Tasting soils in Pinot noir wines of the Willamette valley, Oregon

La producción mundial de uvas para mesa es obtenida de viñedos localizados entre los paralelos 30 y 50º Latitud Norte y 30 y 40º Latitud Sur.

Gum arabic is composed of a polysaccharide rich in galactose and arabinose along with a small protein fraction [1, 2], which gives its stabilizing power with respect to the coloring substances or tartaric precipitation of bottled wine. It is a gummy exudation from Acacia trees; the products used in enology have two possible botanical origins, i.e. Acacia seyal and Acacia senegal, with different chemical-physical features and consequently different technological effects on wines. The aim of this work is to evaluate the feasibility of discrimination of commercial gums Arabic between their two different sources, on the basis of the absorption of the Fourier Transform Infrared (FT-IR) spectra of their aqueous solutions, in order to propose an extremely rapid and cost-saving method for quality control laboratories.

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.

Targeted analytical methods can overlook compounds that are a priori unknown to play a role in the mouthfeel sensations. This limitation can be overcome with the information provided by untargeted metabolomic analysis using UPLC‐QTOF-MS. To this end, an untargeted metabolomic approach applied to 42 red wines has allowed development of a model with predictive capacity by cross-validation for the “dry”, “oily” and “unctuous” sensations perceived by a sensory panel. The optimal PLS model for “dry” retained compounds with positive regression coefficients (≥ 0.17) including a trimer procyanidin, a peptide, and four anthocyanins.

Over the past few decades, viticultural research has made numerous contributions which have made it possible to better understand the behavior of the vine as well as its response to the conditions imposed on it by the environment and agronomic practices. However, these results have only rarely been used in the practical management of vineyards because the research has been carried out using partial experimental models where reality is only represented by a few factors which are sometimes even made more complex by the introduction of elements foreign to the existing situation and difficult to apply to production (varieties, methods of cultivation, management techniques, etc.). To these reasons, one could add a low popularization of the results obtained, as well as the difficulty of implementing the scientific contributions, which does not allow the different production systems to fully express their potential. This limit of viticultural research can only be exceeded by the design of integrated projects designed directly on and for the territory. Indeed, only the integrated evaluation of a viticultural agro-system, which can be achieved through zoning, makes it possible to measure, or even attribute to each element of the system, the weight it exerts on the quality of the wine.