Elicitors used as a tool to increase stilbenes in grapes and wines

Under standard champagne tasting conditions, the complex interplay between the level of dissolved CO2 found in champagne, its temperature, the glass shape, and the bubbling rate, definitely impacts champagne tasting by modifying the neuro-physico-chemical mechanisms responsible for aroma release and flavor perception. Based on theoretical principles combining heterogeneous bubble nucleation, ascending bubble dynamics and mass transfer equations, a global model is proposed (depending on various parameters of both the wine and the glass itself), which quantitatively provides the progressive losses of dissolved CO2 from laser-etched champagne glasses.

The present work contributes by developing a rapid sensory-directed methodology for the screening and selection of high quality wines with different sensory profiles Therefore, Verdejo and Tempranillo musts were fermented with 50 different yeasts each under controlled laboratory conditions. Resulting samples were firstly categorized according to five levels of quality by a panel of wine professionals (Sáenz-Navajas, Ballester et al. 2013). Higher quality samples were described by flash profiling by a semi-trained panel
(Valentin, Chollet et al. 2012) and most distinctive samples were screened by gas chromatography-olfactometry (GC-O) (López, Aznar et al. 2002).

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.

The above-ground parts of plants, which constitute the phyllosphere, have long been considered devoid of bacteria and fungi, at least in their internal tissues and microbial presence there was long considered a sign of disease. However, recent studies have shown that plants harbour complex bacterial communities, the so-called “microbiome”[1]. We are only beginning to unravel the origin of these bacterial plant inhabitants, their community structure and their roles, which in analogy to the gut microbiome, are likely to be of essential nature. Among their multifaceted metabolic possibilities, bacteria have been recently demonstrated to emit a wide range of volatile organic compounds (VOCs), which can greatly impact the growth and development of both the plant and its disease-causing agents.

The use of multivariate statistics to correlate chemical data to spectral information seems as a valid alternative for the quantification of red wine phenolics. The advantages of these techniques include simplicity and cost effectiveness together with the limited time of analysis required. Although many
publications on this subject are nowadays available in the literature most of them only reported feasibility
studies. In this study 400 samples from thirteen fermentations including five different cultivars plus 150
wine samples from a varying number of vintages were submitted to spectrophotometric and chromatographic phenolic analysis.