Plastic debris at vines: carriers of pollutants in the environment?

Volatile phenols from wildfire smoke are absorbed by wine grapes, resulting in undesirable smoky and ashy sensory attributes in the affected wine.[1] Unfortunately the severity of wildfires is increasing, particularly when grapes are ripening on the vine. The unwanted flavors of the wine prompted a need for solutions to prevent the uptake of smoke compounds into wine grapes. Films using cellulose nanofibers as the coating forming matrix were developed as an innovative means to prevent smoke phenols from entering Pinot noir grapes. Different film formulations were tested by incorporating low methoxy pectin or chitosan.

Light is a fundamental part at sales points which influences in the conservation of wines, particularly in those that are sold in transparent glass bottles such as rosé wines and increasingly white wines. The photochemical effect known as “light-struck taste” can cause changes in the aromatic characteristics of the wine. This “light-struck taste” is due to reactions triggered by the photochemical sensitivity of riboflavin (RBF).

Two of the most harmful microbial metabolites for human health that can be present in wines and either fermented or raw foods are biogenic amines (BA) and ochratoxine A (OTA). Winemakers are aware of the need to avoid their presence in wine by using different strategies, one of them is the use of enzymes. Some recombinant laccases have been characterized and revealed as potential tools to degrade these toxic compounds in wine[1], specifically biogenic amines[2].

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 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).