Changing New Zealand climate equals a changing New Zealand terroir?

Agiorgitiko (Vitis vinifera L. cv.) is the most widely cultivated indigenous red grape variety in Greece, known for the production of Protected Designation of Origin Nemea wines.

País grape has been estimated to arrive to Chile almost 500 years ago, being the first strain grown in this country. Traditionally, this grape has been used to mix with other varieties, to produce poor quality wines, but today is beginning to be used in the production of high quality wines. However, very little is known about the chemical characteristics of this variety. The aroma is one of the most important quality attributes of wine. Volatile compounds of this beverage may come from the grape (varietal aromas), from the fermentation process, from the ageing. The aromatic compounds are found in the grape in two forms: as free volatile compounds and as non-volatile compounds. The last ones, are aroma precursors present mainly as glycoconjugates formed by a sugar and an aglycone…

According to the Kyoto Protocol objectives, it’s necessary to identify alternative carbon dioxide sinks, and vineyard soils could be a significant opportunity.

Visual clarity in wines is crucial for commercial purposes [1]. Potential protein haze in white wines remains a constant concern in wineries, commonly addressed using bentonite [2].

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.