Abstract
The rapidly analytical method for authenticity of edible oil was established by Fourier transform infrared spectroscopy (FTIR) combined with soft independent modeling of class analogy (SIMCA). Based on fingerprint characteristics of FTIR, the spectra of 53 qualified edible oils and 13 false edible oils were analyzed. After preprocessing these spectra data with second derivative and normalization, principal com- ponent analysis (PCA) was used to extract the characteristic variables in pattern recognition. Then, 43 quali- fied oils and 9 false oils were selected as training set to establish SIMCA classification model. And the model was validated by other 10 qualified oils and 4 false oils as validation set with the correct recognition rate of 100%. The results demonstrated that FTIR combined with chemometrics could be alternatively used
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