Evaluation of colloidal stability in white and rosé wines investing Dynamic Light Scattering technology

Lately several works highlighted the capacity of grape cell-wall material (CWM) to interact with proanthocyanidins (PA), indicating its potential use as fining agent for red wines.1–4 However, those studies were performed by using purified PAs and very high doses of CWM (almost ten-fold higher than those used in wine industry for other commercial fining agents). The present study focuses on the applicability of CWM from Cabernet sauvignon pomace as fining agent for red wines under real winery conditions. Grapes of cultivar Cabernet sauvignon were harvested at three different maturity levels
(unripe, mature, and overripe) and used for red winemaking. The pomace of such vinifications were used as source of CWM, and applied into red wines at two different concentrations: 0.2 g/L and 2.5 g/L.

A critical aspect of wine quality from a consumer perspective is the overall impression of wine flavour, which is formed by the interplay of volatile aroma compounds, their precursors, and taste and matrix components. Grapes contribute some potent aroma compounds, together with a large pool of non-volatile precursors (e.g. glycoconjugates and amino acid conjugates). Aroma precursors can break down through chemical hydrolysis reactions, or through the action of yeast or enzymes, significantly changing the aroma profile of a wine during winemaking and storage. In addition, glycoconjugates of monoterpenes, norisoprenoids and volatile phenols, together with sulfur-conjugates in wine, provide a reservoir of additional flavour through the in-mouth release of volatiles which may be perceived retro-nasally.

Fining is a technique that is used to remove unwanted wine components that affect clarification, astringency, color, bitterness, and aroma. Fining involves the addition of adsorptive or reactive material in order to reduce or eliminate the presence of certain less desirable wine components and to ensure that a wine remains in a particular stable state for a given period of time Recently concerns have been raised about the addition of animal proteins, such as gelatin, to wine due to the disease known as bovine spongiform encephalopathy (Mad Cow disease). Although the origin of gelatins has been moved to porcine, winemakers are asking for substitute products with properties and application protocols similar to the traditional animal-derived ones, making the use of plant-derived proteins in fining a practically viable possibility. As a consequence, various fining agents derived from plants have been proposed, including proteins from cereals, legumes, and potato.

Champagne or sparkling wines elaborated through the same traditional method, which consists in two major yeast-fermented steps, typically hold about 10 to 12 g/L of dissolved CO2 after the second fermentation in a closed bottle. Hundreds of molecules and macromolecules originating from grape and yeast cohabit with dissolved CO2; they are essential compounds contributing to many organoleptic characteristics (effervescence, foam, aroma, taste, colour…). Indeed, the second alcoholic fermentation and the maturation on lees (which may last from 12 months up to several years) both induce various quantitative and qualitative changes in the wine through the action of yeast, as listed hereafter: development of aromas during aging on lees, release of nitrogen compounds during autolysis and release of macromolecules (polysaccharides, lipids, nucleic acids) in wine.

Bacterial malolactic fermentation (MLF) has a considerable impact on wine quality. The yeast strain used for primary fermentation can consistently stimulate (MLF+ phenotype) or inhibit (MLF- phenotype) malolactic bacteria and the MLF process as a function of numerous winemaking practices, but the molecular evidence behind still remains a mystery. In this study, such evidence was elucidated by the direct comparison of extracellular metabolic profiles of MLF+ and MLF- yeast phenotypes. Untargeted metabolomics combining ultrahigh-resolution FT-ICR-MS analysis, powerful machine learning methods and a comprehensive wine metabolite database, discovered around 800 putative biomarkers and 2500 unknown masses involved in phenotypic distinction.