Nucleophilic fraction to estimate the antioxidant activity of inactivated yeast derivates

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).

Pinking of white wine is an undesired change potentially occurring over storage, leading to the turning of color from yellow into salmon-red hue.

For the period of 10 years in the condition of Skopje vineyard area, at two regional (Vranec and Smederevka) and two international (Cabernet sauvignon and Chardonnay) grapevine cultivars, the researches are done.

Analysis of phenolic compounds typically involve spectrophotometric methods as well as liquid chromatography combined with DAD, fluorimetric, or MS detection. However, the complexity of wine phenolic composition generated, in recent years, attention towards other analytical approaches, including those allowing rapid and inexpensive operations. Voltametric AIM Oxidation of white wine phenolics occurs at different stages during winemaking and storage and can have important implications for wine sensory quality. Phenolic compounds, in particular those with a ortho-diphenol moiety, are main target of oxidation in wine. Strategies for the methods are particularly suited for the analysis of oxidizable compounds such as phenolics. The redox-active species can be oxidized and reduced at the electrode, therefore, applications of electrochemistry have been developed both to quantify such species, and to probe wine maturation processes.3 The project on the diversity of Italian wines aims at collecting and analysing large-scale compositional dataset related to Italian white wines.

Synthetic pesticides are widely used in viticulture to ensure steady harvest quality and quantity. Fungicides are primarily used to control grapevine diseases but insecticides and herbicides are likewise used. Pesticide residues in viticultural areas currently represent a strong societal concern, but may also affect different trophic chains in such areas. In this project we wish to analyse honeybees collected from hives placed in different vineyards, their natural predator (the invasive hornet Vespa velutina), as well as the honey, grape berries, and wines produced.