Phenolic composition of Cabernet Sauvignon wines from Argentina, Portugal and Spain

The vineyard has experienced a general increase in yields mainly due to the elevated use of technology which caused a quality loss of grapes in more than one case. A large percentage of the Spanish vineyard is covered by a Denomination of Origin which limits the productive level of the vineyards as one of its regulations. The maximum production limit is a variable characteristic of each vineyard and is not usually regulated by agronomic criteria, and this explains the fact that each vineyard can reach high quality with a totally different yield from that set by the Denomination of Origin.

The context of climate crisis leads to the acceleration of technological ripening of grapes, with unsuitable loss of acidity, so various vineyard management alternatives are being considered to delay the grape ripening. The delay of the vegetative cycle towards a period of milder temperatures affects ripening, but vine behavior can vary according to the area, conduction, watering, variety, etc. A work is proposed to know the response to the green pruning of shoots, executed in fruit set and in pea size, in cv. Verdejo.

Yeast species S. cerevisiae, S. uvarum, S. kudriavzevii and their hybrids present clear metabolic differences, even when we compared S. cerevisiae wine versus wild strain. These species and hybrids produced significantly higher amounts of glycerol, organic acids, 2,3-butanediol, and 2-phenyl ethanol and a reduction of the ethanol yield, properties very interesting in the sector to deal with climate change effects. To understand the existing differences, we have used several omics techniques to analyze the dynamics of the (intra- and extracellular) metabolomes and/or transcriptomes of representative strains of S. cerevisiae, S. uvarum, S. kudriavzevii, and hybrids.

The utilization of non-Saccharomyces yeasts in the wine industry has increased significantly in recent years. Alternative species need commonly be employed in combination with Saccharomyces cerevisiae to avoid stuck fermentation, or microbial spoilage. The employment of more than one yeast starter can lead to interactions between different species with an impact on the outcome of wine fermentation. Previous studies[1] demonstrated that S. cerevisiae elicits transcriptional responses with both shared and species-specific features in co-culture with other yeast species.

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).