Irrigation and terroir: two opposite concepts? Point of view of international experts and french consumers

In the context of global warming, water scarcity is becoming an increasing issue worldwide. However, the reference method to characterize vine water deficit is based on water potential measurement, which is a destructive and discontinuous method. The current climatic context emphasizes the need for more precise and more continuous vineyard water use measurements in order to optimize irrigation and vine water deficit monitoring.

Context and purpose of the study. Berry sunburn in vineyards is a recurring disorder that can cause severe yield loss. As sunburn observations are often associated with heat waves, a link to climate change is likely.

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.

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.

Context and purpose of the study ‐ Vine balance is a concept describing the relationship between carbon assimilation (usually estimated using a measure of vine vigour, e.g. pruning weight) and its utilisation for fruit production (usually estimated using harvest yield). Manipulating vine balance through leaf area or crop load adjustments affects the proportion of the vine’s total carbohydrate production required to mature the fruit. It is commonly considered that composition of the berry, and resulting wine, is strongly affected by vine balance.