Effects of yeast product addition and fermentation temperature on lipid composition and sensory of pinot noir wines

Yield is an agronomic trait that is critical to the sustained success and profitability of the wine industry. In the context of global warming, overall yield tends to decrease. Rootstock has been identified as a relevant lever for adaptation to changing environmental conditions. The aims of this study are; i) to finely identify the components of the yield influenced by rootstock; ii) to characterise the rootstock × scion interaction; iii) to understand the trade-off between vigour and yield.

Improving our knowledge on biotic and abiotic factors that influence the composition of the grapevine mycobiome is of great agricultural significance, due to potential effects on plant health, productivity, and wine characteristics. Among the various environmental factors affecting the morphological, physiological, biochemical and molecular attributes of grapevine, drought stress is one of the most severe, becoming increasingly an issue worldwide.

Sustainability is becoming an increasingly present challenge, whether due to an increase in the level of perception and demand from consumers and stakeholders or the rise of events linked to climate change, which directly impacts agricultural-based sectors such as the vine and wine industry.

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.

Historical terrace vineyards are simultaneously impressive documents of the human inclination to design, sites for the production of high quality wines and habitats for a rich variety of flora and fauna