Improvement of sparkling wines production by a zoning approach in Franciacorta (Lombardy, Italy)

Nitrogen (N) supply strongly influences vine productivity and berry composition, matching availability and uptake requirements of vines during the growing season is essential to optimize vine nutrition. The nutritional status of grapevines is commonly assessed by the determination of petiole nutrient concentrations at flowering. The reserve N could also be an earlier indicator for grapevine N status, this work aimed to assess how the petiole levels relate to these perennial N reserves.

A study of the influence of environmental factors on the ripening of grapes under the conditions of Alsace is carried out. Emphasis is placed on the analysis of the mesoclimate and pedoclimate. The experiment is conducted on a network of plots of gewurztraminer grafted on SO4. The production conditions are standardized throughout the device.

Different yeasts were isolated from spontaneous fermentation of Assyrtiko grape must in Santorini Island, Greece. Molecular typing revealed the presence of three Saccharomyces cerevisiae strains (S9, S13, S24) and one strain of the yeast species Nakazawaea ishiwadae (N.i). The four isolated strains were further tested in laboratory scale fermentations of Assyrtiko must in pure inoculation cultures and in sequential inoculation (72 hours) of each S. cerevisiae strain with the strain of N. ishiwadae. All fermentation trials were realised in duplicate.

Current environmental, ecological and economic issues require a better vineyard production management. In fact, a poor use of fertilizing could lead to harmful impact on environment. Another issue concerns the cultures themselves which couldn’t use fertilizers efficiently, leading to a loss of income or too much expense for farmers. Presently, estimation of fertilization’s needs is realized by the laboratory analysis of leaves selected through a random sampling. The present study aims at optimizing fertilization’s management by using a map of biophysical parameters estimated from satellite images.

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.