Antioxidant activity

Antioxidant scavenging activity was studied using the DPPH⁺ free radical as described by Blois [10] and the ABTS⁺⁻ free radical as described by Re et al. [11]. The capacity of free radical scavenging was expressed by IC50 (mg/L) value, which represents the concentration required to scavenge 50% of free radicals. The best antioxidant wines present the lowest IC50 values.

Chemical analysis

Total phenolic compounds, flavonoids, tannins and anthocyanins were determined respectively by Folin-Ciocalteu, Arvouet-Grand, Broadhurst and Cheng methods (for more information and references, [12]). The results are respectively expressed in gallic acid, quercetin, catechin and cyanidin-3-glucoside equivalent mg/L of wine.

HPLC analyses for quercetin and resveratrol were performed using an Agilent chromatographic system equipped with an UV-Vis diode-array detector. Samples were injected in a Zorbax Eclipse column maintained at 35°C.

Sensory analysis

Sensory analyses were performed by a panel of 20 experienced tasters at room temperature 20°C. 100 mL of wine were presented in the INAO standard tasting glasses identified by random code numbers.

Results and discussion

The antioxidant scavenging activity has been quantified using the DPPH and ABTS tests. Wines A3, B3, A5 and B5 presented the best antioxidant activities, *ie* the lowest IC₅₀ (Figure 1). Antioxidant activity was revealed with wines produced with a hot maceration before (A3, B3) or after fermentation (A5, B5), whatever the presence of enzymes. These results suggested that hot maceration gave the best antioxidant activity to wine. Wines A1 and B1 presented the lowest antioxidant activity, suggesting that classical alcoholic fermentation with punching gave the smallest antioxidant activity to wine.

<figure><img src="image_396.png" /><figcaption>**Fig. 1** - Effect of winemaking processes on wine antioxidant activity (DPPHª and ABTSᵇ Tests, IC50 (mg/L)) compared to classical alcoholic fermentation without enzymes (A1) used as external reference, standard error less than 10%.</figcaption></figure>

Highest value of total polyphenols, anthocyanins and tannins was obtained for wines A3 and B3 (Figure 2). The highest value of flavonoids was for wine A3. These results suggested that hot maceration before fermentation allowed better extraction of the four families of compounds. Lowest values of flavonoids, anthocyanins and tannins were obtained with wines A4 and B4, suggesting that cold maceration after fermentation extracted the least of these three classes of compounds. Winemaking processes significantly altered both chemical composition and antioxidant properties of wine [12].

PCA analysis between winemaking processes, chemical composition and antioxidant activities of wines revealed that the activity of hot macerated wines A3, B3 and A5, B5 appeared to be supported respectively by total polyphenols and flavonoids (Figure 3). These results suggested that flavonoids present in wines obtained with hot maceration after fermentation presented a strong antioxidant activity.
<figure><img src="image_397.png" /><figcaption>**Fig. 2** - Effect of winemaking processes on chemical composition compared to classical alcoholic fermentation without enzymes (A1) used as external reference, standard error less than 10%.</figcaption></figure>

<figure><img src="image_398.png" /><figcaption>**Fig. 3** - Effect of winemaking processes on chemical composition. PCA analysis F1 (83.2%) and F2 (10.1%): 93.3%.</figcaption></figure>

PCA analysis between winemaking processes and sensory analysis revealed that hot macerated wines before fermentation (A3, B3) or after fermentation (A5, B5), with enzymes or not, presented the best colored, aromatic, tannic and overall wines (Figure 4).

<figure><img src="image_399.png" /><figcaption>**Fig. 4** - Effect of winemaking processes on sensory analysis. PCA analysis F1 (56.3%) and F2 (18.5%): 74.8%.</figcaption></figure>

Hot macerated A3 wine was treated with condensed or hydrolysable tannins (A3C, A3H) or a mixture of both (A3CH, Figure 5). The presence of condensed tannins increased the amount of resveratrol but decreased the concentration of quercetin. Quercetin presence seemed to be in opposition to that of resveratrol.
<figure><img src="image_400.png" /><figcaption>Fig. 5 - Effect of condensed or hydrolysable tannins on quercetin and resveratrol concentrations, standard error less than 10%.</figcaption></figure>

## Conclusion

The information yielded can be used to obtain wines with maximum “French paradox” capacities and sensory properties. Wines obtained with hot maceration before or after fermentation presented the best antioxidant and sensory properties. These properties seemed to be due to the presence of total polyphenols and flavonoids. The effect of enzymes was negligible. Condensed tannins increased the amount of resveratrol but decrease that of quercetin. In order to increase both polyphenol contents, antioxidant activity and sensory properties, the impact of grapes varieties within *Vitis labrusca* has to be done.

## Acknowledgements

The authors would like to thank the Dept of Wine and Food Fermentation Technology of Young-Dong University for their financial support.

## Abbreviations

DPPH, 2,2-diphenyl-1-picrylhydrazyl; ABTS, 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid); PCA, Principal component analysis.

## References

1. St Leger AS, Cochrane AL, Moore F (1979) Factors associated with cardiac mortality in developed countries with particular reference to the consumption of wine. *Lancet* **1**: 1017-1020.

2. Renaud S, de Lorgeril M (1992) Wine, alcohol, platelets, and the French paradox for coronary heart disease. *Lancet* **339**: 1523-1526.

3. Di Castelnuovo A, Rotondo S, Iacoviello L et al (2002) Meta-analysis of wine and beer consumption in relation to vascular risk. *Circulation* **105**: 2836-2844.

4. Pedersen A, Johansen C, Grønbaek M (2003) Relations between amount and type of alcohol and colon and rectal cancer in a Danish population based cohort study. *Gut* **52**: 861-867.

5. Barstad M, Sørensen TI, Tjønneland A et al (2005) Intake of wine, beer and spirits and risk of gastric cancer. *Eur J Cancer Prev* **14**: 239-243.

6. Chao C (2007) Associations between beer, wine, and liquor consumption and lung cancer risk: a meta-analysis. *Cancer Epidemiol Biomarkers Prev* **16**: 2436-2447.

7. Lanzman-Petithory D (2009) Consommation de boissons alcoolisées (vin, bière et alcools forts) et mortalité par différents types de cancers sur une cohorte de 100 000 sujets suivie depuis 25 ans, pp 30-34. *In Colloque de Cloture du PNRA*, 10-12 mars 2009, www.agence-nationale-recherche.fr/fileadmin/user_upload/documents/uploaded/2009/BOOK-PNRA-2005.pdf.

8. He S, Sun C, Pan Y (2008) Red wine polyphenols for cancer prevention. *Int J Mol Sci* **9**: 842-853.

9. Arranz S, Chiva-Blanch G, Valderas-Martinez P et al (2012) Wines, beer, alcohol and polyphenols on cardiovascular disease and cancer. *Nutrients* **4**: 759-781.

10. Blois MS (1958) Antioxidant determinations by the use of a stable free radical. *Nature* **181**: 1199-1200.

11. Re R, Pellegrini N, Proteggente A et al (1999) Antioxidant activity applying an improved ABTS radical cation decolorization assay. *Free Radic Biol Med* **26**: 1231-1237.

12. Yvon Y, Bouajila J, Cazaux S et al (2012) Investigations on chemical composition of French wines (southwest) and its antioxidant activity: effect of winemaking processes and grape varieties on wine quality. *In Oeno 2011*, Dunod Paris, pp 620-625.
# Impact of maceration time and temperature on the extraction and evolution of polyphenols in Lebanese musts

C. GHANEM¹,², P. TAILLANDIER³,⁴, L.H. WAKIM¹, Z. RIZK¹,², N. NEHME⁵, J.P. SOUCHARD⁴,⁶, Y. EL RAYESS¹,⁴*

¹Faculty of Agricultural and Food Sciences, Holy Spirit University of Kaslik, Jounieh, Lebanon

²Lebanese Agricultural Research Institute, Fanar Station, P.O. Box 90-1965, Jdeidet El-Metn, Fanar, Lebanon

³Université de Toulouse, INPT, UPS, CNRS, Laboratoire de Génie Chimique, 4 Allée Emile Monso, F-31432 Toulouse, France

⁴Centre de Viticulture et d'Œnologie de Midi-Pyrénées, Avenue de l'Agrobiopôle, 31320 Castanet-Tolosan, France

⁵Faculty of Agricultural Engineering and Veterinary Medicine, Lebanese University, Dekwaneh, Lebanon

⁶Laboratoire des Interactions Moléculaires et Réactivité Chimique et Photochimique UMR CNRS 5623, Université de Toulouse, 118 Route de Narbonne, F-31062 Toulouse Cedex 9, France

Phenolic compounds – antioxidant activity – Lebanese wine – maceration

## Introduction

Lebanon's wine industry has hit booms and busts since 2000. In 2012, the Lebanese production was estimated to 8 million bottles. In the literature, studies on the Lebanese wines are scarce. Therefore, we aim to introduce scientific knowledge to improve the quality and safety of products and the productivity of the sector.

A better understanding of the phenolic composition of Lebanese wines, their biological activities and the parameters influencing their extraction and evolution allows Lebanon to present on the international markets the most interesting products for the pleasure and the health of the consumer.

During winemaking, phenolic compounds contained in the grapes are transferred to the wine by diffusion due to the contact between the juice and the solid part of the grapes. The diffusion period called maceration can be affected by several factors such as grape variety and maturity, temperature of must or wine, contact duration between juice and grape skin and seeds, concentration of alcohol and sulfur dioxide and use of enzymes.

This study focuses on measuring the incidence of maceration, the first step of red winemaking, on wine polyphenols. It evaluates the impact of maceration time (0, 2, 4, 8, 24 and 48 hours) and temperature (10, 60 and 80°C) on the content and evolution of the phenolic compounds in musts prepared from two grape varieties: Syrah and Cabernet Sauvignon.

## Materials and methods

### *Samples*

Red grapes of *Vitis vinifera* var. Cabernet Sauvignon (CS) and Syrah (Sy) were supplied by Chateau St Thomas (West Bekaa/Lebanon). Grapes were harvested in 2014 at maturity (Brix = 20.53 and 23.56; titratable acidity = 4.4 and 3.7 g/l as sulfuric acid for Sy and CS, respectively). After reception of the grapes they were crushed, destemmed and sodium metabisulfite was added (5 g of SO₂/100 kg). The pre-fermentative maceration was conducted at different temperatures (10, 60, and 80°C) for 48 hours. All macerations were carried out in triplicate.
### Spectrophotometric determinations

The color density (CD) was determined by summing the absorbances at 420 and 520 nm [1]. Total polyphenol index was determined following the method described by Ribéreau-Gayon et al. [2]. Total anthocyanins were calculated by measuring the absorbance at 520 nm after treatment with bisulfite bleaching solution. Total anthocyanin concentration was expressed in mg/l as described by Ribéreau-Gayon and Stonestreet [3]. Total tannins were determined by measuring the absorbance at 550 nm after acid hydrolysis of the samples and the utilization of blank. Total tannin concentration was expressed in mg/l as described by Ribéreau-Gayon and Stonestreet [4]. Total phenolics were determined according to the Folin-Ciocalteu colorimetric method [5] and the results were expressed as gallic acid equivalent (mg GAE/l).

ABTS radical scavenging activity of musts was measured by the ABTS cation decolorization assay as described by Re et al. [6]. Vitamin C was used as a reference compound. The results were expressed as total polyphenols equivalent (mg GAE/l).

### HPLC analysis of phenolic compounds

The HPLC analyses were performed using a Shimadzu chromatographic system equipped with a quaternary pump (LC-20AD), an UV-Vis diode-array detector (SPD-M20A), an automatic injector (SIL-20A) and Shimadzu LC solution software. Samples (20µl injection volume) previously filtered through a 0.45µm cellulose acetate membrane (Greyhound Chromatography and Allied Chemicals, England) were injected in a Shim-pack VP-ODSC18 column (250\*4.6 mm, 5µm particle size) protected with a guard column of the same material (10 mm x 4.6 mm, 5µm particle size) maintained at 40°C. All analyses were made in triplicate. The anthocyanin identification was performed according to the method described by Heredia et al. [7] with some modifications. Acetonitrile/acetic acid/water (3:10:87, v/v/v) were used as solvent A and acetonitrile/acetic acid/water (50:10:40, v/v/v) were used as solvent B at a flow rate of 0.6 ml/min. The elution profile was as follows: 0-10 min 90% A-10% B; 10-13 min 85% A-15% B; 13-20 min 75% A-25% B; 20-40 min 45% A-55% B; 40-43 min 100% B followed by washing and re-equilibration of the column. Quantification of flavan-3-ols and phenolic acids was performed following the method described by Ducasse et al. [8] with modifications. The elution conditions were as follows: 0.6 ml/min flow rate, acetonitrile/acetic acid (97:3 v/v) as solvent A, and acetic acid/water (3:97, v/v) as solvent B. The elution profile consisted of 100% B for 0-25 min, 40% A-60% B for 25-45 min; 90% A-10% B for 45-55 min, then washing and re-equilibration of the column. Chromatograms were recorded at 520, 280 and 320 nm for anthocyanins, flavan-3-ols and phenolic acids, respectively. Individual calibration curves were obtained for standards bought from Extrasynthese and the concentrations were expressed as mg/l.

### Statistical data treatment

Analysis of variance (ANOVA) and Principal Components Analysis (PCA) were conducted using Xlstat software (2009).

## Results and discussion

### Influence of maceration temperature and time on must composition

According to the kinetics of extraction, the two grape varieties showed the same profile at the same temperatures with differences in the concentrations due to grape variety and maturity. The release of anthocyanins was hugely affected by the temperature (Figure 1). When macerating at 10°C, the anthocyanin concentration increased slightly during 48 hours to reach a total of 193.4 mg/l for CS and 129.8 mg/l for Sy. At 60°C, a gradual increase in the anthocyanin concentration was observed and reached a maximum at 24 hours. The maximum concentrations of anthocyanins were 837 mg/l and 634 mg/l for CS and Sy, respectively. A slight decrease was observed when heating up to 48 hours and the concentrations reached were 725 mg/l and 544 mg/l for CS and Sy, respectively. The results of the maceration at 80°C showed a sharp increase in the concentrations of anthocyanins for both varieties and reached a maximum level at around 4 hours. The maximum concentration was 923 mg/l for CS and 680 mg/l for Sy. After 4 hours of maceration, a net decrease in the anthocyanin levels was observed. The concentrations were reduced by 7-fold. The rate and the level of extraction were higher at 80°C because the high temperatures weakened the cell walls thus increasing the diffusion of the components from the cells to the musts [9]. The color density did not follow the same logic or kinetics as anthocyanins. For example, the maceration at 80°C showed values of CD higher than the other temperatures after 48 hours. HPLC analysis showed that malvidin-3-O glucoside was the most represented anthocyanin in the musts of both varieties and at different temperatures; its kinetics followed the same logic as total anthocyanins.
<figure><img src="image_401.png" /><figcaption>**Fig. 1** - Evolution of the anthocyanin concentration during maceration time and temperature for the Syrah (Sy) and Cabernet Sauvignon (CS) grape musts.</figcaption></figure>

The extraction of tannins was favored by temperature. At 60°C, the concentration of tannins was doubled compared to 10°C. Tannins showed a maximum extraction at 24 hours with maximum values of 8.4 g/l and 9.2 g/l for Sy and CS, respectively (Figure 2). Tannins were less affected by high temperatures than anthocyanins. Epigallocatechin was the most extracted tannin monomer (1266 mg/l for CS). Total polyphenol index showed an increase with the maceration time and the temperature. According to the results of PCA (Figure 3), the total polyphenol index was more correlated to tannins than to anthocyanins. HPLC analysis of flavan-3-ols and phenolic acids showed that the concentrations of flavan-3-ols and phenolic acids increased with maceration time and temperature with the exception of gallic acid that decreased with time. All grape musts tested in this study showed an evident antioxidant effect which was the highest at 60°C for Sy (IC50 2.95 mg/l) and for CS (IC50 2 mg/l). PCA results showed that tannins and phenolic acids (except for gallic acid) were positively correlated to the antioxidant activity.

<figure><img src="image_402.png" /><figcaption>**Fig. 2** - Evolution of the tannin concentration during maceration time and temperature with Syrah (Sy) and Cabernet Sauvignon (CS) musts.</figcaption></figure>
<figure><img src="image_403.png" /><figcaption>Fig. 3 - Biplot of the two principal components of Cabernet Sauvignon musts obtained from phenolic compounds.</figcaption></figure>

## Conclusion

The results obtained showed that the technique of pre-fermentative maceration increased the phenolic compound concentration and the antioxidant activity of musts according to the maceration temperature and time. Maceration at high temperatures enabled a rapid extraction of anthocyanins with maximum values reached after 4 and 24 hours of maceration at 80°C and 60°C, respectively. The extraction of tannins was more regular and increased with maceration time and temperature. The results showed that it would be more interesting to perform maceration at 80°C for 4 hours in order to maintain an optimum ratio between anthocyanins and tannins, good color stabilization and to optimize the structure and complexity of the must.

## Acknowledgements

The authors would like to thank LARI (Lebanese Agricultural Research Institute) for their financial support and Chateau St Thomas for supplying the grapes.

## References

1. Glories Y (1984) La couleur des vins rouges, lère partie : les équilibres des anthocyanes et des tanins. *Conn Vigne Vin* **18**: 195-217.

2. Ribéreau Gayon P, Dubourdieu D, Donèche B et al (1998) *Traité d'œnologie 2. Chimie du vin. Stabilisation et traitements*. Dunod, Paris, France.

3. Ribéreau-Gayon P, Stonestreet E (1965) Le dosage des anthocyanes dans le vin rouge. *Bull Soc Chim Fr* **9**: 2649-2652.

4. Ribéreau-Gayon P, Stonestreet E (1966) Dosage des tanins du vin rouge et détermination de leur structure. *Chim Anal* **48**: 188-196.

5. Ribereau-Gayon J, Peynaud E, Sudraud P et al (1972) *Sciences et techniques du vin*. Paris: Dunod.

6. Re R, Pellegrini N, Proteggente A et al (1999) Antioxidant activity applying an improved ABTS radical cation decolorization assay. *Free Radic Biol Med* **26**: 1231-1237.

7. Heredia FJ, Escudero-Gilete ML, Hermanz D et al (2010) Influence of the refrigeration technique on the colour and phenolic composition of syrah red wines obtained by pre-fermentative cold maceration. *Food Chem* **118**: 377-383.

8. Ducasse MA, Canal-Llauberes RM, de Lumley M et al (2010) Effect of macerating enzyme treatment on the polyphenol and polysaccharide composition of red wines. *Food Chem* **58**: 11333-11339.

9. Koyama K, Goto-Yamamoto N, Hashizume K (2007) Influence of maceration temperature in red wine vinification on extraction of phenolics from berry skins and seeds of grape (*Vitis vinifera*). *Biosci Biotechnol Biochem* **71**: 958-965.
# The effect of different oak treatments on the phenolic composition of red wines

B. ÖZTÜRK<fnref n="1" />, R.E. ANLI<fnref n="2" />*

Red wine – phenols – oak barrel – ageing

## Introduction

Phenolic compounds are the secondary metabolites found in the plant structure. They are produced by the essential aminoacid phenylalanine via the phenylpropanoid pathway aiming at various goals like protection of the plant from the UV light and harmful microorganisms, pigmentation, etc [1].

