth. Thus, it is very important to protect the plants at the right time so that the farmers does not face losses. Farmers usually analyse the damaged yield very late, thus failing to prevent it. They rush to domain experts which results in delay as they are not present in all regions. Thus a tool needs to be generated approaching to smart farming which will help farmers protect their crops and reduce losses with less human efforts. This can be made using various models of machine learning. In this paper, a review of various existing approaches is done in order to find which algorithm works better and provides higher accuracy. This paper consists of research in disease detection of various plants and vegetables such as potato, tomato, bell pepper, apple, grapes, cherry, strawberry, orange etc.