Wine growing terroirs: management of potential. New issues at stake for AOCs in France

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.

Bottle aging is crucial for wine quality, influencing its chemical and sensory properties [1]. Ideally, a phase of qualitative ageing enhances sensory attributes before a decline in quality occurs. Understanding the impact of oenological variables on these phases is a key challenge in modern winemaking.

The effects of climate change produce an increase in sugar concentration and a decrease in acidity, without reaching the optimum grape phenolic maturity [1]. The aim of this work was to characterize 25 white grape varieties

The vocabulary used to describe wine aroma is commonly organized according to color, raising the question of whether they reflect the reality of olfactory perception. Previous studies have assumed this convention of color-aroma matching, and have investigated color’s influence on the perception of aroma only in dyed white wine or in red wine from particular places of origin. Here 48 white and red varietal wines from around the world were evaluated in black glasses then in clear glasses by a panel of wine experts, who gave intensity ratings for aroma attributes commonly used by wine professionals. In black glasses, aromas conventionally associated with white wine were perceived in the red wines, and vice versa.

Light-induced reactions can be responsible for detrimental changes of white and rosé wines. This is associated to the photo-degradation of riboflavin (RF) and of methionine (Met) causing the appearance of light-struck taste (LST).