Oenological compatibility of biocontrol yeasts applied to wine grapes 

The production of most red wines that are sold involves an alcoholic fermentation carried out by yeasts of the Saccharomyces genus, and a subsequent fermentation carried out by lactic bacteria of the Oenococus oeni species after the first one is fully completed. However, the traditional process can face complications, which can be more likely in grape juices with high levels of sugar and pH. Because of climate change, these situations are more frequent in the wine industry. The main hazards in those scenarios are halts or delays in the alcoholic fermentation or the growth of unwanted bacteria while the alcoholic fermentation is not done yet and the wine still has residual sugars.

Vines are exposed to environmental conditions that cause abiotic stress on the plants (drought, nutrient and mineral deficits, salinity, etc.). Polyamines are growth regulators involved in various physiological processes, as in abiotic plant stress responses. Stressful conditions can modify grape’s composition, and in this work, we have focused on studying the effect of abiotic stress on the composition of polyamines and amino acids in grapes. In addition, the effect of grape variety on these compounds has been studied.

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.

Since the mid-1980s, several surveys have been carried out in La Rioja to search for populations of the sylvestris grapevine subspecies (Vitis vinifera L. subsp. sylvestris Gmelin). The banks of the Ebro River and its tributaries (Alhama, Cidacos, Leza, Iregua, Najerilla, Oja and Tirón rivers), as well as the surrounding vegetation of their valleys have been covered. So far, all the populations found are alluvial, forming part of the riparian vegetation of the Najerilla (the first reported population in La Rioja [1]), Iregua, and the vicinity of Oja valleys.

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).