Abstract: The study was based on the application of the low field nuclear magnetic resonance( NMR) technology combined with simple classification algorithm( SIMCA),linear discriminant method( LDA) and support vector machine method( SVM) to identify the milk in different days cold storage,and also to compare with the modeling effect of SIMCA and LDA in different function and SVM in the arguments of different types,different kernel functions. The results showed that the building function model of the LDA in Mahalanobis was better than the function model of Linear and Quadratic,the model of C- SVM in SVM was better than that model of Nu- SVM,the function model of the radial basis and linear was better than the function of S- shaped and polynomial. The total recognition accuracy of SIMCA model was 95.83%,the total recognition accuracy of the LDA Mahalanobis building function model was 100%,the total recognition accuracy was 87.50%,which was based on the radial basis function of C- SVM in SVM Mahalanobis model.The results showed that the using of Mahalanobis model in LDA was the most suitable for predicting the cold days of fresh milk.