Zonage et caractérisation des terroirs de l’AOC Côtes-du-Rhône: exemple du bassin de Nyons-Valreas

In the study of terroir, a separate analysis of its many component factors can be of great help in accurately identifying a vineyard’s natural elements that impact wine quality and typicity. This research used a dedicated pluri-disciplinary approach to investigate the ecological characteristics, including geology and geographical features, of 14 vineyards that produce Gewürztraminer and Sauvignon Blanc cultivars in the alpine Alto Adige DOC wine region. Both the geopedological method using Vineyards Geological Identity (VGI) and the new Solar Radiaton Identity (SRI) topoclimatic classification method were used to provide analytical measurements and qualitative/quantitative characterisations. In addition, wide-ranging targeted and untargeted oenological and chemical analyses were carried out on grapes, musts and wines to correlate the soils’ geomineral and physical conditions with the biochemical properties of their fruits and wines. The research identified strong correlations between vineyard geo-identity and wine biofingerprint, confirming a mineral traceability of strontium rubidium ratio and some minerals distinctive to the local geology, such as K, Ca, Ag, Ba and Mn.  The study also discovered that particular geomineral and physical soil conditions of the studied vineyards are related to the different amount of amino acids, primary varietal aromas and polyphenols found in grapes, musts and wines. The research confirmed that winemaking technologies support oenological quality, although in some cases, human practices can overpower certain characteristic elements in wine, erasing the typical imprint left by the vineyards’ natural terroir, which becomes less traceable. Terroir abiotic ecological factors and vineyard identity can be classified in detail using the new VGI and SRI analysis methods to discover interrelationships between geo-pedological and topoclimatic conditions that impact wine quality. These methods are also helpful in identifying which ecological elements are exclusive to a particular vineyard or wine sub-region.

In viticulture, the challenges of local climate modelling are multiple: taking into account the local environment, fine temporal and spatial scales, reliable time series of climate data, ease of implementation and reproducibility of the method. At the local scale, recent studies have demonstrated the contribution of spatialization methods for ground-based climate observation data considering topographic factors such as altitude, slope, aspect, and geographic coordinates (Le Roux et al, 2017; De Rességuier et al, 2020). However, these studies have shown questions in terms of the reproducibility and sustainability of this type of climate study. In this context, we evaluated the potential of MODIS thermal satellite images validated with ground-based climate data (Morin et al, 2020). Previous studies have been encouraging, but questions remain to be explored at the regional scale, particularly in the dynamics of the massive use of bioclimatic indices to classify the climate of wine regions. The results at the local scale were encouraging, but this approach was tested in the current study at the regional scale. Several objectives were set: 1) to evaluate the downscaling method for land surface temperature time series, 2) to identify regional thermal structure variations. We used weekly minimum and maximum surface temperature time series acquired by MODIS satellites at a spatial resolution of 1000 m and downscaled at 500 m using topographical variables. Two types of analyses were performed:

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.

The use of rootstocks tolerant to soil water deficit is an interesting strategy to cope with limited water availability. Currently, several nurseries are breeding new genotypes, but the physiological basis of its responses under water stress are largely unknown. To this end, an ecophysiological assessment of the conventional 110-Richter (110R) and SO4, and the new M1 and M4 rootstocks was carried out in potted ungrafted plants. During one season, these Vitis genotypes were grown under greenhouse conditions and subjected to two water regimes, well-watered and water deficit. Water potentials of plants under water deficit down to < -1.4 MPa, and net photosynthesis (AN) <5 μmol m-2 s-1 did not cause leaf oxidative stress damage compared to well-watered conditions in any of the genotypes. The antioxidant capacity was sufficient to neutralize the mild oxidative stress suffered. Under both treatments, gravimetric differences in daily water use were observed among genotypes, leading to differences in the biomass of root, shoot and leaf. Under well-watered conditions, SO4 and 110R were the most vigorous and M1 and M4 the least. However, under water stress, SO4 exhibited the greatest reduction in biomass while M4 showed the lowest. Remarkably, under these conditions, SO4 reached the least negative stem water potential (Ψstem), while M1 reduced stomatal conductance (gs) and AN the most. In addition, SO4 and M1 genotypes also showed the highest and lowest hydraulic conductance values, respectively. Our results suggest that there are differences in water use regulation among genotypes, not only attributed to differences in stomatal regulation or intrinsic water use efficiency at the leaf level. Therefore, because no differences in canopy-to-root ratio were achieved, it is hypothesized that xylem vessel anatomical differences may be driving the reported differences among rootstocks performance. Results demonstrate that each Vitis rootstock differs in its ecophysiological responses under water stress.

The Fruška Gora mountain is a traditional wine-growing region in Serbia situated in the Pannonian Basin. Due to such a position, the vicinity of the Danube River and the presence of concave configuration, it is suitable for grape production. This paper provides analyses of spatial variations in meteorological parameters and grape juice quality within Fruška Gora wine region over three consecutive vintages (2018-2020). The examined period can be defined as warm with cool nights during September (AVG 18,9°C; GDD 1918°C; CI 12°CF) and with the presence of mesoclimatic variability. The East part of the study area was somewhat drier and hotter compared to other parts of the region. The analyses of grape must samples (190 in total) of five cultivars (Cabernet-Sauvignon, Merlot, Chardonnay, Sauvignon blanc and Grašac (Welschriesling)) commonly grown across the region (19 sites), were performed using Fourier Transform Infrared Technology (FTIR). Among all cultivars, Sauvignon blanc was harvested first in the East area (DOY=246±5, GDD at harvest=1552±74, 22.2±0.7 °Brix), while the latest harvest was recorded for Cabernet-Sauvignon in the West (DOY=283±5, GDD at harvest=1936±187, 23.4±1.0 °Brix ). Both the red and white cultivars had higher acidity and YAN in the grape must if the vines were grown in the North and East compared to South and West areas. According to PCA analysis, Grašac showed the lowest variation in grape must chemical composition. Thus, the results confirm that Grašac is the most stable cultivar in Fruška Gora. All monitored cultivars reached technological fruit ripeness by the end of the growing season. However, it was difficult to reach full ripeness of red cultivars, mostly beacuse of uncoupling of technolocical and phenolic ripeness. Thus, Cabernet-Sauvignon had higher variations in GDD sums at harvest compared to other cultivars, which probably increased variations in grape must quality.