Survey on Crop Disease Prediction using different techniques For Crop Yield Prediction

  • Shruti Kudagi, Suhas Patil, Mrunal Bewoor


Due to advancement   in technology, the research in agriculture is rapidly increased. This is giving opportunity to many researchers to solve upcoming challenges in area of agriculture. In India agriculture being the main part which is responsible for development of countries economy. Sugarcane is one of the paddy crops which is playing important role in crop production. But due to underlying diseases there is large number of financial loss. So climate, soil, type of sugarcane and disease will affect the yield. So, prediction of crop disease is one of the essential which is responsible for crop yield. So, predicting crop disease increase the growth rate of agriculture. Many researchers are proposing different technique to predict crop diseases by using artificial intelligence, image processing, neural network. In this paper, survey has been done on different solution to predict   crop disease. This paper introduces machine learning technique which uses Support Vector Machine(SVM) to predict crop disease which will help  to select appropriate algorithm for  predicting the crop disease and to increase the pace of crop yield .