Grape pomace, an active ingredient at the intestinal level: Updated evidence

Controlling the development of the bacterial population during the winemaking process is essential for obtaining correct wines[1]. Carbonic Maceration (CM) wines are recognised as high-quality young wines. However, due to its particularities, CM winemaking implies a higher risk of bacterial growth: lower SO2 levels, enrichment of the must in nutrients, oxygen trapped between the clusters… Therefore, wines produced by CM have slightly higher volatile acidity values than those produced by the destemming/crushing method[2].

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).

The application of remote and proximal sensing is a fast and efficient method to monitor grapevine vegetative and physiological parameters and is considered valuable to derive information on associated yield and quality traits in the vineyard. Further details can be obtained by the application of molecular analysis at the gene expression level aiming at elucidating how pathways controlling the formation of different grape quality traits are influenced by spatial variability. This work aims at evaluating intra-vineyard variability in grape composition at harvest and at comparing this with remotely sensed canopy vegetation data and molecular-based approaches.

In grapevine, phenology from bud break to berry maturation, depends on temperature and water availability. Increases in average temperatures accelerates initiation of bud break, exposing newly formed shoots to detrimental environmental stresses. It is therefore essential to identify genotypes that could delay phenology in order to adapt to the environment. The use of different rootstocks has been applied to change scion’s characteristics, to adapt and resist to abiotic and biotic stresses[1].

Wine, a sensitive and intricate agricultural product, is being affected by climate change, which accelerates grapevine phenological stages and alters grape composition and ripening. This influences the synthesis of key aroma compounds, shaping wine’s sensory attributes [1]. The complex aroma profile, resulting from compound interactions, presents a metabolomics challenge to identify these indicators and their environmental change responses, which is being addressed using diverse analytical techniques.