Terroir and precision viticulture: are they compatible?

Vineyard soil surveys can be costly and time consuming. The Soils Information System (SIS) provides a set of tools to do a quick evaluation of soil physical properties in the vineyard. First, a system equipped with GPS and EM38 equipment, provides a very precise DEM and a soil electrical conductivity map. Specific sampling points are located for a tractor-mounted geotechnical probe to make soil physical measurements.

Amino acids are crucial nitrogen sources in yeast metabolism, influencing both biomass production and fermentation rate. The breakdown byproducts of amino acids contribute to the aroma of the wine and wine’s health benefit compounds. This study focused on the yeast’s extracellular metabolic profile of tryptophan, tyrosine, and phenylalanine belonging to the group of aromatic amino acids in experimental Maraština wines. Alcoholic fermentations were conducted on sterile grape Maraština must using seven autochthonous non-Saccharomyces yeasts in sequential fermentation with commercial Saccharomyces cerevisiae.

Climate change is causing a gap between the technological and phenolic maturity of grapes, resulting in wines with high alcohol content and low polyphenol concentration. Another phenomenon associated with high temperatures and whose effect is more pronounced if the harvest is delayed is the decrease in the acidity of the grapes, mainly in malic acid, and an increase in pH caused by the accumulation of potassium derived from the increase in temperature. Therefore, climate change and the effects it causes on the vine leads to unbalanced wines, with high alcohol content and lack of color, with green tannins, astringency and excessively low acidity if not corrected.

The notion of terroir covers multiple components, from geology, pedology, geomorphology and climatology (Doledec, 1995), to aspects that are less well identified but which also intervene in the “typicality” of wines. This justifies the “zoning” approach (Moncomble and Panigaï, 1990) to define homogeneous areas, under the same agro-viticultural management and also identified at the product level (Morlat and Asselin, 1992).

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.