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.

Atmospheric and statistical models were used to increase understanding of potential climatic impacts, resulting from mesoscale physical processes that cause significant temperature variability for viticulture within the Stellenbosch Wine of Origin district. Hourly temperature values from 16 automatic weather stations and 40 tinytag data loggers located in the vineyards were analysed.

Aim: Wine quality and character are defined in part by the terroir in which the grapes are grown. Metabolomic techniques, such as nuclear magnetic resonance (NMR) spectroscopy and inductively coupled plasma mass spectrometry (ICP-MS), are used to characterise wines and to detect wine fraud in other countries but have not been extensively trialled in Australia. This study aimed to investigate the use of ICP-MS and NMR to characterise a selection of Pinot noir wines.

Context and purpose of the study. Albeit standing as a fashionable research topic dual use of land as viti-voltaic still lacks of fundamental knowledge about whole canopy grapevine response to altered microclimate under panels vs open field conditions.

One of the key factors of the economical development of viticulture and wine industry in specific limited areas is the exploitation of ancient, local grape varieties. Therefore, in recent years the growing interest to rediscover minor varieties, previously cultivated, has promoted many studies. With this regard, the focus of this study was the Vitis vinifera L. cultivar Moscato nero d’Acqui, nowadays found only in old vineyards in the Acqui zone (North-West Italy). In particular, the aims of this work were: i) to investigate secondary metabolites profile of the grapes, and ii) to evaluate the attitude to the production of special wines.