Critical assessment of chemometric models employed for varietal authentication of wine based on UHPLC-HRMS data

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22330%2F23%3A43926145" target="_blank" >RIV/60461373:22330/23:43926145 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1016/j.foodcont.2022.109336" target="_blank" >https://doi.org/10.1016/j.foodcont.2022.109336</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.foodcont.2022.109336" target="_blank" >10.1016/j.foodcont.2022.109336</a>

Result language

angličtina

Original language name

Critical assessment of chemometric models employed for varietal authentication of wine based on UHPLC-HRMS data

Original language description

The use of metabolic fingerprinting combined with advanced chemometric tools for wine authentication has increased in recent years. Although numerous studies, showing different authentication strategies, have been published, rarely any attention has been paid to the stability of used classification models over a longer time period. Here, we present a reliable and robust metabolic fingerprinting-based multiclass strategy for varietal authentication of wine. Analysis was conducted using ultra-high-performance liquid chromatography coupled to high-resolution tandem mass spectrometry. Two sets of commercial wine samples, one for the creation of classification models (201 wines, five red and five white grape varieties) and one for the verification of their validity over a longer time period (138 wines, three white varieties), were analysed. The generated data from the first sample set were subjected to orthogonal partial least squares discriminant analysis (OPLS-DA). The resulting models were validated and used to build decision trees, which enabled the classification of wine samples according to the grape variety. The individual classification rates of the OPLS-DA models were 90–100%. Overall classification rates of the decision trees were 94 and 96% for red and white wines, respectively. In case of the white wine decision tree, verification of its validity over a longer time period was performed using an additional sample set, analysed four months after the original sample set. From the additional sample set, 87% of samples were correctly classified, thus, the stability of the OPLS-DA classification models over a longer time period was verified. In addition, 25 varietal markers of significant statistical importance, mostly flavonoids, phenolic acids and their derivatives, were tentatively identified. © 2022

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10406 - Analytical chemistry

Project

<a href="/en/project/LM2018100" target="_blank" >LM2018100: Infrastructure for Promoting Metrology in Food and Nutrition in the Czech Republic</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Food control

ISSN

0956-7135

e-ISSN

1873-7129

Volume of the periodical

143

Issue of the periodical within the volume

JAN 2023

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

11

Pages from-to

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UT code for WoS article

000862886700002

EID of the result in the Scopus database

2-s2.0-85137105831