An Ag+ SPE method combined with Deans’ switch heart-cutting MDGC–MS/Olfactometry approach for identifying unknown volatile thiols in wine

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.

There are yet many gaps in our knowledge about the aroma potential of winemaking grapes and its measurement. Trying to bring some light into this question, a new general strategy based on the accelerated hydrolysis of reconstituted phenolic and aromatic fractions (PAFs) extracted from grapes has been developed

It is not easy at first sight to give an exhaustive definition of the notion of terroir as it can be simplified or complicated at will. Thus the vagueness that surrounds this concept leaves the door open to various interpretations of the terroir. These tend towards a questionable level of objectivity because the fields they explore are not sufficient to explain the notion on their own, constituting only part of a whole.

Grape by-products (including skins, seeds, stems and vine shoots) are rich in health promoting polyphenols. Their extraction from winery waste and their following purification are of special interest to produce extracts with high added value compounds. Meanwhile, the growing concern over environmental problems associated with economic constraints, require the development of environmentally sustainable extraction technologies. The extraction using semi-continuous subcritical water, as a natural solvent at high temperature and high pressure a technology is promising “green” technology that is environmentally friendly, energy efficient and improve the extraction process in plant tissues.

Understanding grapevine responses to increasing atmospheric CO2 (aCO2) concentrations is crucial for assessing the impact of climate change on viticulture. Previously, at the VineyardFACE (Free Air Carbon dioxide Enrichment) experiment in Geisenheim, leaf gas exchange measurements were made as Vitis vinifera cv. Cabernet Sauvignon established from planting (2014 to 2016) under aCO2 or elevated CO2 (eCO2, aCO2 + 20%) concentrations. Contrary to many preceding observations with grapevines and other perennial plant species the young vines showed an increased intrinsic water use efficiency (WUEi) that was mainly associated with an increase in net assimilation (A) rather than a decrease in stomatal conductance (gs) under eCO2.