Analysis of the interaction of melatonin with glycolytic proteins in Saccharomyces cerevisiae during alcoholic fermentation 

Vineyards from mild temperature, high humidity locations receive often treatments with fungicides to prevent damages produced by fungi responsible for mildium, oidium and botrytis infections. In addition, insecticides are also applied to vineyards to fight again pests, which affect directly, or indirectly (as vectors of different diseases), their productivity. A fraction of the above compounds reaches the soil of vineyards, either during application, or when released from the canopy of vines due to rain-wash-off. Thereafter, depending on soil conditions (pH, organic matter) and environmental variables (regimen of rain, slope of vineyards), they might persist in this compartment, be degraded and/or transferred to water masses, modifying the biodiversity of soils and/or affecting the quality of water reservoirs.

The barrel-making process is widely recognized as a crucial practice that affects the composition of barrel-aged wine. After the drying process, the staves are considered ready for barrel assembly, which includes the processes of bending and toasting the barrel structure. Toasting is considered one of the most critical stages in determining the physical and chemical composition of the staves, which can influence the chemical and sensory composition of the wine aged in barrels made from them [1].

Targeted analytical methods can overlook compounds that are a priori unknown to play a role in the mouthfeel sensations. This limitation can be overcome with the information provided by untargeted metabolomic analysis using UPLC‐QTOF-MS. To this end, an untargeted metabolomic approach applied to 42 red wines has allowed development of a model with predictive capacity by cross-validation for the “dry”, “oily” and “unctuous” sensations perceived by a sensory panel. The optimal PLS model for “dry” retained compounds with positive regression coefficients (≥ 0.17) including a trimer procyanidin, a peptide, and four anthocyanins.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).

The universalization in wine production has been restricting the imprint of terroir in regional wines, resulting in loss of typicity. Microbes are the main driving force in wine production, conducting fermentation and originating a myriad of metabolites that underly wine aroma. Grape berries harbor an ecological niche composed of filamentous fungi, yeasts and bacteria, which are influenced by the ripening stage, cultivar and region. The research project GrapeMicrobiota gathers a consortium from University of Zaragoza, University of Minho and University of Tours and aims at the isolation of native yeast strains from berries of the wine region Douro, UNESCO World Heritage, towards the production of wines that stand out in the market for their authenticity and for reflecting their region of origin in their aroma.