Neural networks and ft-ir spectroscopy for the discrimination of single varietal and blended wines. A preliminary study.

The sulphur dioxide (SO2) is the most widely used additive in the wine industry because of its preservative action. However, in recent years the number of wineries that produce wines without SO2 has increased significantly because its allergenic character.

Climate influence on grapevine physiology is prevalent and this influence is only expected to increase with climate change. Although governed by a general determinism, climate influence on grapevine physiology may present variations according to the terroir. In addition, these site-specific differences are likely to be enhanced when climate influence is studied using farm data. Indeed, farm data integrate additional sources of variation such as a varying representativity of the conditions actually experienced in the field. Nevertheless, there is a real challenge in valuing farm data to enable grape growers to understand their own terroir and consequently adapt their practices to the local conditions. In such a context, this article proposes a framework to site-specifically study climate influence on grapevine physiology using farm data. It focuses on improving the analysis of time series of weather data. The analytical framework includes the synchronization of time series using site-specific thermal indices computed with an original method called Extended Growing Degree Days (eGDD). Synchronized time series are then analyzed using a Bayesian functional Linear regression with Sparse Steps functions (BLiSS) in order to detect site-specific periods of strong climate influence on yield development. The article focuses on temperature and rain influence on grape yield development as a case study. It uses data from three commercial vineyards respectively situated in the Bordeaux region (France), California (USA) and Israel. For all vineyards, common periods of climate influence on yield development were found. They corresponded to already known periods, for example around veraison of the year before harvest. However, the periods differed in their precise timing (e.g. before, around or after veraison), duration and correlation direction with yield. Other periods were found for only one or two vineyards and/or were not referred to in literature, for example during the winter before harvest.

l lavoro presenta l’evoluzione dei contenuti di arsenico nelle uve durante lo sviluppo e la maturazione, e la sua distribuzione nell’acino; verifica inoltre la relazione tra i contenuti di As nelle uve

Wine quality is influenced by grape maturity, typically monitored by measuring sugar content and acidity.

In mid to late ripening, sugar and potassium (K+) accumulation into the berry slows and is eventually completed1. K+ is the most abundant cation in the berry, undertaking important physiological roles.