Cumulative effect of deficit irrigation and salinity on vine responses

Melatonin is a bioactive compound with antioxidant properties, that has been found in many fermented beverages, such as beer and wine [1]. Indeed, it has been shown that yeast can synthesize melatonin during alcoholic fermentation, although its role inside the cell, as well as the metabolic pathway involved in its synthesis, is still unclear [1]. Recent studies showed that during fermentation, melatonin interacts with different proteins of the glycolytic pathway in both Saccharomyces and non-Saccharomyces yeast, for instance glyceraldehyde 3-phosphate dehydrogenase, pyruvate kinase or enolase [2].

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).

The use of barrels is a practice that improves the quality of wines. The porous structure of wood favors the accumulation of microorganisms that can deteriorate the quality of wines so that barrel cleaning and sanitizing treatments are essential. The burning of sulphur discs has been the most common practice in winemaking because ots biocide effect. Nevertheless, its effectiveness is still insufficient and it is harmful for human health.

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.

Soil is important in the carbon cycle and the dynamics of greenhouse gases (CO2, CH4 and N2O). Key soil characteristics, such as organic matter content, texture, structure, pH and microbial activity, play a determining role in GHG emissions[1]. The objective of the study is to delimit different types of soil, with different soil management and to be able to verify the differences in CO2, CH4 and N2O emissions. The study was carried out in a vineyard of Bodegas Campo Viejo in Logroño (La Rioja), whose plant material is Vitis vinifera L. cv. Tempranillo.