Mathematical models of the dynamics of fermentation of wine yeasts under the influence of vitamins

In winemaking, the use of wood products alternative to barrels, has become a useful tool for the achievement of numerous oenological objectives, including the fast release of desirable volatile and polyphenolic compounds, colour stabilization, and important economic advantages if compared to the traditional barrel production. Among a huge array of variables, the wood format, the vinification protocol, especially the moment of the infusion of the woods and the exposed surface area of the alternative woods are of relevant significance, since they may influence the speed and intensity of the aroma transfer from the wood to the wine defining different sensory profiles.

One of the main effects of global warming is an increase in the sugar concentration of grapes at harvest time, resulting in wines with a high alcohol content and an unbalanced structure. The fruit to leaf ratio is a key factor in determining the final sugar concentration, and training systems and management techniques can help to control this parameter.

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.

Cyprus is one of the very few phyloxera-free areas worldwide where the vast majority of vines are own-rooted and non-irrigated. ‘Xynisteri’ is a predominant indigenous cultivar, particularly amenable to extreme conditions such as drought and hot climate, thus rendering it appropriate for marginal soils and adverse climatic conditions. In the current work, a comparative study between irrigated (irrigation initiated at BBCH 71) and non-irrigated vines was conducted.

The Txakoli, a white wine produced in the Basque Country (North of Spain), has recently gained popularity due to wine quality improvement and increase in both acreages of production and wine consumption. The aim of this study was to characterize the chemical and microbiological differences between Txakoli wines made with grapes from different sites.