Identification of green, aggressive and hard character of wines by a chemo-sensory directed methodology

Nutrient availability – nitrogen, lipids, vitamins or oxygen – has a major impact on the kinetics of winemaking fermentations. Nitrogen is usually the growth-limiting nutrient and its availability determines the fermentation rate, and therefore the fermentation duration. In some cases, in particular in Champagne, grape musts have high nitrogen concentrations and are sometimes clarified with turbidity below 50 NTU. In these conditions, lipid deficiencies may occur and longer fermentations can be observed. To better understand this situation, a study was realized using a synthetic medium simulating the composition of a Champagne must : 180 g/L of sugar, 360 mg/L of assimilable nitrogen and a lipid content ranging from 1 to 8 mg/L of phytosterols (mainly β-sitosterol).

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.

Úbeda-Aguilera, C a, b, Peña-Neira, A.b Del Barrio-Galán, R.b, c a Biomedical Sciences Institute, Science Faculty, Universidad Autónoma de Chile, Chile. b Department of Agro-Industry and Enology, Faculty of Agronomical Sciences, University of Chile, Post Office Box 1004, Santa Rosa 11315, La Pintana, Santiago, Chile c Lallemand Inc. Chile y Compañía Limitada, Rosario Norte 407, piso 6, Las Condes, Santiago, Chile The wine is a complex matrix made up of several compounds which can interact among themselves throughout the wine ageing process, thereby modifying their sensorial characteristics. It is well known that during ageing of wines on lees, polysaccharides (mainly mannoproteins) can be released and can interact with the aromatic fraction modifying its volatility.

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.

“The Human being has an excellent ability to detect and discriminate odors but typically has great difficulty in identifying specific odorants”(1). Furthermore, “from a cognitive point of view the mechanism used to judge wines is closer to pattern recognition than descriptive analysis.” Therefore, when one wants to reveal the volatile “wine-like feature” pattern recognition techniques are required. Sensomics is one of the most recent “omics”, i.e. a holistic perspective of a complex system, which deals with the description of substances originated from microorganism metabolism that are “active” to human senses (2). Depicting the relevant volatile fraction in wines has been an ongoing task in recent decades to which several research groups have allocated important resources. The most common strategy has been the “target approach” in order to identify the “key odorants” for a given wine varietal.