Evaluation of phenology, agronomic and oenological quality in minority wine varieties in Madrid as a strategy for adaptation to climate change

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.

In the Bordeaux vineyards, press wine represents approximately 15% of the total volume of wine produced[1]. Valuing this large volume of wine is necessary from an economic point of view, but also because of their organoleptic contribution to the blend, and their contribution to the construction of wines for laying down. Therefore, this study was developed considering the lack of recent scientific knowledge on the composition of red press wines. The aim of this study is to establish an initial assessment of their chemical composition including aromatic compounds and a phenolic part.

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).

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 vinification by Carbonic maceration (CM) involves the process whereby the whole bunches are subjected to anaerobic conditions during several days. In this anaerobic condition, the grape endogenous enzymes begin an intracellular fermentation. This situation favors that whole grapes split open and release their juice into the tank, increasing the liquid phase that is fermented by yeasts [1]. Then, two types of wines are obtained; one from the free-run liquid in the tank (FCM) and other from the liquid after pressing the whole grape bunches (PCM). PCM wines are recognized as high quality young wines because their fruity and floral aromas[2] that although they are very intense at the end of the winemaking they gradually disappear during conservation.