Climatic potential to produce grapes for wine-making in the tropical north region of Minas Gerais State, Brazil

Global warming is responsible for a lack of organic acid in grape berries, leading to wines with higher pH and lower titrable acidity. The chemical, microbiological and organoleptic equilibriums are impacted by this change of organic acid concentration. It is common practice to acidify the wine in order to prevent these imbalances that can lead to wine defects and early spoilage. Tartaric acid (TA) is most commonly used by winemaker for wine acidification purposes. Fumaric acid (FA), which is authorized by the OIV in its member states for the inhibition of malolactic fermentation, could also be used as a potential acidification candidate since it has a better acidifying power than tartaric acid.

Wine industry is looking forward for innovative, safe and eco-friendly antimicrobial products allowing the reduction of chemical treatments in the grape defense and the winemaking process that can affect negatively the quality of the product. Ozone has been tested in food industry giving good results in preventing fungi and bacteria growth on a wide spectrum of vegetables and fruits, due to its oxidant activity and ability to attack numerous cellular constituents. Ozone leaves no chemical residues on the food surface, decomposing itself rapidly in oxygen. Gaseous ozone has been already tested for table grapes storage and on wine grapes during withering.

AIM: Proteins in white wine can cause cloudiness or haze after bottling, which consumers may consider an indicator of poor quality. . As a consequence, winemakers often use bentonite, a clay-based material that binds protein, to remove proteins and achieve protein stabilisation. However, removing bentonite from wine after treatment can result in a 3-10% loss of wine (1)…

Aims: The aims of this study were to (1) detect alterations in the reflectance spectra of vines with fungal diseases, (2) map these alterations, and (3) determine the best wavelengths which may be used as early indicators of fungal diseases in vines.

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.