Effect of Quercus Alba oak barrels from different forests on the polyphenolic composition of Tempranillo red wines

Wine growing regions have recently faced intense and frequent droughts that have led to substantial economical losses, and the maintenance of grapevine productivity under warmer and drier climate will rely notably on planting drought-resistant cultivars. Given that plant growth and yield depend on water transport efficiency and maintenance of photosynthesis, thus on the preservation of the vascular system integrity during drought, a better understanding of drought-related hydraulic traits that have a significant impact on physiological processes is urgently needed. We have worked towards this end by assessing vulnerability to xylem embolism in 30 grapevine commercial varieties encompassing red and white Vitis vinifera varieties, hybrid varieties characterized by a polygenic resistance for powdery and downy mildew, and commonly used rootstocks. These analyses further allowed a global assessment of wine regions with respect to their varietal diversity and resulting vulnerability to stem embolism. Hybrid cultivars displayed the highest vulnerability to embolism, while rootstocks showed the greatest resistance. Significant variability also arose among Vitis vinifera varieties, with Ψ12 and Ψ50 values ranging from -0.4 to -2.7 MPa and from -1.8 to -3.4 MPa, respectively. Cabernet franc, Chardonnay and Ugni blanc featured among the most vulnerable varieties while Pinot noir, Merlot and Cabernet Sauvignon ranked among the most resistant. In consequence, wine regions bearing a significant proportion of vulnerable varieties, such as Poitou-Charentes, France and Marlborough, New Zealand, turned out to be at greater risk under drought. These results highlight that grapevine varieties may not respond equally to warmer and drier conditions, outlining the importance to consider hydraulic traits associated with plant drought tolerance into breeding programmes and modeling simulations of grapevine yield maintenance under severe drought. They finally represent a step forward to advise the wine industry about which varieties and regions would have the lowest risk of drought-induced mortality under climate change.

Excell laboratory has initiated the development of an analytical method based on electrochemistry to evaluate the ability of wines to undergo or resist to oxidative phenomena. Electrochemistry is a powerful tool to probe reactions involving electron transfers and offers possibility of real-time measurements. In that context, the laboratory has implemented electrochemical analysis to assess oxidation state of different wine matrices but also in order to evaluate oxidative or reduced character of leaf and soil. Initially, our laboratory focused on dosage of compounds involved in responses of plant stresses and we were also interested in microbiological activity of soils. These analyses were compared with the measurement of redox potential (Eh) and pH which are two fundamental variables involved in the modulation of plant metabolism. Indeed, the variation of redox states of the plant reflects its biological activity but also its capacity to absorb nutriments. The Eh-pH conditions mainly determine metabolic processes involved in soil and leaf and our goal is to determine if this combined analytical approach will be sufficiently precise to detect biological evolutions (plant health, parasitic attack…).

Our research aimed to determine the effect and efficiency of foliar application of urea on the phenolic composition of Tempranillo Blanco grapes. The field experiment was carried out in 2019 and 2020 seasons and the plot was located in D.O.Ca Rioja (North of Spain). The vineyard was Vitis vinifera L. Tempranillo Blanco and grafted on Richter-110 rootstock. The treatments were control (C), whose plants were sprayed with water and three doses of urea: plants were sprayed with urea 3 kg N/ha (U3), 6 kg N/ha (U6) and 9 kg N/ha (U9). The applications were performed in two phenological stages, pre-veraison (Pre) and veraison (Ver). Also, each of the treatments was repeated one week later. Control and treatments were performed in triplicate and arranged in a randomised block design. Grapes were harvested at optimum ripening stage. High-performance liquid chromatography was used to analyse the phenolic composition of the grapes. Finally, the results obtained from the analytical determinations – flavonols, flavanols and non-flavonoid (hydroxybenzoic acids, hydroxycinnamic acids and stilbenes) – were studied statistically by analysis of variance. The results showed that, in 2019, U6-Pre and U9-Pre treatments increased the hydroxybenzoic acid content in grapes, and also all foliar treatments applied at Pre enhanced the stilbene concentration. Moreover, U3-Ver was the only treatment that rose flavonol and stilbene contents in the Tempranillo Blanco grapes. In 2020, all treatments applied at Pre enhanced the flavonol concentration in grapes. Furthermore, U3-Pre and U9-Pre treatments increased stilbene content in grapes. Nevertheless, the hydroxybenzoic acid content was improved by U6-Ver and U9-Ver and besides, hydroxycinnamic acid concentration in grapes was increased by all treatments applied at Ver. In conclusion, the lower and highest dose of urea (U3 and U9), applied at pre-veraison, were the best treatments to improve the Tempranillo Blanco grape phenolic composition.

Climate influence on grapevine physiology is prevalent and this influence is only expected to increase with climate change. Although governed by a general determinism, climate influence on grapevine physiology may present variations according to the terroir. In addition, these site-specific differences are likely to be enhanced when climate influence is studied using farm data. Indeed, farm data integrate additional sources of variation such as a varying representativity of the conditions actually experienced in the field. Nevertheless, there is a real challenge in valuing farm data to enable grape growers to understand their own terroir and consequently adapt their practices to the local conditions. In such a context, this article proposes a framework to site-specifically study climate influence on grapevine physiology using farm data. It focuses on improving the analysis of time series of weather data. The analytical framework includes the synchronization of time series using site-specific thermal indices computed with an original method called Extended Growing Degree Days (eGDD). Synchronized time series are then analyzed using a Bayesian functional Linear regression with Sparse Steps functions (BLiSS) in order to detect site-specific periods of strong climate influence on yield development. The article focuses on temperature and rain influence on grape yield development as a case study. It uses data from three commercial vineyards respectively situated in the Bordeaux region (France), California (USA) and Israel. For all vineyards, common periods of climate influence on yield development were found. They corresponded to already known periods, for example around veraison of the year before harvest. However, the periods differed in their precise timing (e.g. before, around or after veraison), duration and correlation direction with yield. Other periods were found for only one or two vineyards and/or were not referred to in literature, for example during the winter before harvest.

Barolo DOCG is an economically important wine producing region in Northwest Italy. It is a small region of approximately 70 km2 gross area. The topography is very complex with steep sloped hills ranging in elevation from below 200 m to 550 m. Barolo DOCG wine is made exclusively from the Nebbiolo grape. Bioclimatic indexes are often used in viticulture to gain a better understanding of broader climate trends which can be compared temporally and geographically. These indexes are also used for identifying potential phenological timing, growing region suitability, and potential risks associated with expected climatic changes. Understanding how topography influences bioclimatic indexes can help with understanding of mesoscale climate behaviour leading to improved decision making and risk management strategies. The average monthly maximum and minimum temperatures, the Cool Night Index, the Huglin Index, and the monthly diurnal range (from July to October) were calculated using data from 45 weather stations within a 40 km radius of the Barolo DOCG growing area between the years 1996 and 2019. Linear and multiple regression models were developed using independent variables (elevation, aspect, slope) extracted from a digital elevation model to identify significant relationships. Bioclimatic indexes were then kriged with external drift using independent variables that showed significant relationships with the bioclimatic index using a 100 m resolution grid. The maximum monthly temperatures and the Huglin Index showed consistent significant negative relationships with elevation in all years. The minimum monthly temperatures showed no relationship with elevation but in some months a small but significant relationship was observed with aspect. Due to the lack of a relationship between minimum monthly temperatures and elevation compared to the significant relationship between maximum monthly temperatures and elevation, monthly diurnal range had a negative relationship with elevation.