The tolerance of grapevine rootstocks to water deficit is related to root morphology and xylem anatomy traits 

The study conducted various fermentations of different grape juices using various strains of Lachancea thermotolerans and one strain of Saccharomyces cerevisiae. Because of the new conditions caused by climate change, wine acidity must be influenced as well as the volatile profile. Non-Saccharomyces yeasts such as L. thermotolerans are real options to mitigate the impact of climate change in wine production.

The presence of undesirable compounds in wines, such as OTA, biogenic amines and pesticides residues, affects wine quality and can cause health problems for the consumer. The main tool that a winemaker has to reduce their content in the wine is fining. However, some of the fining agents commonly used in the winery can cause allergies or even increase the protein content in the wine, increasing the turbidity. To avoid these problems, the use of plant fibers may be an alternative, such as those from grape pomace[1] or other plant origins.

Grape and wine phenolic compounds have been shown to be highly related to both wine quality (color, flavor, and taste) and health-promoting properties (antioxidant and cardioprotective, among others). The aim of this work was to evaluate and compare the phenolic contents of Cabernet Sauvignon wines from different geographical areas and climatic conditions, namely from Argentina, Portugal and Spain vintage 2022. In addition, the phenolic profiles of the Portuguese wines from three vintages (2020, 2021, 2022) was compared.

Performing accurate vineyard yield estimation is of upmost importance as it provides important benefits to the whole vine and wine industry. Recently, image-analysis approaches have been explored to address this issue however this approach has as main challenge the bunch occlusion, mostly by vegetation but also by neighboring bunches. The present work aims at assessing the magnitude of bunch occlusion by neighboring bunches and to evaluate its dependency on a selection of vegetative and reproductive vine parameters assessed at fruiting zone. Forty vine segments (1 m) of two vineyard plots of the white cultivars ‘Alvarinho’ and ‘Arinto’ were assessed for vegetative and reproductive features at fruiting zone and imaged with a 2D camera.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).