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FTIR Spectroscopy and Chemometric Class Modeling Techniques for Authentication of Chinese Sesame Oil

  • Original Paper
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Journal of the American Oil Chemists' Society

Abstract

This investigation was aimed at developing a rapid analysis method for authentication of Chinese sesame oils by FTIR spectrometry and chemometrics. Ninety-five sesame oil samples were collected from the six main producing areas of China to include most if not all of the significant spectral variations likely to be encountered in future authentic materials. Two class modeling techniques, the soft independent modeling of class analogy (SIMCA) and the partial least squares class model (PLSCM) were investigated and the data preprocessing techniques including smoothing, derivative and standard normal variate (SNV) tests were performed to improve the classification performance. It was demonstrated that SIMCA and PLSCM can detect various adulterated sesame oils doped with 3% or more (w/w) of other cheaper oils, including rapeseed, soybean, palm and peanut oils. First derivative, second derivative and SNV tests significantly enhanced the class models by reducing baseline and background shifts. Smoothing of raw spectra led to inferior identification performance and proved itself to be unsuitable because some of the detailed frequency details were lost during smoothing. The best model performance was obtained with second derivative spectra by SIMCA (sensitivity 0.905 and specificity 0.944) and PLSCM (sensitivity 0.952 and specificity 0.937). Although it is difficult to perform an exhaustive sampling of all types of pure sesame oils and potential adulterations, PLS and SIMCA combined with FTIR spectrometry can detect most of current adulterations of sesame oils on the Chinese market.

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Acknowledgments

This work was financially supported by the National Public Welfare Industry Projects of China (no.201210010), Hangzhou Programs for Agricultural Science and Technology Development (no.20101032B28) and the Key Scientific and Technological Innovation Team Program of Zhejiang Province (no.2010R50028). Dr. Chen-Bo Cai is grateful to the financial aid of the Applied and Basic Research Project of Yunan Provincial Science and Technology Department (no.2010CD087).

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Authors and Affiliations

  1. College of Life Sciences, China Jiliang University, Hangzhou, 310018, People’s Republic of China

    De-Hua Deng, Lu Xu, Zi-Hong Ye, Hai-Feng Cui & Xiao-Ping Yu

  2. College of Chemistry and Chemical Engineering, Anyang Normal University, Anyang, 455002, People’s Republic of China

    De-Hua Deng

  3. Department of Chemistry and Life Science, Chuxiong Normal University, Chuxiong, 675000, People’s Republic of China

    Chen-Bo Cai

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  1. De-Hua Deng
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  2. Lu Xu
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  3. Zi-Hong Ye
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  4. Hai-Feng Cui
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  5. Chen-Bo Cai
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  6. Xiao-Ping Yu
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Correspondence to Lu Xu or Xiao-Ping Yu.

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Deng, DH., Xu, L., Ye, ZH. et al. FTIR Spectroscopy and Chemometric Class Modeling Techniques for Authentication of Chinese Sesame Oil. J Am Oil Chem Soc 89, 1003–1009 (2012). https://doi.org/10.1007/s11746-011-2004-8

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  • DOI: https://doi.org/10.1007/s11746-011-2004-8

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