Acta Chimica Sinica ›› 2012, Vol. 70 ›› Issue (08): 995-1000.DOI: 10.6023/A1110193 Previous Articles     Next Articles

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傅里叶变换红外光谱结合模式识别法快速鉴别食用油的真伪

刘玲玲a,b, 武彦文b, 张旭b, 欧阳杰a, 李冰宁b, 侯敏b, 陈舜琮b   

  1. a 北京林业大学生物科学与技术学院食品科学与工程系 北京 100083;
    b 北京市理化分析测试中心 北京市食品安全分析测试工程技术研究中心 北京 100089
  • 投稿日期:2011-10-19 修回日期:2012-01-18 发布日期:2012-02-06
  • 通讯作者: 欧阳杰 E-mail:chemist003@sohu.com
  • 基金资助:

    北京市自然科学基金(No. 7102021)资助项目.

Application of Fourier Transform Infrared Spectroscopy Combined with Pattern Recognition Method for Rapid Authentication of Edible Oil

Liu Linglinga,b, Wu Yanwenb, Zhang Xub, Ouyang Jiea, Li Bingningb, Hou Minb, Chen Shuncongb   

  1. a Department of Food Science and Engineering, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083;
    b Beijing Engineering Research Center of Food Safety Analysis, Beijing Center for Physical and Chemical Analysis, Beijing 100089
  • Received:2011-10-19 Revised:2012-01-18 Published:2012-02-06
  • Supported by:

    Project supported by the Natural Science Foundation of Beijing (No. 7102021).

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 component analysis (PCA) was used to extract the characteristic variables in pattern recognition. Then, 43 qualified 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 to rapidly and simply determine the authenticity of edible oil.

Key words: edible oils, authentication, FTIR, SIMCA