Discriminating geographical origins and determining active substances of water caltrop shells through near-infrared spectroscopy and chemometrics.

Chemometrics Flavonoid Geographical discrimination Near-infrared spectroscopy Phenolic compound Water caltrop shell

Journal

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
ISSN: 1873-3557
Titre abrégé: Spectrochim Acta A Mol Biomol Spectrosc
Pays: England
ID NLM: 9602533

Informations de publication

Date de publication:
15 Dec 2023
Historique:
received: 22 03 2023
revised: 28 05 2023
accepted: 24 07 2023
medline: 20 9 2023
pubmed: 3 8 2023
entrez: 2 8 2023
Statut: ppublish

Résumé

Near-infrared spectroscopy (NIRS) combined with chemometric methods were used to discriminate the geographical origins of the water caltrop shells from different regions of China. Two active substances, the total phenolic content (TPC) and total flavonoid content (TFC) in the water caltrop shells were determined through the technique as well. Principal component analysis (PCA) combined with linear discriminant analysis (LDA) was adopted to build the geographical discriminant model. Quantitative analysis models of TPC and TFC were built using partial least squares (PLS) regression. 1st derivative and randomization test (RT) methods were used to optimize the quantitative analysis models. It was found that the geographical discriminant model can correctly recognize the water caltrop shells from different regions of China with a total accuracy of 93.33%. The values of TPC and TFC obtained by the optimized models and the standard method are close. The coefficient of determination (R

Identifiants

pubmed: 37531683
pii: S1386-1425(23)00883-1
doi: 10.1016/j.saa.2023.123198
pii:
doi:

Substances chimiques

Phenols 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

123198

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Rui Li (R)

College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China.

Yan Liu (Y)

College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China; Key Laboratory for Deep Processing of Major Grain and Oil (Wuhan Polytechnic University), Ministry of Education, College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China; Hubei Key Laboratory for Processing and Transformation of Agricultural Products (Wuhan Polytechnic University), College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China; Center of Food Safety, Hubei Key Research Base of Humanities and Social Science, College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China. Electronic address: liuyanwhpu@163.com.

Zhenzhen Xia (Z)

Institute of Agricultural Quality Standards and Testing Technology Research, Hubei Academy of Agricultural Science, Wuhan 430064, PR China.

Qiao Wang (Q)

College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China.

Xin Liu (X)

College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China.

Zhiyong Gong (Z)

College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, PR China.

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Classifications MeSH