Identification and Detection of Seed Borne Diseases of Soybean Using Image Processing - A Survey

Soybean is an important commercial crop known as the “GOLDEN BEAN”. Damage is an important quality factor for grading, marketing and end use of Soybean. Seed damage can be caused by weather, fungi, insects, artificial drying, and by mechanical damage during harvest, transportation, storage and handling. Seed-borne pathogens causes enormous losses to crops in the world as well as in India. The presence of pathogenic propagules in a seed lot is pivotal because infected seed may fail to germinate, causes infection to seedlings and growing plants. The crop currently earns about Rs. 6976 crores of foreign exchange through exports of defatted oil cake. India now ranks 4th in terms of global soybean area sown and 5th in terms of soybean production after USA, Brazil, Argentina and China. Currently, soybean yield losses due to individual disease/insect/weed species ranges from 20 to 100 per cent. However, with integrated pest management schedule, 30-35 per cent additional yield can be obtained. Main challenge here is without disintegration finding the defected seeds in big lot. Image processing helps to extract low level features such as colour, texture and shape to identify the diseases and classify them. The paper discusses detail study of diseases, causes and different techniques that can be used to identify and detect them. Input data set consists of 100 Soybean colour images and also microscopic images used in the research at University of Agricultural Science, Dharwad. Proposed work has greater social impact by helping farmers to identify the seed borne diseases at early stage and thereby increasing yield.