Phenolic characterization of four different red varieties with “Caíño” denomination cultivated in Northwestern Spain

Majority of California’s vineyards rely on supplemental irrigation to overcome abiotic stressors. In the context of climate change, increases in growing season temperatures and crop evapotranspiration pose a risk to adaptation of viticulture to climate change. Vineyard cover crops may mitigate soil erosion and preserve water resources; but there is a lack of information on how they contribute to vineyard resiliency under tillage systems. The aim of this study was to identify the optimum combination of cover crop sand tillage without adversely affecting productivity while preserving plant water status. Two experiments in two contrasting climatic regions were conducted with two cover crops, including a permanent short stature grass (P. bulbosa hybrid), barley (Hordeum spp), and resident vegetation under till vs. no-till systems in a Ruby Cabernet (V. vinifera spp.) (Fresno) and a Cabernet Sauvingon (Napa) vineyard. Results indicated that permanent grass under no-till preserved plant available water until E-L stage 17. Consequently, net carbon assimilation of the permanent grass under no-till system was enhanced compared to those with barley and resident vegetation. On the other hand, the barley under no-till system reduced grapevine net carbon assimilation during berry ripening that led to lower content of nonstructural carbohydrates in shoots at dormancy. Components of yield and berry composition including flavonoid profile at either site were not adversely affected by factors studied. Switching to a permanent cover crop under a no-till system also provided a 9% and 3% benefit in cultural practices costs in Fresno and Napa, respectively. The results of this work provides fundamental information to growers in preserving resiliency of vineyard systems in hot and warm climate regions under context of climate change.

With the aim of producing premium wines, it is admitted that moderate environmental stresses may contribute to the accumulation of compounds of interest in grapes. However the ongoing climate change, with the appearance of more limiting conditions of production is a major concern for the wine industry economic. Will it be possible to maintain the vineyards in place, to preserve the current grape varieties and how should we anticipate the adaptation measures to ensure the sustainability of vineyards? In this context, the question of the responses and adaptation of grapevine to abiotic stresses becomes a major scientific issue to tackle. An abiotic stress can be defined as the effect of a specific factor of the physico-chemical environment of the plants (temperature, availability of water and minerals, light, etc.) which reduces growth, and for a crop such as the vine, the yield, the composition of the fruits and the sustainability of the plants. Water stress is in many minds, but a systemic vision is essential for at least two reasons. The first reason is that in natural environments, a single factor is rarely limiting, and plants have to deal with a combination of constraints, as for example heat and drought, both in time and at a given time. The second reason is that plants, including grapevine, have central mechanisms of stress responses, as redox regulatory pathways, that play an important role in adaptation and survival. Here we will review the most recent studies dealing with this issue to provide a better understanding of the grapevine responses to a combination of environmental constraints and of the underlying regulatory pathways, which may be very helpful to design more adapted solutions to cope with climate change.

Climate change represents a major challenge for the French wine industry. Climatic conditions in French vineyards have already changed and will continue to evolve. One of the notable effects on grapevine is the advancing growing season. The aim of this study is to characterise the evolution of agroclimatic indicators (Huglin index, number of hot days, mean temperature, cumulative rainfall and number of rainy days during the growing season) at French wine-growing regions scale between 1980 and 2019 using gridded data (8 km resolution, SAFRAN) and for the middle of the 21th century (2046-2065) with 21 GCMs statistically debiased and downscaled at 8 km. A set of three phenological models were used to simulate the budburst (BRIN, Smoothed-Utah), flowering, veraison and theoretical maturity (GFV and GSR) stages for two grape varieties (Chardonnay and Cabernet-Sauvignon) over the whole period studied. All the French wine-growing regions show an increase in both temperatures during the growing season and Huglin index. This increase is accompanied by an advance in the simulated flowering (+3 to +9 days), veraison (+6 to +13 days) and theoretical maturity (+6 to +16 days) stages, which are more noticeable in the north-eastern part of France. The climate projections unanimously show, for all the GCMs considered, a clear increase in the Huglin index (+662 to 771 °C.days compared to the 1980-1999 period) and in the number of hot days (+5.6 to 22.6 days) in all the wine regions studied. Regarding rainfall, the expected evolution remains very uncertain due to the heterogeneity of the climates simulated by the 21 models. Only 4 regions out of 21 have a significant decrease in the number of rainy days during the growing season. The two budburst models show a strong divergence in the evolution of this stage with an average difference of 18 days between the two models on all grapevine regions. The theoretical maturity is the most impacted stage with a potential advance between 40 and 23 days according to wine-growing regions.

In the context of LIFE project MIDMACC (LIFE18 CCA/ES/001099), several pilots have been installed in vineyards in mid mountain areas of Catalonia (NE Spain) to test well stablished agronomic practices to increase the adaptation of Mediterranean mid mountain to climate change. Soil water content (SWC) at three different depths (15, 30 and 45cm) was measured in continuum from August 2020. One pilot (WC) included a well-established green cover (GC), a new GC (NC) and a conventional soil management (CM, tilling+herbicides). NC presented an intermediate state between WC and CM, responding similarly to CM in autumn but quickly reaching similar SWC to WC, then following the same evolution till next spring, with CM presenting lower values along autumn and winter. Then vegetation activation decreased SWC in all plots, (much slower in CM, lacking GC). Sensibility to spring rains is again intermediate for NC, which joins SWC evolution of CM by the end of spring till next autumn. It is expected that NC will resemble WC more and more as its GC develops. In the pilot combining vine training (VSP vs Gobelet) and hillside management (slope vs terrace), no clear pattern could be related with these conditions. However, both terraces seem to be more sensitive to spring rains. A third pilot included new vineyards (7 and 1 year old). In the new vineyard (N), higher canopy development, a spontaneous green cover and row straw resulted in a slower SWC dynamic, not so sensitive to rains but conserving more soil water in spring and most of summer, even with presumably a higher water extraction by vines. In the newest vineyard (VN) the deepest sensor is still sensitive to rain events all over the year and SWC is always highest at this depth, revealing small water capture by vines.

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.