The wines that completed fermentation are decanted, aiming at separating insoluble materials, and are aged for a length of time with the aim of revealing and stabilising their characteristics. Ageing is carried out either in neutral containers like stainless steel and concrete tank or in wooden barrels improving the chemical and sensory characteristics of wines [2].

The amount and diversity of the phenolic compounds in wine vary depending on different factors. One of the most important factors is barrel ageing, which is the latest stage of wine production [1, 3]. Several complex chemical changes occur in the course of barrel ageing of wine, such as colour stabilisation and softening of the taste as a result of polymerisation and precipitation of phenolic compounds, especially tannins and anthocyanins. The barrel makes great contribution to wine by allowing trace amount of oxygen into the wine and adding woody character to different extents depending on the source, level of toasting and age of the barrel [2].

Substantial amount of barrel-originated phenolics (basically ellagitannins) are extracted into the wine in the course of barrel ageing [4]. Barrel ageing is a commonly used technique in winemaking practices, since it increases the durability and health benefits of wine by increasing the colour intensity & stability and antioxidant capacity and improving the sensory quality [5].

The goal of this research is to monitor the changes in the phenolic composition of certain red wines aged in barrels of different sources and ages. The wines from Merlot and Cabernet Franc grapes were aged in barrels of different ages from French and American oak for 4 months and the phenolic composition was monitored throughout the ageing process.

## Materials and methods

### Materials

Seven 2014 vintage single-variety dry red wines from Merlot and Cabernet Franc grape varieties of *Vitis vinifera* cv. were studied in this research. These wines were supplied from a winery located in Şarköy, Tekirdağ city (Turkey). Grapes were harvested and processed by traditional red vinification technique. Both alcoholic and malolactic fermentation took place in the wooden barrels then the wines were racked and transferred into the different oak barrels as stated in the previous paragraph. The basic chemical parameters of the studied wines are reported in Table 1.

One group Merlot (Me1) wine samples were stored in new and 3-year-old American and French oak barrels with the same toasting level (M+). The other group Merlot (Me2) wine samples were stored in new and 1-year-old oak barrels from the same origin (French). Cabernet Franc (CF) wines were stored in new and 1-year-old oak barrels from the same origin (French-Vosges) and toasting level (M+). All the samples were stored under the same conditions of humidity (75%) and temperature (14°C) in the cellar for 4 months.

<footnote n="1">¹Namık Kemal University Şarköy Vocational School, Wine Production Technologies Programme, 59800, Şarköy/Tekirdağ, Turkey</footnote>

<footnote n="2">²Ankara University Engineering Faculty, Food Engineering Department, 06110, Dışkapı/Ankara, Turkey</footnote>

<footnote>*Corresponding author: anli@eng.ankara.edu.tr</footnote>
<table><caption>**Table 1** - Chemical parameters of wine samples before ageing</caption><thead><tr><th rowspan="2">Wine sample</th><th>Density</th><th>Ethanol<br>(v/v %)</th><th>Reducing<br>sugar (g/L)</th><th>Titratable<br>acidity (g/L)</th><th>Volatile<br>acidity (g/L)</th><th>pH</th></tr><tr><th>Mean±S.D.</th><th>Mean±S.D.</th><th>Mean±S.D.</th><th>Mean±S.D.</th><th>Mean±S.D.</th><th>Mean±S.D.</th></tr></thead><tbody><tr><td>Merlot</td><td>0,99±0,01</td><td>13,4±0,11</td><td>2,5±0,02</td><td>5,8±0,01</td><td>0,35±0,05</td><td>3,5±0,01</td></tr><tr><td>Cabernet Franc</td><td>0,99±0,02</td><td>14,5±0,05</td><td>1,8±0,01</td><td>4,7±0,03</td><td>0,27±0,10</td><td>3,7±0,04</td></tr></tbody></table>

*Methods*

The wine samples under investigation were analysed for titratable and volatile acidity, alcohol level, free SO₂ level and reducing sugar content by using the analytical methods recommended by the OIV [6]. Wine colour was measured directly at 420, 520 and 620 nm by spectrophotometer [7].

Total phenol and tannin contents of the wine samples were determined by means of Folin-Ciocalteu micro method, a method derived from total phenol analysis and Folin-Denis method (AOAC 952.03), respectively [8, 9]. The monomeric and total anthocyanin concentrations of wines were measured using AOAC 2005.02 pH differential method and modified Somers assay, respectively [10].

**Results and discussion**

Basic chemical (oenological) characteristics of wine samples studied are shown in Table 2. All the chemical parameters of wine samples analysed are within the legal limitations in force [11, 12].

As far as the phenolic profile is concerned, Merlot wine stored in the French oak barrel has higher phenolic concentration together with total and monomeric anthocyanin content than the American oak aged wine. On the other hand, the wine stored in 3-year-old barrel showed low phenolic profile except total anthocyanin amounts (Table 3).

<table><caption>**Table 2** - Oenological characteristics of wine samples after four months of barrel treatment</caption><thead><tr><th rowspan="2">Oenological<br>Characteristic</th><th colspan="7">Wine<br>Samples</th></tr><tr><th>Me1-F</th><th>Me1-A</th><th>Me1-3</th><th>Me2-0</th><th>Me2-1</th><th>CF-0</th><th>CF-1</th></tr></thead><tbody><tr><td>Ethanol (%v/v)</td><td>13,67±0,06</td><td>13,67±0,15</td><td>13,37±0,15</td><td>14,47±0,23</td><td>14±0,44</td><td>14,17±0,12</td><td>14,13±0,21</td></tr><tr><td>Reducing sugar<br>(g/L)</td><td>2,41±0,03</td><td>2,27±0,04</td><td>2,49±0,12</td><td>2,35±0,10</td><td>2,47±0,14</td><td>2,12±0,03</td><td>1,90±0,14</td></tr><tr><td>Titratable acidity<br>(g TA/L)<sup>a</sup></td><td>5,75±0,12</td><td>5,81±0,09</td><td>5,48±0,13</td><td>5,25±0,07</td><td>5,64±0,06</td><td>4,5±0,05</td><td>4,3±0,11</td></tr><tr><td>Volatile acidity<br>(g AA/L)<sup>b</sup></td><td>0,44±0,02</td><td>0,37±0,03</td><td>0,33±0,03</td><td>0,42±0,02</td><td>0,45±0,02</td><td>0,48±0,02</td><td>0,42±0,03</td></tr><tr><td>Free SO<sub>2</sub> (mg/L)</td><td>24,96±0,64</td><td>20,27±0,37</td><td>24,11±0,37</td><td>24,53±0,33</td><td>33,52±0,46</td><td>26,45±0,47</td><td>37,12±0,69</td></tr></tbody></table>

As for the difference between the new and 1-year-old barrel effect on wine, total phenol content and degree of anthocyanin ionisation of wine samples stored in 1-year-old barrels was higher than that of the wines stored in new barrels. Furthermore, regarding total and monomeric anthocyanin contents, it is observed that the wines stored in new barrels have higher anthocyanin content.

The colour profile results of wine samples support the phenolic profile, since the wines treated with American oak barrel have higher colour intensity and hue than those treated with French oak barrels. This result proves the direct relationship between colour intensity and polymeric anthocyanin amounts and also ionisation degree of anthocyanins. Similarly, the wines stored in 1-year-old barrel have higher colour intensity with lower monomeric anthocyanin content than the wines stored in new barrels. The SO₂ resistant pigments increase with the polymerisation of the anthocyanins [13]. The degree of anthocyanin polymerisation and SO₂ resistant pigments are reported to be lower in the wines stored in French oak barrels (Table 3).

<footnote><sup>a</sup>Expressed as tartaric acid (TA), <sup>b</sup>expressed as acetic acid (AA), Me1-F: wine from Merlot grape treated with French oak barrel, Me1-A: wine from Merlot grape treated with American oak barrel, Me1-3: wine from Merlot grape treated with 3-year-old French oak barrel, Me2-0: wine from Merlot grape treated with new oak barrel, Me2-1: wine from Merlot grape treated with 1-year-old oak barrel, CF-0: wine from Cabernet Franc grape treated with new French-Vosges oak barrel, CF-1: wine from Cabernet Franc grape treated with 1-year-old French-Vosges oak barrel</footnote>
<table><caption>**Table 3 - Phenolic characteristics and colour parameters of wine samples**</caption><thead><tr><th rowspan="2">Oenological<br>Characteristic</th><th colspan="7">Wine<br>Samples</th></tr><tr><th>Me1-F</th><th>Me1-A</th><th>Me1-3</th><th>Me2-0</th><th>Me2-1</th><th>CF-0</th><th>CF-1</th></tr></thead><tbody><tr><td>Total phenol<br>(mg GA/L)<sup>a</sup></td><td>2574,67±77</td><td>2437,67±30</td><td>2175±49</td><td>1960±44</td><td>2078±44</td><td>1390,33±32</td><td>1498,33±19</td></tr><tr><td>Total tannins<br>(mg TA/L)<sup>b</sup></td><td>15,42±0,06</td><td>18,52±0,57</td><td>9,41±0,21</td><td>17,17±0,64</td><td>16,72±0,14</td><td>14,11±0,51</td><td>15,23±0,21</td></tr><tr><td>Monomeric<br>anthocyanins<br>(mg M-3-g/L)<sup>c</sup></td><td>96,92±1,34</td><td>70,77±0,11</td><td>66,46±1,80</td><td>76,08±0,91</td><td>32,60±0,04</td><td>84,41±0,44</td><td>27,08±0,74</td></tr><tr><td>Total<br>anthocyanins<br>(mg/L)</td><td>255,71±6,59</td><td>224,05±25</td><td>265,48±4,24</td><td>312,66±5,30</td><td>289,96±39</td><td>347,29±7,43</td><td>304,91±50</td></tr><tr><td>Degree of<br>ionisation of<br>anthocyanins<br>(%)</td><td>21,77±1,33</td><td>25,02±6,94</td><td>23,32±0,56</td><td>22,10±0,86</td><td>28,12±9,61</td><td>18,80±3,63</td><td>22,03±0,09</td></tr><tr><td>SO<sub>2</sub> resistant<br>pigments</td><td>1,88±0,03</td><td>1,96±0,14</td><td>1,91±0,10</td><td>3,42±0,10</td><td>3,64±0,47</td><td>2,11±0,17</td><td>2,45±0,08</td></tr><tr><td>Colour intensity</td><td>4,34±0,02</td><td>4,46±0,03</td><td>4,07±0,03</td><td>4,18±0,02</td><td>4,76±0,03</td><td>4,25±0,02</td><td>4,55±0,02</td></tr><tr><td>Hue</td><td>0,93±0,01</td><td>0,94±0,01</td><td>0,93</td><td>0,89±0,09</td><td>0,94±0,01</td><td>0,93</td><td>0,94±0,01</td></tr><tr><td>Yellow %</td><td>0,38±0,02</td><td>0,37±0,02</td><td>0,37</td><td>0,33</td><td>0,34</td><td>0,35</td><td>0,35</td></tr><tr><td>Red %</td><td>0,41</td><td>0,39</td><td>0,40</td><td>0,36</td><td>0,38±0,04</td><td>0,38</td><td>0,38</td></tr><tr><td>Blue %</td><td>0,22</td><td>0,24</td><td>0,23</td><td>0,30</td><td>0,29±0,04</td><td>0,26</td><td>0,27</td></tr></tbody></table>

## Conclusion

The results obtained in this research suggest that the origin and age of the barrel has a significant effect on phenolic profile of red wines. The changes in phenolic composition of the wines aged in barrel result from the phenolic components extracted from barrel that react with the wine phenols along with the polymerisation and copigmentation of the anthocyanins with the help of the oxygen that penetrated through the barrel tissue. The amount of phenols extracted from the barrel depends on the origin and age of the barrel. The oak type also has a significant effect on the degree of polymerisation of anthocyanins since each wood type has distinctive grain and pore size [14]. As summary, the effect of French oak on phenol concentration is higher than that of American oak. In addition, as a result of pore structure (oxygen allowance), it is determined that French oak barrel has lower effect on anthocyanin polymerisation & ionisation and SO₂ resistance, thus the wines in French barrels have higher monomeric anthocyanin concentration. As a result of this study it is also detected that 1-year-old barrel has higher effect then new barrel on phenolics, anthocyanin ionisation and colour intensity. The sample wines will be chromatographically searched for detailed phenolic information in the subsequent part of the research. On the other hand, for more accurate results longer period of barrel ageing is necessary.

## Acknowledgements

The authors would like to thank to the wine supplier MEY Spirits, Kayra Winery for their share on this research study.

## References

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2. Jackson RS (2008) *Wine Science Principles and Applications*, Academic Press imprint of Elsevier; pp 281-300, Canada-USA.

3. Vázquez EV, Segade SR, Fernández IO (2010) Effect of the winemaking technique on phenolic composition and chromatic characteristics in young red wines. *Eur Food Res Technol* **231**: 789-802.

4. Arfelli G, Sartini E, Corzani C et al (2007) Impact of wooden barrel storage on the volatile composition and sensorial profile of red wine. *Food Sci Technol Int* **13**: 293-299.

<footnote>a expressed as gallic acid (GA), b expressed as tannic acid (TA), c expressed as malvidin-3-glycoside (M-3-g)</footnote>
5. Alañón ME, Castro-Vazquez L, Diaz-Maroto MC et al (2011) A study of the antioxidant capacity of oak wood used in wine ageing and the correlation with polyphenol composition. *Food Chem* **128**: 997-1002.

6. OIV (1990) *Recueil des méthodes internationales d'analyse des vins et des moûts*. Office International de la Vigne et du Vin, Paris.

7. Glories Y (1984) La couleur des vins rouges. 2e partie. Mesure, origine et interprétation. *Conn Vigne Vin* **18**: 253-271.

8. Slinkard K, Singleton VL (1977) Total phenol analysis: automation and comparison with manual methods. *Am J Enol Vitic* **28**: 49-55.

9. Horwitz W (1970) *Official Methods of Analysis of the Association of Official Analytical Chemists*, 11th Edition, AOAC, Washington, DC.

10. Mercurio MD, Dambergs RG, Herderich MJ et al (2007) High throughput analysis of red wine and grape phenolics adaptation and validation of methyl cellulose precipitable tannin assay and modified Somers color assay to a rapid 96 well plate format. *J Agric Food Chem* **55**: 4651-4657.

11. Turkish Food Codex, Wine Legislation (Legislation Number: 2008/67).

12. Turkish Standard, Wines, TS 521/January 1976, UDK663. 2/3.

13. Gambuti A, Capuano R, Lisanti MT et al (2010) Effect of aging in new oak, one-year-used oak, chestnut barrels and bottle on color, phenolics and gustative profile of three monovarietal red wines. *Eur Food Res Technol* **231**: 455-465.

14. Espitia-López J, Escalona-Buendia HB, Luna H et al (2015) Multivariate study of the evolution of phenolic composition and sensory profile on mouth of Mexican red Merlot wine aged in barrels vs wood chips. *J Food* **13**: 26-31.
# Phenolic oxidation in red Port wine

C.M. OLIVEIRA<fnref n="1" />,<fnref n="2" />*, A.C. LOPES CARDOSO<fnref n="3" />, A. BARROS<fnref n="1" />, A.C. SILVA FERREIRA<fnref n="2" />,<fnref n="3" />,<fnref n="4" />, A.M.S. SILVA<fnref n="1" />

Phenolics – oxidation – red Port wine – anthocyanins

## Introduction

The main non-enzymatic reactions occurring during food and beverage processing or storage are the degradation of polyphenols, Maillard reaction, sugar caramelization, and oxidation, leading to browning and aroma/flavor formation. Polyphenols are reactive compounds, which can be degraded and polymerized through both enzymatic and non-enzymatic reactions during food and beverage processing and storage. Polyphenol chemical reactions have been particularly studied in wine [1], where these reactions include mainly oxidations and/or polymerizations.

Constituents of both red and white wines are capable of reacting with significant amounts of oxygen, polyphenols being among the most readily oxidized wine constituents [2, 3]. Nevertheless, red wines contain higher levels of polyphenols, among which, anthocyanins, procyanidins, and flavan-3-ols are in particularly highest levels [4, 5].

It is established that oxygenation could improve the evolution of red wines during aging, by color stabilization and decrease in astringency. On another hand, a long oxidation process will reduce wine antioxidants, such as sulfur dioxide or ascorbic acid, and the oxidation of desirable volatile compounds [3]. Concomitantly, temperature will accelerate the oxidation process [6].

The present work aims to illustrate the oxidation of red Port wine based on its phenolic formation or depletion rate during a forced aging protocol by the effect of both thermal and oxygen exposure. For this purpose a red Port wine was subject to four different storage temperatures, respectively, 20, 30, 35 and 40°C, and two adjusted oxygen saturation levels, no oxygen addition (treatment I), and oxygen addition (treatment II). Three hydroxycinnamic esters (trans-caftaric acid, trans-coutaric acid, and trans-fertaric acid), three hydroxycinnamic acids (caffeic acid, para-coumaric acid, and ferulic acid), three hydroxybenzoic acids (gallic acid, protocatechuic acid, and syringic acid), two flavan-3-ols [(+)-catechin and (-)-epicatechin], and six anthocyanins (malvidin-3-O-coumaroylglucoside, malvidin-3-O-acetylglucoside, peonidin-3-glucoside, petunidin-3-glucoside, delphinidin-3-glucoside, and malvidin-3-glucoside) were quantitated weekly, during 63 days, along with oxygen consumption. Due to the higher rate of anthocyanin depletion, a kinetic approach to their degradation in red Port wine was also established. These models are very important in the extent assessment of specific chemical reactions, the rate at which the changes occur and they can be an important tool in wine processing or storage condition optimization. Furthermore, the knowledge and control of the kinetic parameters can greatly enhance the thermal and oxidative processing conditions in terms of maximizing the rate of generation/formation of flavor/color.

## Materials and methods

### Wine samples

A forced aging protocol was performed in order to promote red Port wine oxidation. Ten liters of red Port wine (pH = 3.4; 2.5 mg/L of dissolved oxygen; SO₂ level of 17 mg/L; 105 g/L of reducing sugars; and alcohol content of 20%) were divided into 8 portions and placed on sealed vessels. The red Port wine was produced in the year of the experiment without oak contact. Each set of 4 vessels was kept for 63 days at 4 different storage temperatures, respectively, 20, 30, 35 and 40°C. Next, for all temperature regimes,

<footnote n="1">¹Departamento de Química & QOPNA, Universidade de Aveiro, 3810-193 Aveiro, Portugal</footnote>

<footnote n="2">²Escola Superior de Biotecnologia, Universidade Católica Portuguesa, Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal</footnote>

<footnote n="3">³Cork Supply Portugal, S.A., Rua Nova do Fial, 102 - São Paio de Oleiros, 4535-549 São Paio de Oleiros, Portugal</footnote>

<footnote n="4">⁴Stellenbosch University, Private Bag X1, Matieland, 7602, Stellenbosch, South Africa</footnote>

<footnote>*Corresponding author: cm.dias@ua.pt</footnote>
2 oxygen saturation levels were adjusted, during the protocol, as follows: (i) no oxygen addition (treatment I); and (ii) oxygen addition every sampling point (treatment II). Oxygen was injected by bubbling a mixture of O₂/N₂ (20/80) (Gasin, Portugal) until its content was close to 8.0 mg/L. Analyses were performed weekly during 63 days (9 weeks, P1 to P9).

