Paper Title
Review Paper on Oilseed Disease Diagnosis, Classification of Diseases and Forecasting of Diseases

Abstract
This paper focuses on Oilseed disease diagnosis, classification and forecasting of an Oilseed disease. Oilseeds are of two types one is inedible (linseed and castor) and other one is edible (safflower, sunflower, groundnut, sesame, Niger, rapeseed, mustard, and soybean). The disease identification and classification of various oilseeds like sunflower, safflower, peanuts, soybean, rapeseed, sesame, mustard, and soybean are included in this study. Machine Learning techniques, Expert systems, Convolution Neural Network, Particle Swarm Optimization with image processing etc. are used for disease classification and diagnosis. For predicting an epidemic of a disease, weather parameters are utilized in regression analysis. Keywords - Machine Learning, Expert Systems, Convolution Neural Network, Particle Swarm Optimization, Oilseed Disease Diagnosis, Forecasting.