Cover crops competition for water in vineyards: case studies in mediterranean terroirs

Australia is the seventh largest producer of wine and crushed 1.42 million tonnes of wine grapes in the 2001 vintage.

The yeast residue left over after wine-making, known as wine yeast lees, is a source of various compounds that are of interest for wine and food industry. In winemaking, yeast-derived glycocompounds and proteins represent an example of circular economy approach since they have been proven to reduce the need for bentonite and animal-based fining agents. This leads to a reduced environmental impact in the stabilization and fining processes in winemaking. (de Iseppi et al., 2020, 2021).

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.

In this work, results about the composition in polyphenols and polyamines in important wine-grape cultivars from the Emilia-Romagna region are presented. Spectrophotometric and HPLC analyses suggest that especially coloured berries are particularly rich of antioxidant species (stilbenes and catechins). Potential allergenic capability of biogenic amines was also characterized.

Cabernet Sauvignon is the top red wine cultivar in CA, however, the hot climate in Fresno is not ideal for Cabernet Sauvignon, particularly for berry color development. Fruit-zone leaf removal and irrigation were studied previously to have the significant effect on grape yield performance and berry quality. But the timing of leaf removal and the timing of irrigation are still inconclusive. Also, mechanical fruit-zone leaf removal is relatively new in CA. Our study aims to identify the interactive effect of mechanical fruit-zone leaf removal and irrigation on Cabernet Sauvignon’s yield performance and fruit quality and find the ideal timing of leaf removal and irrigation to maximize the berry color while maintaining the sustainable yield level.