### *Dissolved oxygen measurements*

Concentration of dissolved oxygen was measured in the above experimental design using a Fibox 3 LCD fiber optic oxygen transmitter, coupled to a polymer optical fiber of 2.5 meters and to planar oxygen sensitive spots (PSt3), from PreSens Precision Sensing GmbH (Germany).

### *Identification and quantification of phenolic compounds*

For the identification of phenolic compounds both a HPLC-DAD and a LC-MS triple quadrupole were used, while their quantification was achieved by the LC-MS triple quadrupole. The method features direct analysis of wines with no preparation or dilution.

### *HPLC-DAD analysis*

Phenolic identification was conducted on a Beckman model 126 quaternary solvent system, equipped with a System 32 Karat 5.0 software and a 168 rapid scanning, UV-visible photodiode array detector. The absorption spectra were recorded between 212 and 600 nanometers (nm). Stationary Phase: XDB-C18 (150 x 4.6 mm) 5-Micron (Agilent, USA). Mobile Phase: Solvent A: acetonitrile (100%) (Merck pure grade) with 0.2% TFA; Solvent B: acetonitrile/water (5:95 v/v) (Merck pure grade and pure water) with 0.2% TFA (Sigma-Aldrich, Germany); flow rate = 1 mL/min. The following gradient was employed: 0-2 min (100% B); 2-28 min (60% B); and 28-30 min (100% B). Hydroxybenzoic acids and flavan-3-ols were detected at 280 nm. Hydroxycinnamic acids and their esters were detected at 320 nm. Anthocyanins were detected at 528 nm. Samples were analyzed in duplicate.

### *LC-MS-MS analysis*

Phenolic identification/quantification was conducted on a LC-MS Varian 1200 triple quadrupole mass spectrometer with electrospray ionization in positive and negative modes. The operating parameters of the ESI source was as follows: API drying gas 19 psi at 200°C; API chamber temperature 50°C; API nebulizing gas, Air 41 psi; Capillary voltage -85 to +25 V; Q2 collision cell pressure Argon 1.42 mTorr; Collision energy 15 to 25 V. Stationary Phase: XDB-C18 (150 x 4.6 mm x 5 µm) (Agilent, USA). Mobile Phase: Solvent A: acetonitrile (100%) (Merck pure grade) with 0.1% formic acid; Solvent B: acetonitrile/water (5:95 v/v) (Merck pure grade/ultra-pure water, from a Millipore system) with 0.1% formic acid (Sigma-Aldrich, Germany); flow rate = 0.35 mL/min. The following gradient was employed: 0 min (95% B); 0-26 min (70% B); 26-28 min (95% B); and 28-30 min (95% B). Each run took 30 min to complete.

Phenolics were identified by comparison with commercially available standard retention times and MS-MS data (Table 1). For anthocyanins, neutral loss scanning modes were obtained for the identification of, respectively, anthocyanin-glycosides (neutral loss m/z 162), acetylglucosides (neutral loss m/z 204), and coumaroylglucosides (neutral loss m/z 308) [7]. For the unavailable standards of the anthocyanins: delphinidin-3-glucoside, petunidin-3-glucoside, peonidin-3-glucoside, Mv-3-O-acetylglucoside, and (trans)-Mv-3-O-coumaroylglucoside, and for the hydroxycinnamic esters: *trans*-caftaric acid, *trans*-coutaric, and *trans*-fertaric acid, available published MS-MS data were used (Table 1).

### *Kinetic analysis*

The most usual kinetic models reported in literature to describe kinetics of compound depletion are zero order [c = c₀ + kt], first order [c = c₀ exp (kt)] or second order [1/c = 1/c₀ + kt] reaction models. Assuming a first order [c = c₀ exp (kt)], the dependence of the rate constant k upon the temperature T is expressed by the Arrhenius equation: k = k₀e⁻ Ea/RT, where k₀ is the pre-exponential factor, Ea is the activation energy and R is the gas constant equal to 8.314 J mol⁻¹K⁻¹. According to the Arrhenius equation the activation energy for anthocyanin depletion in wine can be calculated by plotting the logarithm of the rate constants at four temperatures against the reciprocal of the absolute temperature: ln(k) = -Ea/RT + ln(k₀).

## Results and discussion

Figure 1 represents the evolution (mg/L/day) of the hydroxycinnamic esters, *trans*-caftaric acid, *trans*-coutaric, and *trans*-fertaric acid, the hydroxycinnamic acids, caffeic acid, *para*-coumaric acid, and ferulic acid, the hydroxybenzoic acids, gallic acid, protocatechuic acid, and syringic acid, and finally, the flavan-3-
ols, (+)-catechin and (-)-epicatechin for, respectively, oxygen treatments I and II. *Hydroxycinnamic acids and respective esters*: caffeic and *para*-coumaric acids have increased during the forced aging protocol (Figure 1). These compounds are formed during the hydrolyses of the respective esters, caftaric and coutaric acids. On the contrary, ferulic acid has declined during the forced aging protocol (Figure 1). Esters of tartaric acid, namely caftaric acid, coutaric acid, and fertaric acid are highly hydrolyzed into their corresponding acids, caffeic, *para*-coumaric and ferulic acids, which can explain their decrease during the forced aging process (Figure 1). *Hydroxybenzoic acids*: Polyphenols containing a 1,2,3-trihydroxybenzene (gallic acid), or a 1,2-dihydroxybenzene ring (protocatechuic acid) are easiest to oxidize because the resulting phenoxyl semi-quinone radical can be stabilized by a second oxygen atom. Equivalent methoxy substituted phenols (syringic acid) are not as readily oxidized because they do not produce stabilized semi-quinone radicals. However, the hydroxybenzoic acids may increase during aging due to anthocyanin cleavage, and this can explain their enlargement during the forced aging process of red Port wine samples (Figure 1). The major increase was observed for syringic acid (Figure 1). This phenolic acid may be formed by malvidin-3-glucoside cleavage. *Flavan-3-ols*: (+)-catechin and (-)-epicatechin have decreased during the forced aging protocol (Figure 1). Furthermore, oxygen supplements increase the consumption of these easily oxidizable phenolic compounds (Figure 1 - treatment II).

<table><caption>**Table 1** - Retention times and MS-MS data of phenolics identified in the wine samples</caption><thead><tr><th>Retention time (min)</th><th>Compound</th><th>Precursor [M - H]<sup>-</sup></th><th>MS/MS fragments</th></tr></thead><tbody><tr><td></td><td><strong>Hydroxybenzoic acids:</strong></td><td></td><td></td></tr><tr><td><strong>7.8</strong></td><td>Gallic acid</td><td>169</td><td>125</td></tr><tr><td><strong>12.3</strong></td><td>Protocatechuic acid</td><td>153</td><td>109</td></tr><tr><td><strong>14.5</strong></td><td>Syringic acid</td><td>197</td><td>182</td></tr><tr><td></td><td><strong>Hydroxycinnamic acids:</strong></td><td></td><td></td></tr><tr><td><strong>14.3</strong></td><td>Caffeic acid</td><td>179</td><td>135</td></tr><tr><td><strong>19.7</strong></td><td><em>para</em>-Coumaric acid</td><td>163</td><td>119</td></tr><tr><td><strong>19.9</strong></td><td>Ferulic acid</td><td>193</td><td>134</td></tr><tr><td></td><td><strong>Hydroxycinnamic esters:</strong></td><td></td><td></td></tr><tr><td><strong>12.9</strong></td><td><em>trans</em>-Caftaric acid</td><td>311</td><td>179</td></tr><tr><td><strong>14.9</strong></td><td><em>trans</em>-Coutaric</td><td>295</td><td>163</td></tr><tr><td><strong>16.4</strong></td><td><em>trans</em>-Fertaric acid</td><td>325</td><td>193</td></tr><tr><td></td><td><strong>Flavan-3-ols:</strong></td><td></td><td></td></tr><tr><td><strong>13.1</strong></td><td>(+)-Catechin</td><td>289</td><td>245</td></tr><tr><td><strong>15.8</strong></td><td>(-)-Epicatechin</td><td>289</td><td>245</td></tr><tr><td></td><td><strong>Anthocyanins:</strong></td><td></td><td></td></tr><tr><td><strong>15.5</strong></td><td>Delphinidin-3-glucoside</td><td>465</td><td>303</td></tr><tr><td><strong>16.0</strong></td><td>Petunidin-3-glucoside</td><td>479</td><td>317</td></tr><tr><td><strong>16.5</strong></td><td>Peonidin-3-glucoside</td><td>463</td><td>301</td></tr><tr><td><strong>16.6</strong></td><td>Mv-3-glucoside</td><td>493</td><td>331</td></tr><tr><td><strong>21.0</strong></td><td>Mv-3-O-acetylglucoside</td><td>535</td><td>331</td></tr><tr><td><strong>22.4</strong></td><td>(<em>trans</em>)-Mv-3-O-coumaroylglucoside</td><td>639</td><td>331</td></tr></tbody></table>

In order to gather more information concerning the relationship between anthocyanins, storage temperature and oxygen consumption, an Arrhenius study was performed. The activation energies (Ea), the pre-exponential factor (k₀), and the rate constants estimated at a medium reference temperature (kTref) are reported in Table 2. The degradation rate constants follow the order delphinidin-3-glucoside > petunidin-3-glucoside ≈ malvidin-3-glucoside > Mv-3-O-coumaroylglucoside > peonidin-3-glucoside > Mv-3-O-acetylglucoside. Delphinidin-3-glucoside has the highest degradation rate followed by petunidin-3-glucoside, in both oxygen treatments (Table 2).

## Conclusion

The most relevant phenolic oxidation markers were anthocyanins and catechin-type flavonoids, which had the highest decreases during the thermal and oxidative red Port wine process. This observed depletion of anthocyanins associated to the flavan-3-ol (catechins and condensed tannins) decline is related with their
transformation into more stable colored pigments resulting in new color enhanced wines with less astringency that could affect the quality of red Port wines positively. In addition, temperature seems to influence mostly the phenolic kinetic degradation. As such these identified phenolic compounds could be used as oxidation markers, and their modulation may well be used for the optimization of wine processing and/or storage conditions.

<figure><img src="image_404.png" /><figcaption>**Fig. 1** - Rate of phenolic formation or depletion during the forced aging protocol of red Port wine. Treatment I - no oxygen addition; Treatment II - oxygen addition.</figcaption></figure>

<table><caption>**Table 2** - Kinetic parameters of anthocyanin depletion in wine, given by the Arrhenius equation</caption><thead><tr><th rowspan="2">Anthocyanin</th><th colspan="4">no oxygen addition</th><th colspan="4">oxygen addition</th></tr><tr><th>Ea (kJ/mol)</th><th>K<sub>0</sub> (1/day)</th><th>r</th><th>K<sub>TRef</sub> (mg/L/day)</th><th>Ea (kJ/mol)</th><th>K<sub>0</sub> (1/day)</th><th>r</th><th>K<sub>TRef</sub> (mg/L/day)</th></tr></thead><tbody><tr><td><b>Mv-3-O-coumaroylglucoside</b></td><td><b>18.5±2.3</b></td><td>4.6E+01</td><td>-0.95</td><td><b>0.031</b></td><td><b>35.2±0.8</b></td><td>4.2E+04</td><td>-0.99</td><td><b>0.039</b></td></tr><tr><td><b>Mv-3-O-acetylglucoside</b></td><td><b>29.9±3.3</b></td><td>2.8E+03</td><td>-0.96</td><td><b>0.020</b></td><td><b>46.9±3.0</b></td><td>3.0E+06</td><td>-0.98</td><td><b>0.027</b></td></tr><tr><td><b>Peonidin 3-Glucoside</b></td><td><b>34.6±3.5</b></td><td>2.5E+04</td><td>-0.96</td><td><b>0.029</b></td><td><b>52.9±2.7</b></td><td>4.1E+07</td><td>-0.99</td><td><b>0.035</b></td></tr><tr><td><b>Petunidin-3-Glucoside</b></td><td><b>39.1±2.2</b></td><td>1.8E+05</td><td>-0.99</td><td><b>0.035</b></td><td><b>52.9±2.2</b></td><td>5.7E+07</td><td>-0.99</td><td><b>0.047</b></td></tr><tr><td><b>Delphinidin-3-Glucoside</b></td><td><b>41.5±1.7</b></td><td>1.8E+05</td><td>-0.99</td><td><b>0.040</b></td><td><b>51.6±2.1</b></td><td>3.7E+07</td><td>-0.99</td><td><b>0.052</b></td></tr><tr><td><b>Malvidin-3-Glucoside</b></td><td><b>44.1±3.2</b></td><td>1.3E+06</td><td>-0.98</td><td><b>0.036</b></td><td><b>60.7±2.9</b></td><td>1.2E+09</td><td>-0.99</td><td><b>0.045</b></td></tr></tbody></table>

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# On-line monitoring of oak wood volatiles by active capillary plasma ionisation mass spectrometry

R. FARRELL<fnref n="1" />*, J.-C. WOLF<fnref n="2" />, R. ZENOBI<fnref n="2" />

Oak volatile organic compounds – on-line monitoring – mass spectrometry

## Introduction

Oak wood volatile composition has a significant impact on the sensory quality of oak-aged wine. The current approach to the analysis of oak wood volatile organic compounds (VOC’s) is offline gas chromatography requiring lengthy sample preparation and run times in excess of 20 minutes. This preliminary study examines the potential for a direct mass spectrometry method that allows oak wood volatiles to be monitored online.

## Materials and methods

A thermal desorption chamber was coupled to an active capillary plasma ionization (ACPI) source for mass spectrometry (MS). The active capillary serves two functions (a) the inlet to the MS and (b) the ion-source. A sine modulated (6000 Hz) high voltage (2 kV, peak to peak) was applied to the electrodes, and the plasma ignited inside the capillary by dielectric discharge. Thermally desorbed oak wood VOC’s were transferred to the active capillary by the pressure difference between the ambient environment of the thermal desorption chamber and vacuum of the MS. Gas-phase analytes were ionized by the plasma and subsequently drawn into the MS. MS and MS/MS data were recorded on an LCQ DECA XP ion trap mass spectrometer (Thermo Scientific, St Jose, USA) operated in positive ion mode.

## Results and discussion

Several oak wood VOC’s were detected in positive ion mode, mostly as protonated molecular ions. The soft-ionization process (greatly aiding compound identification) has been commonly observed with CPI in previous research [1, 2]. Further confidence regarding compound identification was provided by determination of the MS/MS fragmentation pattern for ions of interest. By adjusting the thermal desorption temperature and sampling time, changes in the volatile composition of oak wood were observed. The changes in volatile composition were indicative of the oak toasting process. Different time-intensity profiles were evident for different peaks, indicating volatilization and or generation of compounds from non-volatile precursors.

## Conclusion

The thermal desorption CPI-MS approach allowed oak VOC’s to be monitored online. Several compounds were tentatively identified by their MS/MS fragmentation pattern. Changes in the volatile composition of the oak could be monitored during toasting and differences were clearly observed within one minute of heat application. Our preliminary findings indicate the suitability of the CPI approach for the direct, sensitive detection of oak wood volatiles of oenological importance.

## Acknowledgements

The work described was supported by an Australian Endeavour Research Fellowship.

<footnote n="1">¹Australian Centre for Research on Separation Science (ACROSS), School of Chemistry, The University of Tasmania, Private Bag 75, Hobart, 7001, Australia</footnote>

<footnote n="2">²Department of Chemistry and Applied Bioscience, ETH Zurich, HCI E329, CH-8093 Zurich, Switzerland</footnote>

<footnote>*Corresponding author: ross.wpc@gmail.com</footnote>
References

1. Nudnova MM, Zhu L, Zenobi R (2012) Active capillary plasma source for ambient mass spectrometry. *Rapid Commun Mass Spectrom* **26**: 1447-1452.

2. Wolf J-C, Schaer M, Siegenthaler P et al (2015) Direct quantification of chemical warfare agents and related compounds at low ppt levels: comparing active capillary dielectric barrier discharge plasma ionization and secondary electrospray ionization mass spectrometry. *Anal Chem* **87**: 723-729.
# Grape cluster zone defoliation and choice of yeast strain – Impact on TDN potential in Riesling wines

A. SCHÜTTLER¹*, C. GUTHIER¹,², M. STOLL², P. DARRIET³,⁴, D. RAUHUT¹

¹Hochschule Geisenheim University, Department of Microbiology and Biochemistry,
Von-Lade-Str. 1, 65366 Geisenheim, Germany

²Hochschule Geisenheim University, Department of General and Organic Viticulture,
Von-Lade-Str. 1, 65366 Geisenheim, Germany

³Univ. de Bordeaux, Institut des Sciences de la Vigne et du Vin, Unité de recherche Œnologie,
EA 4577, 210 Chemin de Leysotte, 33882 Villenave d'Ornon, France

⁴INRA, Institut des Sciences de la Vigne et du Vin, USC 1366 Œnologie, 33882 Villenave d'Ornon, France

Defoliation – TDN management – Riesling – yeast strain

## Introduction

Many cool climate grapevine growing regions are or will be affected by global climate change [1]. It is likely that increasing temperatures, as well as changing precipitation pattern, will impact wine composition and wine styles [2]. In the last decades, the sensory concept of German Riesling wines was considered to represent fresh and fruity notes. However, aged wines of this variety are characterized by petrol-like aroma, which is not appreciated in modern Riesling wines. The C13-norisoprenoid 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN) is considered to be the marker compound for this undesired sensory impression [3].

Norisoprenoids are breakdown products of tetraterpenic carotenoid compounds which play manifold roles in biochemical signalling processes such as pheromone properties or hormone-like growth regulation in plants [4]. The C13-norisoprenoid TDN is transformed into glycosidically bound non-volatile precursors by the plant. It is then liberated during bottle aging by acidic hydrolysis and complex rearrangements [5-7]. The biogenesis of these classes of compounds in general and particularly TDN is impacted by grapevine growth conditions [8]. Wines made from Riesling grapes grown in warmer climate have higher concentrations of TDN [9]. Moreover, vineyard management impacts the development of this compound [10, 11]. In addition, grapevine clones and yeast strains also seem to have an impact on TDN concentrations [12]. Therefore, ‘TDN management’ will be one of the most challenging tasks in viticulture in Riesling growing regions in general, and particularly in cool climate regions because of rising temperatures due to climate change. Appropriate canopy management of the grapevines, as well as an appropriate selection of yeast strain during alcoholic fermentation, are two considered approaches to tackle excessive TDN concentrations in Riesling wines.

## Materials and methods

### Experimental vineyard

The vineyard was located in Heppenheim, Germany (Heppenheimer Stemmler) and was planted with Riesling vines in 1982 on sandy loam. The vines were trained to a VSP-type trellis system at six to eight canes. Interrow distance was 1.60 m, whereas intervine distance was 1.10 m, resulting in a surface of 1.76 m² for each vine. In four rows, four treatments were established in threefold repetition according to an incomplete randomised block design. The first treatment was not defoliated, representing the control (CTR); the second treatment was defoliated in the grape cluster zone after bloom (June 11th) only on the eastern side (LREE); the third treatment was defoliated in the grape cluster zone after blossom (June 11th) on the eastern and western side of the canopy (LREB); and the fourth treatment was defoliated in the grape cluster zone at veraison (September 5th) on the eastern and western side of the canopy (LRLB). Each treatment consisted of 16 vines. In order to regulate yield, all but two clusters per shoot were removed for all treatments at berry set.

