Effects of yeast product addition and fermentation temperature on lipid composition and sensory of pinot noir wines

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.

This study assessed the suitability of grapevine growing in three DOs (Empordà, Pla de Bages and Penedès) of Catalonia (NE Spain) over the 21st century. For this purpose, an estimation of water needs and agroclimatic and phenological indicators was made. Climate change impacts were estimated at 1 km pixel resolution using temperature and precipitation projections from several general circulation models (GCM) and two climate change scenarios: RCP 4.5 (stabilization scenario) and RCP 8.5 (worst-case scenario). Potential crop evapotranspiration (following FAO procedure) and a daily water balance considering soil water holding capacity were used to estimate actual evapotranspiration of vines and, finally, water needs. Dynamics would be similar in the three DOs studied although the magnitude of impact differs. Water needs would be 2 and 3 times greater (ranging from 0 to more than 1500 m3/ha) than current water needs at both climate change scenarios. Moreover, blooming date would advance from 3 to 6 weeks, harvest date from 1 to 2.5 months, resulting in growing cycles from 10 to 80 days shorter. It should also be noted that frost risk would decrease from 6 to 76%, the number of days with temperatures above 30ºC during ripening would rise from 48 to 500% and tropical nights (minimum temperature >20ºC) at ripening would increase from 28 to 150%, depending on the scenario and the DOs. The impacts of climate change in the three DOs could result in significant limitations for grapevine cultivation and wine production if adaptive strategies are not applied. This result could serve as a basis for the design of specific and particular adaptation strategies to improve and maintain vineyards in the DOs studied and could be extrapolated to similar DOs and regions.

Vitis champinii cultivars Ramsey and Dog-ridge are main choices for rootstocks to adapt viticulture in semi-arid and arid regions thanks to their distinctive tolerance to drought and salinity. However, genetic studies on non-vinifera rootstocks have heavily relied on the grapevine (Vitis vinifera) reference genome, which difficulted the assessment of the genetic variation between rootstock species and grapevines. In the present study, this limitation is addressed by introducing a novo phased genome assembly and annotation of Vitis champinii. This new Vitis champinii genome was employed as reference for mapping RNA-seq reads from the same species under drought and salt stresses, and for comparison the same reads were also mapped to the Vitis vinifera PN40024.V4 reference genome. A significant increase in alignment rate was gained when mapping Vitis champinii RNA-seq reads to its own genome, compared to the Vitis vinifera PN40024.V4 reference genome, thus revealing the expression levels of genes specific to Vitis champinii. Moreover, differences in coding sequences were observed in ortholog genes between Vitis champinii and Vitis vinifera, which therefore challenges previous differential expression analyses performed between contrasting Vitis genotypes on the same gene from the Vitis vinifera genome. Genes with possible implications in drought and salt tolerance have been identified across the genome of Vitis champinii, and the same genomic data can potentially guide the discovery of candidate genes specific from Vitis champinii for other traits of interest, therefore becoming a valuable resource for rootstock breeding designs, specially towards increased drought and salinity due to climate change.

One of the major issues for the wine sector is the impact of climate change linked to the increasing temperatures which affects physicochemical parameters of the grape varieties planted in Bordeaux vineyard and consequently, the quality of wine. In some varietals, the attenuation of their fresh fruity character is accompanied by the accentuation of dried-fruit notes [1]. As a new adaptive strategy on climate change, some winegrowers have initiated changes in the Bordeaux blend of vine varieties [2]. This study intends to explore the fruitiness in wines produced from grape varieties adapted to the future climate of Bordeaux. 10 commercial single–varietal wines from 2018 vintage made from the main grape varieties in the Bordeaux region (Cabernet franc, Cabernet-Sauvignon and Merlot) as well as from indigenous grape varieties from the Mediterranean basin, such as Cyprus (Yiannoudin), France (Syrah), Greece (Agiorgitiko and Xinomavro), Portugal (Touriga Nacional) and Spain (Garnacha and Tempranillo), were selected among 19 samples using sensory descriptive analyses. Both sensory and instrumental analyses were coupled, to investigate their fruity aroma expression. For sensory analysis, samples were prepared from wine, using a semi preparative HPLC method which preserves wine aroma and isolates fruity characteristics in 25 specific fractions [3,4]. Fractions of interest with intense fruity aromas were sensorially selected for each wine by a trained panel and mixed with ethanol and microfiltered water to obtain fruity aromatic reconstitutions (FAR) [5]. A free sorting task was applied to categorize FAR according to their similarities or dissimilarities, and different clusters were highlighted. Instrumental analysis of the different FAR and wines demonstrated variations in their molecular composition. Results obtained from sensory and gas chromatography analysis enrich the knowledge of the fruity expression of red wines from “new” grape varieties opening up new perspectives in wine technology, including blending, thus providing new tools for producers.

Wine quality is strongly linked to climate. Quality scores are often driven by climate variation across different winegrowing regions and years, but also influenced by other aspects of terroir, including variety. While recent work has looked at the relationship between quality scores and climate across many European regions, less work has examined New World winegrowing regions. Here we used scores from three major rating systems (Wine Advocate, Wine Enthusiast and Wine Spectator) combined with daily climate and phenology data to understand what drives variation across wine quality scores in major regions of the Western US, including regions in California, Oregon and Washington. We examined effects of variety, region, and in what phenological period climate was most predictive of quality. As in other studies, we found climate, based mainly on growing degree day (GDD) models, was generally associated with quality—with higher GDD associated with higher scores—but variety and region also had strong effects. Effects of region were generally stronger than variety. Certain varieties received the highest scores in only some areas, while other varieties (e.g., Merlot) generally scored lower across regions. Across phenological stages, GDD during budbreak was often most strongly associated with quality. Our results support other studies that warmer periods generally drive high quality wines, but highlight how much region and variety drive variation in scores outside of climate.