Agricultural productivity is something on which the economy highly depends. This is one of the reasons that disease detection in plants plays a vital role in the agriculture field, as having disease in plants is quite natural. If proper care is not taken in this area, then it causes severe effects on plants and due to which respective product quality, quantity, or productivity is affected. In this proposed approach optimized segmentation to find active area for features and reduce noise, then extract texture base features and learning by ensemble classifier approach. In Proposed framework main emphasis on getting sufficient features from disease and learning combination of classifier use linear and nonlinear classification function.