<footnote>*Corresponding author: armin.schuettler@hs-gm.de</footnote>
Winemaking

Harvest date was October 16th. Each treatment and replicate, in total 16 lots, was harvested and pressed separately using a 20-kg press. Grape juice was clarified by sedimentation in 48 h. Then the clarified juice of one treatment was mixed, aliquoted into 750-mL bottles and inoculated using two commercial yeast strains with vitamin B1 and diammonium phosphate. The fermentation was monitored by determining the loss of carbon dioxide.

Analysis of TDN

Analysis of TDN and TDN-glycosides was carried out using GC-MS after SPE sample preparation [13].

Results and discussion

TDN potential in grape juice

The four grape juices without leaf removal (CTR) showed the lowest TDN potential of 63 ± 3 µg/L, whereas the treatment with the leaves removed on both sides of the canopy at an early stage of berry development (LREB) showed the highest TDN potential of 154 ± 35 µg/L. Both the treatment defoliated at an early stage of berry development on the eastern side of the canopy (LREE) and the one defoliated at veraison on both sides of the canopy (LRLB) also showed higher TDN potential (112 ± 9 µg/L and 119 ± 6 µg/L, respectively) compared to the control treatment, but lower TDN levels compared to the LREB treatment.

TDN potential in wines

After fermentation, the TDN potential pattern was highest for the treatments defoliated on both sides of the canopy (LREB, LRLB) and using yeast strain A, showing TDN potential of 135 µg/L and 132 µg/L, respectively. This was also the case for yeast strain B (111 µg/L and 100 µg/L, respectively). Furthermore, TDN potential in the non-defoliated treatment (CTR) was lowest for yeast B (56 µg/L), while the lowest TDN potential obtained from yeast B for LREE equalled the TDN potential from yeast B for CTR (63 µg/L and 69 µg/L, respectively) and was well under the TDN potential from LREE wines obtained with the same yeast (82 µg/L).

The results presented here provide evidence that the TDN potential in grape must is highly correlated with the sun exposure of grape clusters. These results also show that TDN potential does not necessarily depend on the timing of leaf removal, which is generally in accordance with earlier studies [8, 10]. However, the TDN potential pattern corresponds well to that of the grape juice. It can be observed that after alcoholic fermentation the difference in TDN potential between early and late leaf removal on both sides of the canopy (LREB and LRLB) is less than expected from the grape juice results. This may be explained by not analyzing all possible TDN-precursors in the grape juice, which are then transformed into TDN-precursors during alcoholic fermentation. There are some indications that TDN can be formed from different precursors [5, 6], which would fit into the results from the current study. Furthermore, the yeast strain has been shown to impact the TDN potential of wines. All wines fermented with yeast strain A showed higher TDN potential than those fermented with yeast strain B. It can be assumed that yeast strains have different enzymatic glycosidase activity during fermentation [14] and, therefore, can more effectively liberate the aglycons from glycosylated precursors.

Conclusion

The results of the study demonstrate the impact of both grape cluster leaf removal and yeast strain selection on TDN potential in Riesling wines. These two factors are considered to be effective tools for the management of TDN potential and thus important for aroma development of Riesling wines during bottle aging.

Acknowledgements

The authors would like to thank ‘Hessische Bergsträsser Winzergenossenschaft e.G.’ in Heppenheim for the experimental vineyard and technical support.
References

1. Jones GV, White MA, Cooper OR et al (2005) Climate change and global wine quality. *Clim Change* **73**: 319-343.

2. Schultz H (2000) Climate change and viticulture: a European perspective on climatology, carbon dioxide and UV-B effects. *Aust J Grape Wine Res* **6**: 2-12.

3. Simpson RF, Miller GC (1983) Aroma composition of aged Riesling wine. *Vitis* **22**: 51-63.

4. Britton G (2008) Functions of carotenoid metabolites and breakdown products. In Britton G, Liaaen-Jensen S & Pfander H (eds.) *Carotenoids*. Birkhäuser Basel.

5. Waldmann D, Winterhalter P (1992) Identification of a novel vitispirane precursor in Riesling wine. *Vitis* **31**: 169-174.

6. Versini G, Rapp A, Marais J et al (1996) A new 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN) precursor isolated from Riesling grape products: partial structure elucidation and possible reaction mechanism. *Vitis* **35**: 15-21.

7. Daniel MA, Capone DL, Sefton MA et al (2009) Riesling acetal is a precursor to 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN) in wine. *Aust J Grape Wine Res* **15**: 93-96.

8. Marais J, van Wyk CJ, Rapp A (1992) Effect of sunlight and shade on norisoprenoid levels in maturing Weisser Riesling and Chenin blanc grapes and Weisser Riesling wines. *South Afr J Enol Vitic* **13**: 23-32.

9. Marais J, Versini G, van Wyk CJ et al (1992) Effect of region on free and bound monoterpene and C13-norisoprenoid concentrations in Weisser Riesling wines. *South Afr J Enol Vitic* **13**: 71-77.

10. Kwasniewski MT, Vanden Heuvel JE, Pan BS et al (2010) Timing of cluster light environment manipulation during grape development affects C13 norisoprenoid and carotenoid concentrations in Riesling. *J Agric Food Chem* **58**: 6841-6849.

11. Linsenmeier AW, Löhnertz O (2007) Changes in norisoprenoid levels with long-term nitrogen fertilisation in different vintages of *Vitis vinifera* var. Riesling wines. *South Afr J Enol Vitic* **28**: 17-24.

12. Sponholz WR, Hühn T (1997) Einfußfaktoren von Klonenmaterial und verwendetem Hefestamm auf die Alterung von Riesling Weinen. *Vitic Enol Sci* **52**: 103-108.

13. Schüttler A, Friedel M, Jung R et al (2015) Characterizing aromatic typicality of Riesling wines: merging volatile compositional and sensory aspects. *Food Res Int* **69**: 26-37.

14. Grossmann M, Rapp A, Rieth W (1987) Enzymatische Freisetzung gebundener Aromastoffe. *Deutsche Lebensmittelrundschau* **83**: 7-12.
# Tentative identification of a fruity aroma compound, recalling blackcurrant, released from grape skins of Vitis vinifera grape var. Cabernet Sauvignon during alcoholic fermentation using MDGC-MS-Olfactometry

L. BOUTEGRABET<fnref n="1" />,<fnref n="2" />, R. SAKURAI<fnref n="3" />, M.J. RUIZ-MORENO<fnref n="1" />,<fnref n="2" />,<fnref n="4" />, Ph. DARRIET<fnref n="1" />,<fnref n="2" />*

Cabernet Sauvignon – fruity aroma – multidimensional GC-MS-O – aroma precursors

## Introduction

Among red wines, those originated from Cabernet Sauvignon grapes have great success. This variety, historically associated to the Bordeaux region, frequently gives, from ripe grapes, wines presenting a large diversity of aromatic nuances in which fruity notes reminiscent of "dark" fruits such as blackcurrant and blackberry dominate.

Aroma complexity in red wines and the difficulty of studying it reflect the diversity of the mechanisms involved in its genesis. Despite the various studies on red wine aromas, our knowledge of the volatile odoriferous compounds contributing to the sensory characteristics of Cabernet Sauvignon wines, and particularly those originating from aroma precursors in grapes which are later released during vinification, is still incomplete. Various volatile compounds participating to red wine fruity aroma are released during the winemaking process by the activity of the yeast *Saccharomyces cerevisiae* [1, 2].

The aim of this research study was to further characterize volatile odoriferous compounds with fruity nuances, mainly red and black fruity notes, originating from Cabernet Sauvignon grape aromatic potential, which are released during alcoholic fermentation, with a particular interest in their corresponding varietal precursors.

## Materials and methods

### Grape samples

A plot of Cabernet Sauvignon grapes (2011, 2012, 2013 and 2014 vintages) was selected at Château Lagrange (3rd Grand Cru Classé, Saint-Julien, Gironde) and representative samples were harvested at maturity. The grapes were transported to the laboratory and immediately placed at -20°C.

### Grape skin preparation

After thawing, grapes were de-stemmed and pressed using a pneumatic press (Bellot SA Vinicoplast, Gradignan, France) in order to remove the juice (must). Thereafter, grape skins were manually separated from the seeds before being crushed into small fragments using liquid nitrogen (N₂).

After grinding, the crushed grape skins were macerated in a water/ethanol solution (1/1; v/v) for four to five days at room temperature (20-25°C). The obtained alcoholic solution was centrifuged at 7000 r.p.m. for 10 min, lyophilized (Christ Alpha 2-4 LSC instrument), and the dried extract stored at -20°C.

<footnote n="1">¹Université de Bordeaux, Institut des Sciences de la Vigne et du Vin (ISVV),
Unité de Recherche Œnologie, EA 4577, F-33882 Villenave d'Ornon, France</footnote>

<footnote n="2">²INRA, USC 1366 Œnologie, ISVV, F-33882 Villenave d'Ornon, France</footnote>

<footnote n="3">³Suntory Wine International Limited, 2-3-3, Daiba, Minato-ku, Tokyo, 135-8631, Japan</footnote>

<footnote n="4">⁴Current address: FAPA, Centro Alameda del Obispo, CAPDA,
Junta de Andalucía, 14004 Córdoba, Spain</footnote>
*Aroma precursor extraction*

The extraction of aroma precursors was performed on 15 g of grape skin extract. Three solvents were used for that purpose, namely water, butanol and ethyl acetate. First, the grape skin extract was recovered in water and extracted three times with ethyl acetate (v/v/v; 120 mL/50 mL/50 mL). Then, the recovered aqueous layer was extracted three times with butanol (v/v/v; 120 mL/50 mL/50 mL). The three obtained extracts (aqueous, ethyl acetate and water) were evaporated, lyophilized and stored at -20°C.

*Wine extraction*

Fermented grape skin extracts (100 mL) were extracted three times with dichloromethane (1/1, v/v; 1 × 10 mL and 2 × 5 mL). The organic layer was dried over Na₂SO₄ and then concentrated to 0.5 mL under nitrogen flow (approximately 100 mL/min).

*Capillary Gas Chromatography-Olfactometry (GC-O)*

The analysis was carried out on a Hewlett-Packard HP5890 series II (Agilent Technologies, Palo Alto, CA) coupled with olfactory detection using an ODO-1 installation (Scientific Glass Engineering (SGE), Ringwood, Australia). A 2-µL sample was introduced into an apolar BPX5 capillary column (SGE, 60 m, 0.25 mm i.d., 1-µm film thickness). The carrier gas was H₂ (Linde Gas, Bordeaux, France), with a flow rate of 1 mL/min for all of the analyses. The injector was operated in splitless mode (purge time 1 min); purge flow (50 mL/min) was set at 230°C. Oven temperature was initially set at 45°C for 1 min, then raised to 250 at 3°C/min and held for 20 min. Linear retention indices (LRI) were obtained by simultaneous injection of samples and a series of alkanes (C8-C23).

*Heart-Cut Multidimensional Gas Chromatography-Olfactometry-Mass Spectrometry*

The MDGC separations were performed in two capillary columns with different stationary phases or film thicknesses on two Agilent 7890A GC ovens coupled with a high resolution AccuTOF mass spectrometer (JMS-T100GC; JEOL Japan). The two chromatographs were connected with a temperature-controlled transfer line set at 230°C (West 4400 from ILS, Lyon, France). The outlet of the precolumn was connected to a sniff port (ODO I; SGE France) to determine odor retention time in this configuration and to the second column, via a Gerstel MCS 2 multicolumn switching system. A cryotrap was also placed at the start of the second column for cryofocusing. The end of the second column was split (1:1) via a crosspiece (Gerstel) between the TOF-MS detection (JEOL) and the sniffing port (ODP II, Gerstel). For oven I, only 10% of the total flow was transferred to the deactivated fused silica column connected to ODO I, whereas 50% of the flow was transferred to ODP II in oven II. The MDGC system was operated under constant pressure to maintain the balance between the two columns throughout the oven temperature program.

The injector temperature was set at 230°C. The sample was transferred from the precolumn to the main column via the MCS (Gerstel) system at a defined cut time. Preseparation was performed using a nonpolar BPX5 capillary column (30 m*0.25 mm*0.5 µm). The GC oven was programmed from 45°C (1 min) to 250°C at 3°C/min. The cut time (15.5-16.5 min) was selected with the ODO I system. During this period the cryogenic trap was maintained at -50°C. The second column was a 50 m*0.22 mm*1 µm BP1 (SGE France). Column head pressures were 279 kPa (oven I) and 195.5 kPa (oven II) at 45°C. Helium 5.3 (Linde Gas) was used as the carrier gas, with a flow rate of 2 mL/min. The temperatures of the ion source and transfer line were 250 and 230°C, respectively. The electron energy for the EI mass spectra was 70 eV and the MS was operated in the scan mode only (m/z from 45 to 250). The identification of sample constituents was performed by comparing linear retention indices and mass spectrometric data with those of reference compounds.

# Results and discussion

*Evidence for the perception of fruity nuances in fermented model wines in the presence of Cabernet Sauvignon grape skin extracts without correlation with color*

The extraction of grape skins using ethyl acetate, butanol and water allowed us to obtain three extracts with different properties. In Figure 1, the difference in color between the extracts is illustrated, related to the nature of the extracted compounds in each solvent. Anthocyanins, for example, are extracted preferentially in the butanol extract in comparison to the two other extracts (ethyl acetate and water).
<figure><img src="image_405.png" /><figcaption>**Fig. 1** - The Cabernet Sauvignon grape skin extracts obtained with 1) ethyl acetate, 2) butanol and 3) water.</figcaption></figure>

Another important and prominent parameter is the evidence of different and typical fruity aromas in the three fermented skin extracts. In fact, sensory analyses revealed red fruit aromas, namely strawberry and raspberry, in the fermented aqueous extract and very intense black notes, particularly blackcurrant, in the fermented ethyl acetate extract. However, the fermented butanol extract did not show any interesting fruity notes. The sensory evaluation was confirmed and validated several times by our panel of tasters.

*Release of a volatile compound associated with an odorous zone recalling blackcurrant, detected by GC-olfactometry in fermented ethyl acetate extract from grape skin*

Two columns (BP20 and BPX5) were used to analyze the three ethyl acetate, butanol and water fractions in order to study and detect the different fruity fragrant zones (ZO). More concretely, BPX5 column permitted to evidence the elution of a very intense blackcurrant odorous zone similar to the aroma detected during the sensory analysis of the fermented ethyl acetate extract (Table 1). This fruity zone is absent in the control and in the two other fermented extracts (water and butanol). The same analysis performed on the unfermented ethyl acetate extract showed no fruity ZO, as in the cases of the fermented extracts.

<table><caption>**Table 1** - Aromagrams of the obtained fermented fractions using GC-O (BPX5 column)</caption><thead><tr><th>Blank</th><th>Ethyl acetate</th><th>Water</th><th>Butanol</th></tr></thead><tbody><tr><td>-</td><td>Meat<br>(IRL 839)</td><td>-</td><td>-</td></tr><tr><td>Green, floral<br>(IRL 848)</td><td>Roasted<br>(IRL 849)</td><td>Roasted<br>(IRL 850)</td><td>-</td></tr><tr><td>-</td><td>Cabbage<br>(IRL 854)</td><td>-</td><td>-</td></tr><tr><td>-</td><td style="background-color: #8FBC8F;">Blackcurrant,<br>green<br>(IRL 874)</td><td>-</td><td>Green<br>(IRL 851)</td></tr><tr><td>Grilled meat<br>(IRL 880)</td><td>Grilled meat<br>(IRL 878)</td><td>Meat<br>(IRL 876)</td><td>Grilled meat<br>(IRL 878)</td></tr></tbody></table>

*Tentative identification of the volatile compound associated with a blackcurrant odor using GC-GC-O-TOF-MS*

In order to further characterize the blackcurrant aroma compound, a two dimensional GC analysis (GC-GC-O-MS-TOF-MS) was carried out on the organic extract obtained from the fermented ethyl acetate fraction. The separation method involved the isolation and transfer of the blackcurrant fraction from a first column (precolumn) to a second column (main column) with different selectivity.

The blackcurrant aroma fraction was successfully isolated and separated on nonpolar column (BPX5: 30 m\*0.25 mm\*0.5 µm) at a retention time of 16.22 min. The blackcurrant heart cut was performed on a time window between 15.5 min and 16.5 min and transferred to a second more nonpolar column (BP1: 50 m\*0.22 mm\*1 µm). Thus, using these previous separation conditions, we were able to separate with a high resolution the peak corresponding to the compound recalling the blackcurrant aroma at a retention time of 24.77 min (Figure 2). The used time of flight mass spectrometer offered a high resolution analysis of the obtained mass spectra along with the precise and accurate mass of the peak related to the isolated blackcurrant compound. The first information obtained was attributed with high precision, namely the exact mass m/z 140.119 Da and molecular formulae C9H16O. Structure characterization of the identified blackcurrant aroma through the synthesis of odoriferous chemicals is under progress.
<figure><img src="image_406.png" /><figcaption>Fig. 2 - A) Chromatogram of the isolated blackcurrant peak on the main column (BP1: 50 m*0.22 mm*1 µm); B) mass spectrometer of the blackcurrant peak.</figcaption></figure>

## Acknowledgements

We thank Château Lagrange 3ième Grand Cru Classé (Saint Julien) for providing the grape sample. We also thank the judges who participated in the sensory analysis.

## References

1. Loscos N, Hernandez-Orte P, Cacho J et al (2007) Release and formation of varietal aroma compounds during alcoholic fermentation from nonfloral grape odorless flavor precursors fractions. *J Agric Food Chem* **55**: 6674-6684.

2. Pineau B, Barbe J-C, Van Leeuwen C et al (2011) Contribution of grape skin and fermentation microorganisms to the development of red- and black-berry aroma in Merlot wines. *J Int Sci Vigne Vin* **45**: 27-37.
<figure><img src="image_407.png" /></figure>
# THÈME 4

## Analyse sensorielle et interface consommateur

*Sensory analysis and consumer interface*
<figure><img src="image_408.png" /></figure>
# Mieux comprendre les goûts des consommateurs grâce à l'économie expérimentale

P. COMBRIS*

INRA, UR 1303 ALISS (Alimentation et Sciences sociales), 65 boulevard de Brandebourg, 94200 Ivry-sur-Seine, France

Consentement à payer – analyse sensorielle – marque – AOC

## Introduction

L'évaluation d'un vin par un consommateur est influencée par l'ensemble des informations dont il dispose. Elle aboutit à une appréciation globale qui traduit le plaisir ou le déplaisir ressenti lors de la dégustation de ce vin. Lorsque qu'une échelle de notation normalisée est utilisée, on parle souvent de note hédonique. Une note hédonique est purement déclarative. Elle ne coûte rien à celui qui la donne. Elle ne l'engage à rien. Les économistes sont généralement réticents à utiliser ce genre de mesure. Ils préfèrent observer les achats qui, selon eux, sont un bien meilleur révélateur des préférences sous-jacentes. Mais comment faire pour estimer les préférences d'un consommateur pour des produits qu'il n'a pas achetés ?

