Spatial variability of grape berry maturation program at the molecular level 

Over the last decade, the use of non-Saccharomyces yeasts in the winemaking process has been re-assessed and accepted by winemakers. These yeasts can be used to achieve specific objectives such as lowering the ethanol content, preventing wine spoilage and increasing the production of specific aroma compounds. Since these species are unable to complete alcoholic fermentation, strategies of co- and sequential inoculation of non-Saccharomyces and Saccharomyces cerevisiae have been developed. However, when mixed starter cultures are used, several parameters (e.g. strain yeast, inoculation timing and nutrient competitions) impact the growth of the individual yeasts, the fermentation kinetics and the metabolites/aroma production. In particular, competition for nitrogen compounds could have a major impact, potentially leading to sluggish fermentation when the yeast assimilable nitrogen (YAN) availability is low. Moreover, many aroma compounds produced by the yeasts are directly produced and influenced by nitrogen metabolism such as higher alcohols, acetate esters and ethyl esters which participate in the organoleptic complexity of wine.

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).

Valpolicella is an Italian wine producing region, famous for the production of high-quality red wines. A distinctive characteristic of this region is the extensive use of post-harvest withering.

Merlot grapevine is the second wine cultivar most planted in the world and especially in the Bordeaux wine region. This cultivar has many advantages in producing high quality wine; however, in the last decade, climate change has increased the sugar concentration in berries at harvest and shortened the maturation cycle. If this has been up to now a great opportunity to improve wine quality profile, we are touching the tipping point. High sugar concentration at harvest induces high alcool content in wine which can negatively impact wine quality. There are many viticultural and oenological practices possible to limit this effect. In this study we focus on plant material through intra-varietal diversity of Merlot cultivar.

Studies suggest that ethanol (EtOH), triggers plant adaptation to various stresses at low concentrations (10 µM to 10 mM).