Advancing grapevine science through genomic research

During cold storage, grapes undergo changes that affect their visual, mechanical, and organoleptic properties, potentially impacting quality and negatively influencing consumer acceptance. Key parameters include uniform color, crunchiness, and flesh consistency. We evaluated the influence of two distinct packaging methods on the chromatic characteristics, hardness, and pedicel detachment resistance of fourteen new seedless white and red grape varieties during cold storage. These factors are crucial for maintaining the quality of the product and extending its shelf-life. The novel grape varieties were obtained through a breeding program at CREA-VE of Turi, Southern Italy.

Color is one of the key elements in the marketing of rosé wines[1]. Their broad range of color is due to the presence of red pigments (i.e. anthocyanins and their derivatives) and yellow pigments, likely including polyphenol oxidation products. Clarifying agents are widely used in the winemaking industry to enhance wine stability and to modulate wine color by binding and precipitating polyphenols[2]. During this study, the impact of four different fining agents (i.e. two vegetal proteins, potatoe and pea proteins, an animal protein, casein, and a synthetic polymer, polyvinylpolypyrrolidone, PVPP) on Syrah Rose wine color and phenolic composition (especially pigments) was investigated. Color was characterized by spectrophotometry analysis using the CIELab system in addition to absorbance data. Fining using PVPP had the highest impact on redness (a*) and lightness (L*) parameters, whereas patatin strongly reduced the yellow component (b*) of the wine color. In parallel, the concentration of 125 phenolic compounds including 85 anthocyanins and derived pigments was determined by Ultra High Performance Liquid Chromatography coupled to elestrospray ionisaion triple-quadrupole Mass Spectrometry (UHPLC-QqQ-ESI-MS) in the Multiple Reaction Monitoring mode[3] .

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.

In order to avoid the loss of grapevine intra-varietal diversity of DOCa Rioja grape varieties, Regional Government of La Rioja established a germplasm bank with more than 1.600 accessions, whose origin lies in the prospecting and sampling of ancient vineyards located throughout the whole region. 30 clones of Tempranillo and 13 clones of Graciano were preselected and multiplied in a new vineyard for further observations. The aim of this work is to describe the first results from the physiological characterization by an optical sensor of these preselected clones, which constitute the base of a new clonal selection that aims to increase the range of available certified clones and to improve the adaptation of these varieties to future objectives and environmental conditions.

The use of multivariate statistics to correlate chemical data to spectral information seems as a valid alternative for the quantification of red wine phenolics. The advantages of these techniques include simplicity and cost effectiveness together with the limited time of analysis required. Although many
publications on this subject are nowadays available in the literature most of them only reported feasibility
studies. In this study 400 samples from thirteen fermentations including five different cultivars plus 150
wine samples from a varying number of vintages were submitted to spectrophotometric and chromatographic phenolic analysis.