Pour cela, les économistes ont mis au point des méthodes pour mesurer le "consentement à payer", c'est-à-dire le prix maximum qu'un consommateur est prêt à offrir pour obtenir un produit. Pour éviter de retomber dans le travers déclaratif, ces consentements à payer sont évalués grâce à des protocoles expérimentaux dans lesquelles des ventes réelles sont effectuées. Ces protocoles s'inspirent des méthodes d'enchères, et en particulier des enchères sous pli cacheté, dans lesquelles chaque participant souhaitant acquérir un produit fait une offre par écrit.

L'évaluation des consentements à payer n'est pas un substitut à l'évaluation sensorielle hédonique, c'est un outil complémentaire destiné à évaluer la demande du marché en fonction des prix. Les protocoles qui sont présentés dans cette communication ont été développés dans le cadre d'une collaboration étroite entre des spécialistes de l'analyse sensorielle et des économistes. L'objet de cette collaboration était de combiner les méthodes de l'analyse sensorielle et celles de l'économie expérimentale pour mettre au point des protocoles permettant de mieux comprendre les préférences des consommateurs. Le marché du vin, plus encore que celui des biens de grande consommation, est un marché arrivé à maturité sur lequel une multitude de produits sont en concurrence. Dans un tel contexte, les producteurs doivent différencier leurs produits s'ils ne veulent pas les voir disparaître peu à peu du marché. Différencier un produit, c'est lui ajouter des caractéristiques et surtout s'assurer que les consommateurs les ont bien perçues, et leur attribuent de la valeur. Le point important est donc d'être en mesure d'évaluer la valeur attribuée par les consommateurs à un produit en fonction de ses caractéristiques. C'est précisément l'objet des méthodes d'économie expérimentale. Ces méthodes viennent s'ajouter aux outils d'évaluation habituels en leur apportant une dimension incitative qui leur fait généralement défaut. En se rapprochant des conditions du marché, ces méthodes ouvrent des perspectives stimulantes pour mieux comprendre les mécanismes qui gouvernent les choix des consommateurs.

## La révélation des consentements à payer

Différentes méthodes sont à la disposition des investigateurs intéressés par les consentements à payer des consommateurs. La méthode la plus directe consiste à estimer une fonction de prix hédonique, qui analyse les variations des prix de marché en fonction des caractéristiques des produits. Cette méthode a l'avantage de s'appuyer sur les prix d'équilibre qui résultent des transactions réelles sur le marché, mais elle n'est évidemment pas utilisable pour tester des produits nouveaux, ou des caractéristiques nouvelles. Dans ce cas, il n'y a souvent pas d'autre choix que d'utiliser des méthodes déclaratives (évaluation hédonique, focus groups, analyse conjointe, enquêtes,...). Ces méthodes permettent d'identifier les facteurs qui agissent sur les préférences et les mécanismes de choix, mais elles sont souvent biaisées lorsqu'il s'agit d'estimer les

<footnote>*Auteur principal : pierre.combris@ivry.inra.fr</footnote>
intentions d'achat et surtout les consentements à payer. Les répondants ont en effet généralement tendance à
surestimer leur probabilité d'acheter pour un prix donné.

Pour éviter ces biais, les économistes ont recours à des expérimentations qui reposent sur des transactions
effectives réalisées par des échantillons restreints de consommateurs dans des conditions contrôlées.
Pour révéler le prix maximum que chaque participant est prêt à payer pour un produit donné, ces méthodes
s'inspirent des techniques d'enchères sous pli, dans lesquelles chaque participant soumet une offre par écrit.
Différentes variantes ont été développées avec pour objectif d'impliquer les participants et de faire en sorte
qu'ils aient intérêt à évaluer et à déclarer leur consentement à payer aussi honnêtement que possible.
Les travaux présentés dans cette communication, reposent sur un mécanisme de ce type. Il s'agit de ventes à
un prix aléatoire. Dans ces ventes chaque participant indique son prix maximum par écrit, en sachant que le
prix effectif de la transaction sera tiré au sort. Un participant n'achètera que si le prix de vente tiré au sort
est inférieur, ou égal, au prix maximum qu'il a proposé. Cette méthode, connue sous le nom de mécanisme
BDM d'après les initiales de ses initiateurs [1], présente l'avantage d'impliquer tous les participants,
puisqu'il n'y a pas qu'un seul acheteur comme c'est le cas dans une enchère. C'est, en fait, une vente
classique dans laquelle chaque acheteur potentiel a un prix limite. Comme le prix n'est pas déterminé par le
vendeur en fonction des offres, mais tiré au sort, les acheteurs peuvent indiquer leur prix limite sans crainte
de révéler une information qui serait stratégique dans un marchandage classique. L'incitation découle du
fait que chaque participant est certain de toujours faire une bonne affaire, puisqu'il n'achètera qu'à un prix
inférieur ou égal à un prix qu'il a lui-même déterminé.

Un protocole pour mesurer les effets respectifs du goût et de l'information sur le consentement à payer

Les travaux présentés ici s'intéressent aux effets respectifs du goût et des informations extrinsèques (appellation, marque,...) sur le consentement à payer pour un vin. Ils utilisent un protocole intra-sujet (within), qui consiste à demander aux participants d'évaluer successivement les mêmes vins avec de plus en plus d'information. L'information sur les caractéristiques des vins testés est délivrée élément par élément, en mesurant à chaque fois l'impact sur le consentement à payer [2].

En pratique, ces expérimentations sont conduites avec des sujets sélectionnés aléatoirement dans la
population générale. Un questionnaire téléphonique permet de filtrer les répondants en fonction de leurs
habitudes de consommation. Seuls les consommateurs réguliers de la catégorie de vins testés sont retenus.
Des quotas de catégories socioprofessionnelles sont parfois appliqués pour éviter une sur-représentation de
sujets très disponibles (étudiants et retraités en particulier). Les personnes qui acceptent de participer
reçoivent une convocation accompagnée d'informations sur le déroulement de l'expérience, et en particulier
sur le mécanisme de la vente à prix aléatoire. Les sessions expérimentales se déroulent d'autant mieux que
les participants ont eu le temps de se familiariser avec des procédures qui sont nouvelles pour la plupart
d'entre eux. Le plus souvent les sessions regroupent une dizaine de sujets dans une salle d'analyse
sensorielle, et chaque expérience porte au total sur une centaine de personnes.

A leur arrivée, les participants reçoivent un dédommagement pour leur déplacement et pour le temps qu'ils
consacrent à l'expérimentation. L'expérimentateur leur présente ensuite, en groupe, les principes et les
étapes de la session expérimentale. Les vins testés sont dans un premier temps évalués à l'aveugle, puis sur
la base de l'examen des bouteilles ou des seules étiquettes et, enfin, dans une dernière étape, en dégustant
les vins avec la bouteille présentée simultanément. A chaque étape, pour chacun des vins testés,
les participants doivent indiquer par écrit leur prix d'achat maximum. Pour éviter les comportements
stratégiques (attendre la dernière étape pour indiquer sincèrement son prix) et éliminer l'incertitude sur le
nombre de bouteilles achetées, la méthode consiste habituellement à informer les participants, dès le début
de la session, que chacun ne pourra acheter qu'une seule bouteille. Pour cela, une étape de l'évaluation et un
des vins évalués à cette étape sont tirés au sort à la fin de la session, et la vente se fait sur la base du prix
proposé pour ce vin à cette étape. La bouteille mise en vente peut donc être différente pour chaque
participant si le tirage au sort est individualisé.

A chaque étape, on demande donc aux participants d'évaluer chaque bouteille comme s'il devait l'acheter immédiatement avec les seules informations dont il dispose à ce moment. Les participants qui ne souhaitent pas acheter, indiquent simplement que leur prix maximum est nul. Le mécanisme de vente à prix aléatoire
est mis en pratique au début de chaque session en procédant à la vente d'un produit de faible valeur, et l'expérience proprement dite ne débute que lorsque toutes les questions des participants ont reçu une réponse. A partir de là, les participants sont placés dans des cabines individuelles et ils ne peuvent communiquer qu'avec les expérimentateurs. A la fin de l'expérience, la bouteille mise en vente et son prix sont tirés au sort, le plus souvent au niveau individuel. Les participants qui tirent un prix de vente inférieur ou égal au prix maximum qu'ils ont indiqué achètent une bouteille et la payent au prix de vente tiré au sort.

## Exemple 1 : Consentement à payer pour le champagne, goût ou marque ?

Ce protocole, qui peut faire l'objet de différentes variantes, a été utilisé pour la première fois en décembre 2000 et mai 2001, pour tester cinq champagnes différents avec un échantillon de 120 consommateurs réguliers (46 femmes et 74 hommes de 23 à 77 ans) [3, 4]. Les résultats reportés sur la figure 1 montrent qu'après la dégustation à l'aveugle les prix moyens offerts par les participants pour les cinq champagnes ne sont pas significativement différents. En revanche, lorsque seules les bouteilles sont examinées la hiérarchie des prix est claire : les trois champagnes du syndicat des grandes marques (B1, B2 et B3) sont très significativement mieux valorisés que le champagne de milieu de gamme (MR), lui-même significativement mieux valorisé que le champagne sans marque d'un grand distributeur (FP). De façon intéressante, l'évaluation finale fait apparaître une baisse significative des prix proposés pour les trois champagnes du syndicat des grandes marques, comme si les attentes sensorielles des participants avaient finalement été un peu déçues lorsqu'ils ont pris connaissance des marques des champagnes qu'ils étaient en train de déguster.

Ces résultats montrent que les consentements à payer des participants sont principalement influencés par la notoriété de la marque et secondairement par le goût du champagne, sachant que les caractéristiques des champagnes testés dans cette expérience étaient très proches. On peut cependant se demander si l'absence de différence ente les prix moyens proposés à l'aveugle révèle une incapacité de chaque individu à distinguer entre les champagnes testés, ou plutôt une compensation entre des évaluations individuelles très différentes selon les champagnes. En traitant les données, non plus par marque, mais par rang, c'est-à-dire en classant les prix de chaque participant et en faisant la moyenne des prix de chaque rang pour tous les participants, on observe que, même à l'aveugle, les participants établissent des différences significatives entre les cinq champagnes (Figure 2). Ces différences sont accentuées lorsque les marques des champagnes sont connues, mais la discrimination individuelle apparaît beaucoup plus forte que les moyennes par produit ne l'avaient laissé supposer.

<figure><img src="image_409.png" /><figcaption>Fig. 1 - Prix moyens par marque</figcaption></figure>

<figure><img src="image_410.png" /><figcaption>Fig. 2 - Prix moyens par rang</figcaption></figure>

## Exemple 2 : La valorisation des AOC

Le même protocole a été utilisé dans une étude comparative entre la France et l'Allemagne pour analyser l'efficacité de l'appellation d'origine contrôlée "Bourgogne" sur le marché international [5]. L'effet de la
mention de l'appellation d'origine est souvent confondu avec celui de la notoriété des grands crus de l'appellation. La question est ici de savoir si la mention de l'appellation a aussi un impact dans le cas des appellations génériques pour des vins de "milieu de gamme". Deux échantillons de consommateurs ont été testés, l'un à Paris (n=60) et l'autre à Munich (n=59), pour tester l'effet de l'appellation d'origine et le comparer à celui d'autres signaux comme la marque ou le cépage.

Les résultats obtenus montrent des consentements à payer moyens un peu plus élevés à Munich qu'à Paris. Dans les deux pays, les prix proposés après la dégustation à l'aveugle sont inférieurs aux prix proposés lorsque les étiquettes sont visibles. La différence la plus importante entre les deux groupes est l'impact significatif de l'appellation "Bourgogne" sur le consentement à payer moyens des participants du groupe parisien, et l'absence d'impact sur le groupe munichois. Encore convient-il d'observer que l'impact de l'appellation n'est significatif qu'après le seul examen des étiquettes et disparaît après la dégustation finale. L'effet du signal est donc limité, à la fois aux participants français et à l'évaluation sur la base de l'étiquette uniquement.

De façon encore plus frappante que dans le cas des champagnes, on observe de très faibles écarts entre les consentements à payer moyens dès lors que les vins sont dégustés. A nouveau, se pose la question de savoir s'il s'agit d'une incapacité à distinguer les différents vins ou d'une forte hétérogénéité entre les participants, masquée par le calcul des moyennes. Le traitement des données en fonction des classements individuels montrent que les participants discriminent assez bien les différents vins quelles que soient les informations fournies (dégustation et/ou étiquette). Comme dans le cas du champagne, l'analyse des consentements à payer selon le rang conduit à deux conclusions : (i) les consommateurs ont des préférences marquées, (ii) ces préférences sont extrêmement hétérogènes.

## Exemple 3 : L'expertise sensorielle fait-elle une différence ?

L'expertise sensorielle, acquise par l'entraînement ou l'habitude, est un des facteurs à prendre en compte pour analyser l'hétérogénéité des préférences individuelles. Une expérimentation identique aux précédentes réalisée avec un panel de spécialistes de l'évaluation sensorielle, montre qu'après la dégustation à l'aveugle, les participants ne semblent pas faire beaucoup de différence entre un chardonnay générique et un chardonnay d'appellation, alors qu'ils sont très sensibles à l'information apportée par les étiquettes (Figure 3) [2]. Mais à la différence d'un panel non entrainé (Figure 4), leur appréciation finale (étiquette + dégustation) est plus déterminée par leur évaluation sensorielle que par l'étiquette. On observe également, comme pour les sujets non-entraînés, que leurs goûts apparaissent très hétérogènes lorsque les consentements à payer moyens sont calculés en fonction de l'ordre de leurs préférences. Il ressort de cette analyse que les sujets "entraînés" n'ont pas forcément des goûts plus homogènes que les sujets non-entraînés, mais simplement qu'ils sont plus sûrs de leurs jugements et moins influencés par les étiquettes.

<figure><img src="image_411.png" /><figcaption>Fig. 3 - Dégustateurs entraînés (n=23)</figcaption></figure>

<figure><img src="image_412.png" /><figcaption>Fig. 4 - Dégustateurs non-entraînés (n=26)</figcaption></figure>
Conclusion

Les protocoles expérimentaux présentés dans cette communication permettent d'estimer les rôles respectifs
des caractéristiques sensorielles et des informations extrinsèques (appellation, marque, ...) dans la
formation du consentement à payer pour un vin. Les résultats obtenus montrent l'extrême hétérogénéité des
préférences individuelles, hétérogénéité souvent masquée par l'utilisation des moyennes dans les
évaluations. Ces différences inter-individuelles ne semblent pas s'atténuer lorsque les expérimentations sont
conduites avec des sujets entraînés. L'entraînement accroît la confiance des individus dans leur propre
jugement, mais, nous l'avons vu, ne fait pas nécessairement converger les évaluations. L'hétérogénéité des
préférences semble donc être un élément structurel qu'il faut analyser plus en détail, et dont il faudra, en
particulier, tester la stabilité dans le temps. Il s'agit là d'une voie prometteuse pour la poursuite de l'étude
expérimentale des comportements des consommateurs.

Enfin, les expériences présentées ici concernent l'estimation des valeurs individuelles. Il ne s'agit pas de savoir si les sujets connaissent ou savent évaluer les prix de marché, mais bien de les amener à révéler combien ils sont prêts à payer. Des protocoles incluant des interactions entre les participants peuvent être utilisés pour analyser comment se forme progressivement une idée commune du prix, et quelles sont les informations et les participants qui l'influencent le plus. Là encore, les perspectives de recherche ne manquent pas.

Références

1. Becker GM, DeGroot MH, Marschak J (1964) Measuring utility by a single response sequential method. *Behav Sci* **9**: 226-232.

2. Combris P, Bazoche P, Giraud-Héraud E et al (2009) Food choices: what do we learn from combining sensory and economic experiments? *Food Qual Prefer* **20**: 550-557.

3. Combris P, Lange Ch, Issanchou S (2006) Assessing the effect of information on the reservation price for Champagne: what are consumers actually paying for? *J Wine Econ* **1**: 75-88.

4. Lange Ch, Martin C, Chabanet C et al (2002) Impact of the information provided to consumers on their willingness to pay for Champagne: comparison with hedonic scores. *Food Qual Prefer* **13**: 597-608.

5. Bazoche P, Combris P, Giraud-Héraud E et al (2013) Willingness to pay for Appellation of Origin: results of an experiment with Pinot Noir wines in France and Germany. In Giraud-Héraud E, Pichery MC (Eds), *Wine Economics. Quantitative Studies and Empirical Applications*, Palgrave Macmillan, pp 27-50.
# Le réchauffement climatique est-il souhaité par les consommateurs de vin ?

## Approches croisées d'économie expérimentale et d'analyse sensorielle

A. FUENTES ESPINOZA<fnref n="1" />, S. PERES<fnref n="2" />, A. PONS<fnref n="3" />,<fnref n="4" />, S. TEMPERE<fnref n="5" />, P. DARRIET<fnref n="3" />, E. GIRAUD-HERAUD<fnref n="1" />*

Economie expérimentale – analyse sensorielle – consommateur – réchauffement climatique

## Introduction

De très nombreux travaux ont souligné l'importance des modifications des conditions de maturation des raisins et notamment la présence de plus en plus fréquente d'épisodes climatiques chauds et secs dans la région Bordelaise. A Bordeaux, ce phénomène climatique est en partie à l'origine d'une modification de la composition chimique des raisins récoltés de façon fortuite ou à dessein en conditions de maturité excessive. Ces vins issus de leurs vinifications, plus riches en alcool, moins acides, sont systématiquement marqués par des nuances caractéristiques de fruits cuits tels la figue et le pruneau rappelant ainsi l'expression aromatique traditionnelle des vins élaborés sous les latitudes plus chaudes et sèches.

Il reste que la nécessité de répondre à la demande d'une certaine clientèle correspond souvent à cette évolution des pratiques culturales. Dans ce contexte, il peut être utile de connaitre la possibilité réelle de généralisation de mise en vente de ces vins sur le marché de l'AOC considérée et de connaitre la capacité des consommateurs à accepter durablement ces nouvelles caractéristiques.

Pour répondre à cette problématique nous proposons un protocole nécessitant la mise en place d'un marché expérimental en laboratoire, couplé à une analyse sensorielle, auprès de consommateurs traditionnellement acheteurs des vins de Bordeaux.

## Matériel et méthodes

### Sélection des vins

Evaluation en laboratoire par un groupe d'experts. 20 vins rouges (millésime 2010) provenant d'une même AOC bordelaise et issus d'un assemblage à dominante merlot ont été dégustés par un jury composé de 48 dégustateurs professionnels. Ces dégustateurs devaient évaluer l'intensité des nuances 'fruit frais' et 'fruit cuit/confituré' sur une échelle continue. Au final, une analyse de comparaison des échantillons (Kruskall-Wallis) couplée à la méthode de majorité de jugement [1] nous a permis de classer l'ensemble de ces vins et de parvenir à la sélection de trois vins A, B, C : le vin A présentait l'intensité fruit cuit/confituré la plus faible, le vin B diamétralement opposé, l'intensité la plus forte, alors que le vin C présente un niveau d'intensité intermédiaire. Enfin, un vin 'pirate' A' a été confectionné à partir du vin A (13,9 %vol), par un ajout artificiel d'éthanol, afin de retrouver le niveau exact de pourcentage d'éthanol obtenu par le vin B (15,2 %vol.). Le vin C présentait un degré intermédiaire (14,4 %vol.). Ces vins ont ensuite été soumis au panel de consommateurs.

