Control of bacterial growth in carbonic maceration winemaking through yeast inoculation

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).

Consumption of wine/alcoholic beverages remains a topic of great uncertainty and controversy worldwide. The term “no safe level” dominates the media communication and policy ever since population studies in 2018 [1,2] were published, which denied the existence of a J-curve and suggested that ANY consumption of an alcoholic beverage is harmful to health. The scientific evidence accumulated during the past decades about the health benefits of moderate wine consumption, were questioned and drinking guidelines considered to be too loose.

The Agenda 2030 of the EU sets out the main guidelines for transitioning towards a resilient, green and safe economy. To this regard, the wine sector is experiencing an ecological transition in different ways such as increasing the production of ecological crops, or promoting the production of wines under more environmental-friendly and healthier (i.e., lower levels of SO2) products. These alternatives to conventional production are a smaller proportion of wines, in constant growth and demand, and follow alternative and minority practices, which range from sustainable to deeply philosophical thoughts. Among these methods there are organic, biodynamic and, more recently, natural wines.

The European wine industry is facing multiple challenges derived from climate change and the pressure of different fungal diseases that are compromising the production of traditional varieties. A sustainable alternative maybe the adoption of resistant varieties.
In this study, we have evaluated the enological potential of 9 resistant varieties (5 white and 4 red varieties) in La Rioja. Microvinifications were carried out with three biological replications. Oenological parameters were very diverse with acid content varying from 2.6 g/L to 6.6 g/L.

Wine contains secondary metabolites derived from aromatic amino acids (AADC), which can determine quality, stability and bioactivity. Several yeast species, as well as some lactic acid bacteria (LAB), can contribute in the production of these aromatic compounds. Winemaking should be studied as a series of microbial interactions, that work as an interconnected network, and can determine the metabolic and analytical profiles of wine. The aim of this work was to select microorganisms (yeast and LAB) based on their potential to produce AADC compounds, such as tyrosol and hydroxytyrosol, and design a microbial consortium that could increase the production of these AADC compounds in wines.