An innovative method for classification of adulterated sesame oil was applied by using synchronous-asynchronous two-dimensional (2D) mid-infrared correlation spectroscopy in combination with way partial least squares discriminant analysis (NPLS-DA). 40 pure sesame oils and 40 adulterated sesame oils with corn oil (3%~60%) were prepared and one-dimensional (1D) infrared absorption spectra(650~4 000 cm-1) were measured at room temperature. 1D spectral characteristics of pure and adulterated sesame oil were studied. Under the perturbation of the concentration of corn oil in sesame oils, the synchronous and asynchronous 2D mid-infrared correlation spectra were calculated and normalized. Synchronous-asynchronous 2D mid-infrared correlation matrix was obtained by computing the sum of the upper triangular part of the normalized synchronous 2D mid-infrared correlation matrix and the strictly lower triangular part of the normalized asynchronous 2D mid-infrared correlation matrix. The qualitative analysis NPLS-DA models were constructed to classify adulterated sesame oil by using synchronous-asynchronous 2D mid-infrared correlation spectra, synchronous 2D mid-nfrared correlation spectra, and asynchronous 2D mid-nfrared correlation spectra. For samples in prediction set, the rate of correct classification was 100% by using synchronous-asynchronous 2D mid-infrared correlation spectra, versus 96.2% by using synchronous and asynchronous 2D mid-infrared correlation spectra. Compared with synchronous, or asynchronous 2D mid-infrared correlation spectra, synchronous-asynchronous 2D mid-infrared correlation spectra not only contain more integrated characteristic information of adulterated oil, but also eliminate redundancy. Therefore, synchronous-asynchronous 2D mid-infrared correlation spectra can provide better classification results.