Monitoring arthropods diversity in the “Costières de Nîmes” viticulture landscape

Increasing wildfire frequency in the United States has led to the indirect impact of smoke in vineyards, affecting grape quality and wine sensory attributes, commonly called “smoke taint”.

Grenache Noir and Syrah are the predominant grape varieties in the French Rhone valley vineyard, and produce wines with well differentiated aromatic notes. This study aimed at investigating the contribution of glycoconjugated precursors to these aromatic specificities, through their analytical profiles and the sensory influence of the odorant compounds they release during wine aging. The aglycones released by enzymatic hydrolysis of glycosidic extracts

Erysiphe necator Schwein is a fungus that causes grapevine powdery mildew. It is one of the most problematic pathogens attacking Vitis vinifera L. The pathogen infects all green parts of the plant and reduces grape yield and quality. The suppression on mildew-susceptible cultivars requires intensive use of fungicides against pathogen, which has negative impact on the environment and human health.

Stomatal traits determine grapevine water use, carbon supply, and water stress, which directly impact yield and berry chemistry. Breeding for stomatal traits has the strong potential to improve grapevine performance under future, drier conditions, but the trait values that breeders should target are unknown. We used a functional-structural plant model developed for grapevine (HydroShoot) to determine how stomatal traits impact canopy gas exchange, water potential, and temperature under historical and future conditions in high-quality and hot-climate California wine regions (Napa and the Central Valley). Historical climate (1990-2010) was collected from weather stations and future climate (2079-99) was projected from 4 representative climate models for California, assuming medium- and high-emissions (RCP 4.5 and 8.5). Five trait parameterizations, representing mean and extreme values for the maximum stomatal conductance (gmax) and leaf water potential threshold for stomatal closure (Ψsc), were defined from meta-analyses. Compared to mean trait values, the water-spending extremes (highest gmax or most negative Ysc) had negligible benefits for carbon gain and canopy cooling, but exacerbated vine water use and stress, for both sites and climate scenarios. These traits increased cumulative transpiration by 8 – 17%, changed cumulative carbon gain by -4 – 3%, and reduced minimum water potentials by 10 – 18%. Conversely, the water-saving extremes (lowest gmax or least negative Ψsc) strongly reduced water use and stress, but potentially compromised the carbon supply for ripening. Under RCP 8.5 conditions, these traits reduced transpiration by 22 – 35% and carbon gain by 9 – 16% and increased minimum water potentials by 20 – 28%, compared to mean values. Overall, selecting for more water-saving stomatal traits could improve water-use efficiency and avoid the detrimental effects of highly negative canopy water potentials on yield and quality, but more work is needed to evaluate whether these benefits outweigh the consequences of minor declines in carbon gain for fruit production.

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).