How artificial intelligence (AI) is helping winegrowers to deal with adversity from climate change

The volatile composition of grapes (free and bound forms) contributes greatly to the varietal aroma and quality of wines. Several agronomical parameters affect grapes composition and wine quality: maturity level at harvest, water status, and the intensity of sun exposure.

The well-known antifungal and antibiotic molecule, eugenol, is widely spread in various plants including clove, basil and bay. It is also abundant in the hybrid grapevine cultivar (cv) Baco blanc (Vitis vi-nifera x Vitis riparia x Vitis labrusca), created by François Baco (19th century) in the Armagnac region. This study confirmed this cv as highly resistant to Botrytis cinerea by comparing fruit rot incidence and severity with two Vitis vinifera cultivars: Folle Blanche and Ugni Blanc. We have demonstrated the efficiency of eugenol in vitro, by further investigating the effect of small concentrations of eugenol, 3 to 4 ppm (corresponding to IC10), on B. cinerea. By comparing the two major modes of action (direct or volatile antibiosis), the vapour inhibiting effect of eugenol was more powerful. In the skin of Baco blanc berry, the total eugenol concentration reached a maximum at veraison, i.e. 1118 to 1478 μg/kg.

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.

A wide range of olfactory descriptors ranging from fresh and jammy fruit notes to cooked and oxidized fruit notes could describe the fruity aroma of red wines [1]. The fruity character of a wine is mainly related to the grape variety selected, to the terroir and the vinification process applied for its conception. In white wines, some volatile compounds confer directly their aroma to the wine while the question of “key” compound is more complex in red wines. According to many studies performed over the past decades, some fruity ethyl esters are directly involved in the fruity perception of red wines while others, present at subthreshold concentrations, participate indirectly to the fruity expression via perceptive interactions [2].

Riesling represents the most widely cultivated grape variety in Germany and is therefore of particular economic interest. During recent years an increase in the petrol-note as well as in undesirable bitter and adstringent notes has been reported. These changes are most likely linked to increasing temperature and sunlight exposure of grapes due to climate changes.
The “petrol note” is caused by the formation of the C13-norisoprenoid 1,1,6-trimethyl-1,2-dihydronaphthalin (TDN), which originates from acid-labile precursors formed by the carotenoid degradation in the grape.