High-throughput sequencing analysis based on nematode indices revealed healthier soils of organic vineyards 

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.

Implementing alternative grapevine systems that incorporate sustainable strategies and innovative farming practices is essential. However, we lack tools for measuring the impact of these new practices on the overall sustainability of vineyards. DEXi PM Vigne (Gary et al., 2015) is a tool developed for ex ante assessment of the sustainability of grapevine cropping systems, from the plot to the farm scale. In the present study, we focused on implementing new strategies of integrated crop protection management with limited pesticide use in vineyards.

SO2 play a major role in wine stability and evolution during its aging and storage. Winemaking without SO2 is a big challenge for the winemakers since the lack of SO2 affects directly the wine chemical evolution such as the aromas compounds as well as the phenolic compounds. During the red wine aging, phenolic compounds such as anthocyanin, responsible of the red wine colour, and tannins, responsible of the mouthfeel organoleptic properties of wine, evolved quickly from the winemaking process to aging [1]. A lot of new interaction and molecules occurred lead by oxygen[2] thus the lack of SO2 will induce wine properties changes. Nowadays, the phenolic composition of the wine without added SO2 have not been clearly reported.

Winegrowing is still characterized by the extensive use of chemical fertilizers and plant protection products, despite strong recommendations to limit these practices. A part of these xenobiotics and metals are then found in grape juice and wine, causing a major health concern, as well as negatively affecting the fermentation process. In recent years, there has been renewed interest in non-Saccharomyces yeasts. These species have a wide phenotypic diversity, which would be exploited to broaden the aromatic palette of wines.

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).