WineMetrics: A new approach to unveil the “wine-like aroma” chemical feature

Climate change and harvest date decisions have led to the evolution of must quality over the last decades. Increases in must sugar concentrations are among the most obvious consequences, quantitatively. Saccharomyces cerevisiae is a robust and acid tolerant organism. These properties, its sugar to ethanol conversion rate and ethanol tolerance make it the ideal production organism for wine fermentations. Unfortunately, high sugar concentrations may affect S. cerevisiae and lead to growth inhibition or yeast lysis, and cause sluggish or stuck fermentations. Even sublethal conditions cause a hyperosmotic stress response in S. cerevisiae which leads to increased formation of fermentation by-products, including acetic acid, which may exceed legal limits in some wines.

The composition of wine is largely determined by the composition of pre-fermentation juice, which is influenced by extraction of grape components. Different grape harvesting and processing conditions could affect the extraction of grape components into juice. Among these grape components, pathogenesis-related (PR) proteins are of great concern for white wine maker as they are the main cause of haze formation in finished white wine. If not removed before bottling, these PR proteins may progress into haze through the formation of complex with phenolics under certain conditions. Thaumatin-like proteins (TLPs) and chitinases are the main constituents of PR proteins found in protein haze.

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.

In general, there is a well-established lexicon related to wine aroma and taste properties; however mouth-feel-related vocabulary usually includes heterogeneous, multimodal and personalized terms. Gawel et al.
(2000) published a wheel related to mouthfeel properties of red wine. However, its use in scientific publications has been limited. The authors accepted that the approach had certain limitations as it included redundant and terms with hedonic tone and some others were absent. It is of high interest to generate a mouth-feel lexicon and finding the chemical compound or group of compounds responsible for such properties in red wine. In the present work a chemical fractionation method has been developed.

Maturation of wine on lees (often referred as sur lie) is a common practice applied by many winemakers around the world. In the past this method was applied mainly on white and/or sparkling wine production but recently also to red wine production. In our experiment, we matured red wine on wine lees of two origins: a) Light wine lees, collected after the completion of the alcoholic fermentation, b) Heavy lees, collected after the completion of the malolactic fermentation. The lees were free of off-odors and were added in the red wine in percentage 3% and 8%, simulating common winemaking addition. The maturation lasted in total six months and samples were collected for analysis after one, three and six months. During storage the lees were stirred.