Merging fast sensory profiling with non-targeted GC-MS analysis for multifactorial experimental wine making

The grapevine is an important economical crop that is very sensitive to climate changes and microclimate. The observations made during the last decades at a vineyard scale all concur to show the impact of climate change on vine physiology, resulting in accelerated phenology and earlier harvest (Jones and Davis 2000). It is well-known that berry content is affected by the ambient temperature. While the first experiences were primarily conducted on the impact of temperature on anthocyanin accumulation in the grape, few studies have focused on others component of phenolic metabolism, such as tannins.

Proteins constitute one of the three main components of grape juice and white wine, phenolic compounds and polysaccharides being the others. A specific group of the total grape-derived proteins resists degradation or adsorption during the winemaking process and remains in finished wine if not removed by the commonplace commercial practice of bentonite fining. While bentonite is effective in removing the problematic proteins, it is claimed to adversely affect the quality of the treated wine under certain conditions, through the removal of colour, flavor and texture compounds. A number of studies have indicated that different protein fractions require distinct bentonite concentrations for protein removal and consequent heat stabilization.

Nitrogen is an important nutrient of yeast and its low content in grape must is a major cause for sluggish fermentations. To prevent problems during fermentation, a supplementation of the must with ammonium salts or more complex nitrogen mixtures is practiced in the cellar. However this correction seems to improve only partially the quality of wine [1]. In fact, yeast is using nitrogen in many of its metabolic pathways and depending of the sort of the nitrogen source (ammonium or amino acids) it produces different flavor active compounds. A limitation in amino acids can lead to a change in the metabolic pathways of yeast and consequently alter wine quality.

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.

Oak wood selection and maturation are essential steps in the course of barrel fabrication. Given the existence of many factors involved in the choice of raw material and in natural seasoning of oak wood, it is very difficult to determine the real impact of seasoning and selection factors on oak wood composition. A sampling was done to study the evolution of oak wood chemical composition during four seasoning steps: non matured, 12 months, 18 months and 24 months. For this sampling, three selection factors were taken into account: age, grain type and the Polyphenolic Index measured by Oakscan®. Besides extractables
(~10%), three polymers constitute the main part of oak wood: cellulose, hemicelluloses and lignins.