Estudio comparativo del potencial enológico de dos varietales tintos cultivados en la isla de Tenerife

Dans le cadre d’une recherche sur les terroirs viticoles du canton de Vaud – Suisse, un modèle du microclimat intégrant température, relief, éclairement et pluviométrie a été conçu.

Brandy de Jerez (BJ) is a spirit drink made exclusively from spirits and wine distillates and is characterized by the use of casks for aging that previously contained Sherries. The quality and sensory complexity of BJ depend on the raw materials and some factors: grape variety, conditions during processing the wine and its distillation, as well as the aging in the cask. Therefore, the original compounds of the grapes from which it comes are of great interest (1 y 2) being in most cases the Airén variety. Their relationship with the quality of the musts and the wines obtained from them has been studied (3) and varies each year of harvest depending on the weather conditions (4).

Fining is a technique that is used to remove unwanted wine components that affect clarification, astringency, color, bitterness, and aroma. Fining involves the addition of adsorptive or reactive material in order to reduce or eliminate the presence of certain less desirable wine components and to ensure that a wine remains in a particular stable state for a given period of time Recently concerns have been raised about the addition of animal proteins, such as gelatin, to wine due to the disease known as bovine spongiform encephalopathy (Mad Cow disease). Although the origin of gelatins has been moved to porcine, winemakers are asking for substitute products with properties and application protocols similar to the traditional animal-derived ones, making the use of plant-derived proteins in fining a practically viable possibility. As a consequence, various fining agents derived from plants have been proposed, including proteins from cereals, legumes, and potato.

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.

Aroma is one of the most important attributes that determine consumer’s perception of the sensory quality of wine and varietal typicity.