Towards a better understanding of the root system diversity and plasticityin young grafted vines using 2D imaging and 3D modelling tools

Marlborough Sauvignon Blanc has rapidly gained an international reputation for style and quality. The extent to which this can be attributed to the climate, soils or vineyard management is at present unclear. However, the young alluvial soils of the Wairau Plains are considered to play an important role in determining this unique wine style. Marked changes in soil texture occur on the Wairau Plains over short distances.

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.

Climate change is profoundly impacting wine tourism in Germany and presents new challenges for wineries.

Mannoproteins (MPs) are released from the yeast cell wall during alcoholic fermentation and aging on the lees, and influence aspects of wine quality such as haze formation and colour stability. Yet, as this is a slow process with microbiological and sensory risks, the exogenous addition of extracted MPs poses an efficient alternative. While Saccharomyces cerevisiae has long been studied as a prominent source for MPs extraction, their structure and composition greatly differ between yeast species. This may influence their behaviour in the wine matrix and subsequent impact on wine properties. However, although wine yeast species other than S. cerevisiae possibly present an untapped source of MPs, they are still ill-characterised in terms of chemical composition and influence on wine.

Oligosaccharides have only recently been characterized in wine, and the information on composition and content is still limited. In wine, these molecules are mainly natural byproducts of the degradation of grape berry cell wall polysaccharides. Wine oligosaccharides present several physicochemical properties, being one relevant factor linked to the astringency perception of wines (1,2). A terroir can be defined as a grouping of homogeneous environmental units based on the typicality of the products obtained. This notion is particularly associated with wine, being the climate and the soil two of the major elements of terroir concept.