Interest and impact of PVP/PVI (Polyvinylpyrrolidone/ Polyvinylimidazole) on winemaking and final quality of wines

Oak wood selection and maturation are essential steps in the course of barrel fabrication. Given the existence of many factors involved in the choice of raw material and in natural seasoning of oak wood, it is very difficult to determine the real impact of seasoning and selection factors on oak wood composition. A sampling was done to study the evolution of oak wood chemical composition during four seasoning steps: non matured, 12 months, 18 months and 24 months. For this sampling, three selection factors were taken into account: age, grain type and the Polyphenolic Index measured by Oakscan®. Besides extractables
(~10%), three polymers constitute the main part of oak wood: cellulose, hemicelluloses and lignins.

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.

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.

Climate change and harvest date decisions have led to the evolution of must quality over the last decades. Increases in must sugar concentrations are among the most obvious consequences, quantitatively. Saccharomyces cerevisiae is a robust and acid tolerant organism. These properties, its sugar to ethanol conversion rate and ethanol tolerance make it the ideal production organism for wine fermentations. Unfortunately, high sugar concentrations may affect S. cerevisiae and lead to growth inhibition or yeast lysis, and cause sluggish or stuck fermentations. Even sublethal conditions cause a hyperosmotic stress response in S. cerevisiae which leads to increased formation of fermentation by-products, including acetic acid, which may exceed legal limits in some wines.

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.