Identification of important genomic regions controlling resistance to biotic and abiotic stresses in Vitis sp. through QTL meta-analysis

Brettanomyces is a world-renowned yeast that negatively impacts the chemical composition of wines through the production of metabolites that negatively impact the sensory properties of the final product. Its resilience in wine conditions and ability to produce off-flavors make it a challenge for winemakers. Currently, the primary control technique involves adding sulfur dioxide (SO2); however, some Brettanomyces strains are developing resistance to this preservative agent. [1] Therefore, new management strategies are necessary to control this spoilage yeast.

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.

Volatile phenols from wildfire smoke are absorbed by wine grapes, resulting in undesirable smoky and ashy sensory attributes in the affected wine.[1] Unfortunately the severity of wildfires is increasing, particularly when grapes are ripening on the vine. The unwanted flavors of the wine prompted a need for solutions to prevent the uptake of smoke compounds into wine grapes. Films using cellulose nanofibers as the coating forming matrix were developed as an innovative means to prevent smoke phenols from entering Pinot noir grapes. Different film formulations were tested by incorporating low methoxy pectin or chitosan.

Addressing modifiable risk factors is the most promising strategy to prevent/delay Alzheimer Disease (AD)[1]. The aim of the study was to establish the connections between dietetic habits, wine consumption and AD. Thus, 98 volunteers were recruited: 50 diagnosed as AD and 48 healthy/controls. The Food Frequency Questionnaire (FFQ) was used for dietary patterns assessment and, based on these data, the Mind Diet Score was calculated. (Poly)phenol metabolites (especially derived from wine consumption) were analyzed by UPLC-QqQ-MS/MS in 24-h urine samples to confirm dietary (poly)phenol consumption.

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).