A first look at the aromatic profile of “Monferace” wines

Extraction of anthocyanins and tannins have been studied for two grape varieties, Carignan and Grenache, two maturation levels and two vintages, in model solutions and in wines, using UHPLC-MS/MS in the MRM mode  and HPSEC.

Drought is considered to be the predominant factor both for determining the geographic distribution of vegetation and for restricting crop yields in agriculture. Furthermore

The ‘Caiño’ cultivar was cultivated in Galicia (Northwestern Spain) before the invasion of grape phylloxera. Genetic diversity from this cultivar have been described and considered as originating in Galicia, ‘Caiño Tinto’, ‘Caiño Bravo’, ‘Caiño Redondo’, ‘Caiño Longo’ and ‘Caiño Blanco’.

La Région Piemonte a commencé en 1994 un projet de caractérisation des productions vitivinicoles des terroirs du Barolo (Piemonte, Italie) par une équipe pluridisciplinaire avec la participation de 6 Instituts de recherche qui travaillent dans la Région et la collaboration de 2 Associations des producteurs viticoles et des organismes de valorisation du vin Barolo.

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.