### Recrutement des consommateurs

184 consommateurs girondins composés de 87 femmes et 97 hommes ont été sollicités sur la base de leur consommation régulière de ce type de vins. Nous avons réparti ces consommateurs en deux groupes G1 et G2 ayant sensiblement les mêmes répartitions sur les critères de l'âge, du sexe et des catégories socio-professionnelles. Ces deux groupes étaient soumis au même protocole expérimental en laboratoire. Néanmoins, le groupe 2 était beaucoup plus familiarisé avec les vins extrêmes A et B puisque ces deux vins

<footnote n="1">¹ISVV, INRA, GREThA UMR CNRS 5113, 33882 Villenave d'Ornon, France</footnote>

<footnote n="2">²ISVV, Bordeaux Sciences Agro, 33882 Villenave d'Ornon, France</footnote>

<footnote n="3">³ISVV, INRA, USC 1366 Œnologie, 33882 Villenave d'Ornon, France</footnote>

<footnote n="4">⁴Seguin Moreau France, Z.I. Merpins, B.P. 94, F-16103 Cognac, France</footnote>

<footnote n="5">⁵ISVV, EA 4577, Unité de recherche Œnologie, F-33882 Villenave d'Ornon, France</footnote>
leur avaient été préalablement fournis. Dans le cadre d'une dégustation 'à la maison' portant sur deux jours, une bouteille de chaque vin avait été fournie à chaque consommateur avec la seule mention de référence A ou B en guise d'étiquetage. Notons par ailleurs que ces consommateurs du groupe G2 n'étaient à aucun moment avertis que les vins A et B étaient également présents le jour de l'expérience en laboratoire.

## Protocole consommateurs

L'objet de l'étude « affichée » auprès des consommateurs consistait à déclarer qu'il s'agissait uniquement de recueillir leur appréciation de différents vins de la région bordelaise, via des 'Notes Hédoniques' (NH sur une échelle non graduée de 0 à 10) en fonction de la couleur des vins, de leur odeur et de leur qualité gustative et d'autres caractéristiques extrinsèques liées à l'étiquetage, ce que nous appellerons des « étapes informationnelles ». Chaque consommateur devait de surcroit, pour chaque étape informationnelle et pour chaque vin, révéler son Consentement à Payer (CAP) en fonction de l'information dont il dispose (BDM, [2]). Le CAP est défini comme le prix maximum consenti pour acheter un vin (i.e. le prix au-delà duquel un consommateur refuse d'acheter le vin). Cette mesure est effectuée par une procédure de révélation directe (le consommateur déclare le CAP en fonction de l'information dont il dispose sur le vin) et incitative (le consommateur est incité à dire la vérité sur ce CAP). Le déroulement des étapes informationnelles était le suivant :

- **Etape 0 (cadrage informationnel)** : Information commune aux quatre vins sur le nom de l'AOC Bordelaise et le millésime (2010). Relevé d'un seul CAP par consommateur pour un seul vin correspondant à cette information.

- **Etape 1 (étape visuelle)** : Evaluation simultanée de la couleur de chacun des quatre vins.

- **Etape 2 (étape olfactive)** : Evaluation simultanée des arômes de chacun des quatre vins.

- **Etape 3 (étape gustative)** : Evaluation simultanée du goût de chacun des quatre vins.

- **Etape 4 (étape 'information degré d'alcool')** : Information donnée sur le degré d'alcool exact de chacun des quatre vins.

Au final, pour les étapes 1 à 4 chaque consommateur a produit une note hédonique pour chaque vin sur une échelle de 0 à 10 puis un CAP recueilli pour chaque vin compte tenu de l'information disponible. Comme on le voit, le protocole expérimental est un protocole en information croissante. Les quatre étapes s'attachent à respecter 'l'ordre naturel' de découverte des caractéristiques intrinsèques des vins.

## Résultats et discussion

La figure 1, représente l'évolution des CAPs moyens des groupes de consommateurs 1 et 2 en normalisant à 100 celui obtenu à l'étape 0 de l'expérience. Pour le groupe 1, le vin B est très nettement préféré au vin A. Les tests non paramétriques de Kruskal-Wallis montrent une préférence du vin B par rapport au vin A avec une significativité de 5% pour ce qui concerne l'étape 3 gustative et l'étape 4 d'information sur le degré d'alcool. Le vin C intermédiaire obtient un CAP moyen également intermédiaire entre le vin A et le vin B. A l'inverse, le vin pirate A' obtient le CAP moyen le plus faible. Cependant l'écart avec le vin A n'est pas significatif.

Sur la deuxième partie de la figure 1, nous montrons comment cette évolution des CAPs du groupe 1 peut être largement remise en question pour le groupe 2 (après familiarisation avec les vins). L'allure générale de l'évolution des CAPs est similaire, mais elle s'accompagne d'une inversion des CAPs, avec le vin A qui devient significativement préféré au vin B, pour les étapes 'olfactive' et 'information degré d'alcool'. Le vin C obtient là encore un CAP intermédiaire entre le vin A et le vin B, alors que le vin A' est maintenant considéré comme très inférieur et de façon significative à l'ensemble des autres vins.

Le point important que nous voulons soulever est que cette inversion des préférences n'est pas particulièrement liée à une meilleure appréciation du vin A entre les deux groupes (le CAP pour ce vin ne varie que de 6% entre les deux groupes et de façon non significative). Il s'agit au contraire d'un dés intérêt pour le vin B qui perd plus de 20% entre le groupe 1 et le groupe 2. Ce dés intérêt, mesuré ici à la dernière étape du protocole, est en réalité perceptible dès l'étape olfactive de l'expérience.

Une enquête complémentaire auprès des consommateurs sur leur perception et leur appréciation des caractéristiques des vins sélectionnés nous enseigne que si 63% des consommateurs du groupe 1 plébiscitaient le vin B, justement pour son caractère de fruit confituré, seulement 39% répondaient positivement à la même question pour ce qui concerne le groupe 2.
<figure><img src="image_413.png" /><figcaption>Fig. 1 - CAP moyen normalisé par vin et par étape d'évaluation</figcaption></figure>

A ce stade de notre interprétation des résultats, deux hypothèses peuvent être formulées afin d'expliquer cette modification des préférences. La première considère que les consommateurs du groupe 2 ont modifié leurs préférences suite à une exposition répétée des deux vins (comme suggéré par Köster [3]) ; ils expriment ainsi un effet de saturation suite à la consommation répétée du vin B, plus « riche » que le vin A. La seconde hypothèse prend en considération l'évolution aromatique et gustative différentes des deux vins au cours de la consommation à la maison. La mémoire sensorielle des consommateurs (pourtant non prévenus de la présence des mêmes vins entre la maison et le laboratoire) aurait alors pu entrainer ce retournement de situation. Rappelons en effet que les consommateurs ont disposé des vins jusqu'au jour de la dégustation et que par conséquent ils ont été à même de conserver en mémoire les sensations perçues au cours de la dégustation à la maison. Des expérimentations complémentaires sont actuellement en cours afin de valider l'ensemble de ces hypothèses.

Dans les deux cas, nous retrouvons ici un phénomène de renforcement de la capacité de discrimination des consommateurs après qu’ils aient été confrontés à la dégustation de différents vins [4], sachant que la reconnaissance des vins peut être acquise grâce à un apprentissage perceptif « incident » (phénomène inconscient observé notamment par Hughson et Boakes [5]). Il reste que la prise en compte des préférences de long terme (suivant les arguments développés entre autres par Köster [3]) est ici essentielle.

Conclusion

Cet article a rendu compte d'une expérience menée sur des caractéristiques des vins de Bordeaux qui seraient liées au réchauffement climatique. Nous avons alors montré la fragilité des jugements que l'on peut avoir sur des préférences de court terme et pourquoi il est indispensable de laisser le temps aux consommateurs d'évaluer les différents vins dans une ambiance familière, si l'on veut recueillir une information réellement structurante et révélatrice des achats répétés et réfléchis.

Ce résultat nous parait essentiel si l'on veut effectuer des projections sur l'adéquation offre-demande et sur les équilibres futurs des marchés. Dans le cas où l'offre de vins ne serait plus en adéquation avec la demande, il y aurait alors un risque important de détournement des consommateurs et, par voie de conséquence, de perte de part de marché.

Références

1. Balinski M, Laraki R (2013) How best to rank wines: majority judgment, pp 149-172. In Giraud-Héraud E, Pichery MC (Eds), *Wine Economics: Quantitative studies and Empirical Applications*, PALGRAVE Macmillan.

2. Becker G, DeGroot M, Marschak J (1964) Measuring utility by a single-response sequential method. *Behav Sci* **9**: 226-232.

3. Köster EP (2009) Diversity in the determinants of food choice: a psychological perspective. *Food Qual Prefer* **20**: 70-82.

4. Owen DH, Machamer PK (1979) Bias-free improvement in wine discrimination. *Perception* **8**: 199-209.

5. Hughson AL, Boakes RA (2009) Passive perceptual learning in relation to wine: short-term recognition and verbal description. *Q J Exp Psychol* **62**: 1-8.
# Making sense of wine:
## Cognitive Psychology's contribution to understanding wine tasting and wine tasters

W.V. PARR*

Department of Wine, Food & Molecular Biosciences, Faculty of AGLS,
Lincoln University, Christchurch, New Zealand

Psychology – wine – sensory – cognition

## Introduction

What allows us to appreciate a fine wine? And how do we make sense of the idiosyncratic thoughts, memories and emotions a wine can evoke?

Wine is as cerebral as it is sensual. Experiencing wine is not just a physical experience but also a cognitive and emotional experience. The sensory input associated with wine tasting is subjected to cognitive processing from the moment of perception. Emile Peynaud's frequently-reported observation that blind tasting is often disappointing alerts us to the importance of our cognitive processes when we experience a wine. Despite research in cognitive psychology and neuroscience confirming the cerebral nature of wine tasting, sensory scientists and professionals have been slow to embrace the opportunities offered by these cognate disciplines. It is within the last 20 years only that significant change has occurred, with innovative scholars challenging the contrived methodologies and a-theoretical, tool-box status of sensory evaluation by incorporating cognitive concepts to explain their data. Introducing methods and theories of cognitive psychology into sensory science, involving a philosophical shift in the field, is most obvious in the increased salience given to the role of the taster in oenological research and in particular, conceptualisation of the taster as a processor of information rather than an instrument that can be calibrated to produce repeatable and reliable data. By elevating the status of the wine taster and the wine-tasting context when considering a wine our understanding of wine-tasting phenomena has begun to progress beyond descriptive reports.

Definitions of *cognitive psychology* and *cognitive processes* are in order before discussing research to exemplify their contribution to understanding wine tasting. Cognitive processes are the subject matter of Cognitive Psychology, a discipline that takes observable facts in the form of an organism's behaviour and works backwards from the observations to infer how the observed state came about. For example, cognitive approaches take behavioural data such as the types of errors made by a wine taster to infer underlying cognitive processing. More specifically, cognitive processes are the cerebral processes involved in acquisition and use of knowledge [1]. These include the processes we use to perceive (i.e., to make sense of incoming sensory input), to carve up the perceived world into a sensible classification system (categorisation), for remembering, imaging, making judgments and decisions, and for communicating our perceptions and judgments to others. Since the 1960s, these processes have been considered within a behavioural model that views humans as information processors, rather than as passive recipients of one-way input [2]. The processes are assumed to occur in real time, either in parallel or consecutively, and are affected by inherent capacity limits of the human information-processing system, and by emotions. Although they are categorised as if they are separate processes, this is simplified for pragmatic reasons and in no way implies that they are not in constant interaction across real time with their boundaries blurred. Finally, much cognitive processing goes on outside conscious awareness; for example, an odour may influence our behaviour in the absence of us being consciously aware of either the presence of the odour or its influence on us.

When we evaluate wine, even by a simple recognition judgment (e.g., we report that we smell berry notes), virtually all the processes mentioned above are likely involved. From a psychological perspective, wine is complex relative to most food stimuli, not least because at the perceptual level wine assessment requires multi-modal processing of visual, olfactory (smell; aroma), gustatory (taste), and trigeminal (mouth-feel)

<footnote>*Corresponding author: wendy.parr@lincoln.ac.nz</footnote>
inputs. Further, the subsequent higher-order cognitive processes implicated in processing sensory input such as semantic (verbal) memory, classification, olfactory imaging, judgment and language tend to be relatively impoverished in humans where smell is involved. Hence, we often have difficulty 'capturing a wine in words' [3]. An important aspect of the cognitive processing implicated in wine tasting is integration of top-down and bottom-up information processes. In brief, this concerns how top-down processes involving knowledge and emotions influence attention and perception. Perception is not a one-way flow of information. An incoming stimulus, once detected, activates information already in our heads (memories; expectations; ideas; emotions) so that during perception, the bottom-up (data-driven) input from the objective stimulus (e.g., the wine in the glass) is interpreted using top-down (higher-order) cognitive processes such as categorisation and memory. Hence, the resulting subjective representation of the stimulus (the wine) that we form has right from the time of perception been modified by our unique physiology and psychological history. This raises the controversial issue regarding degree of objectivity that is possible in wine appreciation, including when analytical wine-tasting methods are employed. The analysis above in no way implies that the stimulus (i.e., the wine in the glass) does not contain objective properties that have potential to be experienced similarly by every taster; it merely argues that we are not blank slates, faithfully recording the objective properties of a stimulus or event, much like a videotape, but that our subjective representations will vary according to our physiology and experience, particularly when the sense of smell is involved.

## Relevant research

Drawing on cognitive psychology's methods and theories has advanced wine sensory science from research limited to mere description of effects (e.g., an influence of wine colour on smell) to studies that permit inferences about the underlying cognitive processing. Due to space limitations, this discussion of cognitive psychology's contribution to understanding wine tasting is highly selective rather than comprehensive.

### Perception and higher-order cognition

Two research areas concerning perceptual processing have high relevance for understanding wine tasting: (i) the multi-sensory nature of wine perception; and (ii) perceptual biases and contextual effects.

When we 'taste' wine, we experience sensory input via our visual, olfactory (smell by nose; aroma by retro-nasal olfaction), gustatory, and trigeminal systems. Recent psychological research concerning fundamentals of flavour perception has shown not only how inherently complex wine tasting is, but has led to a redefining of the term 'flavour' [4]. More specifically, research has shown that the anatomically independent sensory systems involving olfaction, taste, and trigeminal stimulation integrate cerebrally to form our subjective experience of flavour. One specific finding in the area that has relevance to wine tasting is demonstration that concurrent, multi-sensory inputs lead to interactions, the influence of odours on taste perception being the most often reported (e.g., olfactory-induced, enhanced sweetness judgments where a beverage with strawberry odour is judged to be sweeter than a beverage with identical sugar concentration but no odour). Many odour-taste interactions have been shown to be influenced by familiarity with the odour-taste combination (e.g., prior experience of strawberry as sweet), suggesting learning to underlie the effect. Interestingly, odour-taste associations can occur even when the interacting sensory inputs are sub-threshold when presented singularly [5], suggesting cross-modal summation at a neural level. Other fundamental research involving multi-modal perception demonstrates that humans, including experienced perfumers, have difficulty detecting more than two or three separate components in odour-taste mixtures, with smells being more difficult to detect than tastes [6]. The limited capacity of working memory (sometimes referred to as the span of attention) is implicated as the source of this difficulty.

A second influential area of research concerns how our perceptual processes not only facilitate and enhance a wine-tasting experience but can lead us to make erroneous judgments. Known as perceptual biases and contextual effects, specific findings include colour-driven olfactory bias, influence of extrinsic stimuli (e.g., wine price, weight of the bottle, knowledge of the producer) on wine quality judgments, and contextual effects such as influence of music or location (e.g., ambience of a laboratory vs restaurant) on wine judgments. Although influence of colour on perceived taste and/or smell of wine was demonstrated in the early 1960s by Rose Pangborn and colleagues, the data were interpreted descriptively only. Despite a large literature on biased judgment being available in cognitive psychology from the early 1970s [7], it was not until the turn of the century that a cognitive analysis of such effects in wine tasting was reported [8]. Morrot and colleagues demonstrated that when given a white wine coloured red with odourless
anthocyanin, oenology students reported more frequently that the wine had red wine characters (e.g., ‘cherry’) than when the wine presented to them was in opaque glassware so that the wine’s colour could not serve as an information cue to drive the judgment. This robust effect which can be interpreted in terms of the cognitive construct of ‘expectations’, an aspect of top-down cognitive processing, was reported later in highly-experienced wine professionals in New Zealand [9], demonstrating that expertise in the domain of wine does not necessarily protect us from this powerful, visually-driven olfactory bias. Prior knowledge and experience, presumably in the form of knowledge of the likely attributes of a red wine, and typically advantageous when making wine judgments, was in this case demonstrated to inhibit rather than facilitate accurate perceptual processing.

Other influential research drawing on psychological theory to understand wine tasting involves higher-order cognition, namely categorisation, thinking (inferential and deductive reasoning; judgment; decision making), imagery, memory, and language. These processes are considered to involve a deeper level of cognitive processing than many perceptual phenomena. Theories of human categorisation have been influential in interpreting wine sensory data concerned with (i) how we structure our wine knowledge, and (ii) wine typicality. Categorisation theories attempt to explain how we conceptualise the world and classify the myriad of stimuli that impinge upon us at any point in time. Prototype theory provides one view of how we do this, arguing that we form prototypes or ideal examples of a category on the basis of our experience with various exemplars. In other words, prototypes are subjective representations stored in memory. They are based on a measure of central tendency and specify the characteristics expected of an ideal or typical member of a category (e.g., the ideal Sauvignon blanc from Marlborough, New Zealand). Once a prototype has been formed cerebrally, all subsequent judgments of pertinent stimuli are assumed made with reference to the represented ideal. A particularly innovative study in this area was reported in 2001 [10] where the tasting notes of four well-known wine critics were examined via textual analysis (Alceste) to understand their experiences. Alceste [11] identifies within the raw data the language patterns (i.e., descriptions) most frequently used, putting the words/terms into classes. Brochet and Dubourdieu’s results demonstrated that the wine critics’ comments varied greatly across tasters, but fell in general into classes that corresponded with descriptions of either red wines or white wines. The authors referred to these classes in terms of wine prototypes, interpreting their data as demonstrating that tasters were largely driven by top-down cognitive processing. That is, a taster’s immediate experience of each wine (the data-driven input) was very much influenced by what was already in their head, their subjective representations of the categories ‘red wine’ and ‘white wine’ dominating all subsequent judgments. Perceived typicality of a wine is another research area that has progressed theoretically as a result of researchers drawing on theories of human categorisation [12, 13]. Both varietal typicality and regional typicality (provenance) have been investigated, with typical or ideal wines shown to exhibit certain characteristics (e.g., a combination of fruity and green characters in Sauvignon blanc wines from New Zealand) that other wines in the category share less of, and wines outside the category may have none or few of. The work has also demonstrated the importance of top-down cognitive input (i.e., knowledge and experience), with less-experienced tasters exhibiting increased variability regarding the characteristics essential to high typicality exemplars of a wine varietal [14].

