Mapping and tracking canopy size with VitiCanopy

Aging wine on lees benefits different wine sensory and technological properties including an enhanced resistance to oxidation. Several molecules released by yeast, such as membrane sterols and glutathione, have been previously proposed as key factors for this activity [1].

Grapevines are grown grafted in most viticultural regions. Grapevine rootstocks are either hybrids or pure species of different American Vitis spp. (particularly V. berlandieri, V. rupestris and V. riparia), which were primarily used to provide root resistance to the insect pest Phylloxera. In addition to Phylloxera resistance, grapevine rootstocks were also selected in relation their resistance to various abiotic stress conditions. Future rootstocks should have the potential to adapt viticulture to climate change without changing the characteristics of the harvested product. However, high grafting success rates are an essential prerequisite to be able to use them with all the varieties. The objective of this work is to develop quantitative techniques to characterize graft union formation in grapevine.

Sémillon is a cultivated grape variety known for contributing to dry and sweet white wine production. However, only seven approved clones have been officially recognized in France[1]. In this study, we aimed to characterize the genetic diversity and metabolomic profiles of a Sémillon clonal population, shedding light on the potential variations within this important grape variety.

Parallèlement à la connaissance des aptitudes viticoles, le terroir témoigne d’une identité locale, d’une spécificité des conditions de productions et d’une originalité des lieux.

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.