Genetic determinism of grapevine development stages as a tool for the adaptation to climate change

Grapevine downy mildew (GDM), caused by the oomycete Plasmopara viticola, is one of the most destructive diseases of Vitis vinifera worldwide. All V. vinifera cultivars are susceptible to P. viticola infection, and epidemics can spread across an entire vineyard within a matter of weeks. Severe outbreaks cause substantial reductions in yield and fruit quality. Tracking GDM spread by manual scouting is time-consuming and unfeasible over large spatial extents.

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.

La superficie vitata della provincia di Modena é per circa il 70% interessata dai Lambruschi, famiglia di vitigni tipica dei territori pianeggianti emiliani. Tra questi, i più rappresentativi sono il Lambrusco di Sorbara, il Lambrusco salamino e il Lambrusco grasparossa che, unico esempio, predilige gli ambienti collinari della provincia. Nel quinquennio 2001-2005 la Provincia di Modena ed il C.R.P.V. hanno coordinato la zonazione viticola di tutto il territorio dei Lambruschi modenesi, i cui risultati hanno consentito di individuare, in ciascuna zona D.O.C., alcune Terre in cui cias.

The metabolomics era started about 22 years ago, and wine was one of the first foodstuff subjects of analysis and investigation by this technique.

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