Oxygen consumption by diferent oenological tanins in a model wine solution

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.

In the winemaking process, several compounds that remain in the grape skins and seeds after the fermentation stage are bioactive-compounds (substances with potential beneficial effects on health) that can be extracted in order to recovery valuable substances with a high commercial value for the cosmetic, food (nutraceuticals) and pharmaceutical industries. The skins contain significant amounts of bioactive substances such as tannins (16-27%) and other polyphenolic compounds (2-6.5%) in particular, catechins, anthocyanins, proanthocyanins, quercetin , ellagic acid and resveratrol.

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.

One of the major determinants of wine quality is the aroma. Wine aroma is the human perception of the matrix of grape and yeast derived volatiles and their interaction that contribute to flavour wine. Most common are higher alcohols, ester and aldehydes. In previous studies the formation of characteristic volatile compounds have been linked to the metabolism of branched-chain and aromatic amino acids
(BCAAs) in synthetic grape must. Here we report on an investigation to assess the impact of the initial amino acid concentration on the production of aroma compounds by the industrial yeast VIN13 grown in both synthetic and real grape musts.

The color of a red wine is one of the most important parameters of its quality, giving much information on its status, such as the grape variety used or the winemaking style. As the result of a complex equilibrium between different forms of anthocyanins and polymerization reactions which occur over the course of time, color can also serve as an indication of a wines’ age. For this purpose the “chemical age” i and ii indexes have been introduced by Somers in 1977. The chemical age index i measures the color absorbance after the addition of acetaldehyde while chemical index ii provides an indication of how much of the total red pigments are resistant to SO2 bleaching.