ABSTRACT
Tomatoes are one of the important crop cultivated every parts of the world. The tomatoes belong to the family solanaceae, which has more effective growth on summer season. The crops have deep history and originated from South and Central America. This crop is most important because of its usefulness in cooking and in many agro based industries. India is the second largest producer of tomatoes following China and majority of farmers of India are relaying on agriculture.
The tomato farmers all-round the world faces many kinds of economic barriers as well as they face many problems in growth of the crop. The growth of the crop is affected basically by many infections caused due to virus and bacteria. Most common tomato diseases are Early Blight, Late Blight, Septoria leaf spot, Leaf Mold, Bacterial Spot, Tomato Pith Necrosis, Buckeye Rot, Fusarium wilt, southern Blight, seedling Disease, Tomato spotted wilt and Tomato Yellow leaf curl disease.
Farmers face many problems in identifying the different level of infections and to manage with pesticides. Mostly they rely on agricultural officers for understanding the severity level of the infection, which causes time consuming process.
This research work might be useful for farmers and agricultural officers to understand severity level of the affected crop with in time duration. Digital Image Processing plays a major role in evacuating many problems in disease identification process. This research article explains various pre-processing techniques followed during the research work. The final part of the research work is useful in analyzing the affected part from unaffected part of the tomato with the usage of deep learning technique.
