The latest generation of Least Square Twin Support Vector Machine has achieved amazing outcomes in the field of image classification. This paper presents a new method Linear Norms Tree based Least Square Twin Support Vector Machine for developing a plant disease recognition system, which is based on high-resolution multispectral satellite imagery. This proposed model can identify and classify different kinds of plant diseases. Dataset is a composition of diseased trees and other land cover. That are used to identify whether the tree is diseased or not. Experiments with wilt disease data set carried out indicate that new classifier, Linear Norms Tree based Least Square Twin Support Vector Machine, yields a progressively balanced classification accuracy between classes compared to different classification schemes in resolving the imbalanced classification problem.

Twin SVM, SVM, Norm, wilt, diseases, least square, imbalance data

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