Fast, and full microbiological wine analysis using triple cellular staining.

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.

Increasingly warm and dry climate conditions are challenging the viticulture and winemaking sector. Digital technologies and crop modelling bear the promise to provide practical answers to those challenges. As viticultural activities strongly depend on harvest date, its early prediction is particularly important, since the success of winemaking practices largely depends upon this key event, which should be based on an accurate and advanced plan of the annual cycle. Herein, we demonstrate the creation of modelling tools to assess grape ripeness, through sugar concentration monitoring. The study area, the Portuguese Côa valley wine region, represents an important terroir in the “Douro Superior” subregion. Two varieties (cv. Touriga Nacional and Touriga Franca) grown in five locations across the Côa Region were considered. Sugar accumulation in grapes, with concentrations between 170 and 230 g l-1, was used from 2014 to 2020 as an indicator of technological maturity conditioned by meteorological factors. The climatic time series were retrieved from the EU Copernicus Service, while sugar data were collected by a non-profit organization, ADVID, and by Sogrape, a leading wine company. The software for calibrating and validating this model framework was the Phenology Modeling Platform (PMP), version 5.5, using Sigmoid and growing degree-day (GDD) models for predictions. The performance was assessed through two metrics: Roots Mean Square Error (RMSE) and efficiency coefficient (EFF), while validation was undertaken using leave-one-out cross-validation. Our findings demonstrate that sugar content is mainly dependent on temperature and air humidity. The models achieved a performance of 0.65

Climate change strongly affects the wine-growing sector which increasingly requires in situ adaptation strategies aimed at preserving the sustainability of production. Investigating microclimate becomes crucial in comprehending environmental pressures on plants. The microclimatic investigation conducted in the Orvieto PDO (central Italy) allowed us to highlight the climatic dynamics occurring in the last 25 years and the frequency and intensity of abiotic stresses. Two management strategies for the canopy were identified: early defoliation (ELR) and foliar application of Basalt Flour ® (FB) compared to the ordinary management (C) of the company (bud selection and topping). The effects on plant vigour indices (LAI), resource allocation in terms of carbon stored in the above-ground organs of the vine, and the microclimate of the canopy and the berry were evaluated. In particular, microclimate was evaluated through a network of sensors connected wirelessly (Wireless Sensor Network), dedicated to collecting information on temperature and humidity in the canopy and clusters.

Wines from different regions or AVAs have been found to have sensory differences, as these areas are typically located quite far apart and have dramatically different climates, soils and other terroir factors.