IVAS 2022 banner
IVES 9 IVES Conference Series 9 IVAS 9 IVAS 2022 9 Untargeted LC-HRMS analysis to discover new taste-active compounds in spirits.

Untargeted LC-HRMS analysis to discover new taste-active compounds in spirits.

Abstract

​For several years, the chemistry of taste has aroused high interest both from academics and industrials. Plant kingdom is a rich and reliable source of new taste-active compounds. Many sweet, bitter or sour molecules have been identified in various plants [1]. They belong to diverse chemical families and their sensory properties are strongly affected by slight structural modifications. As a consequence, the investigation of natural taste-active products in a given matrix appears as a major challenge for chemists. Such studies are particularly relevant in oenology since they allow a better understanding of wine and spirit taste.

The present study aims at proposing an original methodology for the discovery of new taste-active compounds. In this context, an untargeted metabolomic approach using liquid chromatography–high resolution mass spectrometry (LC-HRMS, Orbitrap analyzer) was implemented on several “eau-de-vie” of Cognac. Different statistical analyzes allowed to assess the overall structure of the data, which represents hundreds of ions, and to select and identify compounds of interest. On this basis, compound A and B were chosen according to several criteria. A fractionation protocol from “eau-de-vie” of Cognac and oak wood extracts, including liquid-liquid extractions, centrifugal partition chromatography (CPC) and Preparative-HPLC, was set up to isolate and characterize these targeted compounds. Their structures were elucidated by HRMS and nuclear magnetic resonance (NMR). Additionally, compound A was perceived as sweet and compound B exhibited a taste of fat in two matrices [2-3].These results highlight the interest of an untargeted differential analysis, hyphenating separative techniques and sensory analysis, to discover new taste-active compounds. These studies provide promising perspectives for a better understanding of the molecular markers responsible for the taste of foods and beverages.

References

[1] Kinghorn, A. D. Biologically Active Compounds from Plants with Reputed Medicinal and Sweetening Properties. Journal of Natural Products 1987, 50 (6), 1009–1024.
[2] Winstel, D.; Bahammou, D.; Albertin, W.; Waffo-Téguo, P.; Marchal, A. Untargeted LC–HRMS Profiling Followed by Targeted Fractionation to Discover New Taste-Active Compounds in Spirits. Food Chemistry 2021, 359, 129825.
[3] Winstel, D.; Capello, Y.; Quideau, S.; Marchal, A. Isolation of a New Taste-Active Brandy Tannin A: Structural Elucidation, Quantitation and Sensory Assessment. Food Chemistry 2022, 377, 131963.

DOI:

Publication date: June 27, 2022

Issue: IVAS 2022

Type: Poster

Authors

Winstel Delphine1, Bahammou Delphine1, Capello Yoan2, Albertin Warren1, Waffo-Teguo Pierre1, Quideau Stephane1 and Marchal Axel1

1UMR ŒNOLOGIE (OENO), UMR 1366, ISVV, University of Bordeaux
2Univ. Bordeaux, ISM (CNRS-UMR 5255)

Contact the author

Keywords

Untargeted approach, Taste-active compounds, Sweetness, Quantitation, ellagitannin

Tags

IVAS 2022 | IVES Conference Series

Citation

Related articles…

Grapevine yield estimation in a context of climate change: the GraY model

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.

Phenological characterization of a wide range of Vitis Vinifera varieties

In order to study the impact of climate change on Bordeaux grape varieties and to assess the adaptation capacities of candidates to the grape varieties of this wine region to the new climatic conditions, an experimental block design composed of 52 grape varieties was set up in 2009 at the INRAE Bordeaux Aquitaine center. Among the many parameters studied, the three main phenological stages of the vine (budburst, flowering and veraison) have been closely monitored since 2012. Observations for each year, stage and variety were carried out on four independent replicates. Precocity indices have been calculated from the data obtained over the 2012-2021 period (Barbeau et al. 1998). This work allowed to group the phenological behaviour of the grapevine varieties, not only based on the timing of the subsequent developmental stages, but also on the overall precocity of the cycle and the total length of the cycle between budburst and veraison. Results regarding the variability observed among the different grape varieties for these phenological stages are presented as heat maps.

