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Food is the most important thing for humans. It provides energy for us. Approximately 700 million people around the world are undernourished. Around 37 percent of the total land on earth is being used for cultivating food. Due to urbanization the cultivating land might become even less in the future. Maximum agricultural productivity is one of the main issues mankind is facing now-a-days. As plants might get affected by various pathogens, insects or other living organisms throughout their crop time since we sow the seed till we get the crop yield.If proper care is not taken throughout the crop time it might cause effects on plants which is serious and because of that crop quality, productivity or quantity would possibly get affected. Detection of disease in plant through some automatic technique will be very useful as it reduces an outsized man work of observance in large crop fields, and at beginning stage itself we will be able to detect the symptoms of diseases in plants when they appear on plants. This paper presents a Convolutional Neural Network model for automatic detection on plants and identifies what kind of disease the plant in the crop is suffering from.