Influenza del sito di coltivazione nella espressione aromatica del Moscato liquoroso di Pantelleria

The mechanization of pruning and harvesting in vineyards has increased the risk of soil compaction. To reclaim soil properties or avoid this degradation process, it is crucial to properly manage the soil organic matter, and the application of compost derived from the vines themselves is a strategy to achieve this. The objective of this study was to evaluate the properties of soil treated with different doses of compost applied both on the vine row and the inter rows of a Vitis vinifera crop.

Astringency is one of the leading quality factors in red wines.

The monitoring of the number of micro-orgranisms in wine is crucial for the wine producer. Traditional counting methods include microscopic enumeration and plating on selective media, which measures the culturability of the cells. The use of epifluorescence microscopy is, however, a method, which can measure both culturability and

Wine grape pomace quantitatively and qualitatively represents the most important fraction of wine waste. Namely, this by-product makes ~ 20% of the total mass of vinified grapes, and it is characterized with high concentrations of polyphenolic antioxidants, as well as grape seed oil. Hence, valorization of wine pomace, as an alternative to traditionally employed disposal, has drown considerable interest in recent years. Earlier studies were mostly focused on the extraction of phenolics, while mechanisms enhancing the extraction of lipid fraction from grape pomace, as well as their impact on the grape seed oil quality are far less investigated.

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.