Other research involving higher-order cognition and wine appreciation has investigated imagery, semantic (verbal) memory, and language. An area of research that implicates higher-order cognition involves investigation of the role of imaging processes in odour identification [15]. The researchers employed innovative methodology requiring study participants to engage in imagery in an odour identification task, demonstrating superior abilities in wine experts relative to less-experienced people. These data support the notion that experience enhances olfactory identification, a notoriously poorly-performed skill that is essential in wine appreciation. Further, the researchers employed dependent measures common to cognitive psychology (response times; types of errors), allowing them to conclude that the longer time taken by experts relative to novices to identify correctly an odour related to a deeper level of cognitive processing by the experts. This type of behavioural work not only aids development of theory pertaining to wine tasting but the results lend themselves to being mapped to neurophysiological data, eventually giving a more complete analysis of the cerebral processes implicated in superior wine-tasting abilities.

Finally in this section, wine-tasting research with a cognitive focus has also shown how tasting-task requirements can lead tasters to adopt different cognitive strategies. A recent study of perceived complexity in white wine [16] reports data suggesting that judging an abstract wine attribute like complexity encouraged tasters to see the wine as an integrated whole, rather than to deconstruct it. That is, tasters
associated other global wine characteristics such as harmony and balance with perceived complexity, rather than qualities such as the number of distinct components identifiable in the wine, the latter more in keeping with seeing the wine's parts as separate elements. Such results suggest that evaluation of global aspects of a wine such as quality or complexity involves cognitive processing that differs to that involved when more concrete, distinct aspects of a wine are evaluated (e.g., degree of sweetness or oaky character).

## Emotion and cognition

Emotion and cognition are easy bedfellows when it comes to wine. An everyday example is how the smell of a wine can effortlessly evoke memories and emotions associated with the perfume of a former lover. Cognitive psychology's extensive literature demonstrating influence of odours on behaviour, memories, moods, and emotions [17], supported by neuroscience evidence of a shared neural substrate, includes findings relevant to wine tasting. First, a robust finding is that olfactory-induced influences (i.e., observed behaviour change associated with presence of an odour) occur even when we are not consciously aware of either the presence of the odour or its effect on our behaviour. Second, autobiographical memories (i.e., memory for personally-experienced events), and the emotions typically associated with autobiographical memories, have been shown to play a major role in how we name and respond both analytically and hedonically to smells, especially smells that we learned during childhood. Hence our histories, exemplifying learning (e.g., prior conditioning where a mouldy odour and negative feelings have become strongly associated) are integral to how we respond to olfactory stimuli. Finally, memory research has shown that not only are distinctive olfactory experiences remembered well, but they are remembered so well that they are relatively impervious to forgetting or modifying. This effect argues against the validity of attempting to train tasters to consensually name a specific odour; linguistic uniformity may result, but this does not imply conceptual uniformity. Indeed, odours are the thorn in the side of consensus methodologies. To conclude this section, a different approach to understanding emotion, cognition, and wine tasting was reported recently in a study focusing not on olfaction but on higher-order cognitive processes related to language [18]. The study aimed at elucidating the emotions, positive and negative, evoked in wine tasters when they experienced wines, an approach that offers promise for broadening our understanding of wine-tasting phenomena.

## The consensus model, inter-individual differences, and wine expertise

Research reported above demonstrates how a consensus model of taster behaviour is inappropriate for most sensory analysis of the complex beverage known as wine. Demonstrated differences amongst wine tasters, reflecting each individual's physiology, experience and knowledge, limit the usefulness of consensus models. Further, research demonstrates that perception involving taste and smell, important to wine tasting, is much more diverse amongst people than is perception involving vision, hearing, and trigeminal stimulation. Hence, contrived methodologies that attempt to align tasters both conceptually and linguistically, often in an effort to align sensory data with wine chemical composition or to limit variability for other reasons, are unlikely to produce valid data in the sense of real-world, wine-tasting phenomena. If a certain degree of consensus is desired, it can be achieved by selection of a tasting task and wine evaluation context to maximise such. None-the-less, research based in methods and theories of cognitive psychology makes clear that aiming for within-taster and between-taster consensus is an ideal, rather than a reality.

Oenological sensory researchers working within cognitive frameworks have progressed the field by modifying the traditional consensus methodologies to allow data demonstrating differences amongst tasters to become the data of interest. Two topic areas have been focused on, cultural differences and understanding wine expertise. Due to space limitations, the latter only will be discussed. Precisely what constitutes wine expertise was considered by psychologists J.J. and E. Gibson in 1955 when they enquired as to what a wine expert had learned that a less-experienced taster had not. Methodologies for studying expertise in a specific domain such as chess, developed in psychology in the 1930s, were slow to appear in sensory science, presumably due to the dominance of consensus methodologies. An innovative Ph.D. student in the late 1980s changed this state of affairs [19], investigating linguistic aspects of wine expertise. Solomon employed matching-task methodology where study participants matched wine descriptions generated by others (experts and novices) to wines. From his study, Solomon concluded that an important aspect of wine expertise involves classification and language processes that develop as a function of experience, with the wine experts' knowledge about wines being better structured (e.g., their wine categories were better differentiated) than those of novices. Subsequent researchers [20] drew on methodology from cognitive research concerning chess Masters, concluding also that organisation of
knowledge (e.g., forming of prototypes of wine varietals) and linguistic skill were important in wine expertise. Other research that has investigated the specific cognitive processes underlying aspects of wine expertise argues that perceptual phenomena play a role also [21, 22]. Overall, recent studies on wine expertise have theoretically and methodologically advanced the research area concerned with cognitive processes implicated in various aspects of wine tasting.

## Conclusion

Research bringing focus to the wine taster as an information processor, actively interacting with the wine in the glass, has markedly advanced our understanding of wine-tasting phenomena. Arguably the most important contributions from cognitive psychology are (i) adoption of methodology that permits wine-tasting data to be interpreted theoretically (i.e., permits inference regarding type of cognitive processing underlying performance within any particular task or context), and (ii) appreciation that inter-individual differences are valid and informative data rather than error in the measuring machine that needs to be ironed out by training to consensus. Together, these aspects have paved the way for research that further delineates the ways in which cognitive processes of perception, categorisation, memory, thinking (sensory and verbal) and language are implicated in wine tasting, including in development of wine expertise. A promise for even greater understanding in future is offered by increased interdisciplinary links between oenology, cognitive psychology and the neurosciences. Cognitive psychology's behavioural data and hypothesised cerebral constructs, in conjunction with recent technological advances in neurosciences (e.g., electrophysiology and neuroimaging techniques), offer opportunities to map specific behavioural phenomena associated with wine tasting to observed cerebral activity.

To end, let us re-visit blind tasting. We have seen that blind tasting may well be disappointing due to the limits it places on use of top-down information processing. But, precisely what is happening cognitively when a wine is tasted blind? With colleagues at the University of Burgundy, we have some hot-off-the-press data that provide one insight into this issue. When wine professionals from Burgundy and New Zealand tasted Pinot noir wines in opaque glasses (the fully 'blind' condition) and in clear glasses to judge overall wine quality, data show an attenuation or truncation of responses in the opaque-glass condition. The tasters not only gave lower quality ratings to the wines when they were presented in opaque glasses, but they were more conservative in their use of the rating scale by scoring within a more narrow range when evaluating the wines in opaque glassware relative to clear glassware. Arguably the clear-glass condition provided a more ecologically-valid context, so that a cognitive interpretation of these data is that the fully-blind condition resulted in more cautious (i.e., less certain) responding by wine professionals due to the context (black glassware) serving as a source of intimidation, influencing both cognitive and emotional behaviour of tasters.

## Acknowledgements

I thank the New Zealand Grape and Wine Research Programme for funding, and the Organising Committee of Oeno2015 for inviting me to present this work.

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# Comment le cerveau perçoit-il le monde des odeurs ?
## De nouvelles perspectives pour la perception sensorielle du vin

G. LEPOUSEZ*, G. GHEUSI, P.-M. LLEDO

CNRS UMR 3571 « Gènes, Synapses et Cognition » Unité « Perception et Mémoire »,
Institut Pasteur, Paris, France

Neuroscience – olfaction – apprentissage – récepteurs olfactifs

"Le gout du vin n'est pas seulement dans le verre, il est aussi dans la tête." Frédéric Brochet

## Introduction

Dans le contexte de la théorie de l'information, une compréhension intégrée et globale de l'univers des arômes présents dans le vin passe non seulement par une analyse biochimique de la complexité des composés volatils contenus par le vin mais aussi par l'étude du système de détection et d'analyse de ces composés. C'est notre système olfactif au sein de notre cerveau qui joue ce rôle à la fois de détection, d'analyse et de stockage en mémoire.

## Système olfactif

Le point d'entrée de la perception olfactive se situe au niveau de l'épithélium olfactif où se trouvent les neurones sensoriels olfactifs. Au sommet de ces cellules, des cils olfactifs portent les récepteurs olfactifs, qui vont détecter et transduire la présence de molécules volatiles en signal électrique. A l'autre extrémité des cellules se retrouvent le début des projections nerveuses axonales qui vont se regrouper pour former le nerf olfactif. Ce nerf fragile traverse un os très fin, la lame criblée, pour se connecter au cerveau au niveau du bulbe olfactif, qui est la première structure du cerveau qui va recevoir l'information olfactive (Figure 1).

<figure><img src="image_414.png" /><figcaption>Fig. 1 - Le système olfactif</figcaption></figure>

<footnote>*Auteur principal : gabriel.lepousez@pasteur.fr</footnote>
Pour reconnaitre les molécules volatiles, ils existent 400 récepteurs olfactifs différents chez l'homme, portés par plusieurs millions de neurones olfactifs. Ces récepteurs fonctionnent comme des serrures dans lesquelles seule une molécule ou des molécules très proches peuvent entrer et activer le récepteur. Cette découverte dans les années 90 a permis aux chercheurs américains Richard Axel et Linda Buck de recevoir le Prix Nobel de Médecine en 2004. Grâce à leurs travaux, nous connaissons aujourd'hui la nature de ces récepteurs, leur nombre et le mécanisme par lequel la fixation d'une molécule volatile induit une cascade de réactions à l'intérieur de la cellule, déclenchant un signal électrique dans la cellule qui est ensuite transmis au bulbe olfactif.

Combien d'odeurs différentes sommes-nous capable de discerner avec 400 récepteurs olfactifs ? Une étude récente [1] vient bouleverser les estimations initiales puisqu'elle suggère que nos 400 récepteurs nous permettraient de discriminer autour de mille milliards d'odeurs. Ce phénomène s'explique par la règle de codage utilisé par le système olfactif : chaque molécule olfactive active une combinaison de récepteurs [2]. En effet chaque molécule possède une structure chimique complexe qui lui permet d'activer différents récepteurs. Ainsi une molécule volatile est reconnue par plusieurs récepteurs et un récepteur reconnait plusieurs molécules similaires.

Les propriétés des récepteurs olfactifs et du codage combinatoire ont plusieurs conséquences importantes. Premièrement, si un composé est capable d'activer 3 récepteurs, ces mêmes récepteurs peuvent aussi être activés avec deux ou plusieurs molécules distinctes. En d'autres termes, un mélange de molécules peut être perçu comme une seule et même odeur, on parle de perception synthétique des mélanges. Le système olfactif réalise donc une synthèse plutôt que d'analyser chaque composé séparément. Deuxièmement, comme chaque récepteur n'est pas sensible à une seule molécule mais à un panel de molécules similaires, il reste très difficile du point de vue théorique et technique d'identifier les "clés" de chaque récepteur. Aujourd'hui, seuls 29 des 400 récepteurs ont été caractérisés [3]. Cette caractérisation indique que 1) un récepteur peut être activé par plusieurs molécules très proches mais avec des efficacités variables en fonction des molécules, 2) les "clés" sont plus complexes qu'une simple fonction chimique théorique (ester, alcool, aldéhyde, etc) et 3) la formule chimique d'une molécule seule ne peut pas permettre de prédire l'odeur de cette molécule. Troisièmement, la présence de plusieurs composés dans un mélange peut amener à des interactions moléculaires non-linéaires au niveau de chaque récepteur qui vont modifier les propriétés de détection des récepteurs et induire des phénomènes de synergie et de masquage [4]. Un exemple œnologique intéressant est celui du 2,4,6-trichloroanisole (TCA) qui est capable d'induire un effet de masquage général en atténuant la transduction des récepteurs olfactifs de manière non-spécifique [5].

Si Richard Axel et Linda Buck ont été les premiers à décrire les récepteurs olfactifs et leur fonctionnement, ils ont aussi fait deux découvertes qui permettent de comprendre la logique du codage des odeurs dans le cerveau. D'une part, chaque neurone olfactif exprime un seul des 400 récepteurs olfactifs et, d'autre part, tous les neurones olfactifs exprimant le même récepteur convergent en un seul et même point à la surface du bulbe olfactif. Ainsi, en identifiant quelle zone du bulbe olfactif est activée en présence d'une odeur, le cerveau peut connaître indirectement les récepteurs activés, et potentiellement, les molécules volatiles olfactives présentes dans l'environnement. Le système olfactif fabrique donc une représentation spatiale des odeurs, on parle de cartes olfactives. De manière intéressante, dans le bulbe olfactif, ces cartes olfactives sont relativement similaires et communes d'un individu à l'autre. Que deviennent ces cartes dans le cerveau ? Elles sont transmises au cortex olfactif, le centre de la mémoire olfactive et de la représentation des odeurs. Or plusieurs travaux récents [6-8] montrent que, dans le cortex olfactif, ces cartes olfactives communes laissent la place à une représentation propre à chacun et largement dépendante de notre expérience olfactive. En d'autres termes, si nous faisons tous appel au même schéma de codage dans le bulbe olfactif basé sur une représentation spatiale commune de l'odeur, nous utilisons et interprétons ces cartes olfactives tous de manière distincte parce que nous avons appris à l'utiliser de manière différente. Une fois l'odeur mise en mémoire, elle sera associée à d'autres informations sensorielles (couleur, saveurs, etc), sémantiques et surtout émotionnelles. Notre expérience, notre apprentissage et notre culture sculptent donc profondément notre mémoire des odeurs et ceci a d'importantes implications jusque dans la sémantique utilisée pour décrire les arômes d'un vin à travers les cultures.

## Mémoire olfactive

Comment l'expérience, la pratique et l'expertise olfactive modifient-elles notre perception olfactive ? Plusieurs travaux de psychophysique montrent que, par rapport à un individu contrôle, les experts olfactifs
(sommeliers, œnologues ou parfumeurs) présentent une meilleure capacité d'identification et de verbalisation des odeurs, associée à une meilleure mémoire de ces odeurs et une meilleure capacité d'identification des composées dans un mélange pour des odeurs familières [9, 10]. L'expertise olfactive a une action directe sur notre cerveau et sur ses capacités de plasticité. Des travaux d'imagerie cérébrale des régions importantes dans le traitement olfactif (cortex olfactif et cortex orbito-frontal) montrent que plus l'expertise est grande, plus les zones d'activation en réponse à une odeur sont réduites [9, 10]. Chez les experts, les représentations olfactives semblent être précises et optimisées, permettant une réduction des interférences entre les représentations de différentes odeurs, une meilleure résolution des mémoires olfactives et potentiellement une extension des capacités de stockage. En plus de cette optimisation dans le fonctionnement de notre cerveau olfactif, des travaux montrent que l'expertise induit aussi une augmentation relative de la taille du cortex olfactif et orbito-frontal, alors que ces régions ont tendance à réduire de taille avec l'âge chez une personne normale. La pratique olfactive serait donc bénéfique pour protéger certaines zones du cerveau contre une dégénérescence lente et progressive liée à l'âge. Les progrès technologiques permettent maintenant d'étudier ces phénomènes de plasticité et de modification avec l'expérience olfactive à l'échelle des neurones et des connections du cerveau. Des travaux récents montrent par exemple qu'un apprentissage olfactif va profondément modifier les connections et l'impact du siège de la mémoire olfactive, le cortex olfactif, sur le bulbe olfactif [11]. Ce travail suggère donc qu'un apprentissage permettrait d'optimiser notre perception précoce de certains composés à la lumière de notre mémoire olfactive. Ceci pourrait expliquer en partie comment le contexte ou comment d'autres modalités sensorielles (ex : couleur) influencent notre perception.

## Conclusion

En intégrant différents niveaux d'analyse, allant de la génétique moléculaire jusqu'aux approches de psychophysique, la recherche actuelle en neurosciences commence donc à mieux comprendre comment notre système olfactif décompose un mélange complexe de composés pour reconstruire une représentation sensorielle, pour la mémoriser et pour l'associer avec d'autres sensations ainsi qu'avec nos émotions. Les perspectives pour les professionnels du vin sont très nombreuses et le champ de la "neuro-œnologie" émerge comme une nouvelle branche de l'œnologie moderne.

## Références

1. Bushdid C, Magnasco MO, Vosshall LB et al (2014) Humans can discriminate more than 1 trillion olfactory stimuli. *Science* **343**: 1370-1372.

2. Malnic B, Hirono J, Sato T et al (1999) Combinatorial receptor codes for odors. *Cell* **96**: 713-723.

3. Mainland JD, Keller A, Li YR et al (2013) The missense of smell: functional variability in the human odorant receptor repertoire. *Nat Neurosci* **17**: 114-120.

4. Thomas-Danguin T, Sinding C, Romagny S et al (2014) The perception of odor objects in everyday life: a review on the processing of odor mixtures. *Front Psychol* **5**: 504.

5. Takeuchi H, Kato H, Kurahashi T (2013) 2,4,6-Trichloroanisole is a potent suppressor of olfactory signal transduction. *Proc Natl Acad Sci USA* **110**: 16235-16240.

6. Ghosh S, Larson SD, Hefzi H et al (2011) Sensory maps in the olfactory cortex defined by long-range viral tracing of single neurons. *Nature* **472**: 217-220.

7. Miyamichi K, Amat F, Moussavi F et al (2012) Cortical representations of olfactory input by trans-synaptic tracing. *Nature* **472**: 191-196.

8. Sosulski DL, Lissitsyna Bloom M, Cutforth T et al (2011) Distinct representations of olfactory information in different cortical centres. *Nature* **472**: 213-216.

9. Royet J-P, Plailly J, Saive A-L et al (2013) The impact of expertise in olfaction. *Front Psychol* **4**: 928.

10. Pazart L, Comte A, Magnin E et al (2014) An fMRI study on the influence of sommeliers' expertise on the integration of flavor. *Front Behav Neurosci* **8**: 358.

11. Lepousez G, Nissant A, Bryant AK et al (2014) Olfactory learning promotes input-specific synaptic plasticity in adult-born neurons. *Proc Natl Acad Sci* **111**: 13984-13989.
# Minerality in wine: what do consumers and wine professionals think about?

