Étude intégrée et allégée des terroirs viticoles en Anjou: caractérisation et zonage de l’unité terroir de base, en relation avec une enquête parcellaire

Increasingly warm and dry climate conditions are challenging the viticulture and winemaking sector. Digital technologies and crop modelling bear the promise to provide practical answers to those challenges. As viticultural activities strongly depend on harvest date, its early prediction is particularly important, since the success of winemaking practices largely depends upon this key event, which should be based on an accurate and advanced plan of the annual cycle. Herein, we demonstrate the creation of modelling tools to assess grape ripeness, through sugar concentration monitoring. The study area, the Portuguese Côa valley wine region, represents an important terroir in the “Douro Superior” subregion. Two varieties (cv. Touriga Nacional and Touriga Franca) grown in five locations across the Côa Region were considered. Sugar accumulation in grapes, with concentrations between 170 and 230 g l-1, was used from 2014 to 2020 as an indicator of technological maturity conditioned by meteorological factors. The climatic time series were retrieved from the EU Copernicus Service, while sugar data were collected by a non-profit organization, ADVID, and by Sogrape, a leading wine company. The software for calibrating and validating this model framework was the Phenology Modeling Platform (PMP), version 5.5, using Sigmoid and growing degree-day (GDD) models for predictions. The performance was assessed through two metrics: Roots Mean Square Error (RMSE) and efficiency coefficient (EFF), while validation was undertaken using leave-one-out cross-validation. Our findings demonstrate that sugar content is mainly dependent on temperature and air humidity. The models achieved a performance of 0.65

This study aims to create an updated, agile viticultural climate index (similar to the Winkler Index) by performing in-depth analyses of current and historical data from industry partners in several major winegrowing regions. The Winkler Index was developed in the early twentieth century based on analysis of various grape-growing regions in California. The index uses heat accumulation (i.e. Growing Degree Days) throughout the growing season to determine which grape varieties are best suited to each region. As viticultural regions are increasingly subject to the complexity and uncertainty of a changing climate, a more rigorous, agile model is needed to aid grape growers in determining which cultivars to plant where. For the first phase of this study, 21 industry partners throughout Napa Valley shared historical phenology, harvest, viticultural practice, and weather data related to their Cabernet sauvignon vineyard blocks. To complement this data, berry samples were collected throughout the 2021 growing season from 50 vineyard blocks located throughout 16 American Viticultural Areas that were then analyzed for basic berry chemistry and phenolics. These blocks have been mapped using a Geographic Information System (GIS), enabling analysis of altitude, vineyard row orientation, slope, and remotely sensed climate data. Sampling sites were also chosen based on their proximity to a weather station. By analyzing historical data from industry partners and data specifically collected for this study, it is possible to identify key parameters for further analysis. Initial results indicate extreme variability at a high spatial resolution not currently accounted for in modern viticultural climate indices and suggest that viticultural practices play a major role. Using the structure of data collection and analyses developed for the first phase, this project will soon be expanded to other wine regions globally, while continuing data collection in Napa Valley.

Vitis vinifera L. ‘Gewürztraminer’ is a historical grape variety of Alto Adige (Südtirol), Italy, which is widely grown in the area of Tramin an der Weinstraße, but is also grown globally. It produces highly aromatic wines that are strongly influenced by the terroir of the vineyard sites where they are grown. This study looked at musts and young wines from ‘Gewürztraminer’ grapes harvested in seven distinct vineyards near Tramin and then processed at Cantina di Termeno, minimizing winemaking protocol variability. Samples were profiled using bidimensional gas chromatography–time-of-flight mass spectrometry, liquid chromatography coupled to electrochemical detection, and near-IR spectrometry. The data were subjected to Principle Component Analysis and Hierarchical Clustering Analysis. Sensory discriminant testing was undertaken using the sorting method with a semi-trained panel, and the data were processed using Multidimensional Scaling. Seven must/wine pairs could be distinguished based on their untargeted volatilome profiles and on sensory evaluation. As expected, there were greater differences in the volatile compounds between the wines than between the musts. The wines from vineyards 4 and 5 were nonetheless quite homogenous in terms of chemical and sensory analyses, as were the wines from vineyards 1 and 3. For the phenolic profile, differences were noted between the musts and wines of vineyards 2, 3, and 4, but the musts from vineyards 5 and 7 were similar. Sensory analysis showed the wines from vineyards 6 and 7 to be distinct from the rest. These results reinforce that the composition of ‘Gewürztraminer’ musts and wines is strongly determined by vineyard site, even in a small geographic area with high variability of the terroir (soil and microclimate), and that these differences are apparent in the flavours and aromas of the finished wines. Further confirmation would require a larger sample of wines, preferably from several vintages.

The parameters that determine the grape quality, and therefore the optimal harvest time, suffer variations during berry ripening, related to climate change, with the widely known problem of the gap between technological and phenolic maturities. However, there are few studies about its incidence on grape nitrogen composition. For this reason, the use of an elicitor, methyl jasmonate (MeJ), alone or with urea, is proposed as a tool to reduce climatic decoupling, allowing to establish the harvest time in order to achieve the optimum grape quality. The aim was to study the effect of MeJ and MeJ+Urea foliar applications on the evolution of Tempranillo amino acids content throughout the grape maturation. Three treatments were foliarly applied, at veraison and 7 days later: control (water), MeJ (10 mM) and MeJ+Urea (10 mM+6 kg N/ha). Grape samples were taken at five stages of maturation: day before the first and second applications, 15 days after the second application (pre-harvest), harvest day, and 15 days after harvest (post-harvest). The amino acids analysis of the samples was carried out by HPLC. Results showed that the evolution of amino acids was similar regardless of the treatment; however, foliar applications influenced the nitrogen compounds content, i.e., there was no qualitative effect but quantitative one. Most of the amino acids reached their maximum concentration in pre-harvest, being higher in grapes from the treatments than in the control. In general, no differences in grape amino acids content were observed between MeJ and MeJ+Urea treatments. Foliar applications with MeJ and MeJ+Urea enhanced the grape amino acids content, without affecting their profile, helping to optimize their quality and allowing to establish a more complete grape ripening standard. Therefore, MeJ and MeJ+Urea foliar applications can be a simple agronomic practice, which has shown promising results in order to enhance the grape quality.

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.