Macrowine 2021
IVES 9 IVES Conference Series 9 Saccharomyces cerevisiae intraspecies differentiation by metabolomic signature and sensory patterns in wine

Saccharomyces cerevisiae intraspecies differentiation by metabolomic signature and sensory patterns in wine

Abstract

AIM: The composition and quality of wine are directly linked to microorganisms involved in the alcoholic fermentation. Several studies have been conducted on the impact of Saccharomyces cerevisiae on volatile compounds composition after fermentation. However, if different studies have dealt with combined sensory and volatiles analyses, few works have compared so far the impact of distinct yeast strains on the global metabolome of the wine.

METHODS: Twelve wines were obtained from fermentations of Chardonnay musts led by twelve different commercial wine yeast strains of S. cerevisiae. In order to establish a possible link between sensory profiles and metabolic signatures, Ultra High Resolution Mass Spectrometry analysis of non-volatile compounds and Gaz Chromatography coupled to Mass Spectrometry detection of volatile compounds, sensory analysis and chemometrics were used in combination.

RESULTS: Wines were clearly discriminated, according to non-volatile, volatile and sensory analyses, despite the similar fermentation kinetics. Three groups of wines, described by similar aromatic descriptors such as fruity, vegetable and apple, were highlighted by the sensory analyses. The profiles of wines from the different groups were characterized based on 35 volatile compounds belonging to esters, medium chain fatty acids, superior alcohols and terpenes. Finally, metabolomics analyses revealed a non volatile composition specific to each wine, with biomarkers specific to each wine yeast strain of S. cerevisiae.

CONCLUSIONS:

The final composition of the wine is intimately linked to the specific production of metabolites by each strains of S. cerevisiae. The combination of analytical and sensory analyses allowed us to discriminate and characterized wines from the twelve strains of S. cerevisiae.

DOI:

Publication date: September 3, 2021

Issue: Macrowine 2021

Type: Article

Authors

Fanny Bordet, Chloé ROULLIER-GALL, Jordi BALLESTER, Régis GOUGEON, Philippe SCHMITT-KOPPLIN, Hervé ALEXANDRE, Anne JULIEN-ORTIZ

University of Bourgogne Franche-Comté, AgroSup Dijon, PAM UMR, Institut Universitaire de la Vigne et du Vin, Jules Guyot, France Lallemand SAS, 19 rue des Briquetiers, Blagnac, France, University of Bourgogne Franche-Comté, AgroSup Dijon, PAM UMR, Institut Universitaire de la Vigne et du Vin, Jules Guyot, France, Centre des Sciences du Goût et de l’Alimentation, AgroSup Dijon, CNRS, INRA, University of Bourgogne Franche-Comté, F-21000 Dijon, France Stephania VICHI, University of Barcelona, Nutrition, Food Science and Gastronomy Department, INSA – XaRTA (Catalonian Reference Network on Food Technology), Santa Coloma de Gramenet, Spain, University of Bourgogne Franche-Comté, AgroSup Dijon, PAM UMR, Institut Universitaire de la Vigne et du Vin, Jules Guyot, France, Lallemand SAS, 19 rue des Briquetiers, Blagnac, France , German Research Center for Environmental Health, Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Neuherberg, Germany, University of Bourgogne Franche-Comté, AgroSup Dijon, PAM UMR, Institut Universitaire de la Vigne et du Vin, Jules Guyot, France

Contact the author

Keywords

yeast saccharomyces cerevisiae-wine- metabolomic-volatile compounds-sensory analysis

Citation

Related articles…

Use of a new, miniaturized, low-cost spectral sensor to estimate and map the vineyard water status from a mobile 

Optimizing the use of water and improving irrigation strategies has become increasingly important in most winegrowing countries due to the consequences of climate change, which are leading to more frequent droughts, heat waves, or alteration of precipitation patterns. Optimized irrigation scheduling can only be based on a reliable knowledge of the vineyard water status.

