基于二维相关谱掺杂牛奶检测方法研究
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摘要
针对乳制品掺假日益严重的现象，国家食品药品监督局、乳制品企业、消费者都亟需一种能实现对牛奶中掺杂的痕量目标物进行快速检测的方法。基于光谱的方法具有快速、简单、可实现在线测量等优势，已被广泛地应用于食品检测的各个领域。但由于牛奶体系的复杂性、掺杂物的多样化和微量化、以及掺杂物特征峰与牛奶特征峰相互重叠等的影响，常规的二维光谱在数据分析过程中还存在以下困难：①选择性低；②特征谱信息提取难；③图谱解析难。二维相关光谱是一种强大而灵活的分析技术，主要强调由外界扰动引起的信号变化的细微特征，具有高分辨率、高图谱解析能力等优点，已经在各个领域得到了广泛的应用研究。本文在对纯牛奶、掺杂牛奶二维相关谱特性研究的基础上，将二维相关谱与化学计量学用于掺杂牛奶的定性、定量分析。主要的研究内容包括以下四个方面：
1、提出了基于二维相关谱提取牛奶中掺杂物特征信息的方法。以掺杂尿素牛奶和掺杂三聚氰胺牛奶为研究对象，以牛奶中掺杂物浓度为外扰，构建二维相关谱(IR-IR, NIR-NIR, IR-NIR)，提取了牛奶中掺杂物特征信息，根据相关交叉峰的正负和有无对掺杂物的特征峰进行相互指认，验证了该方法的有效性。
2、发展了一种基于二维相关谱统计参量建模以判别牛奶掺杂的方法。通过两种方法：统计理论和多维主成分分析（Multi-way principal components analysis, MPCA)，提取了二维相关谱的特征参量，建立掺杂尿素牛奶、掺杂三聚氰胺牛奶、及两种掺杂牛奶与纯牛奶的判别模型，验证了该方法的可行性。
3、提出将基于核隐变量正交投影（Kernel orthogonal projection to latent structure, KOPLS）掺杂牛奶的判别方法，以解决牛奶中掺杂物信息与光谱信息的非线性问题。采用该方法建立两种掺杂牛奶与纯牛奶的KOPLS-DA模型，相对于OPLS-DA和PLS-DA模型，该方法提高了掺杂牛奶判别准确度。
4、提出了直接基于二维相关谱矩阵与多维偏最小二乘法（Multi-way partial least squares discriminant analysis，N-PLS）结合定量分析掺杂牛奶的检测方法。采用该方法对掺杂尿素牛奶和掺杂三聚氰胺牛奶的相关谱矩阵建立定量分析的N-PLS模型，相对于采用常规掺杂牛奶光谱建立的PLS模型，该方法可提高掺杂牛奶的预测精度。
本论文主要在量化相关谱矩阵的基础上，将其与化学计量学方法结合起来实现掺杂牛奶的检测。论文中所得到的实验研究结果，为相关谱矩阵在食品掺杂检测中的应用提供了理论和实验依据。
In view of the serious situation of adulteration in milk, it is urgent to develop a rapid, widely available and cost-effective method to detect the trace adulterant in the complex system of milk for the State Food and Drug Administration, the dairy industry and the consumers. The conventional one-dimensional spectroscopy analysis, which is widely applied in the examinations of milk quality, is a fast, non-destructive method, with no environmental pollution. However, milk is a complicated biological system, which contains both dissolved substances and colloidal suspensions and it has strong absorption and scattering. So it is impossible to extract the feature information of adulterants in milk using conventional one-dimensional spectrum due to the diversity and trace of adulterants and overlapping characteristic peaks between adulterants and milk. Two-dimensional (2D) correlation spectroscopy is an effective method for three major problems encountered by the conventional spectrum: low selectivity of the spectra, difficulty in extracting the information of the spectral feature and difficulty in spectrogram analysis. The2D correlation spectroscopy is a powerful tool for the detailed analysis of various spectroscopic data by external perturbation.2D correlation spectroscopy has been successfully applied in many complex biological systems because of high resolution, and good ability of spectrogram analysis. Qualitative and quantitative analysis of adulterated milk were studied systemically by2D correlation spectroscopy. The main content of the work and innovation, include the following four aspects:
1. The method of extracting effectively feature information of adulterant in milk based on2D correlation spectroscopy was proposed. By taking urea-tainted milk and melamine-tainted milk as the research objects,2D correlation analysis (IR-IR, NIR-NIR, IR-NIR) were performed under the perturbation of adulterants’ concentration to extract the characteristic information of adulterants. The effectiveness of this method was verified in terms of positive or negative corss peaks of adulterants in milk.
2. A new method for discrimination analysis of adulterated milk was developed based on parameterization of2D correlation spectroscopy. The characteristic parameters of2D correlation spectra of adulterated milk and pure milk were extracted by statistical theory and multi-way principal components analysis (MPCA). The discriminant models for milk adulterated with melamine, milk adulterated with urea and milk adulterated with either melamine or urea were constructed, respectively. The results showed that the proposed method was feasible.
3. A discrimination method of adulterated milk was proposed based on kernel orthogonal projection to latent structure for solving the problem of non-linear relationship between predictor and spectra variables. The KOPLS-DA models of adulterated milk and pure milk were built. The results showed that, comparing with OPLS-DA and PLS-DA models, the proposed new method could improve effectively discriminant accuracy of adulterated milk.
