High-throughput sequencing analysis based on nematode indices revealed healthier soils of organic vineyards 

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 wine closure industry is mainly divided into three categories: screw caps, synthetic closures, and cork-based closures. Among this latter, microagglomerated cork stoppers treated with supercritical CO2 are now widely used, especially to avoid cork taint contaminations[1]. They are designed with cork granules obtained from cork offcuts of the punching process during the natural cork stoppers production. A previous study[2] showed that these stoppers released fewer polyphenols in 12 % (v/v) hydroalcoholic solution than natural cork stoppers.

Sparkling wine (SW) production entails a two-steps process where grape must undergoes a primary fermentation to produce a base wine (BW) which is then refermented to become a SW. This process allows for the development of a new physicochemical profile characterized by the presence of foam and a different organoleptic profile.

Targeted analytical methods can overlook compounds that are a priori unknown to play a role in the mouthfeel sensations. This limitation can be overcome with the information provided by untargeted metabolomic analysis using UPLC‐QTOF-MS. To this end, an untargeted metabolomic approach applied to 42 red wines has allowed development of a model with predictive capacity by cross-validation for the “dry”, “oily” and “unctuous” sensations perceived by a sensory panel. The optimal PLS model for “dry” retained compounds with positive regression coefficients (≥ 0.17) including a trimer procyanidin, a peptide, and four anthocyanins.

Performing accurate vineyard yield estimation is of upmost importance as it provides important benefits to the whole vine and wine industry. Recently, image-analysis approaches have been explored to address this issue however this approach has as main challenge the bunch occlusion, mostly by vegetation but also by neighboring bunches. The present work aims at assessing the magnitude of bunch occlusion by neighboring bunches and to evaluate its dependency on a selection of vegetative and reproductive vine parameters assessed at fruiting zone. Forty vine segments (1 m) of two vineyard plots of the white cultivars ‘Alvarinho’ and ‘Arinto’ were assessed for vegetative and reproductive features at fruiting zone and imaged with a 2D camera.