In this context, this work aims at the development of a novel methodology, using a contactless, miniaturized, low-cost NIR spectral tool to monitor (on-the-go) the vineyard water status variability. On-the-go spectral measurements were acquired in the vineyard using a NIR micro spectrometer, operating in the 900–1900 nm spectral range, from a ground vehicle moving at 3 km/h. Spectral measurements were collected on the northeast side of the canopy across four different dates (July 8th, 14th, 21st and August 12th) during 2021 season in a commercial vineyard (3 ha). Grapevines of Vitis vinifera L. Graciano planted on a VSP trellis were monitored at solar noon using stem water potential (Ψs) as reference indicators of plant water status. In total, 108 measurements of Ψs were taken (27 vines per date).

Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r2cv) of 0.67 and a root mean square error of cross-validation (RMSEcv) of 0.131 MPa. This predictive model was employed to map the spatial variability of the vineyard water status and provided useful, practical information towards the implementation of appropriate irrigation strategies. The outcomes presented in this work show the great potential of this low-cost methodology to assess the vineyard stem water potential and its spatial variability in a commercial vineyard.

Variations of soil attributes in vineyards influence their reflectance spectra

Knowledge on the reflectance spectrum of soil is potentially useful since it carries information on soil chemical composition that can be used to the planning of agricultural practices. If compared with analytical methods such as conventional chemical analysis, reflectance measurement provides non-destructive, economic, near real-time data. This paper reports results from reflectance measurements performed by spectroradiometry on soils from two vineyards in south Brazil. The vineyards are close to each other, are on different geological formations, but were subjected to the same management. The objective was to detect spectral differences between the two areas, correlating these differences to variations in their chemical composition, to assess the technique’s potential to predict soil attributes from reflectance data.To that end, soil samples were collected from ten selected vine parcels. Chemical analysis yield data on concentration of twenty-one soil attributes, and spectroradiometry was performed on samples. Chemical differences significant to a 95% confidence level between the two studied areas were found for six soil attributes, and the average reflectance spectra were separated by this same level along most of the observed spectral domain. Correlations between soil reflectance and concentrations of soil attributes were looked for, and for ten soil traits it was possible to define wavelength domains were reflectance and concentrations are correlated to confidence levels from 95% to 99%. Partial Least Squares Regression (PLSR) analyses were performed comparing measured and predicted concentrations, and for fifteen out of 21 soil traits we found Pearson correlation coefficients r > 0.8. These preliminary results, which have to be validated, suggest that variations of concentration in the investigated soil attributes induce differences in reflectance that can be detected by spectroradiometry. Applications of these observations include the assessment of the chemical content of soils by spectroradiometry as a fast, low-cost alternative to chemical analytical methods.

Impact on leaf morphology of Vitis vinifera L. cvs Riesling and Cabernet Sauvignon under Free Air Carbon dioxide Enrichment (FACE)

Atmospheric carbon dioxide (CO2) concentration has continuously increased since pre-industrial times from 280 ppm in 1750, and is predicted to exceed 700 ppm by the end of 21st century. For most of C3 plant species elevated CO2 (eCO2) improve photosynthetic apparatus results in an increased plant biomass production. To investigate the effects of eCO2 on morphological leaf characteristics the two Vitis vinifera L. cultivars, Riesling and Cabernet Sauvignon, grown in the Geisenheim VineyardFACE (Free Air Carbon dioxide Enrichment) system were used. The FACE site is located at Geisenheim University (49° 59′ N, 7° 57′ E, 94 m above sea level), Germany and was implemented in 2014 comparing future atmospheric CO2-concentrations (eCO2, predicted for the mid-21st century) with current ambient CO2-conditions (aCO2). Experiments were conducted under rain-fed conditions for two consecutive years (2015 and 2016). Six leaves per repetition of the CO2 treatment were sampled in the field and immediately fixed in a FAA solution (ethanol, H2O, formaldehyde and glacial acetic acid). After 24 h leaf samples were transferred and stored in an ethanol solution. Subsequently, leaf tissue was dehydrated using ethanol series and embedded in paraffin. By using a rotary microtomesections of 5 µm were prepared and fixed on microscopic slides. Subsequent the samples were stained using consecutive staining and washing solutions. Afterwards pictures of the leaf cross-sections were taken using a light microscope and consecutive measurements were conducted with an open source image software. Differences found in leaf cross-sections of the two CO2 treatments were detected for the palisade parenchyma. Leaf thickness, upper and lower epidermis and spongy parenchyma remained less affected under eCO2 conditions. The observed results within grapevine leaf tissues can provide first insights to seasonal adaptation strategies of grapevines under future elevated CO2 concentrations.

