Oxygen consumption by diferent oenological tanins in a model wine solution

3-Isobutyl-2-methoxypyrazine (IBMP) is one of the key molecules in wine aroma with a bell pepper aroma and a very low threshold in wine, 1-6 ng/L for white wine and 10-16 ng/L in red wine1. The differences in these thresholds are likely due to IBMP-non volatile matrix interactions. It has indeed been shown that polyphenols may influence the volatility of flavor compounds2. In the present study, we focus on IBMP-polyphenols interactions in relation to volatility and sensory perception in model wine solution. Methods: 1. GC-MS Static Headspace Analysis: Samples were analyzed by Static headspace analysis with an Agilent 7890A gas chromatograph coupled to HP 5975C mass spectrometry detector (Agilent Technologies, Santa Clara, CA, USA).

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.

Comprehensive two-dimensional gas chromatography (GCxGC) has emerged as a powerful analytical technique for unraveling the volatile composition of complex matrices. This work will present three applications of GCxGC Tof-MS to the oenological field, aimed to identify novel biomarkers to be used in the quality control process of the wine industry. Comprehensive mapping of volatile compounds was conducted in a large sample of 70 sparkling wines, produced by 48 different wineries across 6 vintages and representative of the two main production areas for premium Italian sparkling wines (Franciacorta (FC) and Trentodoc (TN)), using HS-SPME followed by GCxGC-Tof-MS and multivariate analysis. Selection and identification of 196 putative biomarkers allowed clear separation of sparkling wines from FC and TN.

“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.

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.