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The productivity in agricultural field is the one on which economy is highly determined. It may be the reason why disease identification in plants plays a good role in the field of agriculture. If we are not giving proper care, then it creates serious problems on plants and due to this the product quality, quantity or productivity will be affected. In a large portion of the fields, real gains have been acquired by the properties of computational intensity of Deep Learning systems for settling master errands. Deep Learning technology is used in the area of agriculture to solve the problem of diagnosing the plant disease based on the image taken in Smartphone. The images of leaves of healthy and diseased plants were used for plant disease detection and recognition by making use of convolutional neural network models as the learning tool. The total preparing of the models was finished with the utilization of a dataset of 1000 pictures, containing 4 distinct plants including healthy plants. The proposed system is expected to give a significant high success rate. This can be used as an advisory or early warning tool, and this approach could be further expanded to support an advanced plant disease identification system to operate in real cultivation conditions.

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