Automatic detection techniques of disease in plants are very important in the field of agriculture for balancing the yield and population of the country. It assures food security of the country and helps to avoid agricultural economic losses. Many of us think that farmers are always suffering only from problems like unexpected rainfall, Natural Disaster, soil erosion and nutrient imbalance, but there are various other problems among them the major key problem is Plant Disease. Most of the plant diseases are classified and detected using the leaves part of the plant. The images of the Leaves always play an important role in Plant Disease Detection Automation. Image classification and detection are implemented by ML and DL algorithms. Especially in the plant disease images many authors have implemented ML and DL techniques. This paper has listed various techniques and methodologies used by ML and DL algorithms in detection of diseases in plants and Deep Neural Network implementation is explained in the experiment and result section.