Which potential for Near Infrared Spectroscopy to characterize rootstock effects on grapevines?

Terroirs represent a heritage that must be studied and managed with appropriate methods; recourse to agronomic and oenological sciences alone is necessary, but is in no way sufficient without the contribution of the humanities.

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.

The application of remote and proximal sensing is a fast and efficient method to monitor grapevine vegetative and physiological parameters and is considered valuable to derive information on associated yield and quality traits in the vineyard. Further details can be obtained by the application of molecular analysis at the gene expression level aiming at elucidating how pathways controlling the formation of different grape quality traits are influenced by spatial variability. This work aims at evaluating intra-vineyard variability in grape composition at harvest and at comparing this with remotely sensed canopy vegetation data and molecular-based approaches.

The impact of climate change is noticeable in the present weather, making water scarcity the most immediate mediator reducing the performance and viability of crops, including grapevine (Vitis vinifera L.). The present study developed a system (hardware, firmware, and software) for the determination of plant water use through changes in weight through a period. The aim is to measure the differences in grapevine water consumption in response to climate change (+4oC and 700 ppm) under controlled conditions. The results reveal a correlation between daily plant consumption rates and reference evapotranspiration (ETo).

Non-saccharomyces yeasts play a crucial role in fermentation, producing a variety of secondary metabolites and enzymes that contribute to aromatic and sensory complexity compared to saccharomyces yeasts. It is crucial to understand and control the dynamics of non-saccharomyces yeasts to produce distinctive and high-quality fermented beverages.