Evidence map›Paper›PMID 37048322›Full record

ArticleFoods (Basel, Switzerland)2023

Targeted HPLC-UV Polyphenolic Profiling to Detect and Quantify Adulterated Tea Samples by Chemometrics.

Thom Romers, Javier Saurina, Sònia Sentellas, Oscar Núñez

Open access · goldAbstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2023. 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
2.3field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 9 citations in OpenAlex.

  1. Review
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

4 authors at 2 institutions in 1 country.

Thom RomersDepartment of Chemical Engineering and Analytical Chemistry, Universitat de Barcelona, Martí i Franquès 1-11, E08028 Barcelona, Spain.
Javier SaurinaDepartment of Chemical Engineering and Analytical Chemistry, Universitat de Barcelona, Martí i Franquès 1-11, E08028 Barcelona, Spain.ORCID 0000-0002-4892-9535
Sònia SentellasDepartment of Chemical Engineering and Analytical Chemistry, Universitat de Barcelona, Martí i Franquès 1-11, E08028 Barcelona, Spain.ORCID 0000-0002-5757-7236
Oscar NúñezDepartment of Chemical Engineering and Analytical Chemistry, Universitat de Barcelona, Martí i Franquès 1-11, E08028 Barcelona, Spain.ORCID 0000-0001-5850-8972
Generalitat de Catalunya · ESUniversitat de Barcelona · ES

Funding

Agencia Estatal de Investigación (Spain) PID2020-114401RB-C22 (AEI/10.13039/501100011033)
6 · The paper itself

Abstract

Tea can be found among the most widely consumed beverages, but it is also highly susceptible to fraudulent practices of adulteration with other plants such as chicory to obtain an illicit economic gain. Simple, feasible and cheap analytical methods to assess tea authentication are therefore required. In the present contribution, a targeted HPLC-UV method for polyphenolic profiling, monitoring 17 polyphenolic and phenolic acids typically described in tea, was proposed to classify and authenticate tea samples versus chicory. For that purpose, the obtained HPLC-UV polyphenolic profiles (based on the peak areas at three different acquisition wavelengths) were employed as sample chemical descriptors for principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) studies. Overall, PLS-DA demonstrated good sample grouping and discrimination of chicory against any tea variety, but also among the five different tea varieties under study, with classification errors below 8% and 10.5% for calibration and cross-validation, respectively. In addition, the potential use of polyphenolic profiles as chemical descriptors to detect and quantify frauds was evaluated by studying the adulteration of each tea variety with chicory, as well as the adulteration of red tea extracts with oolong tea extracts. Excellent results were obtained in all cases, with calibration, cross-validation, and prediction errors below 2.0%, 4.2%, and 3.9%, respectively, when using chicory as an adulterant, clearly improving on previously reported results when using non-targeted HPLC-UV fingerprinting methodologies.

Indexed as

chemometricschicoryfood authenticationfood safetyHPLC-UVpolyphenolstea

Identifiers

PMID37048322
PMCPMC10094304
OpenAlexW4362590693

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.