Epigenetic Modulation Of Inflammation And Synaptic Plasticity By Polyphenolic Metabolites Promotes Resilience Against Stress In Mice

The use of multivariate statistics to correlate chemical data to spectral information seems as a valid alternative for the quantification of red wine phenolics. The advantages of these techniques include simplicity and cost effectiveness together with the limited time of analysis required. Although many
publications on this subject are nowadays available in the literature most of them only reported feasibility
studies. In this study 400 samples from thirteen fermentations including five different cultivars plus 150
wine samples from a varying number of vintages were submitted to spectrophotometric and chromatographic phenolic analysis.

The use of glutathione (GSH) in winemaking has been legitimated recently, according to OIV resolutions OENO 445-2015 and OENO 446-2015 a maximum dose of 20 mg/L is now allowed to use in must and wine. Several studies have proven the benefits of GSH, predominantly in Sauvignon blanc. Thus, oxidative coloration of must and wine is limited, aroma compounds such as volatile thiols are preserved, and the development of ageing flavors such as sotolon and 2-aminoacetophenone is impeded. The protective effect may be explained by the high affinity of GSH to bind o-quinones which are formed during phenolic oxidation and which are known to initiate browning and other oxidative changes. Some researchers have proposed the hydroxycinnamic acid to GSH ratio (HGR) as an indicator of oxidation susceptibility of must and could show that lower ratios yielded lighter musts.

Increasing drought poses a challenge to viticulture, with complex impacts on grape yield and quality. The use of Unmanned Aerial Vehicles (UAV) in Precision Viticulture offers a valuable tool to detect drought stress, capturing its spatio-temporal variability and thus, supports management strategies.

Winegrape cultivars are particularly sensitive to temperature and recent changes in climate have advanced the onset of berry ripening, resulting in unbalanced fruit composition at harvest.

Water is the main limiting factor for yield in viticulture. Improving drought adaptation in viticulture will be an increasingly important issue under climate change. Genetic variability of water deficit responses in grapevine partly results from the rootstocks, making them an attractive and relevant mean to achieve adaptation without changing the scion genotype. The objective of this work was to characterize the rootstock effect on the diurnal regulation of scion transpiration. A large panel of 55 commercial genotypes were grafted onto Cabernet Sauvignon. Three biological repetitions per genotype were analyzed. Potted plants were phenotyped on a greenhouse balance platform capable of assessing real-time water use and maintaining a targeted water deficit intensity. After a 10 days well-watered baseline period, an increasing water deficit was applied for 10 days, followed by a stable water deficit stress for 7 days. Pruning weight, root and aerial dry weight and transpiration were recorded and the experiment was repeated during two years. Transpiration efficiency (ratio between aerial biomass and transpiration) was calculated and δ13C was measured in leaves for the baseline and stable water deficit periods. A large genetic variability was observed within the panel. The rootstock had a significant impact on nocturnal transpiration which was also strongly and positively correlated with maximum daytime transpiration. The correlations with growth and water use efficiency related traits will be discussed. Transpiration data were also related with VPD and soil water content demonstrating the influence of environmental conditions on transpiration. These results highlighted the role of the rootstock in modulating water deficit responses and give insights for rootstock breeding programs aimed at identifying drought tolerant rootstocks. It was also helpful to better define the mechanisms on which the drought tolerance in grapevine rootstocks is based on.