Abstract: A rapid method was developed for quantification detection of adulteration of corn oil in olive oil based on near-infrared spectroscopy (NIRS) . A total of 191 olive oil samples and mixed oil samples (olive oil and corn oil) were analyzed by NIRS, respectively. After first derivative and smooth processing, principal component analysis (PCA) was used to reduce the dimensionality of the spectral data. Through the loading graph of the first three principal components, characteristic wave band (7520⁶927cm-1, 6270⁵440cm-1and 4970⁴400cm-1, respectively) with max-relativity was determined. Predictive models of corn oil content were established in three bands using the partial least squares (PLS) method, respectively. The results showed that the model with best accuracy and stability were in 6270⁵440cm-1 band and 7 factors. In the range of 0.5% to 100%, the R2 of calibration samples and test sample were 0.9999, and the standard deviation between 0.126⁰.139. The results indicated that it would be feasible to destructive analysis the content of corn oil in olive oil by NIRS, and better prediction results could be obtained in 6270⁵440cm-1 band.