Proposal of zonification and characterization of terroirs in the Yalde-Najerilla-Uruñuela vine growing area (DOC Rioja, Spain), based on the soil influence

s it is well known, myo and scyllo-inositol are two characteristic sugars of grape must and, for this reason, their quantification has been proposed to control the authenticity of the concentrated and rectificated grape must.

Stilbenes are natural bioactive polyphenols produced by grapevine. Recently, we have reviewed the na- tural presence of these compounds in wines [1]. This study showed that the resveratrol and its glycoside, the piceid, are the most abundant stilbenes in wines. Resveratrol is a well-known stilbene with a wide range of biological activities. Due to its specific structure, resveratrol can be oxidized in wines to form various derivatives including oligomers [2]. In this study, we investigate the resveratrol and piceid transformation in wines.

The integration of digital social networks (DSN) has profoundly transformed communication practices within the wine industry, reorganizing the dynamics of prescription and marketing.

The main goal of the current study is the development of a cost-effective and easy-to-use method suitable for use in the laboratory of commercial wineries to analyze wine aroma. Additionally, this study attempted to establish a prediction model for wine quality gradings based on their aroma, which could reveal the important aroma compounds that correlate well with different grades of perceived quality METHODS: Parameters of the SHS−GC−IMS instrument were first optimized to acquire the most desirable chromatographic resolution and signal intensities. Method stability was then exhibited by repeatability and reproducibility. Subsequently, compound identification was conducted. After method development, a total of 143 end-ferment wine samples of three different quality gradings from vintage 2020 were analyzed with the SHS−GC−IMS instrument. Six machine learning methods were employed to process the results and construct a quality prediction model. Techniques that aim to explain the model to extract useful insights were also applied.

Botrytis cinerea is a fungus that causes common infection in grapes and other fruits. In winemaking, its presence can be both considered desirable in the case of noble rot infection or undesirable when grey rot is developed. This fungus produces an extracellular enzyme known as laccase which is able to cause oxidation of phenolic compounds present in must and wine, causing most of the times a decrease in its quality and problems during the winemaking process [1]. Material and methods: Three B. cinerea strains (B0510, VA612 and RM344) were selected and grown in a liquid medium adapted from one previously described [2]. The enzyme was isolated by tangential ultrafiltration of the culture medium using a QuixStand system equipped with a 30 KDa filtration membrane.