Molecularly imprinted polymers: an innovative strategy for harvesting polyphenoles from grape seed extracts

Cabernet Sauvignon is one of the most cultivated grape varieties worldwide being grown in different environmental conditions due to its excellent adaptability. Volatile compounds deeply contribute to the sensory properties of wines therefore to wine quality. The aim of this work was to compare the aroma profile of Cabernet Sauvignon wines from different geographical areas and climatic conditions, namely from Argentina, Portugal and Spain, from the vintage 2022. In addition, the volatile composition of the Cabernet Sauvignon Portuguese wines from three vintages was evaluated.

Vines require proper light levels, temperature, and water availability, and climate change is modifying these factors, hampering yield and quality. Despite the large diversity of rootstocks, varieties, and clones, we still lack knowledge of their combined effects and potential role in a warmer and dryer future. Therefore, we aim to characterize some of the existing diversity of rootstocks and genotypes and their interaction at the eco-physiological level, combining stomatal conductance (gs) and chlorophyll a fluorescence analysis.

Deleterious mutations that severely reduce population fitness are rapidly removed from the gene pool by purifying selection. However, evolutionary drivers such as genetic drift brought about by demographic bottlenecks may comprise its efficacy by allowing deleterious mutations to accumulate, thereby limiting the adaptive potential of populations. Moreover, positive selection can hitchhike mildly deleterious mutations due to linkage caused by lack of recombination. Similarly, in the context of species domestication, artificial selection mimics these evolutionary processes, which can have undesirable consequences for production and resilience. In this study, we evaluated the extent of the accumulation of deleterious mutations and the magnitude of their effects (also known as genetic load) at the whole-genome scale for ca.

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).