Fourier transform infrared spectroscopy (FTIR) combined with principal component analysis (PCA) and two-dimensional correlation infrared spectroscopy is applied to identify eight different varieties of Chinese rose leaves. The results show that the spectra of different varieties of rose leaves are similar, but there are obvious differences in second derivative spectra in the range of 1800~700 cm-1 which are selected to perform principal component analysis by SPSS software. The first three principal components have a cumulative contribution rate of 97.72% and yield classification accuracies of 95%. Two-dimensional correlation infrared spectroscopy is applied to study Chinese rose leaves. The significant differences in the position, intensity of auto-peaks and cross peaks are observed in the range of 1500~1275 cm-1and 1700~1520 cm-1. It is demonstrated that FTIR combined with principal component analysis and two-dimensional correlation infrared spectroscopy is a rapid and effective method for discriminating Chinese roses.