Moderate wine consumption – part of a balanced diet or a health risk?

Viticulture is globally important for socioeconomic and environmental reasons. The EU is globally leading grape and wine production, and Spain is among the top grape and wine producers. As climate change affects viticulture, mitigation and adaptation are crucial for protecting grape production. In this research work, data on viticultural management practices such as soil cultivation, irrigation, energy, machinery, plant protection and the use of fertilizers from vineyards located in Logroño (La Rioja) have been obtained.

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.

Enzymatic browning[1] is an oxidation process that occurs in many foods that increases the brown colour[2]. This problem is especially harmful in the wine industry[3]. especially when the grapes are infected by grey rot since this fung release the oxidative enzyme laccase[4]. In the particular case of red wines, the presence of laccase implies the deterioration of the red colour and can even cause the precipitation of the coloring matter (oxidasic haze)[5].

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).

Light is responsible for adverse reactions in wine including the formation of unpleasant flavors, loss of vitamins or photodegradation of anthocyanins. Among them, the riboflavin degradation leads to the formation of undesirable volatile compounds, known as light-struck taste. These photo-chemical reactions could be avoided by simply using opaque packaging. However, most rosé wines are kept in transparent bottles due to different commercial reasons. Some agri-food waste extracts have been studied for their photoprotective action which turn to be highly correlated with phenolic content [1].