Evidence map›Paper›PMID 39071928›Full record

ArticleFood chemistry: X2024

Fast and non-invasive identification of Baijiu based on Tyndall effect and chemometrics.

Qifei Zhu, Jun Zou, Chunfeng Guo, Rizeng Tao, Wenyue Li, Yifan Chen, Bobo Yang, Lihua Chen

Abstract read
In one paragraph

Article in Food chemistry: X, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Qifei ZhuSchool of Science, Shanghai Institute of Technology, Shanghai 201418, PR China.
Jun ZouSchool of Science, Shanghai Institute of Technology, Shanghai 201418, PR China.
Chunfeng GuoSchool of Science, Shanghai Institute of Technology, Shanghai 201418, PR China.
Rizeng TaoSchool of Science, Shanghai Institute of Technology, Shanghai 201418, PR China.
Wenyue LiSchool of Science, Shanghai Institute of Technology, Shanghai 201418, PR China.
Yifan ChenSchool of Science, Shanghai Institute of Technology, Shanghai 201418, PR China.
Bobo YangSchool of Science, Shanghai Institute of Technology, Shanghai 201418, PR China.
Lihua ChenSchool of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai 201418, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The value of Baijiu is affected by its flavor, age, and adulteration. Therefore, a simple and rapid identification method is crucial for the market. In this study, we present a rapid, non-intrusive identification technique for Baijiu utilizing the Tyndall effect combined with chemometrics analysis. Our experiment begins illuminating Baijiu with a 405 nm wavelength laser and recording the resulting bright light path due to the Tyndall effect. To further analyze the color and brightness information, Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Hierarchical Cluster Analysis (HCA), and Multilayer Perceptron (MLP) were employed. This study establishes correlations between the brightness of the Tyndall light path and seven trace flavor compounds in Baijiu. The findings demonstrate that this method effectively identifies the flavor, age cellar, and adulteration of Baijiu and also quantitatively detects the concentrations of flavor compounds. Additionally, an analysis platform was developed to enable the rapid identification of Baijiu.

Indexed as

Acetaldehyde (PubChem CID: 177)Acetal (PubChem CID: 7765)Acetic Acid (PubChem CID: 176)BaijiuCaproic Acid (PubChem CID: 8892)ChemometricsEthanol (PubChem CID: 702)Ethyl Acetate (PubChem CID: 8857)Ethyl hexanoate (PubChem CID: 31265)Ethyl lactate (PubChem CID: 7344)IdentificationIsoamyl alcohol (PubChem CID: 31260)Lactic Acid (PubChem CID: 612)Machine learningTyndall effect

Identifiers

PMID39071928
PMCPMC11280020

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.