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.

Aim of the study was to investigate the metabolomic differences between Chilean Cabernet Sauvignon wines, divided according to their quality in two main groups: “Varietal” and “Premium”, and to point out metabolites tentative markers of their chemical signature and sensorial quality. Initially, 150 (50 x 3 biological replicates) experimental wines were produced by the same semi-industrial process, which covered 8 different Chilean valleys. The wine classification made by experts, divided the wines into two major groups (“Varietal” and “Premium”) and four subgroups (two for each major group). All the samples were analyzed according to a robust LC-MS based untargeted work-flow (Arapitsas et al 2018), and the proposed minimum reporting standards for chemical analysis of the Metabolomics Standards Initiative (Sumner et al 2007)

Aims: This study aimed to (1) characterise colour and phenolic profiles of commercial Australian Pinot noir wines, (2) understand regional drivers of sensory and volatile profiles of commercial Australian Pinot noir wines, and (3) generate a deeper understanding of where Australian Pinot noir wines profiles sit in an international context.

Rootstocks play a key role in the grapevine’s adaptation to the increasing soil water scarcity related to climate change. A pot experiment carried out in 2022 aimed at assessing the physiological responses of seven ungrafted rootstocks to a progressive soil water deficit and a subsequent recovery to field capacity.

Nel 2009 sono stati prelevati e analizzati mediante XRF (X-ray fluorescence) campioni di suolo, in vigneti sperimentali siti nelle province di Vicenza e di Ancona. Sono stati inoltre determinati in 2 campioni di mosto e 2 di vino delle varietà Verdicchio e Refosco dal peduncolo rosso, ed in 2 di uva Refosco dal peduncolo rosso, gli elementi in traccia mediante ICP-MS (Inductively coupled plasma-mass spectrometry).