Geospatial trends of bioclimatic indexes in the topographically complex region of Barolo DOCG

Barolo DOCG is an economically important wine producing region in Northwest Italy. It is a small region of approximately 70 km2 gross area. The topography is very complex with steep sloped hills ranging in elevation from below 200 m to 550 m. Barolo DOCG wine is made exclusively from the Nebbiolo grape. Bioclimatic indexes are often used in viticulture to gain a better understanding of broader climate trends which can be compared temporally and geographically. These indexes are also used for identifying potential phenological timing, growing region suitability, and potential risks associated with expected climatic changes. Understanding how topography influences bioclimatic indexes can help with understanding of mesoscale climate behaviour leading to improved decision making and risk management strategies. The average monthly maximum and minimum temperatures, the Cool Night Index, the Huglin Index, and the monthly diurnal range (from July to October) were calculated using data from 45 weather stations within a 40 km radius of the Barolo DOCG growing area between the years 1996 and 2019. Linear and multiple regression models were developed using independent variables (elevation, aspect, slope) extracted from a digital elevation model to identify significant relationships. Bioclimatic indexes were then kriged with external drift using independent variables that showed significant relationships with the bioclimatic index using a 100 m resolution grid. The maximum monthly temperatures and the Huglin Index showed consistent significant negative relationships with elevation in all years. The minimum monthly temperatures showed no relationship with elevation but in some months a small but significant relationship was observed with aspect. Due to the lack of a relationship between minimum monthly temperatures and elevation compared to the significant relationship between maximum monthly temperatures and elevation, monthly diurnal range had a negative relationship with elevation.

Long-term drought resilience of traditional red grapevine varieties from a semi-arid region

In recent decades, the scarcity of water resources in agriculture in certain areas has been aggravated by climate change, which has caused an increase in temperatures, changes in rainfall patterns, as well as an increase in the frequency of extreme phenomena such as droughts and heat waves. Although the vine is considered a drought-tolerant specie, it has to satisfy important water requirements to complete its cycle, which coincides with the hottest and driest months. Achieving sustainable viticulture in this scenario requires high levels of efficiency in the use of water, a scarce resource whose use is expected to be severely restricted in the near future. In this regard, the use of drought-tolerant varieties that are able to maintain grape yield and quality could be an effective strategy to face this change. During three consecutive seasons (2018-2020) the behavior in rainfed regime of 13 traditional red grapevine varieties of the Spain central region was studied. These varieties were cultivated in a collection at Centro de Investigación de la Vid y el Vino de Castilla-La Mancha (IVICAM-IRIAF) located in Tomelloso (Castilla-La Mancha, Spain). Yield components (yield, mean bunch and berry weight, pruning weight), physicochemical parameters of the musts (brix degree, total acidity, pH) and some physiological parameters related with water stress during ripening period (δ13C, δ18O) were analysed. The application of different statistical techniques to the results showed the existence of significant differences between varieties in their response to stressful conditions. A few varieties highlighted for their high ability to adapt to drought, being able to maintain high yields due to their efficiency in the use of water. In addition, it was possible quantify to what extent climate can be a determinant in the δ18O of musts under severe water stress conditions.

Impact of climate variability and change on grape yield in Italy

Viticulture is entangled with weather and climate. Therefore, areas currently suitable for grape production can be challenged by climate change. Winegrowers in Italy already experiences the effect of climate change, especially in the form of warmer growing season, more frequent drought periods, and increased frequency of weather extremes.
The aim of this study is to investigate the impact of climate variability and change on grape yield in Italy to provide winegrowers the information needed to make their business more sustainable and resilient to climate change. We computed a specific range of bioclimatic indices, selected by the International Organisation of Vine and Wine (OIV), and correlated them to grape yield data. We have worked in collaboration with some wine consortiums in northern and central Italy, which provided grape yield data for our analysis.
Using climate variables from the E-OBS dataset we investigate how the bioclimatic indices changed in the past, and the impact of this change on grape productivity in the study areas. The climate impact on productivity is also investigated by using high-resolution convection-permitting models (CPMs – 2.2 horizontal resolution), with the purpose of estimating productivity in future emission scenarios. The CPMs are likely the best available option for this kind of impact studies since they allow a better representation of small-scale processes and features, explicitly resolve deep convection, and show an improved representation of extremes. In our study, we also compare CPMs with regional climate models (RCMs – 12 km horizontal resolution) to assess the added value of high-resolution models for impact studies. Further development of our study will lead to assessing the future suitability for vine cultivation and could lead to the construction of a statistical model for future projection of grape yield.