The landscape of wine as an expression of cultural transversality

Many parameters affect the organoleptic characteristics of wine: internal parameters like the chemical composition or polyphenol content and external as for example storage conditions or the type of obturator. The aim of this study was to characterize sensorally the impacts of several type of obturator on a white wine: Chasselas. To determine the organoleptic characteristics of this wine, a quantitative descriptive analysis could be used. But rapid sensory methods were preferred in this project. Indeed these methods are an appropriate alternative to conventional descriptive methods for quickly assessing sensory product discrimination.

In the French AOCs, the production area of ​​the raw material can be subject to plot delimitation based on criteria of physical environment and use. On the other hand, many environmental zonings are developing and the AOCs are called upon include provisions relating to these concerns. Hedges, through their effects on local changes in the regional climate and on functional biodiversity, can impact the functioning of vines and orchards. It is for this reason that their consideration as a delimitation criterion is envisaged.

Modern grapevine breeding programs have overcome many challenges using genomic selection, which has allowed breeders to make targeted selections at earlier stages in the breeding process. However, the cost of genetic testing may present a burden for some programs, and markers often struggle to accurately predict quantitative traits. Recent advances in high throughput, high-dimensional data have provoked investigation into the use of high-dimensional phenomics as a low-cost addition to the grape breeder’s toolkit that may offer advantages in predicting quantitative traits. High-dimensional secondary trait (HDST) data has been employed in annual crops for prediction of agriculturally important traits such as yield.

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.

Remote sensing applications in viticulture have been a research theme now for nearly two decades, becoming a valuable tool for vineyard management. Metrics produced using remotely sensed images of vineyards have yielded relationships with grape quality and yield that can help optimise vineyard performance