Validation of long-term stability of chemometric models employed for varietal authentication of wines (follow-up study)

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22330%2F22%3A43925451" target="_blank" >RIV/60461373:22330/22:43925451 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Validation of long-term stability of chemometric models employed for varietal authentication of wines (follow-up study)

Popis výsledku v původním jazyce

On the occasion of RAFA 2021 (www.rafa2021.eu), we presented a metabolic fingerprinting-bases multiclass strategy for varietal authentication of wines, which was developed within a joint research project of University of Chemistry and Technology Prague (UCT Prague) and German Federal Institute for Risk Assessment (BfR Berlin). 201 samples of five red and five white wine varieties were analysed and used for the creation of classification models. These models were arranged into decision trees and used for wine varietal identification. With classification rates ≥ 94% for both red and white wines, this strategy proved to be highly reliable. In the follow-up study, an additional sample set of 138 white wine samples was analysed and used for the verification of long-term stability of the previously created classification models. With a classification rate of 87%, the tested white wine decision tree appeared to be robust. Hence, the developed authentication strategy is very promising.

Název v anglickém jazyce

Validation of long-term stability of chemometric models employed for varietal authentication of wines (follow-up study)

Popis výsledku anglicky

On the occasion of RAFA 2021 (www.rafa2021.eu), we presented a metabolic fingerprinting-bases multiclass strategy for varietal authentication of wines, which was developed within a joint research project of University of Chemistry and Technology Prague (UCT Prague) and German Federal Institute for Risk Assessment (BfR Berlin). 201 samples of five red and five white wine varieties were analysed and used for the creation of classification models. These models were arranged into decision trees and used for wine varietal identification. With classification rates ≥ 94% for both red and white wines, this strategy proved to be highly reliable. In the follow-up study, an additional sample set of 138 white wine samples was analysed and used for the verification of long-term stability of the previously created classification models. With a classification rate of 87%, the tested white wine decision tree appeared to be robust. Hence, the developed authentication strategy is very promising.

Druh

O - Ostatní výsledky

CEP obor

—

OECD FORD obor

10700 - Other natural sciences

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

2022

Kód důvěrnosti údajů

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