发光学报, 2018, 39 (4): 568, 网络出版: 2018-05-07   

三维荧光光谱结合Tchebichef矩快速鉴别掺伪芝麻油

D Fluorescence Spectra Combined with Tchebichef Moments for Rapid Identification of Doping Sesame Oil
作者单位
1 燕山大学 测试计量技术及仪器河北省重点实验室, 河北 秦皇岛066004
2 燕山大学 信息科学与工程学院, 河北 秦皇岛066004
摘要
应用FS920荧光光谱仪测定样品的三维荧光光谱数据,直接利用Tchebichef矩提取三维光谱灰度图的特征信息,然后对其进行聚类分析,最后通过逐步回归建立样本中各成分的线性模型。聚类分析能够准确识别掺伪芝麻油,并正确解析其组成成分,得到的线性模型相关系数R>0.99。研究表明,Tchebichef矩能够有效提取光谱的特征信息,应用于掺伪芝麻油鉴别可获得良好的定性和定量分析结果。
Abstract
The three-dimensional fluorescence spectra of the samples were measured by FS920 fluorescence spectrometer, and the characteristic information of three-dimensional spectral grayscale was extracted directly by Tchebichef moments. And then, the cluster analysis was carried out. Finally, a linear model of each component in the sample was established by the stepwise regression. Clustering analysis can identify doping sesame oil with a high recognition rate and can correctly analyze its constituent components. R-squared of the obtained linear model is greater than 0.99. The results show that Tchebichef moments can effectively extract the characteristic information of the spectrum and can be used to identify the doping sesame oil and obtain good qualitative and quantitative analysis results.
参考文献

[1] 吴希军, 潘钊, 赵彦鹏, 等. 荧光光谱及平行因子分析法在植物油鉴别中的应用 [J]. 光谱学与光谱分析, 2014, 34(8):2137-2142.

    WU X J, PAN Z, ZHAO Y P, et al.. Application of fluorescence spectroscopy and parallel factor analysis in the identification of vegetable oils [J]. Spectrosc. Spect. Anal., 2014, 34(8):2137-2142. (in Chinese)

[2] 吴希军, 田瑞玲, 孙梦菲, 等. 基于荧光光谱及矩阵分析的植物油鉴别技术 [J]. 光谱学与光谱分析, 2016, 36(7):2155-2161.

    WU X J, TIAN R L, SUI M F, et al.. Identification technology of vegetable oil based on fluorescence spectroscopy and matrix analysis [J]. Spectrosc. Spect. Anal., 2016, 36(7):2155-2161. (in Chinese)

[3] ZHAI H L, ZHAI Y Y, LI P Z, et al.. A simple approach to quantitative analysis using three-dimensional spectra based on selected Zernike moments [J]. Analyst, 2012, 138(2):683-687.

[4] JING C, BAO Q L, HONG L Z, et al.. A practical application of wavelet moment method on the quantitative analysis of Shuanghuanglian, oral liquid based on three-dimensional fingerprint spectra [J]. J. Chromat. A, 2014, 1352:55-61.

[5] CHEN J, LI B Q, XU M L, et al.. Krawtchouk image moment method for the simultaneous determination of three drugs in human plasma based on fluorescence three-dimensional spectra [J]. Talanta, 2016, 161:99-104.

[6] LI B Q, CHEN J, XU M L, et al.. The determination of multi-components utilizing 1 H NMR three-dimensional spectra combined Tchebichef moments [J]. Chemomet. Intell. Lab. Syst., 2016, 156:128-136.

[7] MUKUNDAN R, ONG S H, LEE P A. Image analysis by Tchebichef moments [J]. IEEE Trans. Image Proc., 2001, 10(9):1357-1364.

[8] 张辉, 周健, TOUMOULIN C, 等. Tchebichef矩的快速算法 [J]. 东南大学学报(自然科学版), 2006, 36(5):857-862.

    ZHANG H, ZHOU J, TOUMOULIN C, et al.. Fast algorithm for Tchebichef moments [J]. J. Southeast Univ.(Nat. Sci. Ed.), 2006, 36(5):857-862. (in Chinese)

[9] 梁曼, 黄富荣, 何学佳, 等. 荧光光谱成像技术结合聚类分析及主成分分析的藻类鉴别研究 [J]. 光谱学与光谱分析, 2014, 34(8):2132-2136.

    LIANG M, HUANG F R, HE X J, et al.. Identification of algae by fluorescence spectroscopy combined with cluster analysis and principal component analysis [J]. Spectrosc. Spect. Anal., 2014, 34(8):2132-2136. (in Chinese)

[10] 刘丙新, 李颖, 韩亮, 等. 基于光谱反射率数据的水面油种鉴别研究 [J]. 光谱学与光谱分析, 2016, 36(4):1100-1103.

    LIU BI X, LI Y, HAN L, et al.. Identification of surface oil based on spectral reflectance data [J]. Spectrosc. Spect. Anal., 2016, 36(4):1100-1103. (in Chinese)

潘钊, 崔耀耀, 吴希军, 刘婷婷, 苑媛媛. 三维荧光光谱结合Tchebichef矩快速鉴别掺伪芝麻油[J]. 发光学报, 2018, 39(4): 568. PAN Zhao, CUI Yao-yao, WU Xi-jun, LIU Ting-ting, YUAN Yuan-yuan. D Fluorescence Spectra Combined with Tchebichef Moments for Rapid Identification of Doping Sesame Oil[J]. Chinese Journal of Luminescence, 2018, 39(4): 568.

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