The invention belongs to the field of visible-near infrared spectroscopic analysis technology, and more specifically relates to a visible-near infrared spectrum PLS-DA modeling method combining Adaboost algorithm. The visible-near infrared spectrum PLS-DA modeling method is characterized in that: a classifier with high performances is obtained by integration of a plurality of PLS-DA models through Adaboost algorithm. PLS-DA models are common identification models used in infrared spectrum technology. PLS-DA models are not capable of reflecting the non-linear relationship between the visible-near infrared spectrum and samples to be analyzed effectively, so that the accuracy of PLS-DA models on data with high nonlinearity is reduced. Adaboost algorithm is capable of providing a framework, and a plurality of methods can be used for construction of sub-classifiers. The high-performance classifier, which is capable of realizing accurate classification of the data with high nonlinearity, is obtained by using PLS-DA models as the sub-classifiers, and combining Adaboost algorithm, so that popularized application of PLS-DA models in identification of the data with high nonlinearity is realized.