Phenolic composition of Tempranillo Blanco grapes changes after foliar application of urea

Our research aimed to determine the effect and efficiency of foliar application of urea on the phenolic composition of Tempranillo Blanco grapes. The field experiment was carried out in 2019 and 2020 seasons and the plot was located in D.O.Ca Rioja (North of Spain). The vineyard was Vitis vinifera L. Tempranillo Blanco and grafted on Richter-110 rootstock. The treatments were control (C), whose plants were sprayed with water and three doses of urea: plants were sprayed with urea 3 kg N/ha (U3), 6 kg N/ha (U6) and 9 kg N/ha (U9). The applications were performed in two phenological stages, pre-veraison (Pre) and veraison (Ver). Also, each of the treatments was repeated one week later. Control and treatments were performed in triplicate and arranged in a randomised block design. Grapes were harvested at optimum ripening stage. High-performance liquid chromatography was used to analyse the phenolic composition of the grapes. Finally, the results obtained from the analytical determinations – flavonols, flavanols and non-flavonoid (hydroxybenzoic acids, hydroxycinnamic acids and stilbenes) – were studied statistically by analysis of variance. The results showed that, in 2019, U6-Pre and U9-Pre treatments increased the hydroxybenzoic acid content in grapes, and also all foliar treatments applied at Pre enhanced the stilbene concentration. Moreover, U3-Ver was the only treatment that rose flavonol and stilbene contents in the Tempranillo Blanco grapes. In 2020, all treatments applied at Pre enhanced the flavonol concentration in grapes. Furthermore, U3-Pre and U9-Pre treatments increased stilbene content in grapes. Nevertheless, the hydroxybenzoic acid content was improved by U6-Ver and U9-Ver and besides, hydroxycinnamic acid concentration in grapes was increased by all treatments applied at Ver. In conclusion, the lower and highest dose of urea (U3 and U9), applied at pre-veraison, were the best treatments to improve the Tempranillo Blanco grape phenolic composition.

Estimating bulk stomatal conductance of grapevine canopies

In response to changes in their environment, grapevines regulate transpiration using various physiological mechanisms that alter conductance of water through the soil-plant-atmosphere continuum. Expressed as bulk stomatal conductance at the canopy scale, it varies diurnally in response to changes in vapor pressure deficit and net radiation, and over the season to changes in soil water deficits and hydraulic conductivity of both soil and plant. It is necessary to characterize the response of conductance to these variables to better model how vine transpiration also responds to these variables. Furthermore, to be relevant for vineyard-scale modeling, conductance is best characterized using data collected in a vineyard setting. Applying a crop canopy energy flux model developed by Shuttleworth and Wallace, bulk stomatal conductance was estimated using measurements of individual vine sap flow, temperature and humidity within the vine canopy, and estimates of net radiation absorbed by the vine canopy. These measurements were taken on several vines in a non-irrigated vineyard in Bordeaux France, using equipment that did not interfere with ongoing vineyard operations. An inverted Penman-Monteith equation was then used to calculate bulk stomatal conductance on 15-minute intervals from July to mid-September 2020. Time-series plots show significant diurnal variation and seasonal decreases in conductance, with overall values similar to those in the literature. Global sensitivity analysis using non-parametric regression found transpiration flux and vapor pressure deficit to be the most important input variables to the calculation of bulk stomatal conductance, with absorbed net radiation and bulk boundary layer conductance being much less important. Conversely, bulk stomatal conductance was one of the most important inputs when calculating vine transpiration, further emphasizing the need for characterizing its response to environmental changes for use in vineyard water use modeling.