Camellia oleifera oil has the reputation of “oriental olive oil”; it is important to detect the adulterated camellia oleifera oil. In this paper, NIR spectra were used to detect camellia oleifera oil adulterated with sunflower oil. Camellia oleifera oil adulterated with varying mass fraction of sunflower oil were prepared, i. e., 11 samples in 0%～10% with the gradient of 1%, 6 samples in 15%～40% with the gradient of 5%, 6 samples in 50%～100% with the gradient of 10%, and all the samples were divided into four groups such as A(0%～5%), B(6%～10%), C(15%～40%) and D(50%～100%). A total of 207 absorbance spectra(1 000～2 500 nm) were acquired by sampling 9 times in each adulteration. Calibration set was consist of two-thirds of the spectra data in each group selected randomly, and the validation set was made up of the last spectral data. After removing the noise in both ends of the spectra, principal component analysis(PCA) was used to reduce the dimensionality, then the first four PCs were used to build the support vector machine (SVM) identification model, and the identification accuracies of 96.38% and 94.20% in calibration and validation set were obtained. Furthermore, five characteristic wavelengths (1 212, 1 705, 1 826, 1 905 and 2 148 nm) were selected based on the loading of the PCs, the peaks or troughs of the original spectra and the chemical functional groups they were corresponding to. A NIR simplified SVM identification model was built by them, and the identification accuracies were 94.20% and 92.75%. Overall, both NIR spectroscopy and NIR characteristic spectra can realize the identification of camellia oleifera oil adulterated with sunflower oil, and the characteristic wavelengths, selected in this study, provide a basis for the design of corresponding instrument.