Development, validation and application of a fast UHPLC-HRMS method for the analysis of amino acids and biogenic amines in wines and musts.

Using viticultural and enological techniques to increase aromatics in white wine is a prized yet challenging technique for commercial wine producers. Equally difficult are challenges encountered in hastening phenolic maturity and thereby increasing color intensity in red wines. The ability to alter organoleptic and visual properties of wines plays a decisive role in vintages in which grapes are not able to reach full maturity, which is seen increasingly more often as a result of climate change. A new, yeast-based product on the viticultural market may give the opportunity to increase sensory properties of finished wines. Manufacturer packaging claims these yeast derivatives intensify wine aromas of white grape varieties, as well as improve phenolic ripeness of red varieties, but the effects of this application have been little researched until now. The current study applied the yeast derivative, according to the manufacture’s instructions, to the leaves of both neutral and aromatic white wine varieties, as well as on structured red wine varieties. Chemical parameters and volatile aromatics were analyzed in grape musts and finished wines, and all wines were subjected to sensory analysis by a tasting panel. Collective results of all analyses showed that the application of the yeast derivative in the vineyard showed no effect across all varieties examined, and did not intensify white wine aromatics, nor improve phenolic ripeness and color intensity in red wine.

Anthocyanin potential of grape berries is an important quality factor in wine production. Anthocyanin concentration and profile differ among varieties but it also depends on the environmental conditions, which are expected to be greatly modified by climate change in the future. These modifications may significantly modify the biochemical composition of berries at harvest, and thus wine typicity. Among the diverse approaches proposed to reduce the potential negative effects that climate change may have on grape quality, genetic diversity among clones can represent a source of potential candidates to select better adapted plant material for future climatic conditions. The effects of individual and combined factors associated to climate change (increase of temperature, rise of air CO2 concentration and water deficit) on the anthocyanin profile of different clones of Tempranillo that differ in the length of their reproductive cycle were studied. The aim was to highlight those clones more adapted to maintain specific Tempranillo typicity in the future. Fruit-bearing cuttings were grown in controlled conditions under two temperatures (ambient temperature versus ambient temperature + 4ºC), two CO2 levels (400 ppm versus 700 ppm) and two water regimes (well-watered versus water deficit), both in combination or independently, in order to simulate future climate change scenarios. Elevated temperature increased anthocyanin acylation, whereas elevated CO2 and water deficit favoured the accumulation of malvidin derivatives, as well as the acylation and tri-hydroxylation level of anthocyanins. Although the changes in anthocyanin profile observed followed a common pattern among clones, such impact of environmental conditions was especially noticeable in one of the most widely distributed Tempranillo clones, the accession RJ43.

Wine growing regions have recently faced intense and frequent droughts that have led to substantial economical losses, and the maintenance of grapevine productivity under warmer and drier climate will rely notably on planting drought-resistant cultivars. Given that plant growth and yield depend on water transport efficiency and maintenance of photosynthesis, thus on the preservation of the vascular system integrity during drought, a better understanding of drought-related hydraulic traits that have a significant impact on physiological processes is urgently needed. We have worked towards this end by assessing vulnerability to xylem embolism in 30 grapevine commercial varieties encompassing red and white Vitis vinifera varieties, hybrid varieties characterized by a polygenic resistance for powdery and downy mildew, and commonly used rootstocks. These analyses further allowed a global assessment of wine regions with respect to their varietal diversity and resulting vulnerability to stem embolism. Hybrid cultivars displayed the highest vulnerability to embolism, while rootstocks showed the greatest resistance. Significant variability also arose among Vitis vinifera varieties, with Ψ12 and Ψ50 values ranging from -0.4 to -2.7 MPa and from -1.8 to -3.4 MPa, respectively. Cabernet franc, Chardonnay and Ugni blanc featured among the most vulnerable varieties while Pinot noir, Merlot and Cabernet Sauvignon ranked among the most resistant. In consequence, wine regions bearing a significant proportion of vulnerable varieties, such as Poitou-Charentes, France and Marlborough, New Zealand, turned out to be at greater risk under drought. These results highlight that grapevine varieties may not respond equally to warmer and drier conditions, outlining the importance to consider hydraulic traits associated with plant drought tolerance into breeding programmes and modeling simulations of grapevine yield maintenance under severe drought. They finally represent a step forward to advise the wine industry about which varieties and regions would have the lowest risk of drought-induced mortality under climate change.

Grapevine yield is a key indicator to assess the impacts of climate change and the relevance of adaptation strategies in a vineyard landscape. At this scale, a yield model should use a number of parameters and input data in relation to the information available and be able to reproduce vineyard management decisions (e.g. soil and canopy management, irrigation). In this study, we used data from six experimental sites in Southern France (cv. Syrah) to calibrate a model of grapevine yield limited by water constraint (GraY). Each yield component (bud fertility, number of berries per bunch, berry weight) was calculated as a function of the soil water availability simulated by the WaLIS water balance model at critical phenological phases. The model was then evaluated in 10 grapegrowers’ plots, covering a diversity of biophysical and technical contexts (soil type, canopy size, irrigation, cover crop). We identified three critical periods for yield formation: after flowering on the previous year for the number of bunches and berries, around pre-veraison and post-veraison of the same year for mean berry weight. Yields were simulated with a model efficiency (EF) of 0.62 (NRMSE = 0.28). Bud fertility and number of berries per bunch were more accurately simulated (EF = 0.90 and 0.77, NRMSE = 0.06 and 0.10, respectively) than berry weight (EF = -0.31, NRMSE = 0.17). Model efficiency on the on-farm plots reached 0.71 (NRMSE = 0.37) simulating yields from 1 to 8 kg/plant. The GraY model is an original model estimating grapevine yield evolution on the basis of water availability under future climatic conditions.  It allows to evaluate the effects of various adaptation levers such as planting density, cover crop management, fruit/leaf ratio, shading and irrigation, in various production contexts.

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.