Mathematical models of the dynamics of fermentation of wine yeasts under the influence of vitamins

The perception of wine quality is determined by the assessment of multiple sensory stimuli, including aroma, taste, mouthfeel and visual aspects. With so many different parameters contributing to the overall perception of wine quality, it is important to consider the contribution of all metabolites in a wine when attempting to relate composition to quality.

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.

The market trend heads to food products with less chemical inputs, including in oenology. During the winemaking process, sulfites are commonly use to avoid microbiological contamination and stabilization of the wine thanks to its antimicrobial and antioxidant activities. Nevertheless, this use is not without consequences on human health and environment, leading for example to allergic reaction and pollution. A biological alternative to these sulfites has emerges: the bioprotection.

Context and purpose of the study. Globally, vineyard cultivation uses conventional methods to manage pests, diseases and increase yield.

The increasing vulnerability of food systems is a pressing challenge amplified by global interconnectedness.