The environmental footprint of selected vineyard management practices: A case study from Logroño (La Rioja) Spain

Brandy de Jerez (BJ) is a spirit drink made exclusively from spirits and wine distillates and is characterized by the use of casks for aging that previously contained Sherries. The quality and sensory complexity of BJ depend on the raw materials and some factors: grape variety, conditions during processing the wine and its distillation, as well as the aging in the cask. Therefore, the original compounds of the grapes from which it comes are of great interest being in most cases the Airén variety. Their relationship with the quality of the musts and the wines obtained from them has been studied (1) and varies each year of harvest depending on the weather conditions (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).

During red wine fermentation, the extraction of phenolics compounds and sufficient oxygen provision are critical for wine quality [1,2]. In this trial, we aimed at evaluating the kinetics of phenolic extraction and dissolved oxygen during red wine fermentations using the airmixing system. Twenty lots of red grape musts were fermented in 300.000 L tanks, equipped with airmixing, using two injection regimes (i.e., high and low intensity, and high and low daily frequency). An oxygen analyzer was introduced into the tanks in order to record the concentration of dissolved oxygen over time.

Recently, there has been a shift toward sustainable wine production, according to EU policy (F2F and Green Deal), to reduce pesticide usage, improve workplace health and safety, and prevent the impacts of climate change. These trends have gained the interest of consumers and winemakers. The cultivation of disease resistant hybrid grape cultivars (DRHGC), known as ‘PIWI’ grapes can help with these objectives [1]. This study aimed to profile white and red wines produced from DRHGC in South Tyrol (Italy). Wines produced from DRHGCs were compared with conventional wines produced by the same wineries. The measured parameters were residual sugars, organic acids, alcohol content, pigments and other phenolics by LC-QqQ/MS, colorimetric indexes (CIELab); and volatile profiles (HS-SPME-GCxGC-ToF/MS [2]).

The application of remote and proximal sensing is a fast and efficient method to monitor grapevine vegetative and physiological parameters and is considered valuable to derive information on associated yield and quality traits in the vineyard. Further details can be obtained by the application of molecular analysis at the gene expression level aiming at elucidating how pathways controlling the formation of different grape quality traits are influenced by spatial variability. This work aims at evaluating intra-vineyard variability in grape composition at harvest and at comparing this with remotely sensed canopy vegetation data and molecular-based approaches.