Leaf elemental composition in a replicated hybrid grape progeny grown in distinct climates

The Registered Appellation of Origin Mark (RAOM) « Jerez-Xérès-Sherry and Manzanilla Sanlucar de Barrameda » is one of the oldest and more important zone in wine history and production. «Albarizas» unit (white calcareous marls with sea-fossils) is the most representative geological material of the RAOM (75%) and even more in the central-NW area of the RAOM, known as «Jerez Superior» area (Superior Quality Sherry Area). « Albarizas » form undulated hillocks (3-10% slope) and hills (>10% slope), the litologic unit has E-W and S-W direction, and Regosols and Leptosols are the principal soils.

It is well known that the vinification of grapes at full maturation can produce rich, full-bodied wines,
with intense and complex flavour profiles. However, the juice obtained from such grapes may have very
high sugar concentration, resulting in wines with an excessive concentration of ethanol. In addition, the decoupling between technological maturity and phenolic/aromatic one due to global warming, exacerbates this problem in some wine-growing regions. In parallel with the increase of the mean alcohol content of wines on the market, also the demand for reduced alcohol beverages has increased in recent years, mainly as a result of health and social concerns about the risks related to the consumption of alcohol.

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.

This work aimed to evaluate the evolution of phenolic compounds during white winemaking process up to bottling and 12 months storage, together with the influence of different antioxidant strategies

Vineyards are highly variable and this variation is largely driven by environmental conditions and seasonal variation. For example, warm temperatures