New biotechnological approaches for a comprehensive characterization of AGL11 and its molecular mechanism underlying seedlessness trait in table grape

Tempranillo is the most widely grown red grapevine variety in Spain, currently representing 42% of the total number of red varieties and 21% of the total vineyard area. Due to the economic importance that this variety represents in Spanish viticulture, in some areas where it is traditionally grown, there is a special concern about the viability of the future growing of this variety is being compromised by the climate change effects.

Wine polysaccharides (PS) play an important role in balancing mouthfeel and stability of wine and even influence aroma volatility. Despite this, there is limited research into the effect of winemaking additives on the polysaccharide profile and other macromolecules of New Zealand (NZ) Pinot noir wine. In this study the influence of a selection of commercial S. cerevisiae strains on the chemical profile, including polysaccharides, of New Zealand Pinot noir (PN) wine was investigated. Research scale PN fermentations using five strains of commercially available S. cerevisiae (Lalvin EC1118 and RC212, Levuline BRG YSEO, Viallate Ferm R71 and R82) were undertaken. PS were qualified and quantified using HPLC-RID.

Soil and climate of 3 vineyards have been characterised in order to determine their influence on grape quality. These vineyards are located in Conca de Barberà (Catalonia, NE Spain) and belong to Cabernet sauvignon and Grenache noir cultivars. All 3 plots are very close, so only interannual climatic data of the nearest meteorological station have been considered.

Bioactive polyphenols from grapes and wines, like stilbenes and flavonols (SaF), are often determined to nutritional evaluation, but also for many other purposes. The objective of this study was to quantify SaF in red wines from “Campanha Gaúcha”, a large and young viticultural region from South Brazil. Moreover, through statistical analysis, evaluate the influence of these compounds according to varieties, production process, harvest years and micro-regions of cultivation. A total of 58 samples of red wines were analyzed by high-performance liquid chromatography coupled to diode array detector (HPLC-DAD) for determination of trans-resveratrol (R), quercetin (Q), myricetin (M), kaempferol (K), trans-e-viniferin (V) and their precursor, cinnamic acid (C).

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).