Influence of temperature and light on vegetative growth and bud fruitfulness of grapevine cv. Semillon

Aroma and mouthfeel cues are the main characteristics defining red wine quality. During wine tasting, perceptual and physical-chemical phenomena leading to mutual interactions between volatiles and non-volatiles sensory active compounds, can occur. Aroma perception depends on the release of volatiles from wine, that is affected by wine constituents present in the medium (Pittari et al. 2021; Lyu et al. 2021). Our aim was to evaluate the effect of the non-volatile wine matrix composition (polyphenols, PPh) on the release and perception of red wine aromas by an experiment of matrix enrichment.

Mediterranean viticulture is increasingly exposed to more frequent extreme conditions such as heat waves. These extreme events co-occur with low soil water content, high air vapor pressure deficit and high solar radiant energy fluxes and result in leaf and berry sunburn, lower yield, and berry quality, which is a major constraint for the sustainability of the sector. Grape growers must find ways to proper and effectively manage heat waves and extreme canopy and berry temperatures. Irrigation to keep soil moisture levels and enable adequate plant turgor, and convective and evaporative cooling emerged as a key tool to overcome this major challenge. The effects of irrigation on soil and plant water status are easily quantifiable but the impact of irrigation on soil and canopy temperature and on heat convection from soil to cluster zone remain less characterized. Therefore, a more detailed quantification of vineyard heat fluxes is highly relevant to better understand and implement strategies to limit the effects of extreme weather events on grapevine leaf and berry physiology and vineyards performance. Low-cost sensor technologies emerge as an opportunity to improve monitoring and support decision making in viticulture. However, validation of low-cost sensors is mandatory for practical applicability. A two-year study was carried in a vineyard in Alentejo, south of Portugal, using low-cost thermal cameras (FLIR One, 80×60 pixels and FLIR C5, 160×120 pixels, 8-14 µm, FLIR systems, USA) and pocket thermohygrometers (Extech RHT30, EXTECH instruments, USA) to monitor grapevine and soil temperatures. Preliminary results show that low-cost cameras can detect severe water stress and support the evaluation of vertical canopy temperature variability, providing information on soil surface temperature. All these thermal parameters can be relevant for soil and crop management and be used in decision support systems.

Since 1996, we study the soil in viticulture, specially in the South of France. In the field, we delimit soil units and observe soil profiles and take samples to analyse its physical, mineral, organic and microbial mass composition

Colour is an important quality parameter in wines and is the result of a complex mixture of pigments
(including anthocyanins and their derivatives, quinones, xanthyllium compounds, etc.). Red wine colour changes over time as pigments react between themselves and with other wine macromolecules
(particularly polyphenols). During wine tasting, colour is normally assessed on the outer rim of the wine profile in a tilted glass, since most wines are too opaque to be analysed in the middle of the glass. Therefore, depending on the depth of observation considered, the perception of wine colour can be different.

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.