Full automation of oenological fermentations and its application to the processing of must containing high sugar or acetic acid concentrations

This study investigates how the sensory profile of Pinot Blanc is affected from different maceration and pressing techniques. Grapes were sourced from four vineyards in the village Tramin in South Tyrol. For the experiment 200 kg of grapes from each vineyard site were hand picked the day before harvest for the commercial winery took place. Grapes were stored over night at 4°C, homogenized and processed in the experimental winery at Laimburg research centre the day after harvest. Four different pressing techniques were applied in duplicates of 100kg each.

Must oxidation is a complex process involving multiple enzymatic transformations, including the oxidation of phenolics containing an ortho-diphenol function. The latter process has a primary influence on wine aroma characteristics and stability, due to the central role of ortho-diphenols in the non-enzymatic oxidative reactions taking place during winemaking and in finished wine. Although oxidation of must is traditionally avoided, in recent years its contribution to wine quality has been revisited, and in some cases improvements to wine aroma have been observed with the application of controlled must oxidation. Nowadays there is a great interest in the wine industry towards the identification of specific markers or patterns to characterize and classify the response of grape must to oxidation.

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.

Laboratório de Análisis del Aroma y Enologia (LAAE). Department of Analytical Chemistry, Faculty of Sciences, Universidad de Zaragoza, 50009, Zaragoza, Spain, During alcoholic fermentation, fusel (or Strecker) aldehydes are intermediates in the amino acid catabolism to form fusel alcohols following the Ehrlich Pathway (1). One of the main enzymes involved in this pathway is Alcohol Dehydrogenase (ADH), whose activity is highly strain dependent and determines the rate of conversion of aldehydes into fusel alcohols (2). This enzyme has a Zn2+ catalytic binding site, which suggests that the must Zn2+ levels will most likely influence the rate of reduction of aldehydes into alcohols. On the other hand, SO2 is commonly used in winemaking for its antiseptic and antioxidant properties.

Yeast cells possess a cell wall comprising primarily glycoproteins, mannans, and glucan polymers. Several yeast phenotypes relevant for fermentation, wine processing, and wine quality are correlated with cell wall properties. To investigate the effect of wine fermentation on cell wall composition, a study was performed using mid-infrared (MIR) spectroscopy coupled with multivariate methods (i.e., PCA and OPLS-DA). A total of 40 yeast strains were evaluated, including Saccharomyces strains (laboratory and industrial) and non-Saccharomyces species. Cells were fermented in both synthetic MS300 and Chardonnay grape must to stationery phase, processed, and scanned in the MIR spectrum.