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| Detection of Adulterated Sesame Oil Based on Synchronous-Asynchronous Two-Dimensional Mid-Infrared Correlation Spectroscopy |
| YU Ge1, YANG Ren-jie2, LÜ Ai-jun1, TAN En-zhong1 |
1. Department of Mathematics and Physics, Beijing Institute of Petrochemical Technology, Beijing 102617, China
2. College of Engineering and Technology, Tianjin Agricultural University, Tianjin 300384, China |
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Abstract An innovative method for classification of adulterated sesame oil was applied by using synchronous-asynchronous two-dimensional (2D) mid-infrared correlation spectroscopy in combination with way partial least squares discriminant analysis (NPLS-DA). 40 pure sesame oils and 40 adulterated sesame oils with corn oil (3%~60%) were prepared and one-dimensional (1D) infrared absorption spectra(650~4 000 cm-1) were measured at room temperature. 1D spectral characteristics of pure and adulterated sesame oil were studied. Under the perturbation of the concentration of corn oil in sesame oils, the synchronous and asynchronous 2D mid-infrared correlation spectra were calculated and normalized. Synchronous-asynchronous 2D mid-infrared correlation matrix was obtained by computing the sum of the upper triangular part of the normalized synchronous 2D mid-infrared correlation matrix and the strictly lower triangular part of the normalized asynchronous 2D mid-infrared correlation matrix. The qualitative analysis NPLS-DA models were constructed to classify adulterated sesame oil by using synchronous-asynchronous 2D mid-infrared correlation spectra, synchronous 2D mid-nfrared correlation spectra, and asynchronous 2D mid-nfrared correlation spectra. For samples in prediction set, the rate of correct classification was 100% by using synchronous-asynchronous 2D mid-infrared correlation spectra, versus 96.2% by using synchronous and asynchronous 2D mid-infrared correlation spectra. Compared with synchronous, or asynchronous 2D mid-infrared correlation spectra, synchronous-asynchronous 2D mid-infrared correlation spectra not only contain more integrated characteristic information of adulterated oil, but also eliminate redundancy. Therefore, synchronous-asynchronous 2D mid-infrared correlation spectra can provide better classification results.
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Received: 2016-02-25
Accepted: 2016-06-30
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[1] Salghi R, Armbruster W, Schwack W. Food Chem., 2014, 153: 387.
[2] Peng D, Bi Y, Ren X, et al. Food Chem., 2015, 188: 415.
[3] Mendes T O, da Rocha R A, Porto B L, et al. Food Anal. Method, 2015, 8: 2339.
[4] SUN Qiao-chu, XIAO Chuang-bo, GUO Ben, et al(孙翘楚，肖创柏，郭 犇，等). Journal of Harbin Institute of Technology(哈尔滨工业大学学报), 2010, 42(11): 1814.
[5] Zhao X, Dong D, Zheng W, et al. Food Anal. Method, 2015, 8: 2308.
[6] Noda I. Journal of Molecular Structure, 2014, 1069: 3.
[7] Noda I. Journal of Molecular Structure, 2014, 1069: 23.
[8] YANG Ren-jie, YANG Yan-rong, LIU Hai-xue, et al(杨仁杰，杨延荣，刘海学，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2015, 35(8): 2124.
[9] Yang Renjie, Dong Guimei, Sun Xueshan, et al. Analytical Methods, 2015, 7(10): 4302.
[10] Yang Renjie, Liu Rong, Xu Kexin, et al. Applied Spectroscopy, 2013, 67(12): 1363.
[11] YANG Ren-jie, LIU Rong, XU Ke-xin, et al(杨仁杰, 刘 蓉, 徐可欣, 等). Acta Photonica Sinica(光子学报), 2013, 42(5): 580.
[12] Yang Renjie, Liu Rong, Xu Kexin. Food Bioscience, 2013, 2: 61.
[13] Yang Renjie, Zhang Weiyu, Yang Yanrong, et al. Analytical Letters, 2014, 47(15): 2560.
[14] Fadzlillah N A, Che Man Y B, Rohman A. Int. J. Food Prop., 2014, 17(6): 1275. |
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