Red wine oxidation study by accelerating ageing tests and electrochemical method

Global warming is one of the biggest environmental, social and economic threats in several viticultural regions. In the Douro Valley, changes are expected in the coming years, namely an increase in temperature and a decrease in precipitation. These changes are likely to have consequences for the production and quality of wine. The aim of this study was to explore the effects of different soil characteristics combined with several deficit irrigation strategies, managed throughout ETc references and predawn leaf water potentials thresholds, on physiology, yield, and qualitative attributes on the Touriga Nacional variety under years of mild to severe water and heat stress. The studies were conducted over seven years (2015 to 2021) in two plots of a commercial vineyard located at Quinta do Ataíde (Symington Family Estates) planted in 2011 and 2014 at 170 meters elevation, growing under three water regimes: non-irrigated (NI) and two deficit irrigation strategies (30% and 60% ETc) assessed weekly by Ψpd. The site has an annual rainfall below 500 mm, with high atmospheric demand. Climate data was collected from a weather station, located on site. Berry ripening was followed weekly for fruit analysis. At harvest, yield, vigour and pruning weight per vine were determined from 90 vines by treatment. Each season at veraison the NDVI Index was accessed by a drone. The soils physic-chemistry in the experimental blocs were analysed and grouped by SWHC. Delta C-13 analyses were also performed per treatment in two years.Irrigation had a positive effect on yield per vine, mostly due to an increase in berry and cluster weight, and fertility index through the years. A significant increase in sugar content, colour and phenols was observed with deficit irrigation in some years, but vine vigour related to soil characteristics had by far the greatest impact on quality.

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.

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

In the last decades the growers of the Portuguese Dão winegrowing region (center of Portugal) are experiencing changes in climate that are influencing either grape phenology berry health and ripening. Aiming to study the relationships between climate indices (CI), seasonal weather and grapevine phenology, in this work long-term climate and phenological data collected at the experimental vineyard of the Portuguese Dão research centre between 1958 and 2019 (61 years) for the red variety Touriga Nacional, was analyzed. The trends over time for the classical temperature-based indices (Growing Season Temperature – GST -, Growing Degree Days – GDD, Huglin Index – HI and Cool Night Index – CI) presented a significantly positive slope while the Dryness Index (DI) showed a negative trend over the last 61 years. Regarding grapevine phenology, an average advance of 4.5 days per decade in the harvest day was observed throughout the last 61 years. Consequently, the weather conditions during the ripening period have changed, showing an increasing trend over time in the average temperature (higher magnitude in the maximum than in the minimum temperature) and a decrease in the accumulated rainfall. A regression analysis showed that ~50% of harvest date variability over years was explained by the temperature-based indices variability. These observed effects of climate change on bioclimatic indices and corresponding anticipation of harvest date can still be considered advantageous for the Dão terroir as it allows to achieve an optimal berry ripening before the common equinox rains and, therefore, avoid the potential negative impacts of the rainfall on berry health and composition.

Late spring frost is a major challenge for various winegrowing regions across the world, its occurrence often leading to important yield losses and/or plant failure. Despite a significant increase in minimum temperatures worldwide, the spatial and temporal evolution of spring frost risk under a warmer climate remains largely uncertain. Recent projections of spring frost risk for viticulture in Europe throughout the 21st century show that its evolution strongly depends on the model approach used to simulate budburst. Furthermore, the frost damage modelling methods used in these projections are usually not assessed through comparison to field observations and/or frost damage reports.
The present study aims at comparing frost risk projections simulated using six spring frost models based on two approaches: a) models considering a fixed damage threshold after the predicted budburst date (e.g BRIN, Smoothed-Utah, Growing Degree Days, Fenovitis) and b) models considering a dynamic frost sensitivity threshold based on the predicted grapevine winter/spring dehardening process (e.g. Ferguson model). The capability of each model to simulate an actual frost event for the Vitis vinifera cv. Chadonnay B was previously assessed by comparing simulated cold thermal stress to reports of events with frost damage in Chablis, the northernmost winegrowing region of Burgundy. Models exhibited scores of κ > 0.65 when reproducing the frost/non-frost damage years and an accuracy ranging from 0.82 to 0.90.
Spring frost risk projections throughout the 21st century were performed for all winegrowing subregions of Bourgogne-Franche-Comté under two CMIP5 concentration pathways (4.5 and 8.5) using statistically downscaled 8×8 km daily air temperature and humidity of 13 climate models. Contrasting results with region-specific spring frost risk trends were observed. Three out of five models show a decrease in the frequency of frost years across the whole study area while the other two show an increase that is more or less pronounced depending on winegrowing subregion. Our findings indicate that the lack of accuracy in grapevine budburst and dehardening models makes climate projections of spring frost risk highly uncertain for grapevine cultivation regions.