Abstract: In this experiment, near infrared spectroscopy and principal component analysis combined with linear discriminant analysis method and K-nearest neighbors was used to qualify the qualitative discriminant analysis on the phenomenon of matcha added sugar, maltodextrin, mulberry leaf powder, barley seedling powder.The results showed that the qualitative judgment of PCA-LDA was superior to K nearest neighbor method. Pure matcha and fake matcha, pure matcha and matcha adulterated white sugar, pure matcha and matcha adulterated maltodextrin, pure matcha and matcha adulterated mulberry leaf powder, pure match and matcha adulterated barley flour, four kinds of fake matcha, the calibration set recognition rate of qualitative analysis model were respectively 98.3%, 100%, 91.7%, 100%, 100%, 100%, and the predictive set recognition rate were 96.5%, 100%, 87.5%, 95.8%, 90.3%, 95.3%, respectively. It can be seen that the models had very good precision and stabilization and they could quickly and accurately discriminate whether matha was adulterated.