基于异谱二维NIR-IR相关判别掺杂牛奶
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摘要
为更快、更准确的判别掺杂牛奶和纯牛奶,将二维异谱NIR-IR相关谱与多维偏最小二乘判别(NPLS-DA)相结合,建立了掺杂牛奶与纯牛奶NPLS-DA模型。首先,准备并配置纯牛奶和浓度范围为0.01~1g·L-1掺杂淀粉牛奶样品各36个,并在室温的条件下采集所有样品的一维近红外透射光谱和中红外衰减全反射光谱。接着,计算了所有样品在4 200~4 800和900~1 700cm-1范围的同步二维NIR-IR相关谱,研究了其二维相关谱特性,并指出虽然该技术可提供更多的信息,但由于掺杂物微量,仍旧无法根据相关图谱直接对比判定牛奶是否掺杂,需要借助模式识别的方法进行判别。最后,将同步二维NIR-IR相关谱与NPLS-DA结合建立掺杂牛奶与纯牛奶的判别模型,该模型对校正集内部样品和预测集外部样品的判别正确率分别为95.8%和100%。此外,为了比较,分别建立了基于二维NIR和IR相关光谱的NPLS-DA模型,两模型对未知样品的判别正确率均为95.8%。研究结果表明:采用NIR-IR相关谱的NPLS-DA模型能提供更好判别结果。该方法可有效提取食品中掺杂物的特征信息,为检测掺杂食品提供了一个新的方法。
New approach for discriminant analysis of adulterated milk is proposed based on combining hetero-spectral two-dimensional(2D)near-infrared(NIR)and mid-infrared(IR)correlation spectroscopy along with multi-way partial least squares discriminant analysis(NPLS-DA).Firstly,36 pure milk samples were collected and 36 adulterated milk with starch samples(0.01 to 1g·L-1)were prepared by adding appropriate mass of starch into pure milk.Then,one-dimensional NIR transmittance spectra and IR attenuated total reflection spectra of pure milk and adulterated milk with starch were measured at room temperature.And the synchronous 2D NIR-IR(4 200~4 800 vs.900~1 700cm-1)correlation spectra of all samples were calculated.Due to the trace of adulterants,the synchronous 2DIR-NIR correlation spectral differences between adulterated milk with starch and pure milk are very subtle.Consequently,it was impossible to directly distinguish whether the sample was pure milk or adulterated milk.Finally,2DIR-NIR correlation spectra were to build a discriminant model to classify adulterated milk and pure milk.The classification accuracy rates of samples in calibration set and in prediction set were 95.8%and 100%respectively.Also,the NPLS-DA models were built based on 2D NIR and 2DIR correlation spectra,respectively.The classification accuracy rates of samples in prediction set were 95.8%.Comparison results showed that the NPLS-DA model could provide better results using 2D NIR-IR correlation spectra than using 2DNIR,and 2DIR correlation spectra.The proposed method can not only effectively extract the feature information of adulterants in milk,but also explores a new perspective method for detection of adulterated food.
New approach for discriminant analysis of adulterated milk is proposed based on combining hetero-spectral two-dimensional(2D)near-infrared(NIR)and mid-infrared(IR)correlation spectroscopy along with multi-way partial least squares discriminant analysis(NPLS-DA).Firstly,36 pure milk samples were collected and 36 adulterated milk with starch samples(0.01 to 1g·L-1)were prepared by adding appropriate mass of starch into pure milk.Then,one-dimensional NIR transmittance spectra and IR attenuated total reflection spectra of pure milk and adulterated milk with starch were measured at room temperature.And the synchronous 2D NIR-IR(4 200~4 800 vs.900~1 700cm-1)correlation spectra of all samples were calculated.Due to the trace of adulterants,the synchronous 2DIR-NIR correlation spectral differences between adulterated milk with starch and pure milk are very subtle.Consequently,it was impossible to directly distinguish whether the sample was pure milk or adulterated milk.Finally,2DIR-NIR correlation spectra were to build a discriminant model to classify adulterated milk and pure milk.The classification accuracy rates of samples in calibration set and in prediction set were 95.8%and 100%respectively.Also,the NPLS-DA models were built based on 2D NIR and 2DIR correlation spectra,respectively.The classification accuracy rates of samples in prediction set were 95.8%.Comparison results showed that the NPLS-DA model could provide better results using 2D NIR-IR correlation spectra than using 2DNIR,and 2DIR correlation spectra.The proposed method can not only effectively extract the feature information of adulterants in milk,but also explores a new perspective method for detection of adulterated food.
引文
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[3]Noda I,Ozaki Y.John Wiley&Sons;Chichester,West Sussex,England,Hoboken,2004.
[4]Noda I.Vib.Spectrosc.,2004,36(2):143.
[5]Chen J,Zhou Q,Noda I,et al.Applied Spectroscopy,2009,63(8):920.
[6]YANG Ren-jie,YANG Yan-rong,DONG Gui-mei,et al(杨仁杰,杨延荣,董桂梅,等).Spectroscopy and Spectral Analysis(光谱学与光谱分析),2014,34(8):2098.
[7]Yang Renjie,Liu Rong,Xu Kexin,et al.Proc.of SPIE,2014,8939:893912-1.
[8]Yang Renjie,Liu Rong,Xu Kexin.Food Bioscience,2013,2:61.
[9]Yang Renjie,Zhang Weiyu,Yang Yanrong,et al.Analytical Letters,2014,47(15):2560.
[10]Yang Renjie,Liu Rong,Xu Kexin,et al.Anal.Methods,2013,5(21):5949.
[11]Choi H C,Ryu S R,Ji H,et al.J.Phys.Chem.B,2010,114(34):10979.
[12]Kim H J,Kim S B,Kim J K,et al.J.Phys.Chem.B,2006,110(46):23123.
[13]Jung B,Matusewucz C,Ozaki Y.J.Phys.Chem B,2000,104:7812.
[14]Jung Y,Chae J,Yu S,et al.Vibrational Spectroscopy,2009,51:11.
[15]Barton II F E,Himmemsbach D S.Applied Spectroscopy,1993,47(11):1920.
[16]Awichi A,Tee E,Srikanthan G.Applied Spectroscopy,2002,56(7):897.