Abstract: This paper choose 6 kinds of edible vegetable oils for a total of 23 samples as a typical tested object.Partial Least Squares-Linear Discriminant Analysis (PLS-LDA) method was employed to quickly identify a certain kind of edible vegetable oil (olive oil, peanut oil and corn oil) based on Raman. Raman backgrounds were subtracted by adaptive iteratively reweighted Penalized Least Squares (airPLS) method and wavelength variables were selected by Monte Carlo Uninformative Variable Elimination (MCUVE) method. The above spectra preprocessing not only effectively reduced the wavelength points and modeling computation, but also improved the general recognition rates higher than 90%, respectively. The process of identifying different kinds of edible oil using PLS-LDA method was suggested further on above basis. The experimental results showed that the PLS-LDA method had good application prospects and feasibility to identify edible oil species. This method provided a reference for processing the similar problems in food and agricultural products quality detection.