基于二维红外相关谱判别掺假蜂蜜
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摘要
将二维中红外相关谱与多维偏最小二乘判别法相结合,建立了掺假蜂蜜与纯蜂蜜的判别模型。分别配置纯蜂蜜和掺蔗糖蜂蜜样品各30个,室温下,在650~4 000 cm~(-1)范围内采集了所有样品的衰减全反射光谱。在研究纯蜂蜜和掺假蜂蜜光谱特征的基础上,基于二维中红外相关谱矩阵建立了掺假蜂蜜的多维偏最小二乘判别模型,并与常规一维中红外谱的偏最小二乘判别模型的预测结果进行了比较。两个模型对未知样品的判别正确率分别为95%和90%。研究结果表明:基于二维中红外相关谱的多维偏最小二判别模型能更有效地提取掺假蜂蜜的特征信息,能提供高的判别正确率。
The classification model of adulterated honey was constructed based on two-dimensional(2D) mid-infrared correlation spectroscopy combined with N-way partial least squares discriminant analysis(NPLS-DA). Firstly, 30 pure honey samples and 30 adulterated honey with sugar samples were prepared respectively. Then, mid-infrared attenuated total reflectance spectra of all samples were obtained in the region of 650-4 000 cm~(-1) under room temperature. Spectral features of pure honey and adulterated honey were studied. NPLS-DA model was built using 2D mid-infrared correlation spectra. For comparison, the partial least squares discriminant analysis(PLS-DA)model was built using one-dimensional(1D)mid-infrared spectra. The classification accuracies of two classification models for prediction set were 95% and 90%, respectively. The results show that NPLS-DA model can effectively extract feature information of adulterated honey using 2D mid-infrared correlation spectra and provide higher accurate rates.
The classification model of adulterated honey was constructed based on two-dimensional(2D) mid-infrared correlation spectroscopy combined with N-way partial least squares discriminant analysis(NPLS-DA). Firstly, 30 pure honey samples and 30 adulterated honey with sugar samples were prepared respectively. Then, mid-infrared attenuated total reflectance spectra of all samples were obtained in the region of 650-4 000 cm~(-1) under room temperature. Spectral features of pure honey and adulterated honey were studied. NPLS-DA model was built using 2D mid-infrared correlation spectra. For comparison, the partial least squares discriminant analysis(PLS-DA)model was built using one-dimensional(1D)mid-infrared spectra. The classification accuracies of two classification models for prediction set were 95% and 90%, respectively. The results show that NPLS-DA model can effectively extract feature information of adulterated honey using 2D mid-infrared correlation spectra and provide higher accurate rates.
引文
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[10]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.
[11]Yang R J,Sun X S,Wang B H,et al.Adulteration of sesame oil with corn oil detected by use of two-dimensional infrared correlation spectroscopy and multivariate calibration[J].Spectroscopy Letters,2016,49(5):355-361.
[12]Yang R J,Dong G M,Sun X S,et al.Synchronous asynchronous two-dimensional correlation spectroscopy for the discrimination of adulterated milk[J].Analytical Methods,2015,7(10):4302-4307.
[13]杨仁杰,刘蓉,杨延荣,等.二维相关近红外谱多维主成分分析掺杂牛奶判别方法研究[J].光学精密工程,2014,22(9):2352-2358.
[14]Noda I.Frontiers of two-dimensional correlation spectroscopy.Part 1.New concepts and noteworthy developments[J].J Mol Struct,2014,1069:3-22.
[15]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.
[2]Irudayaraj J,Xu R,Tewari J.Rapid determination of invert cane sugar adulteration in honey using FTIR spectroscopy and multivariate analysis[J].Journal of food science,2003,68(6):2040-2045.
[3]梁奇峰,彭梦侠,林鹃.纯蜂蜜与掺假蜂蜜的红外光谱鉴别研究[J].安徽农业科学,2009,37(1):34-35.
[4]赵延华,刘成燕,韩旭,等.傅里叶变换红外光谱法快速鉴别掺假蜂蜜[J].理化检验-化学分册,2012,48(2):136-139.
[5]Wang Y,Xu C,Wang P,et al.Analysis and identification of different animal horns by a three-stage infrared spectroscopy[J].Spectrochim Acta A Mol Biomol Spectrosc,2011,83(1):265-270.
[6]Sun S,Zhou Q,Chen J.Infrared spectroscopy for complex mixtures:Applications in food and traditional chinese medicine[M].Beijing:Chemical Industry Press,2011.
[7]Zhan D,Sun S.Application of wavelet transform in improving resolution of two-dimensional infrared correlation spectroscopy[J].Lecture Notes in Computer Science,2005,3645:356-365.
[8]Chen J,Zhou Q,Noda I,et al.Quantitative classification of two-dimensional correlation spectra[J].Applied Spectroscopy,2009,63(8):920-925.
[9]崔彩路,杨仁杰,朱文碧,等.二维相关红外谱结合PARAFAC-MLR判别掺杂牛奶[J].天津农学院学报,2015,22(1):19-23.
[10]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.
[11]Yang R J,Sun X S,Wang B H,et al.Adulteration of sesame oil with corn oil detected by use of two-dimensional infrared correlation spectroscopy and multivariate calibration[J].Spectroscopy Letters,2016,49(5):355-361.
[12]Yang R J,Dong G M,Sun X S,et al.Synchronous asynchronous two-dimensional correlation spectroscopy for the discrimination of adulterated milk[J].Analytical Methods,2015,7(10):4302-4307.
[13]杨仁杰,刘蓉,杨延荣,等.二维相关近红外谱多维主成分分析掺杂牛奶判别方法研究[J].光学精密工程,2014,22(9):2352-2358.
[14]Noda I.Frontiers of two-dimensional correlation spectroscopy.Part 1.New concepts and noteworthy developments[J].J Mol Struct,2014,1069:3-22.
[15]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.
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