Winemaking processes discrimination by using qNMR metabolomics

Abstract

AIM: Metabolomics in food science has been increasingly used over the last twenty years. Among the tools used for wine, qNMR has emerged as a powerful tool to discern wines based on environmental factors such as geographical origin, grape variety and vintage (Gougeon et al., 2019a). Since human factors are less studied while they also contribute a lot to the wine making, we wondered if this technique could also dissociate physical or chemical processes used in oenology. The goal of this work is to allow a better understanding of the interactions between the oenological processes and wine by finding metabolites that are responsible of winemaking processes’s differentiations through 1H‑NMR metabolomics targeted and untargeted (fingerprinting) approaches combined with advanced chemiometrics.

METHODS: Wine analyses were realized by qNMR approaches. Targeted (based on nearly fifty wine constituents) and untargeted analyses were carried out on wines having undergone several physical and chemical processes. Principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and similarity score (S-score) (Gougeon et al., 2019b) were performed out for the analytical discrimination of winemaking processes.

RESULTS: qNMR analyses associated with chemometrics allow discriminating not only the physical processed such as the filtration but also chemical processes like the maceration temperature, enzyme treatment and fining agent effects. Furthermore, the impacted metabolites were highlighted providing valuable data on the winemaking processes investigated.

CONCLUSIONS:

qNMR metabolomics offers a fast and reliable method to study the effects of winemaking practices on wine quality.