Exogeneous C-S lyase enzyme, a potential tool for thiol enhancement in wine or beer?

The climatic component is one of the elements of the zoning of viticultural potential, alongside the geological and pedological components (Morlat, 1989; Lebon et al , 1993). Many climatic indices have thus been defined to estimate the potential for wine production at the scale of a region or a country (Carbonneau et al ., 1992). The main climatic variables used are temperature and radiation. We note in particular the indices of Branas, Huglin and Ribereau-Gayon (Huglin, 1986). However, few studies have been undertaken on the spatial variability of microclimatic conditions at the scale of a vineyard, a valley, or even a municipality.

The first white settlers arrived in Australia in 1788 and brought grape vine cuttings with them. As migration to Australia continued to grow during the XIX Century more and more vine cuttings, viticulturists and winemakers from Britain, France, Germany, ltaly, Switzerland and Yugoslavia founded their businesses.

The ongoing climate change results in increasing mean air temperature, which is manifested by weather extremes or sudden changes between drought and local heavy rainfalls. These changing conditions are especially challenging for the established grapevine varieties growing under cool climate conditions due to an increased biotic infection pressure. Thus, the scope of most grapevine breeding programs is the selection of mildew fungus-resistant and climatic adapted grapevines with balanced, healthy yield and outstanding wine quality. Since no resistances or candidate genes have yet been described for Botrytis bunch rot (BBR), physical-mechanical traits like berry size and thick, impermeable berry cuticles phenotyped with high-throughput sensors represent novel effective parameters to predict BBR.

Climate change is altering water balances, thereby compromising water availability for crops. In grapevine, the strategic selection of genotypes more tolerant to soil water deficit can improve the resilience of the vineyard under this scenario. Previous studies demonstrated that root anatomical and morphological traits determine vine performance under water deficit conditions. Therefore, 13 ungrafted rootstock genotypes, 6 commercial (420 A, 41 B, Evex 13-5, Fercal, 140 Ru y 110 R), and 7 from new breeding programs (RG2, RG3, RG4, RG7, RG8, RG9 and RM2) were evaluated in pots during 2021 and 2022.

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).