Effect of ageing with Specific Inactivated Dry Yeasts on the volatile composition of Sauvignon Blanc and Carménère wines

Beihong and Beimei were bred as winemaking cultivars released by Institute of Botany, the Chinese Academy of Sciences in 2008. The cultivars are selected from the population of ‘Muscat Hamburg’ (Vitis vinifera) ×V. amurensis. They are extended to most provinces in North of China because they have strong resistance to cold and disease and need not be buried in soil in winter. To better understand the effect of cropload on volatile compounds during wine-making, we surveyed volatiles composition and content of different cropload level in 3-years-old ‘Beihong’ and ‘Beimei’ vines which planted in east foot of Helan mountain of Ningxia (EHN).

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.

Fungal bunch rots of grapes cause major losses to grape yield worldwide, yet the impact these moulds have on grape and wine quality is not well characterised. We sought to investigate the formation of unwanted volatile compounds of fungal origin in both synthetic grape juice culture media and in inoculated grape berries. Botrytis cinerea, Aspergillus niger, Aspergillus carbonarius, or Pencillium expansum were grown in synthetic grape juice medium and the culture homogenates analysed 4 and 7 days post inoculation. HS-SPME-GC-MS analysis of the culture homogenates 4 days post inoculation demonstrated that each of the fungi examined produced varying quantities of the mushroom or fungus-like aroma compounds, 1-Octen-3-ol, 1-Octen-3-one and 3-Octanone with A. carbonarius producing up to ten times the amounts of all three metabolites per mg of dry mycelium.

Acidity adjustments are key to microbial control, sensory quality and wine longevity. Acidification with cation exchange resins -in acid cycle- offers the possibility to reduce the pH by exchanging wine cations, such as potassium (K+), for hydrogen ions (H+). During the exchange process, the removal of potassium and calcium ions contributes to limiting the formation of tartrate salts, thus offering an alternative solution to conventional methods for tartrate stability. Moreover, the reduction of wine pH and the removal of metals catalyzers (e.g. iron) could positively impact the wine’s oxidative stability. Therefore, the aims of this work were (a) to optimize the ion exchange process by testing different volumes and concentrations of sulfuric acid (H2SO4) during the acid cycle, (b) evaluate the effects of the ion exchange process on the formation of tartrate salts, and (c) analyze the oxidative stability of the treated wines.

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.