Can high‑resolution mass spectrometry (HRMS) – based metabolomics be used for a varietal classification of wines?

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22330%2F20%3A43921178" target="_blank" >RIV/60461373:22330/20:43921178 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Can high‑resolution mass spectrometry (HRMS) – based metabolomics be used for a varietal classification of wines?

Popis výsledku v původním jazyce

Wine is one of the most popular alcoholic beverages in many coun¬tries worldwide. However, due to its great financial value and rela¬tively large amount produced, it is also one of the most common commodities which are subject to fraud and mislabelling. Several wine attributes can be adulterated including geographic origin, harvest year, variety etc. Therefore, in the last few years, there has been growing interest in developing analytical methods for wine authentication. While analytical methods for the identification of wine by geographical origin exist and are implemented in official control, a sufficiently reliable strategy for authentication of wine variety is still missing. Considering the complexity of wine matrix, metabolomic fingerprinting in combination with sample direct injection (without prior extraction), was selected as a suitable tool to address this challenging task. As an analytical platform, U HPLC-Q Orbitrap instrument (Q Exactive Plus) was used. In total, 61 authentic samples of three different wine varieties (obtained in cooperation with German Federal Institute for Risk Assessment, Berlin) were analyzed within our study. The generated data, after automated data mining and alignment, were processed by principal component analysis (PCA) and then by partial least squares discriminant analysis (PLS DA). Statistically significant variables important for the grape variety classification were chosen according to their VIP (variable importance in projection) score. The resulting statistical models were validated and assessed according to their R2 (cum) and Q2 (cum) parameters. The most promising model enabled successful classification of 96 % of wine samples. In addition, tentative identification of the variable with highest VIP score (3 O-Caffeoylquinic acid, C16H18O9, also possible: 4 O-, 5 O-) was performed. Our results indicate that the metabolic fingerprinting of wine samples might be used as an effective tool for variety authentication.

Název v anglickém jazyce

Can high‑resolution mass spectrometry (HRMS) – based metabolomics be used for a varietal classification of wines?

Popis výsledku anglicky

Wine is one of the most popular alcoholic beverages in many coun¬tries worldwide. However, due to its great financial value and rela¬tively large amount produced, it is also one of the most common commodities which are subject to fraud and mislabelling. Several wine attributes can be adulterated including geographic origin, harvest year, variety etc. Therefore, in the last few years, there has been growing interest in developing analytical methods for wine authentication. While analytical methods for the identification of wine by geographical origin exist and are implemented in official control, a sufficiently reliable strategy for authentication of wine variety is still missing. Considering the complexity of wine matrix, metabolomic fingerprinting in combination with sample direct injection (without prior extraction), was selected as a suitable tool to address this challenging task. As an analytical platform, U HPLC-Q Orbitrap instrument (Q Exactive Plus) was used. In total, 61 authentic samples of three different wine varieties (obtained in cooperation with German Federal Institute for Risk Assessment, Berlin) were analyzed within our study. The generated data, after automated data mining and alignment, were processed by principal component analysis (PCA) and then by partial least squares discriminant analysis (PLS DA). Statistically significant variables important for the grape variety classification were chosen according to their VIP (variable importance in projection) score. The resulting statistical models were validated and assessed according to their R2 (cum) and Q2 (cum) parameters. The most promising model enabled successful classification of 96 % of wine samples. In addition, tentative identification of the variable with highest VIP score (3 O-Caffeoylquinic acid, C16H18O9, also possible: 4 O-, 5 O-) was performed. Our results indicate that the metabolic fingerprinting of wine samples might be used as an effective tool for variety authentication.

Druh

O - Ostatní výsledky

CEP obor

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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

2020

Kód důvěrnosti údajů

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