Anthocyanin content and composition of Merlot grapes under temperature and late pruning conditions 

The impact of climate change is noticeable in the present weather, making water scarcity the most immediate mediator reducing the performance and viability of crops, including grapevine (Vitis vinifera L.). The present study developed a system (hardware, firmware, and software) for the determination of plant water use through changes in weight through a period. The aim is to measure the differences in grapevine water consumption in response to climate change (+4oC and 700 ppm) under controlled conditions. The results reveal a correlation between daily plant consumption rates and reference evapotranspiration (ETo).

The barrel-making process is widely recognized as a crucial practice that affects the composition of barrel-aged wine. After the drying process, the staves are considered ready for barrel assembly, which includes the processes of bending and toasting the barrel structure. Toasting is considered one of the most critical stages in determining the physical and chemical composition of the staves, which can influence the chemical and sensory composition of the wine aged in barrels made from them [1].

‘Tempranillo Tinto’ is a black-berried Iberian cultivar that originated from a hybridization between cvs. ‘Benedicto’ and ‘Albillo Mayor’ [1]. Today, it is the third most widely grown wine grape cultivar worldwide with more than 200,000 hectares of vineyards mostly distributed along the Iberian Peninsula, where it is also known as ‘Cencibel’, ‘Tinta de Toro’, ‘Tinta Roriz’, and ‘Aragonez’, among other synonyms. Here, we quantified the intra-varietal genomic diversity in this cultivar through the study of 35 clones or ancient vines from seven different Iberian wine-making regions. A comparative analysis after Illumina whole-genome sequencing revealed the presence of 1,120 clonal single nucleotide variants (SNVs).

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).

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.