Classification of Disease in Potato Leaves using Deep Learning Approach

Agriculture is the backbone for every country in the world. and Farmers are the ones who predominantly take care of the crops and fields. In the present paper, we mainly focus on the diseases that are occurring in the farm fields mainly on potato leaves. Basically the leaf diseases occur because of the sudden climate change, improper nourishment, over usage of fertilizers, which involves high amount of NPK (Nitrogen, Phosphorus, Potassium). This study proposes a novel algorithm, which will help the farmers to detect the leaf diseases in the early stages, and eradicating them before growing. For this CNN (Convolutional Neural Network) algorithm, in order to detect the diseases that are present on the leaves by analyzing the leaves, perform feature extraction and provides recommendations and suggestions in order to prevent the disease. It mainly analyses the object, extracts the features and detect the diseases. This will help to eliminate the financial losses for the farmers, helps in yielding the more production of crops and also eradicate the disease completely from its roots, so that it won't occur next time. Additionally, this study incorporates the recommendation system in two distinct ways: first, it bases the recommendation on crop cultivation prior to the commencement of agriculture, and second, it bases the recommendation on crop curing following agriculture, that is, throughout the crop's growth phase.