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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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

Název v anglickém jazyce

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

Popis výsledku anglicky

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

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10406 - Analytical chemistry

Projekt

<a href="/cs/project/LM2018100" target="_blank" >LM2018100: Infrastruktura pro propagaci metrologie v potravinářství a výživě v České republice</a><br>

Návaznosti

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

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Food control

ISSN

0956-7135

e-ISSN

1873-7129

Svazek periodika

143

Číslo periodika v rámci svazku

JAN 2023

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

11

Strana od-do

—

Kód UT WoS článku

000862886700002

EID výsledku v databázi Scopus

2-s2.0-85137105831