Integration of wine cultivation history for characterizing the terroirs of Côte d’Or (Burgundy, France)

Addressing the opportunities and challenges of genomics methods in grapevine (Vitis vinifera L.) requires the development of a comprehensive and accurate reference genome and annotation. We aimed to create a new gene annotation for the PN40024 grapevine reference genome by integrating the highly accurate and complete T2T assembly and the manually curated PN40024.v4 annotation. Here, we present a novel workflow to enhance the annotation of the T2T genome by incorporating past community input found in PN40024.v4. The pipeline’s containerization will improve the workflow’s reproducibility and flexibility, facilitating its inclusion as a shared workflow on the Grapedia portal, the grapevine genomics encyclopedia.

The analysis of polyfunctional thiols in wine is challenging due to their low abundance and instability within a complex matrix. However, volatile thiols are highly aroma-active, making their accurate quantification in wine at low concentrations crucial [1].

L’evoluzione del settore viti-enologico, supportato dalla ricerca ci propone sempre più frequentemente vini unici e inconfondibili. Il merito di ciò è da ricercare nel rapporto vitigno-territorio e dalla

The project VINIoT pursues the creation of a new technological vineyard monitoring service, which will allow companies in the wine sector in the SUDOE space to monitor plantations in real time and remotely at various levels of precision. The system is based on spectral images and an IoT architecture that allows assessing parameters of interest viticulture and the collection of data at a precise scale (level of grape, plant, plot or vineyard) will be designed. In France, three subjects were specifically developed: evaluation of maturity, of water stress, and detection of flavescence dorée. For the evaluation of maturity, it has been decided first to work at the berry scale in the laboratory, then at the bunch scale and finally in the vineyard. The acquisition of the spectral hyperstal image as well as the reference analyzes to measure the maturity, were carried out in the laboratory after harvesting the berries in a maturity monitoring context. This work focuses on a case study to predict sugar content of three different grape varieties: Syrah, Fer Servadou and Mauzac. A robust method called Roboost-PLSR, developed in the framework of this work (Courand et al., 2022), to improve prediction model performance was applied on spectra after the acquirement of hyperspectral images. Regarding the evaluation of water stress, to work with a significant variability in terms of water status, it has been worked first with potted plants under 2 different water regimes. The facilities have allowed the supervision of irrigation and micro-climatic conditions. The regression models on agronomic variables (stomatal conductance, water potential, …) are studied. To detect flavescence dorée, the experimental plan has consisted of work at leaf scale in the laboratory first, and then in the field. To detect the disease from hyper-spectral imaging, a combination of multivariate curve resolution-alternating least squares (MCR-ALS) and factorial discriminant analysis (FDA) was proposed. This strategy proved the potential towards the discrimination of healthy and infected leaves by flavescence dorée based on the use of hyperspectral images (Mas Garcia et al., 2021).

Aim: Temperature corresponds to one of the main terroir factors influencing grapevine physiology, primarily evidenced by its impact on phenology. Numerous studies have aimed at expressing time with thermal indices such as growing degree days (GDD) and have thus enabled a better modelling of grapevine responses to temperature. However, some works have highlighted the need to adapt