Improvement of non-Saccharomyces yeast dominance during must fermentation by using spontaneous mutants resistant to SO₂, EtOH and high pressure of CO₂

Vegetative growth and yield are reported to affect grape and wine quality. They can be controlled through different techniques linked to vine management. The objective of this research was to determine the effect of vine vigour and number of clusters per vine on physicochemical composition and phenolic profile of red wines. The experiment was carried out during two vegetative cycles, with cv. Cabernet Sauvignon grafted onto Paulsen 1103. Three vine vigour were defined, according to shoot weight at previous harvests, being low, medium and high. Five treatments of number of clusters were used for each vigour, with 15, 22, 29, 36, and 45 clusters per vine. Grapes from all treatments were harvested in the same day from Brix and total acidity criteria. Thirty days after bottling, classical analyzes and phenolic compounds were performed. As results, different responses were obtained from each vintage. In 2020, a dry season from veraison to harvest, grapes and wines obtained from low vigour treatment and 45 clusters per vine was the highest in sugar and alcohol content respectively, while grapes and wines from high vigour and 15 clusters presented the lowest sugar and alcohol content. Total anthocyanins were higher in treatment with low vigour and 15 clusters, while the lowest amounts were found in low vigour with 45 clusters, as well as medium and high vigour with 36 clusters per vine. Total tannins were higher in high vigour with 22 clusters and medium vigour with 29 clusters, while were lower in low vigour with 36 clusters. In 2021, a wet season at harvest, responses were different, and great variations were observed between treatments. As conclusions, yield and vine vigour had strong influence on grape and wine quality, promoting different enological potentials on which can be indicated/used for aging strategies of red and even rosé wines.

With contemporary climate change, cultivated Vitis vinifera L. is at risk as climate is a critical component in defining ecologically fitted plant materiel. While winegrowers can draw on the rich diversity among grapevine varieties to limit expected impacts (Morales-Castilla et al., 2020), replacing a signature variety that has created a sense of local distinctiveness may lead to several challenges. In order to sustain wine identity in uncertain climate outcomes, the study of intra-varietal diversity is important to reflect the adaptive and evolutionary potential of current cultivated varieties. The aim of this ongoing study is to understand to what extent can intra-varietal diversity be a climate change adaptation solution. With a focus on early (Sauvignon blanc, Riesling, Grolleau, Pinot noir) to moderate late (Chenin, Petit Verdot, Cabernet franc) ripening varieties, data was collected for flowering and veraison for the various studied accessions (from conservatory plots) and clones. For these phenological growing stages, heat requirements were established using nearby weather stations (adapted from the GFV model, Parker et al., 2013) and model performances were verified. Climate change projections were then integrated to predict the future behaviour of the intra-varietal diversity. Study findings highlight the strong phenotypic diversity of studied varieties and the importance of diversification to enhance climate change resilience. While model performances may require improvements, this study is the first step towards quantifying heat requirements of different clones and how they can provide adaptation solutions for winegrowers to sustain local wine identity in a global changing climate. As genetic diversity is an ongoing process through point mutations and epigenetic adaptations, perspective work is to explore clonal data from a wide variety of geographic locations.

The aim of this study was to evaluate the effects of different soil types on the chemical composition of Mediterranean red wines, through untargeted and targeted 1H-NMR metabolomics. One milliliter of raw wine was analyzed by means of a Bruker Avance II 400 spectrometer operating at 400.15 MHz. The spectra were recorded by applying the NOESYGPPS1D pulse sequency, to achieve water and ethanol signals suppression. No modification of the pH was performed to avoid any chemical alteration of the matrix. The generation of input variables for untargeted analysis was done via bucketing the spectra. The resulting dataset was preprocessed prior to perform unsupervised PCA, by means of MetaboAnalyst web-based tool suite. The identification of compounds for the targeted analysis was performed by comparison to pure compounds spectra by means of SMA plug-in of MNova 14.2.3 software. The dataset containing the concentrations (%) of identified compounds was subjected to one-way analysis of variance (ANOVA) to highlight significant differences among the wines. The untargeted analysis, carried out through the PCA, revealed a clear differentiation among the wines. The fragments of the spectra contributing mostly to the separation were attributed to flavonoids, aroma compounds and amino acids. The targeted analysis leaded to the identification of 68 compounds, whose concentrations were significant different among the wines. The results were related to soils physical-chemical analysis and showed that: 1) high concentrations of flavan-3-ols and flavonols are correlated with high clay content in soils; 2) high concentrations of anthocyanins, amino acids, and aroma compounds are correlated with neutral and moderately alkaline soil pH; 3) low concentrations of flavonoids and aroma compounds are correlated with high soil organic matter content and acidic pH. The 1H-NMR metabolomic analysis proved to be an excellent tool to discriminate between wines originating from grapes grown on different soil types and revealed that soils in the Mediterranean area exert a strong impact on the chemical composition of the wines.

The project VINIoT pursues the creation of a new technological vineyard monitoring service, which will allow companies in the wine sector in the SUDOE space to monitor plantations in real time and remotely at various levels of precision. The system is based on spectral images and an IoT architecture that allows assessing parameters of interest viticulture and the collection of data at a precise scale (level of grape, plant, plot or vineyard) will be designed. In France, three subjects were specifically developed: evaluation of maturity, of water stress, and detection of flavescence dorée. For the evaluation of maturity, it has been decided first to work at the berry scale in the laboratory, then at the bunch scale and finally in the vineyard. The acquisition of the spectral hyperstal image as well as the reference analyzes to measure the maturity, were carried out in the laboratory after harvesting the berries in a maturity monitoring context. This work focuses on a case study to predict sugar content of three different grape varieties: Syrah, Fer Servadou and Mauzac. A robust method called Roboost-PLSR, developed in the framework of this work (Courand et al., 2022), to improve prediction model performance was applied on spectra after the acquirement of hyperspectral images. Regarding the evaluation of water stress, to work with a significant variability in terms of water status, it has been worked first with potted plants under 2 different water regimes. The facilities have allowed the supervision of irrigation and micro-climatic conditions. The regression models on agronomic variables (stomatal conductance, water potential, …) are studied. To detect flavescence dorée, the experimental plan has consisted of work at leaf scale in the laboratory first, and then in the field. To detect the disease from hyper-spectral imaging, a combination of multivariate curve resolution-alternating least squares (MCR-ALS) and factorial discriminant analysis (FDA) was proposed. This strategy proved the potential towards the discrimination of healthy and infected leaves by flavescence dorée based on the use of hyperspectral images (Mas Garcia et al., 2021).

Wine quality is strongly linked to climate. Quality scores are often driven by climate variation across different winegrowing regions and years, but also influenced by other aspects of terroir, including variety. While recent work has looked at the relationship between quality scores and climate across many European regions, less work has examined New World winegrowing regions. Here we used scores from three major rating systems (Wine Advocate, Wine Enthusiast and Wine Spectator) combined with daily climate and phenology data to understand what drives variation across wine quality scores in major regions of the Western US, including regions in California, Oregon and Washington. We examined effects of variety, region, and in what phenological period climate was most predictive of quality. As in other studies, we found climate, based mainly on growing degree day (GDD) models, was generally associated with quality—with higher GDD associated with higher scores—but variety and region also had strong effects. Effects of region were generally stronger than variety. Certain varieties received the highest scores in only some areas, while other varieties (e.g., Merlot) generally scored lower across regions. Across phenological stages, GDD during budbreak was often most strongly associated with quality. Our results support other studies that warmer periods generally drive high quality wines, but highlight how much region and variety drive variation in scores outside of climate.