Effects of future climate change on grape quality: a case study for the Aglianico grape in Campania region, Italy

The historic Tokaj Wine Region in northeast Hungary, a UNESCO World Heritage region since 2002, encompasses 5,500 ha vineyards. Produced from “noble rot” grapes, Tokaji Aszú is known as one of the oldest botrytized wines all over the world. Special microclimatic conditions (due to Bodrog and Tisza rivers, Indian summer), soil conditions (clay, loess on volcanic bedrock) and grape

The environmental biodiversity is important to guarantee essential services to the living communities, its richness is a symptom of a minor disturbance and improves he environment biological quality.

Irrigation initiation timing is a critical annual management decision that has cascading effects on grapevine productivity and wine quality.

If one considers as “physical or sensory attributes” of a wine its concentrations of alcohol and of other substances, it can be stated that another class of attributes exists

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.