Olfactometry approach to assess odorant compounds of grape spirits used for Port wine production-first results

The use of resistant varieties is a long-term but promising solution to reduce chemical input in viticulture. Several important breeding programs in Europe and abroad are now releasing a range of new hybrids performing well regarding fungi susceptibility and producing good quality wines. Unfortunately, insufficient attention is paid by the breeders to the adaptation of these varieties to climatic changes, notably to the increased climatic demand and water deficit (WD). Thus, prior to the adoption of such varieties by the wine industry in Mediterranean regions, there is a need to consider their suitability to WD. This study aimed to characterize the different drought-strategies adopted by 6 new resistant varieties selected by INRAE in comparison to Syrah. To allow the assessment of long-term impacts of WD, field-grown vines were exposed to contrasted WD from 2018 to 2021 under a semi-arid Mediterranean climate. A gradient of WD was applied in the field and controlled through plant measurements at the single plant level. Grape development was non-destructively monitored to determine the arrest of berry phloem unloading. The impacts of WD on berry composition, including water, primary metabolites (sugars, organic acids), secondary metabolites (anthocyanins, thiols precursors) and main cations contents, were assessed at this specific stage. Results showed different varietal responses during the year and inter-annual acclimation in terms of plant water use efficiency, biomass accumulation, as well as yield components and berry composition. WD differentially reduced the accumulation of primary metabolites at plant and berry levels, but it little changed their concentrations in the fruits at the ripe stage. Moreover, WD differentially impacted the accumulation of secondary metabolites and major cations between the varieties. In the talk, we’ll present the main results regarding the WD impacts on fruit metabolites and enlarge the reflection about the practical assessment of the grapevine acclimation to WD.

Understanding vineyard variability to target management strategies, apply inputs efficiently and deliver consistent grape quality to the winery is essential. However, despite inherent vineyard variability, the majority are managed as if they are uniform. VitiCanopy is a simple, grower-friendly tool for precision/digital viticulture that allows users to collect and interpret objective spatial information about vineyard performance. After four years of field and market research, an upgraded VitiCanopy has been created to achieve a more streamlined, technology-assisted vine monitoring tool that provides users with a set of superior new features, which could significantly improve the way users monitor their grapevines. These new features include:
• New user interface
• User authentication
• Batch analysis of multiple images
• Ease the learning curve through enhanced help features
• Reporting via the creation of colour maps that will allow users to assess the spatial differences in canopies within a vineyard.
Use-case examples are presented to demonstrate the quantification and mapping of vineyard variability through objective canopy measurements, ground-truthing of remotely sensed measurements, monitoring of crop conditions, implementation of disease and water management decisions as well as creating a history of each site to forecast quality. This intelligent tool allows users to manage grapevines and make informed management choices to achieve the desired production targets and remain profitable.

Choosing the rootstock, the scion variety and the training system best suited to the local soil and climate are the key elements for an economically sustainable production of wine. The choice of the rootstock/scion variety best adapted to the characteristics of the soil is essential but, by changing climatic conditions, ongoing climate change disrupts the fine-tuned local equilibrium. Higher temperatures induce shifts in developmental stages, with on the one hand increasing fears of spring frost damages and, on the other hand, ripening during the warmest periods in summer. Expected higher water demand and longer and more frequent drought events are also major concerns. The genetic control of the phenotypes, by genomic information but also by the epigenetic control of gene expression, offers a lot of opportunities for adapting the plant material to the future. For complex traits, genomic selection is also a promising method for predicting phenotypes. However, ecophysiological modelling is necessary to better anticipate the phenotypes in unexplored climatic conditions Genetic approaches applied on parameters of ecophysiological models rather than raw observed data are more than ever the basis for finding, or building, the ideal varieties of the future.

Global warming is one of the biggest environmental, social, and economic threats. In the Douro Valley, change to the climate are expected in the coming years, namely an increase in average temperature and a decrease in annual precipitation. Since vine cultivation is extremely vulnerable and influenced by the climate, these changes are likely to have negative effects on the production and quality of wine.
Adaptation is a major challenge facing the viticulture sector where the choice of plant material plays an important role, particularly the rootstock as it is a driver for adaptation with a wide range of effects, the most important being phylloxera, nematode and salt, tolerance to drought and a complex set of interactions in the grafted plant.
In an experimental vineyard, established in the Douro Region in 1997, with four randomized blocs, with five varieties, Touriga Nacional, Tinta Barroca, Touriga Franca and Tinta Roriz, grafted in four rootstocks, Rupestris du Lot, R110, 196-17C, R99 and 1103P, data was collected consecutively over 20 years (2001-2020). Phenological observations were made two to three times a week, following established criteria, to determine the average dates of budbreak, flowering and veraison. During maturation, weekly berry samples were taken to study the dynamics of sugar accumulation, amongst other parameters. Climate data was collected from a weather station located near the vineyard parcel, with data classified through several climatic indices.
The results achieved show a very low coefficient of variations in the average date of the phenophases and an important contribution from the rootstock in the dynamic of the phenology, allowing a delay in the cycle of up to10-12 days for the different combinations. The Principal Component Analysis performed, evaluating trends in the physical-chemical parameters, highlighted the effect of the climate and rootstock on fruit quality by grape varieties.

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.