Digitalization and valorization of the genotypic and phenotypic information retained within the FEM grapevine germplasm

In a highly competitive worldwide market, a current challenge for the beverage sector is to diversify the range of products and to offer wines and spirits with typicity and character.

During alcoholic fermentation, wine yeasts generate a large variety of volatile metabolites, including acetate esters, ethyl fatty acid esters, higher alcohols, volatile fatty acids and volatile sulfur compounds that contribute to the aroma profile of wine. These molecules, refered as fermentative aromas, are the most abundant volatile compounds synthetized by yeasts and the metabolic pathways involved in their formation have been well characterized. Furthermore, other molecules with a major organoleptic impact may be produced during wine fermentation including terpene derivatives. However, little information is available on the contribution of yeasts to the formation of these molecules, in particular on their ability to synthethise de novo the terpens derivatives or to produce hydrolytic enzymes involved in the release of varietal precursors.

Drought is considered to be the predominant factor both for determining the geographic distribution of vegetation and for restricting crop yields in agriculture. Furthermore

In this video recording of the IVES science meeting 2025, Gonzaga Santesteban (Public University of Navarra, Pamplona, Spain) speaks about rootstocks, climate change and meta-analysis. This presentation is based on an original article accessible for free on OENO One.

The assessment of wine authenticity is of great importance for consumers, producers and regulatory agencies to guarantee the geographical origin of wines and grape variety as well. Since mid-infrared (MIR) spectroscopy with chemometrics represent a suitable tool to ascertain the wine composition, including features associated with the polyphenolic compounds, the aim of this study was to generate MIR spectra of red wines to be exploited for classification of red wines based on the relationship between grape variety and wine composition. Several multivariate data analyses were used, including Principal Component Analysis (PCA), Discriminant Analysis (DA), Support Vector Machine (SVM), and Soft Intelligent Modelling of Class Analogy (SIMCA).

A major problem for winemakers is the formation of proteinaceous haze after bottling. Although the exact mechanisms remain unclear, this haze is formed by unfolding and agglomeration of grape proteins, being additionally influenced by numerous further factors.