Depletion Of Vine-Shoots Phenolic Composicion After Being Used As An Enological Tool For Wine Differentiation

Schiava cv. (germ. Vernatsch) is a group of grape varieties used for winemaking (e.g. Kleinvernatsch-Schiava gentile, Grauvernatsch-Schiava grigia, Edelvernatsch-Schiava grossa) historically reported in Northern Italy, Austria, Germany and Croatia. Beside common phenotypic traits, these varieties have been also hypothesized to share a common geographical origin in Slavonia (Eastern Croatia). Nowadays, Schiava cv. are considered historical grape varieties of northern regions of Italy such as Lombardy, Trentino and South Tyrol. Traditionally widely consumed locally and also exported, over the past decades there has been a steady drop in production of these grapes, although with a parallel increase in wine quality. In this report, the effects of three main enological variables on the chemical components of Schiava produced in South Tyrol (var. Schiava grossa) are investigated from grape to bottle.

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).

Today, there is need to design, produce and label terroir wines, with unique organoleptic properties and more “attractive to consumers”. For this purpose, two Saccharomyces cerevisiae yeast strains (Sa and Sb) isolated during spontaneous fermentations were used for white wine production from the Assyrtiko grape of Santorini. A third commercial strain was used as control.

Nowadays, the entire viticultural and enological process is wisely thought out according to the style of wine to be produced and the local climatic conditions. Acquiring the approach of a technical management route specific for wine production remains a complex learning process for students. To enhance such learning, The Ecole d’Ingénieurs de PURPAN (PURPAN), an engineering school located in Toulouse southwest France, has recently developed Creativini, a collaborative card game in English made of 150 cards spread into 14 batches. Students in groups of 3 to 6 must design a technical production route, from plant material to bottling.

Drought and heat waves deriving from climate change have been affecting grapevine plants and altering wine characteristics in the past years, and effects are expected to get worst. Innovative approaches to address this problem have been undertaken in several varieties, that consist in exploring intravarietal variability to identify genotypes that are tolerant to abiotic stress. Such is the case of the variety Arinto, where an experimental population of 165 clones installed according to a resolvable row-column design with 6 replicates, was scanned for several parameters, including surface leaf temperature (SLT). Linear mixed models were fitted to the data of the traits evaluated, and the empirical best linear unbiased predictors (EBLUPs) of genotypic effects for each trait were obtained as well as the coefficient of genotypic variation (CVG) and broad sense heritability.