Nitrogen isotope ratio (δ15N) as a tool to trace the major nitrogen source in vineyards

Vineyard nutrient management is crucial for reaching production-specific quality standards, yet timely evaluation of nutrient status remains challenging. The existing sampling protocol of collecting vine tissue (leaves and/or petioles) at bloom or veraison is time-consuming. Additionally, this sampling practice is too late for in-season fertilizer applications (e.g. N is applied well before bloom). Therefore alternative early-season protocols are necessary to predict the vine nutrient demand for the upcoming season. The main goals of this project are to 1) optimize existing tissue sampling protocols; 2) determine the amount of nutrients removed at the end of the growing season.

AIM: Lactiplantibacillus plantarum and Oenococcus oeni species is worldwide used as starter for malolactic fermentation [1, 2].

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.

Forest fires in the vicinity of vineyards have significantly increased in the last decade and are a concern for grapegrowers and winemakers in many wine producing countries. The fires cause smoke drift throughout vineyards which cannot be avoided and may result in the production of wines described as ‘smoke tainted’. Such wines are characterized by undesirable sensory characters described as ‘smoky’, ‘burnt’, ‘ash’ aromas and flavours, and also may cause a lingering, unpleasant ashy aftertaste [1; 2].

AIM: Stalks are empirically known to bring many benefits to the wine such as alcoholic reduction, color protection or improvement of the tannic intensity. Not much used on Swiss grape varieties, the aim of this study was to identify the relevance of using this type of winemaking in the case of Gamay and Gamaret red grape varieties.