Valutazione dell’equilibrio vegeto-produttivo con metodiche di proximal sensing

A white wine model solution (12% v/v ethanol, 4 g/L tartaric acid, pH 3.2) was used to assess wine colloidal instability as well as the influence of several wine components on bentonite performance in protein removal.

For the first time, it was established that the timing of inoculation with LAB could significantly impact the concentration of many secondary metabolites leading to significant aromatic changes. From studied compounds, the most influenced were esters and diacetyl.

Developments in high-throughput sequencing (HTS) technologies allow us to obtain large amounts of microbial information from wine and must samples. Thus approaches, that are aimed at characterising the microbial diversity during fermentation, can be enhanced, or possibly even replaced, with HTS-based metabarcoding. To reduce experimental biases and increase data reproducibility, we compared 3 DNA extraction methods by evaluating differences in the fungal diversity with Riesling alcoholic fermentation samples at four different vineyards. The fungal diversity profiling was done using the genetic markers ITS2 and D2 using metabarcoding. The extraction methods compared consisted of a commercial kit, a recently published protocol that includes a DNA enhancer, and a protocol based on a buffer containing common inhibitor removal reagents. All methods were able to distinguish vineyard effects on the fungal diversity, but the results differed quantitatively.

Current climate change is increasing inter- and intra-annual variability in atmospheric conditions leading to grapevine phenological shifts as well altered grape ripening and composition at ripeness. This study aims to (i) detect weather anomalies within a long-term time series, (ii) model grape ripening revealing altered traits in time to target specific ripeness thresholds for four Vitis vinifera cultivars, and (iii) establish empirical relationships between ripening and weather anomalies with forecasting purposes. The Day of the Year (DOY) to reach specific grape ripeness targets was determined from time series of sugar concentrations, total acidity and pH collected from a private company in the period 2009-2021 in North-Eastern Italy. Non-linear models for the DOY to reach the specified ripeness thresholds were assessed for model efficiency (EF) and error of prediction (RMSE) in four grapevine cultivars (Merlot, Cabernet Sauvignon, Glera and Garganega). For each vintage and cultivar, advances or delays in DOY to target specified ripeness thresholds were assessed with respect to the average ripening dynamics. Long-term meteorological series monitored at ground weather station by means of hourly air temperature and rainfall data were analyzed. Climate statistics were obtained and for each time period (month, bimester, quarter and year) weather anomalies were identified. A linear regression analysis was performed to assess a possible correlation that may exist between ripening and weather anomalies. For each cultivar, ripeness advances or delays expressed in number of days to target the specific ripening threshold were assessed in relation to registered weather anomalies and the specific reference time period in the vintage. Precipitation of the warmest month and spring quarter are key to understanding the effect of climate change on sugar ripeness. Minimum temperatures of May-June bimester and maximum temperatures of spring quarter best correlate with altered total acidity evolution and pH increment during the ripening process, respectively.

The main objective is to unravel the yeast biosynthetic pathways for MEL, SER and HT by using the respective labelled amino acids precursors: 15N2-L tryptophan and 13C-tyrosine.
The alcoholic fermentation experiments are performed with two different commercial
S cereviseae yeasts using synthetic must with the addition of the labelled compounds and the bioactive compounds were followed during the fermentation process. Six biological replicates of the fermentations were considered. MEL, SER and HT were analysed by UHPLC coupled to High Resolution Mass Spectrometry (HRMS). Accurate mass determination allowed to unequivocally distinguishing labelled and unlabelled compounds.