Optimization of the acquisition of NIR spectrum in grape must and wine 

Among the Moscato grapes, Moscato Giallo is a winegrape variety characterized by a high content of free and glycosylated monoterpenoids, which gives very aromatic wines. The aromatic bouquet of Moscato Giallo is strongly influenced by the high concentration of linalool, geraniol, linalool oxides, limonene, α-terpineol, citronellol, HO-trienol, HO-diols, 8-Hydroxylinalool, geranic acid and β-myrcene, that give citrus, rose, and peach notes.

Several Eurasian wild grapevine populations were found along Extremadura region (southwestern Spain). For conservation and study, one individual from four different populations (named L1, L2, L5 and L6) was vegetatively propagated and planted at Instituto de Investigaciones Agrarias Finca La Orden (CICYTEX), Badajoz. The aim of the present work was to characterize those conserved individuals from four different populations based on both an ampelographic description and a molecular analysis. Three vines per individual were studied.

The study conducted various fermentations of different grape juices using various strains of Lachancea thermotolerans and one strain of Saccharomyces cerevisiae. Because of the new conditions caused by climate change, wine acidity must be influenced as well as the volatile profile. Non-Saccharomyces yeasts such as L. thermotolerans are real options to mitigate the impact of climate change in wine production.

Climate change will increase the frequency of water deficit situation in some European regions, by the increase of the evapotranspiration and the reduction of rainfalls during the growing cycle. This requires finding ways of adaptation, including the use of plant material which is more tolerant to drought. In addition to the varieties used as scions that result in the typicality of wines, rootstocks constitute a relevant way of adaptation to more stressful environmental conditions.

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.