Oenological tannins to prevent Botrytis cinerea damage: reduction of laccase activity

In mid to late ripening, sugar and potassium (K+) accumulation into the berry slows and is eventually completed1. K+ is the most abundant cation in the berry, undertaking important physiological roles.

Temperature and yeast nutrition profoundly impact wine quality and sensory attributes by modulating yeast aroma production and release during fermentation. While temperature and nitrogen’s individual effects are well-studied, their combined influence, including nutrient type and addition timing, remains underexplored. hence, this study aimed to investigate the simultaneous effects of these factors on fermentation kinetics, aroma production and sensory profile, particularly in a Chardonnay wine production selected as a quite aromatically neutral base.

Oenococcus oeni is the predominant lactic acid bacteria species in wine and cider, where it performs the malolactic fermentation (MLF) (Lonvaud-Funel, 1999). The O. oeni strains analyzed to date form four major genetic lineages named phylogroups A, B, C and D (Lorentzen et al., 2019). Most of the strains isolated from wine, cider, or kombucha belong to phylogroups A, B+C, and D, respectively, although B and C strains were also detected in wine (Campbell-Sills et al., 2015; Coton et al., 2017; Lorentzen et al., 2019;

During Champagne or sparkling wine tasting, gas-phase CO2 and volatile organic compounds invade the headspace above glasses [1], thus progressively modifying the chemical space perceived by the consumer. Gas-phase CO2 in excess can even cause a very unpleasant tingling sensation perturbing both ortho- and retronasal olfactory perception [2]. Monitoring as accurately as possible the level of gas-phase CO2 above glasses is therefore a challenge of importance aimed at better understanding the close relationship between the release of CO2 and a collection of various tasting parameters.

Wine is one of the most representative components of Mediterranean diet. Moderate wine intake together with food, has been positively correlated with reduced risk of many chronic diseases. This beneficial effect seems to be ascribed to elevated polyphenolic content of wine [1]. Traditional approaches for the identification of wine biomarkers consumption include targeted metabolomics that focuses on the quantification of well-defined metabolites, losing a valuable information about a massive number of compounds. On the other hand, untargeted metabolomics can disclose a large quantity of signals corresponding to potential biomarkers in a single analysis with high sensitivity and resolution.