Currently existing national standards for honey adulteration are based on one type or certain types of compounds.Therefore,it is necessary to develop a multi-component and multi-index method to identify the honey adulteration.In this research,the changes of fingerprint between pure and adulterated honey were explored based on the NMR fingerprinting analysis and chemometrics method.Unsupervised method of principal component analysis（PCA）,supervised method of partial least squares discriminant analysis（PLS-DA） and orthogonal-PLS-DA（OPLS-DA） were all used to extract the useful information from NMR signals.The results showed that OPLS-DA model could distinguish the adulterated honey from pure honey.The explanation abilities based on the OPLS-DA model was 90.5%.The prediction and recognition abilities were 75.5% and 89.7%，respectively.Through permutation test,the chemometric model showed good stability,accurate predictability and high reliability.Several significant markers were found to distinguish honey from the loading plot and correlation coefficient analysis of OPLS-DA model.Combined with the correlation coefficient analysis,multiple linear regression equation was established to distinguish the adulterated honey from pure honey.The proposed method was simple and sensitive.This method provided an effective approach to control the honey quality and detect the honey adulteration.