New molecular evidence of wine yeast-bacteria interaction unraveled by untargeted metabolomic profiling

Colour is an important quality parameter in wines and is the result of a complex mixture of pigments
(including anthocyanins and their derivatives, quinones, xanthyllium compounds, etc.). Red wine colour changes over time as pigments react between themselves and with other wine macromolecules
(particularly polyphenols). During wine tasting, colour is normally assessed on the outer rim of the wine profile in a tilted glass, since most wines are too opaque to be analysed in the middle of the glass. Therefore, depending on the depth of observation considered, the perception of wine colour can be different.

1,1,6-trimethyl-1,2-dihydronaphtelene (TDN) evokes the odor of “petrol” in wine, especially in the variety Riesling. Increasing UV-radiation due to climate change intensifies formation of carotenoids in the berry skins and an increase of TDN-precursors1. Exploring new viticultural and oenological strategies to limit TDN formation in the future requires precise knowledge of TDN thresholds in different matrices. Thresholds reported in the literature vary substantially between 2 µg/L up to 20 µg/L2,3,4 due to the use of different methods. As Riesling grapes are used for very different wine styles such as dry, sweet or sparkling wines, it is essential to study the impact of varying ethanol and carbonation levels.

Under standard champagne tasting conditions, the complex interplay between the level of dissolved CO2 found in champagne, its temperature, the glass shape, and the bubbling rate, definitely impacts champagne tasting by modifying the neuro-physico-chemical mechanisms responsible for aroma release and flavor perception. Based on theoretical principles combining heterogeneous bubble nucleation, ascending bubble dynamics and mass transfer equations, a global model is proposed (depending on various parameters of both the wine and the glass itself), which quantitatively provides the progressive losses of dissolved CO2 from laser-etched champagne glasses.

The effectiveness of enzyme-mediated maceration processes in red winemaking relies on a clear picture of the target (berry cell wall structure) to achieve the optimum combination of specific enzymes to be used. However, we lack the information on both essential factors of the reaction (i.e. specific activities in commercial enzyme preparation and the cell wall structure of berry tissue). In this study, the different combinations of pure recombinant enzymes and the recently validated high throughput cell wall profiling tools were applied to extend our knowledge on the grape berry cell wall polymeric deconstruction during the winemaking following a combinatorial enzyme treatment design.

Multiple Factor Analysis (MFA) According to the Chenin blanc Association of South Africa, there are three recognized dry wine styles, Fresh and Fruity (FF), Rich and Ripe Unwooded (RRU), and Rich and Ripe Wooded (RRW), classically attributed with the help of sensory evaluation. One of the “rapid methods” has drawn our attention for the purpose of simplifying and making style attribution for large sample sets, evaluated during different sessions, more robust. Polarized Projective Mapping (PPM) is a hybrid of Projective Mapping (PM) and Polarised Sensory Positioning (PSP). It is a reference-based method in which poles
(references) are used for the evaluation of similarities and dissimilarities between samples.