Rootstock differences in soil-water uptake during drying-wetting cycles imaged with 3d electrical resistivity tomography

Introducing natural ingredients using green chemistry practices is a major challenge in cosmetics industry to follow the market trend. Among the plants of cosmetic interest, vine products show a remarkable diversity of natural substances with high potential for the cosmetic and dermatological sectors. To date, research focuses on well-known compounds like E-resveratrol and E-ε-viniferin,

Soil is a reservoir of microorganisms playing important roles in biogeochemical cycles and interacting with plants whether in the rhizosphere or in the root endosphere. Through rhizodeposition, plants regulate their associated microbiome composition depending on the environment and plant factors, including genotypes. Since the phylloxera crisis, Vitis vinifera cultivars are mainly grafted onto American Vitis hybrids. Rootstocks play a pivotal role in the grapevine development, as the interface between the scion and the soil.

The production of sparkling wines requires sugars for the second fermentation. The Solid Rectified Concentrated Must (SRCM) is a water free crystalline form of grape sugar, offering a purer, more stable, and easier-to-use alternative to the liquid Rectified Concentrated Must (RCM).

Characterization of phenolics and VOCs in wines obtained from Malbec vineyards of the Uco Valley submitted to high-altitude solar UV-B and water restriction

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.