二维近红外-中红外相关谱在掺假芝麻油判别中的应用
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摘要
提出了基于二维近红外-中红外相关谱判别掺假芝麻油的方法。分别配制了40个纯芝麻油样品和40个掺假芝麻油(掺入的玉米油的体积分数在3%~60%之间)样品,并采集了所有样品的近红外光谱和中红外光谱。在4 540~6 000cm~(-1)对650~1 800cm~(-1)内进行同步二维近红外-中红外相关谱计算,建立了掺假芝麻油的多维偏最小二乘判别模型,并将其预测性能与二维近红外相关谱和二维中红外相关谱判别模型的预测性能进行了比较。结果表明:上述3个模型对预测集未知样品的判别正确率分别为96.3%,92.6%,96.3%。
A method for identifying adulterated sesame oil using two-dimensional NIR-MIR correlation spectroscopy was proposed.40 pure sesame oil samples and 40 adulterated sesame oil samples(with volume fraction of adulterating corn oil varying from 3% to 60%)were prepared.And NIR and MIR spectra of all these samples were collected.The synchronous 2D NIR-MIR(4 540-6 000cm~(-1) vs.650-1 800cm~(-1))correlation spectra of these samples were calculated to construct N-way partial least squares discriminant analysis(NPLS-DA)model to identify adulterated sesame oil.The NPLS-DA models based on normalized synchronous 2D NIR and 2D MIR correlation spectra,were also constructed and their performance of discrimination to identify adulterated sesame oil were compared.It was found that the rates of accuracy of discrimination of the above mentioned 3NPLS-DA models for the prediction set were 96.3%,92.6%,96.3%,respectively.
A method for identifying adulterated sesame oil using two-dimensional NIR-MIR correlation spectroscopy was proposed.40 pure sesame oil samples and 40 adulterated sesame oil samples(with volume fraction of adulterating corn oil varying from 3% to 60%)were prepared.And NIR and MIR spectra of all these samples were collected.The synchronous 2D NIR-MIR(4 540-6 000cm~(-1) vs.650-1 800cm~(-1))correlation spectra of these samples were calculated to construct N-way partial least squares discriminant analysis(NPLS-DA)model to identify adulterated sesame oil.The NPLS-DA models based on normalized synchronous 2D NIR and 2D MIR correlation spectra,were also constructed and their performance of discrimination to identify adulterated sesame oil were compared.It was found that the rates of accuracy of discrimination of the above mentioned 3NPLS-DA models for the prediction set were 96.3%,92.6%,96.3%,respectively.
引文
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[11]刘蓉,苗静,杨仁杰.基于二维相关近红外光谱判定牛奶中掺杂的目标物[J].理化检验-化学分册,2013,49(4):386-390.
[12]杨仁杰,刘蓉,刘海学,等.基于二维红外相关谱的模式识别技术判别掺杂牛奶[J].中国食品学报,2015,15(4):196-200.
[13]杨仁杰,杨延荣,刘海学,等.二维相关谱在食品品质检测中的研究进展[J].光谱学与光谱分析,2015,35(8):2124-2129.
[14]YANG Ren-jie,YANG Yan-rong,DONG Gui-mei,et al.Multivariate methods for the identification of adulterated milk based on two-dimensional infrared correlation spectroscopy[J].Anal Methods,2014,6(10):3436-3441.
[15]YANG Ren-jie,LIU Rong,XU Ke-xin,et al.Discrimination of adulterated milk based on two-dimensional correlation spectroscopy(2DCOS)combined with kernel orthogonal projection to latent structure(K-OPLS)[J].Applied Spectroscopy,2013,67(12):1363-1367.
[2]VLACHOS N,SKOPELITIS Y,PSAROUDAKI M,et al.Applications of Fourier transform-infrared spectroscopy to edible oils[J].Anal Chim Acta,2006,573:459-465.
[3]YANG H,IRUDAYARAJ J.Comparison of near-infrared,Fourier transform-infrared,and Fourier transform-Raman methods for determining olive pomace oil adulteration in extra virgin olive oil[J].J Am Oil Chem Soc,2001,78(9):889-895.
[4]LUMAKSO F A,RIYANTO S,AHMAD S A S,et al.Application of chemometrics in combination with Fourier transform mid infrared spectroscopy for authentication of avocado oil[J].J Food Pharm Sci,2015,3(1):12-17.
[5]FADZLILLAH N A,CHE MAN Y B,ROHMAN A.FTIR spectroscopy combined with chemometric for analysis of sesame oil adulterated with corn oil[J].Int J Food Prop,2014,17(6):1275-1282.
[6]丁轻针,刘玲玲,武彦文,等.基于FTIR的芝麻油真伪鉴别和掺伪定量分析模型[J].光谱学与光谱分析,2014,34(10):2690-2695.
[7]ZHAO X,DONG D,ZHENG W,et al.Discrimination of adulterated sesame oil using mid-infrared spectroscopy and chemometrics[J].Food Anal Method,2015,8(9):2308-2314.
[8]NODA I,OZAKI Y.Two-dimensional correlation spectroscopy-applications in vibrational and optical spectroscopy[M].Chichester:Johns Wiley and Sons,2004.
[9]NODA I.Frontiers of two-dimensional correlation spectroscopy.Part 1.New concepts and noteworthy developments[J].J Mol Struct,2014,1069:3-22.
[10]NODA I.Frontiers of two-dimensional correlation spectroscopy.Part 2.Perturbation methods,fields of applications,and types of analytical probes[J].J Mol Struct,2014,1069:23-49.
[11]刘蓉,苗静,杨仁杰.基于二维相关近红外光谱判定牛奶中掺杂的目标物[J].理化检验-化学分册,2013,49(4):386-390.
[12]杨仁杰,刘蓉,刘海学,等.基于二维红外相关谱的模式识别技术判别掺杂牛奶[J].中国食品学报,2015,15(4):196-200.
[13]杨仁杰,杨延荣,刘海学,等.二维相关谱在食品品质检测中的研究进展[J].光谱学与光谱分析,2015,35(8):2124-2129.
[14]YANG Ren-jie,YANG Yan-rong,DONG Gui-mei,et al.Multivariate methods for the identification of adulterated milk based on two-dimensional infrared correlation spectroscopy[J].Anal Methods,2014,6(10):3436-3441.
[15]YANG Ren-jie,LIU Rong,XU Ke-xin,et al.Discrimination of adulterated milk based on two-dimensional correlation spectroscopy(2DCOS)combined with kernel orthogonal projection to latent structure(K-OPLS)[J].Applied Spectroscopy,2013,67(12):1363-1367.