Vintage influence on Grenache N, Syrah N and Mourvedre N in Côtes du Rhône (France)

The main innovation in the VINIoT service is the joint use of two technologies that are currently used separately: vineyard monitoring using multispectral imaging and deployed terrain sensors. One part of the system is based on the development of artificial intelligence algorithms that are feed on the images of the multispectral camera and IoT sensors, high-level information on water stress, grape ripening status and the presence of diseases. In order to obtain algorithms to determine the state of ripening of the grapes and avoid losing information due to the diversity of the grape berries, it was decided to work along the first year 2020 at berry scale in the laboratory, during the second year at the cluster scale and on the last year at plot scale. Different varieties of white and red grapes were used; in the case of Galicia we worked with the white grape variety Treixadura and the red variety Mencía. During the 2020 and 2021 campaigns, multispectral images were taken in the visible and infrared range of: 1) sets of 100 grapes classifying them by means of densimetric baths, 2) individual bunches. The images taken with the laboratory analysis of the ripening stage were correlated. Technological maturity, pH, probable degree, malic acid content, tartaric acid content and parameters for assessing phenolic maturity, IPT, anthocyanin content were determined. It has been calculated for each single image the mean value of each spectral band (only taking into account the pixels of interest) and a correlation study of these values with laboratory data has been carried out. These studies are still provisional and it will be necessary to continue with them, jointly with the training of the machine learning algorithms. Processed data will allow to determine the sensitivity of the multispectral images and select bands of interest in maturation.

The research examines how two characteristic cultivations of a territory like the vine and the hazelnut shape the identity of a unique terroir: Langhe (North West italy).

In the conducted research, 30 yeast strains from red grape varieties were isolated from the Purcari wine center, and 28 yeast strains from red grape varieties were isolated from the Trifești wine center in the Republic of Moldova.

To face emerging competition and challenges, wine producers globally rely on precision viticulture (PV) solutions to boost productivity, enhance quality, increase profitability, and reduce the environmental impact of vineyards. Current pv methods predominantly use multispectral sensor data from several platforms (satellites or vineyard installations). However, these applications generally use data analysis strategies lacking physiological grapevine support.

Non-Saccharomyces yeasts not only increase microbial diversity during wine fermentation, but also have a positive effect on improving wine aroma. Among these non-Saccharomyces yeast species, Metschnikowia pulcherrima is often studied and used in winemaking in recent years, but its application in icewine has been rarely reported. In this study, indigenous M. pulcherrima strains and Saccharomyces cerevisiae strains (commercial and indigenous strains) were sequentially inoculated for icewine fermentations; meanwhile, pure S. cerevisiae fermentations were used as the control; indigenous strains used above were screened from spontaneous fermentations of Vidal blanc icewine.