Multisensory experiential wine marketing

Aims: Most consumer research about terroir has focused on wine, particularly with French or other European wine drinkers, rather than those in the Anglo-Saxon world. In Europe, whilst there is no agreement amongst consumers as to what terroir actually is, there is a general recognition of the word and an acceptance that it represents something important

Wine is one of the most representative components of Mediterranean diet. Moderate wine intake together with food, has been positively correlated with reduced risk of many chronic diseases. This beneficial effect seems to be ascribed to elevated polyphenolic content of wine [1]. Traditional approaches for the identification of wine biomarkers consumption include targeted metabolomics that focuses on the quantification of well-defined metabolites, losing a valuable information about a massive number of compounds. On the other hand, untargeted metabolomics can disclose a large quantity of signals corresponding to potential biomarkers in a single analysis with high sensitivity and resolution.

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.

Organic wines, although resulting from a production method based on the non-use of synthetic phytosanitary products, are not always free of residues. These residues can result from cross-contamination during production in the field or in the cellar, during the production or aging of the wine. In recent years, with the improvement of analysis techniques, a molecule, phosphonic acid, the main metabolite of fosetyl-al (banned in organic farming) is regularly quantified in organic wines and its origin is not clearly identified.

Yield estimation is very important for the wine industry since provides useful information for vineyard and winery management. The early yield estimation of the grapevine provides information to winegrowers in making management decisions to achieve a better quantity and quality of grapes. In general, yield forecasts are based on destructive sampling of bunches and manual counting of berries per bunch and bunches per vine.