Multiple adulteration is a commonly used fraud of illegal traders to mask the traditional adulteration detection methods. In this study, rapid detection of multiple adulteration of sesame oil was proposed using a portable Raman spectrometer. Two strategies including simplex theory of mixtures and D-optimal mixture design were used to conduct variable selection and model evaluation, respectively. Based on simplex theory of mixtures, the important variables were selected by orthogonal partial least squares discriminant analysis of preprocessed Raman spectra of sesame oils and four adulterant oils. Moreover, multiple adulteration identification model was built by one-class partial least squares and validated by representative adulterated samples prepared by D-Optimal mixture design. The validation results show that 40 sesame oils adulterated with four types of adulterant oils can be correctly identified, indicating Raman spectroscopy is an effective tool for the detection of multiple adulteration of sesame oil, especially for on-site applications.
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| http://dx.doi.org/10.1016/j.foodchem.2022.134884 | DOI Listing |
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