Photoprotective extracts from agri-food waste to prevent the effect of light in rosé wines 

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.

One of the limitations of vineyards in warm areas is the loss of wine quality due to higher temperatures during the grape ripening period. In order to adapt the vineyards to these new climatic conditions, a possible solution is to delay the ripening process of the grapes towards periods with milder temperatures, by means of management practices and thus improve the quality of the fruit and the wine produced. The technique of severe shoot pruning (SSP) has proven useful in achieving this objective.

Sparkling wine (SW) production entails a two-steps process where grape must undergoes a primary fermentation to produce a base wine (BW) which is then refermented to become a SW. This process allows for the development of a new physicochemical profile characterized by the presence of foam and a different organoleptic profile.

Grapevine cultivars can be unequivocally typed by both physical differences (ampelography) and genetic tests. However due to their very similar characteristics, the identification of clones within a cultivar relies on the accurate tracing of supply records to the point of origin. Such records are not always available or reliable, particularly for older accessions. Whole genome sequencing (WGS) provides the most highly detailed methodology for defining grapevine cultivars and more importantly, this can be extended to differentiating clones within those cultivars.

Yeast species S. cerevisiae, S. uvarum, S. kudriavzevii and their hybrids present clear metabolic differences, even when we compared S. cerevisiae wine versus wild strain. These species and hybrids produced significantly higher amounts of glycerol, organic acids, 2,3-butanediol, and 2-phenyl ethanol and a reduction of the ethanol yield, properties very interesting in the sector to deal with climate change effects. To understand the existing differences, we have used several omics techniques to analyze the dynamics of the (intra- and extracellular) metabolomes and/or transcriptomes of representative strains of S. cerevisiae, S. uvarum, S. kudriavzevii, and hybrids.