Testing the effectiveness of Cell-Wall material from grape pomace as fining agent for red wines

Beihong and Beimei are two wine cultivars from ‘Muscat Hamberg’ (V. vinifera L.) and wild V. amurensis Rupr., which were released in China in 2008. Here，two enology practices were reported. Firstly, the impact of different yeasts including D254, GRE, K1, D21 and BDX on dry wine quality of Beihong and Beimei was investigated. For Beihong, among wines fermented by all yeasts, residual sugar content was the lowest, total anthocyanin and resveratrol contents were the highest in the wine by D254. However, the wine by D254 had lower titrable acid than those by the other yeasts except BDX.

Malolactic fermentation (MLF) is a secondary step in the vinification process and it follows alcoholic fermentation (AF) which is predominantly carried out by Saccharomyces cerevisiae. These two processes result in the degradation of metabolites to produce secondary metabolites which also contribute to the final wine flavour and quality. AF results in the production of ethanol and carbon dioxide from sugars and MLF stems from the degradation of L-malic acid (a dicarboxylic acid) to L-lactic acid (a monocarboxylic acid). The latter process results in a smoother texture as the acidity of the wine is reduced by the process, it also adds to the flavour complexity of the 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.

The use of multivariate statistics to correlate chemical data to spectral information seems as a valid alternative for the quantification of red wine phenolics. The advantages of these techniques include simplicity and cost effectiveness together with the limited time of analysis required. Although many
publications on this subject are nowadays available in the literature most of them only reported feasibility
studies. In this study 400 samples from thirteen fermentations including five different cultivars plus 150
wine samples from a varying number of vintages were submitted to spectrophotometric and chromatographic phenolic analysis.

A part, at least, of the fruity aroma of red wines is the consequence of perceptive interactions between various aromatic compounds, particularly ethyl esters and acetates, which may contribute to the perception of fruity aromas, specifically thanks to synergistic effects.1,2 The question of the indirect impact of non-fruity compounds on this particular aromatic expression has not yet been widely investigated. Among these compounds higher alcohols (HA) represent the main group, from a quantitative standpoint, of volatiles in many alcoholic beverages. Moreover, some bibliographic data suggested their contribution to the aromatic complexity by either increasing or masking flavors of wine, depending of their concentrations.