4. A new detection method of quantitative analysis of adulterated milk was proposed by combining2D correlation spectra with multi-way partial least squares (N-PLS). The N-PLS models for milk adulterated with either melamine or urea were constructed. The results showed that, comparing with PLS models, the proposed new method could improve effectively quantitative analysis precision of adulterated milk.
The detection methods of adulterated milk were studied using chemometrics based on quantification of2D correlation spectra. The experimental results, obtained in the paper, provide a theoretical and experimental basis for2D correlation spectroscopy applications in food safety.
1、提出了基于二维相关谱提取牛奶中掺杂物特征信息的方法。以掺杂尿素牛奶和掺杂三聚氰胺牛奶为研究对象，以牛奶中掺杂物浓度为外扰，构建二维相关谱(IR-IR, NIR-NIR, IR-NIR)，提取了牛奶中掺杂物特征信息，根据相关交叉峰的正负和有无对掺杂物的特征峰进行相互指认，验证了该方法的有效性。
2、发展了一种基于二维相关谱统计参量建模以判别牛奶掺杂的方法。通过两种方法：统计理论和多维主成分分析（Multi-way principal components analysis, MPCA)，提取了二维相关谱的特征参量，建立掺杂尿素牛奶、掺杂三聚氰胺牛奶、及两种掺杂牛奶与纯牛奶的判别模型，验证了该方法的可行性。
3、提出将基于核隐变量正交投影（Kernel orthogonal projection to latent structure, KOPLS）掺杂牛奶的判别方法，以解决牛奶中掺杂物信息与光谱信息的非线性问题。采用该方法建立两种掺杂牛奶与纯牛奶的KOPLS-DA模型，相对于OPLS-DA和PLS-DA模型，该方法提高了掺杂牛奶判别准确度。
4、提出了直接基于二维相关谱矩阵与多维偏最小二乘法（Multi-way partial least squares discriminant analysis，N-PLS）结合定量分析掺杂牛奶的检测方法。采用该方法对掺杂尿素牛奶和掺杂三聚氰胺牛奶的相关谱矩阵建立定量分析的N-PLS模型，相对于采用常规掺杂牛奶光谱建立的PLS模型，该方法可提高掺杂牛奶的预测精度。
本论文主要在量化相关谱矩阵的基础上，将其与化学计量学方法结合起来实现掺杂牛奶的检测。论文中所得到的实验研究结果，为相关谱矩阵在食品掺杂检测中的应用提供了理论和实验依据。
In view of the serious situation of adulteration in milk, it is urgent to develop a rapid, widely available and cost-effective method to detect the trace adulterant in the complex system of milk for the State Food and Drug Administration, the dairy industry and the consumers. The conventional one-dimensional spectroscopy analysis, which is widely applied in the examinations of milk quality, is a fast, non-destructive method, with no environmental pollution. However, milk is a complicated biological system, which contains both dissolved substances and colloidal suspensions and it has strong absorption and scattering. So it is impossible to extract the feature information of adulterants in milk using conventional one-dimensional spectrum due to the diversity and trace of adulterants and overlapping characteristic peaks between adulterants and milk. Two-dimensional (2D) correlation spectroscopy is an effective method for three major problems encountered by the conventional spectrum: low selectivity of the spectra, difficulty in extracting the information of the spectral feature and difficulty in spectrogram analysis. The2D correlation spectroscopy is a powerful tool for the detailed analysis of various spectroscopic data by external perturbation.2D correlation spectroscopy has been successfully applied in many complex biological systems because of high resolution, and good ability of spectrogram analysis. Qualitative and quantitative analysis of adulterated milk were studied systemically by2D correlation spectroscopy. The main content of the work and innovation, include the following four aspects:
1. The method of extracting effectively feature information of adulterant in milk based on2D correlation spectroscopy was proposed. By taking urea-tainted milk and melamine-tainted milk as the research objects,2D correlation analysis (IR-IR, NIR-NIR, IR-NIR) were performed under the perturbation of adulterants’ concentration to extract the characteristic information of adulterants. The effectiveness of this method was verified in terms of positive or negative corss peaks of adulterants in milk.
2. A new method for discrimination analysis of adulterated milk was developed based on parameterization of2D correlation spectroscopy. The characteristic parameters of2D correlation spectra of adulterated milk and pure milk were extracted by statistical theory and multi-way principal components analysis (MPCA). The discriminant models for milk adulterated with melamine, milk adulterated with urea and milk adulterated with either melamine or urea were constructed, respectively. The results showed that the proposed method was feasible.
3. A discrimination method of adulterated milk was proposed based on kernel orthogonal projection to latent structure for solving the problem of non-linear relationship between predictor and spectra variables. The KOPLS-DA models of adulterated milk and pure milk were built. The results showed that, comparing with OPLS-DA and PLS-DA models, the proposed new method could improve effectively discriminant accuracy of adulterated milk.
4. A new detection method of quantitative analysis of adulterated milk was proposed by combining2D correlation spectra with multi-way partial least squares (N-PLS). The N-PLS models for milk adulterated with either melamine or urea were constructed. The results showed that, comparing with PLS models, the proposed new method could improve effectively quantitative analysis precision of adulterated milk.
The detection methods of adulterated milk were studied using chemometrics based on quantification of2D correlation spectra. The experimental results, obtained in the paper, provide a theoretical and experimental basis for2D correlation spectroscopy applications in food safety.
引文
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