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Developing an Excitation-Emission Matrix Fluorescence Spectroscopy Method Coupled with Multi-way Classification Algorithms for the Identification of the Adulteration of Shanxi Aged Vinegars

  • Tian-Qin Peng
  • Xiao-Li YinEmail author
  • Weiqing Sun
  • Baomiao Ding
  • Li-An Ma
  • Hui-Wen GuEmail author
Article
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Abstract

In this paper, an excitation-emission matrix (EEM) fluorescence spectroscopy method coupled with two kinds of multi-way classification algorithms was developed for the identification of the adulteration of Shanxi aged vinegars. The first classification model was built from selective information provided by parallel factor analysis (PARAFAC) based on partial least squares-discriminant analysis (PLS-DA) algorithm and the other one was modeled based on strictly multi-way classification algorithm multi-way partial least squares-discriminant analysis (N-PLS-DA). Both classification models showed good clustering tendency for authentic and adulterated Shanxi aged vinegars. Compared with the PARAFAC-PLS-DA method, more accurate and reliable classification results were provided by the N-PLS-DA method because it is a strictly multi-way classification method and can make the utmost use of the EEM fluorescence information of the vinegar samples. The N-PLS-DA model constructed from the EEM spectra enabled the recognition of adulterated samples with accurate rate of 100% both in training and prediction sets and obtained maximum sensitivity and specificity. This study showed that EEM fluorescence spectroscopy combined with multi-way classification algorithm N-PLS-DA could be used as a good method for the identification of the adulteration of Shanxi aged vinegar samples.

Keywords

Excitation-emission matrix fluorescence Multi-way classification methods Food adulteration Shanxi aged vinegars 

Notes

Funding Information

This work received financial supports from the National Natural Science Foundation of China (Grant No. 31701693), the Hubei Provincial Natural Science Foundation of China (Grant No. 2018CFB165), and the Doctoral Scientific Research Startup Foundation of Yangtze University (Grant Nos. 801090010134 and 801100010140).

Compliance with Ethical Standards

Conflict of Interest

Tian-Qin Peng declares that she has no conflict of interest. Xiao-Li Yin declares that she has no conflict of interest. Weiqing Sun declares that she has no conflict of interest. Baomiao Ding declares that he has no conflict of interest. Li-An Ma declares that she has no conflict of interest. Hui-Wen Gu declares that he has no conflict of interest.

Ethical Approval

This article does not contain any studies with human and animal subjects.

Informed Consent

Not applicable.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.College of Life SciencesYangtze UniversityJingzhouChina
  2. 2.Jingchu Food Research and Development CenterYangtze UniversityJingzhouChina
  3. 3.College of Chemistry and Environmental EngineeringYangtze UniversityJingzhouChina

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