The key role of vineyard parcel in modifying flavor compounds of Cabernet Sauvignon grapes

In this study for the first time, eight natural stilbenes (trans-resveratrol, trans-piceid, cis-piceid, trans-astringin, trans-piceatannol, (+)-trans-s-viniferin, pallidol and hopeaphenol) isolated and purified from Vitis vinifera, were simultaneously separated and analysed within 5 mn by ultra high pressure liquid chromatography coupled with photodiode array detection.

A study of the physiological and agronomical behaviour of the vine (cv. Chasselas) was conducted between 2001 and 2003 by the Swiss Federal Research Station for Plant Production at Changins (Agroscope RAC Changins) on various wine-growing farms (terroirs) in the Canton of Vaud (Switzerland), as part of a study project on Vaudois

In recent years, the consumption of alcoholic beverages is changing, driven by evolving consumer preferences and societal trends, including a wave of health consciousness. Among these changes, the emergence and proliferation of nolo (no alcohol/low alcohol) alcoholic beverages have gained significant attention within the industry. Nolo alcohol beverages are produced to emulate the appearance, aroma, and taste of alcoholic beverages, potentially facilitating a sense of social integration when consuming a product that closely resembles alcohol.

According to the Millennium Ecosystem Assessment (MEA, 2003), ecosystem services are the benefits people receive from ecosystems.

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.