P. DENEULIN<fnref n="1" />,<fnref n="4" />,<fnref n="5" />*, Y. LE FUR<fnref n="2" />, G. LE BRAS<fnref n="3" />, L. GAUTIER<fnref n="4" />, F. BAVAUD<fnref n="5" />

Mineral – semantic cartography – representation of minerality – flinty note

## Introduction

Minerality has emerged as a wine-tasting term quite recently. The concept of minerality is spread worldwide and it seems to be the most widely used word for describing a wine today. While there is no common definition, it is often used to highlight wine quality and as a selling point. Most texts describe minerality as a flinty, smoky, or sulphurous odour or as a palate perception of acidity and freshness [1, 2]. It is therefore legitimate to enquire whether this term is just an “empty marketing concept” or whether it corresponds to one or more hard and fast ideas in people’s minds. Has the professional understanding of the word trickled down to consumers?

## Materials and methods

### On-line survey

To study what consumers and wine professionals think about minerality (without tasting), an on-line survey was conducted among French-speaking people in France and Switzerland between 2011 and 2013 [3]. The survey comprised a socio-demographic section and three open-ended questions about minerality in wine. This study analyses only the first of these open questions: “If I speak to you about minerality in wine, what comes to mind?” The responses from 1697 consumers and 1898 wine professionals varied greatly in length and content. Some pre-processing was necessary before the textual data (sentences) could be analysed:

- Correction of mistakes,

- Lemmatization of the words, that is, conversion of the terms into standardized forms (masculine singular for adjectives and nouns, infinitive for verbs),

- Inclusion of “meaningful” words only (nouns, verbs and adjectives) and removal of all other grammatical forms which we considered here to carry no information.

### Data analysis

Finally, two contingency matrices cross-tabulating respondents and words were compiled, one for each category of respondents (consumers and professionals). Words occurring fewer than five times were removed from each matrix. Then, aggregated lexical tables [4] were created for each variable of interest and compared using the chi-squared test.

## Results and discussion

### Diversity of answers

The number and diversity of words available to wine professionals were greater than those available to consumers. Professionals had more terms to talk about minerality and they seemed more familiar with the concept. Table 1 presents a comparison of lexical diversity between consumers and wine professionals.

<footnote n="1">¹University of Applied Sciences and Arts, Western Switzerland, CHANGINS, Viticulture and oenology, Nyon, Switzerland</footnote>

<footnote n="2">²AgroSup Dijon, France</footnote>

<footnote n="3">³Institut Œnologique de Champagne, Mellecey, France</footnote>

<footnote n="4">⁴University of Burgundy, Dijon, France</footnote>

<footnote n="5">⁵University of Lausanne, Switzerland</footnote>
"Tokens" is the total number of words, "types" is the number of different words and "hapax" is words with just a single occurrence. Lexical diversity was greater for professionals than for consumers. In plain text, professionals used 28 words on average against just 17 for consumers when speaking about minerality. This difference was the same after pre-processing, with 14 meaningful words for professionals versus 9 for consumers.

<table><caption>**Table 1** - Lexical diversity between consumers and wine professionals</caption><thead><tr><th rowspan="2"></th><th colspan="2">1'898 Wine professionals</th><th colspan="2">1'697 Consumers</th></tr><tr><th>Number</th><th>Percentage per professional</th><th>Number</th><th>Percentage per consumer</th></tr></thead><tbody><tr><td></td><td colspan="4" style="text-align: center;">Unprocessed</td></tr><tr><th>Tokens</th><td>52'316</td><td>27.6</td><td>29'371</td><td>17.3</td></tr><tr><th>Types</th><td>4'353</td><td>2.3</td><td>2'767</td><td>1.6</td></tr><tr><td></td><td colspan="4" style="text-align: center;">After pre-processing</td></tr><tr><th>Tokens</th><td>25'908</td><td>13.7</td><td>14'293</td><td>8.6</td></tr><tr><th>Types</th><td>2'634</td><td>1.4</td><td>1'667</td><td>1</td></tr><tr><th>Hapax</th><td>1'302</td><td>0.7</td><td>838</td><td>0.5</td></tr></tbody></table>

*Specific vocabulary between professionals and consumers*

Diversity of the vocabulary used was also an important feature for distinguishing between professionals and consumers. To analyse specific types used by each group, a chi-squared test was conducted on the 192 words used more than 30 times. The analysis revealed two significant semantic profiles (chi-squared=3777.6; ddl=191; p-value < 0.001). 75 types were used significantly (95%) more by professionals but only 40 in all by consumers. Table 2 compares the most significant types used by professionals (on the left) and consumers (on the right).

<table><caption>**Table 2** - Comparison of the most frequent words used by professionals (left) and consumers (right). Percentages represent the number of occurrences divided by the number of individual responses (1898 for professionals and 1697 for consumers).</caption><thead><tr><th rowspan="2">Types</th><th colspan="2">professionals</th><th colspan="2">consumers</th></tr><tr><th>%</th><th>%</th><th>%</th><th>%</th></tr></thead><tbody><tr><td> fusil gun (flint)</td><td>29.56</td><td>8.19</td><td>goût taste</td><td>13.28</td><td>34.65</td></tr><tr><td> fraîcheur freshness</td><td>17.97</td><td>3.65</td><td>Indétermination Indetermination</td><td>0.26</td><td>13.14</td></tr><tr><td> note note</td><td>14.17</td><td>2.47</td><td> minéral mineral</td><td>13.59</td><td>26.10</td></tr><tr><td> silex flint</td><td>19.60</td><td>5.01</td><td>terre earthy</td><td>4.74</td><td>14.50</td></tr><tr><td> salinité salinity</td><td>8.06</td><td>0.77</td><td> comme like/as</td><td>0.00</td><td>3.59</td></tr><tr><td> aromatique aromatic</td><td>7.90</td><td>1.18</td><td> penser to think</td><td>10.70</td><td>16.91</td></tr><tr><td> expression expression</td><td>8.01</td><td>1.24</td><td> vigne vine</td><td>4.06</td><td>9.13</td></tr><tr><td> équilibre balance</td><td>4.00</td><td>0.00</td><td> pousser to grow</td><td>0.63</td><td>4.24</td></tr><tr><td> finesse subtlety</td><td>5.85</td><td>0.59</td><td> eau water</td><td>1.84</td><td>4.89</td></tr><tr><td> minéraux minerals</td><td>3.64</td><td>0.00</td><td> sol soil</td><td>15.75</td><td>18.15</td></tr><tr><td> acidité acidity</td><td>15.49</td><td>4.71</td><td> terrain ground</td><td>0.63</td><td>2.77</td></tr><tr><td> craie chalk</td><td>8.17</td><td>1.71</td><td> différent different</td><td>1.26</td><td>3.54</td></tr><tr><td> tension tenseness</td><td>4.32</td><td>0.41</td><td> composition composition</td><td>0.58</td><td>2.47</td></tr><tr><td> longueur lenght</td><td>4.06</td><td>0.35</td><td>rapport link</td><td>0.90</td><td>2.36</td></tr><tr><td> Riesling Riesling</td><td>5.64</td><td>0.94</td><td></td><td></td><td></td></tr><tr><td> complexité complexity</td><td>3.74</td><td>0.41</td><td></td><td></td><td></td></tr><tr><td> schiste schiste</td><td>3.95</td><td>0.53</td><td></td><td></td><td></td></tr></tbody></table>

Professionals associated minerality with sensory perceptions, both olfactory and palate perceptions. The most relevant type was "fusil" for "pierre à fusil" in French (meaning gunflint or flint in English). About 30% of professionals thought that minerality was a flint odour, whereas it was mentioned spontaneously by only 8% of consumers. Professionals formed a clear response around an aromatic expression of flint ("pierre à fusil" and "silex") associated with chalk, freshness, salinity, acidity and tenseness. Minerality also seems to be a qualitative perception of subtlety, balance and aromatic length.
Semantic terms used by consumers were completely different. Many of them (13%) did not know what minerality was and could not answer the question (they signalled their uncertainty with marks such as ? or ...). The sensory dimension appeared only with the word "taste" but no particular taste (or odour) was mentioned. They associated minerality with the taste of wine given by the soil where the vine grows but they did not know how it expressed itself in wine. They associated it with the composition of wine. They also compared minerality with mineral water and the various minerals it contains.

*Semantic cartography within each group of respondents*

To refine the content of the responses, the respondents in each group were subdivided into specific categories. Professionals and consumers were respectively segmented by their occupation and their declared knowledge on the basis of two of the questions in the socio-demographic part of the survey. Each sub-group was characterized by means of a chi-squared test.

Occupation impacted answers and particularly references employed to talk about minerality. People working in wine-related occupations referred to sensory perception more than people working in vine-related jobs. Wine sellers considered minerality to refer to an odour of stone and chalk notes while marketing people associated it with aromatic length. Sommeliers looked for the wine balance while oenologists spoke more about the wine's complexity. For vine and wine growers, minerality was impacted by soil and the terroir.

For consumers, two opposing sub-groups were contrasted in terms of vocabulary. Novices (respondents with the least knowledge of wine) were those who did not know what minerality was and answered using question or suspension marks. Some thought that minerality was related to the composition of wine and referred to mineral water. By contrast, wine lovers (consumers claiming to be experts were omitted because they were too few to be representative) used a vocabulary very similar to professionals' and referred to flint odour, freshness, and stone, but also found minerality more pronounced in white than red wines. They also gave examples.

## Conclusion

The mental picture analysed for wine professionals and consumers shows that minerality is a polysemic and ambiguous term. For wine professionals, minerality is more a sensory concept based on odour and palate perceptions, but still a good marker of wine quality. For consumers, minerality is more an expression of soil and terroir, with or without particular aromatic notes depending on their knowledge. The connection with the soil is also evoked by vine growers and discussed by Maltman [5].

The use of the term "minerality" might be confusing for novice consumers who may imagine they are being sold something akin to mineral water. Hardly a laughing matter!

## References

1. Coutier M (2007) *Dictionnaire de la langue du vin*, CNRS éditions: Paris, France.

2. Ballester J, Mihnea M, Peyron D et al (2013) Exploring minerality of Burgundy Chardonnay wines: a sensory approach with wine experts and trained panellists. *Aust J Grape Wine Res* **19**: 140-152.

3. Deneulin P, Gautier L, Le Fur Y et al (2014) Corrélats textuels de typologies sensorielles : analyse d'une enquête en œnologie. *In Actes des 12ièmes journées internationales d'analyse statistiques de données textuelles (JADT 2014)*, pp 209-223.

4. Lebart L, Salem A, Berry L (1998) *Exploring textual data*, Dordrecht: Kluwer.

5. Maltman A (2013) Minerality in wine: a geological perspective. *J Wine Res* **24**: 169-181.
# Effet du vieillissement sur la perception sensorielle de la minéralité des vins Chablis 1er Cru

H. RODRIGUES<fnref n="1" />,<fnref n="2" />*, D. VALENTIN<fnref n="2" />,<fnref n="3" />, J. BALLESTER<fnref n="2" />,<fnref n="4" />

Millésime – minéralité – oxydation – perception

## Introduction

Le mot minéralité, largement employé tant par certains professionnels que par les consommateurs, n'est pratiquement jamais défini de manière précise, ce qui en fait un descripteur intrigant [1]. La première apparition du mot minéral associé aux vins date de 1946, dans le livre *Les Imprudents* de Marguerite Duras p. 68 : « Pour leur délier la langue qu'ils retenaient d'habitude (comme si parler en semaine eût été pécher), le vin d'Uderan faisait merveille, un vin blanc un peu sec, qui avait pris la saveur minérale des plateaux ». Dès la première apparition, le mot minéralité dénote clairement qualité aux vins qu'il fait référence. De nos jours, son utilisation est telle qu'elle apparaît comme un phénomène de mode, une tendance autant chez les professionnels que chez les amateurs de vins [2]. L'augmentation de l'utilisation du mot minéralité est remarquable. En effet, ce descripteur était pratiquement inexistant il y a seulement deux décennies, mais il bénéficie maintenant d'une très forte utilisation [3]. Paradoxalement, cette expression qui est très en vogue dans la filière du vin est absente dans les dictionnaires de la langue française, comme le *Larousse* (2014) et le *Petit Robert* (2014), mais elle est présente comme un néologisme dans le *Dictionnaire de la Langue du Vin* de Martine Coutier [4]. Minéral et minéralité, une sensation qui évoque l'odeur ou le goût de certains minéraux ou de roches, silex, pierre-à-fusil, craie. Cependant, il n'existe pas une définition précise, juste des exemples dans lesquels l'expression est retrouvée. Dans ces exemples, l'auteur fait référence à des dimensions du goût « ...dont la minéralité sous-jacente contrebalance la sucrosité (...) » (M. Mastrojanni, *Le Grand Livre des Vins d'Alsace*, 1993, p. 78), des dimensions d'arômes « Nez discret et fermé au départ qui révèle à l'aération une complexité remarquable : minéralité (pierre-à-fusil, silex, craie) enveloppante et élégante, complétés par des notes butyreuses et épicées (...) » (Le Rouge et Le Blanc, 2005, no. 78, p. 19) et d'une liaison avec la composition du sol évoquant le terroir « A l'attaque, la minéralité surprend, expression d'un sol argilo-calcaire sur base de Kimméridgien (...) » (L'Amateur de Bordeaux, sept.-oct. 2002, no. 81, p. 19.).

L'origine de la minéralité des vins est encore une énigme. Peynaud et Blouin, dans *Le Grand Livre de la Dégustation - Le Goût du Vin*, 5ème édition de 2013, consacrent un chapitre à la minéralité où ils affirment que « ...il est très difficile, voire impossible, de simuler, provoquer, accentuer ou supprimer la minéralité, même en laboratoire, contrairement à la plupart des caractères olfactives ou gustatifs » [1].

Généralement, la minéralité des vins est associée dans la littérature à plusieurs descripteurs, parmi eux, les descripteurs métalliques, arômes et goûts salins [5], silex, pierre-à-fusil, iodé, craie, acide, fraîcheur et fumée [6-10]. Heymann et al. [10], en faisant une exploration sur la perception de la minéralité de vins blancs reconnus comme minéraux par la presse spécialisée et en utilisant des experts et un panel entrainé, ont montré une corrélation positive de la note minérale avec le goût acide et citronné, la fraîcheur, la pierre mouillée, les arômes chimiques, les arômes et le goût de réduction, herbacés et calcaires. La note minérale dans cette étude était négativement corrélée avec les notes de beurre, caramel au beurre, vanille, arômes boisés, miel, fruit, moisi et pipi de chat. Certaines publications scientifiques ont mis en évidence le caractère multimodal de la minéralité. Parr et al. [11], dans une étude sur le Sauvignon blanc, ont montré qu'il y avait une corrélation négative dans l'évaluation ortho nasale et rétro nasale de la minéralité, ce qui suggère que l'évaluation de la minéralité en bouche peut être modulée par le goût et/ou la texture du vin. En revanche, Ballester et al. [8] ont montré que sur le Chardonnay de Bourgogne, la minéralité évaluée en bouche était indépendante de la minéralité évaluée au nez.

<footnote n="1">¹Université de Bourgogne, 21000 Dijon, France</footnote>

<footnote n="2">²Centre des Sciences du Goût et de l'Alimentation, UMR 6265 CNRS, UMR 1324 INRA, France</footnote>

<footnote n="3">³AGROSUP, Université de Bourgogne-Franche-Comté, 1 Esplanade Erasme, 21000 Dijon, France</footnote>

<footnote n="4">⁴IUVV Jules Guyot, Université de Bourgogne-Franche-Comté, 1 rue Claude Ladrey, 21078 Dijon, France</footnote>

<footnote>*Auteur principal : heber.rodrigues@dijon.inra.fr</footnote>
Parmi tous les descripteurs associés à la minéralité évoqués plus haut, il est intéressant de noter que certains sont directement liés à la réduction et aux composés soufrés. En plus, ce lien est directement présenté dans le *Traité d'Œnologie*, de Pascal Ribéreau-Gayon et al. [12], dans sa 5ème édition. Les auteurs ont fait référence à la minéralité dans le chapitre sur le vieillissement aromatique prématuré des vins blancs (p. 346), dans les termes suivants : « Cette odeur particulière [la résine, l'encaustique, le camphre ou encore le miel et l'hydromel], qui rappelle celle des vins blancs oxydés, peut concerner tous les vins blancs secs ou liquoreux quels que soient l'origine et le cépage. Elle se développe au détriment des nuances empyreumatiques, minérales et truffées, caractéristiques du bouquet de réduction des vins blancs ». Les auteurs ont donc relié le caractère minéral avec des arômes réducteurs et l'ont opposé aux notes d'oxydation.

A partir de toutes ces études récentes qui indiquent que les notes réductrices provoquées par des composés soufrés pourraient en partie participer au caractère minéral des vins et considérant que les composés soufrés responsables sont sensibles à la présence d'oxygène, nous émettons l'hypothèse que la minéralité pourrait être négativement corrélée avec le degré d'oxydation des vins et, par conséquence, être moins prononcée dans les vins plus âgées.

## Matériel et méthodes

### Participants

Vingt volontaires ont participé à l'étude (7 femmes et 13 hommes, âgés de 23 à 53 ans) et étaient tous impliqués dans le processus de fabrication des vins de Chablis. Le Tableau 1 présente l'âge et le niveau d'éducation des participants.

<table><caption>Tableau 1 - Profil des participants</caption><thead><tr><th>Age (ans)</th><th>Participants</th></tr></thead><tbody><tr><td>21-30</td><td>3</td></tr><tr><td>31-40</td><td>7</td></tr><tr><td>41-50</td><td>8</td></tr><tr><td>51-60</td><td>2</td></tr><tr><th>Niveau d'éducation</th><td></td></tr><tr><td>Collège</td><td>--</td></tr><tr><td>Lycée</td><td>2</td></tr><tr><td>Université</td><td>18</td></tr></tbody></table>

### Vins

Sept différents millésimes Chablis 1er Cru Côte de Léchet (2012, 2011, 2010, 2009, 2006, 2004 et 1998) du même producteur ont été sélectionnés pour cette expérience, avec un écart d'un an entre les quatre plus jeunes et un décalage plus accentué entre les trois plus anciens. Tous les vins étudiés étaient bouchés en liège naturel.

### Procédure

Les panélistes recevaient sept échantillons dans un ordre aléatoire en suivant un carré latin et leur tâche était d'évaluer la minéralité des échantillons sur une échelle d'intensité en sept points, allant de la borne *absente* à gauche jusqu'à *très intense* à droite. Ils devaient ensuite décrire les vins à l'aide d'une liste de descripteurs inspirée de Parr et al. [13] et adaptée au Chardonnay. Cette liste est détaillée dans le Tableau 2 et comporte des descripteurs reliés à l'oxydation (miel/cire), à la réduction (pierre-à-fusil/silex frotté/fumée, soufré/réduit/œuf pourri), d'autres descripteurs reliés à la minéralité dans la littérature, plus d'autres descripteurs plus généraux.

### Analyse de données

Nous avons tout d'abord fait une *Analyse en Composantes Principales* (ACP) sur la matrice vins x dégustateurs afin de regarder l'accord et désaccord des juges. Nous avons ensuite fait une *Classification Ascendante Hiérarchique* (CAH) sur les coordonnées de l'ACP, afin de mettre en évidence des groupes de dégustateurs donnant des réponses similaires. Enfin, une ANOVA suivie d'un test de Duncan a été réalisé pour chaque groupe de dégustateurs afin de déterminer s'il y avait des différences significatives entre les millésimes.
<table><caption>Tableau 2 - Liste des descripteurs</caption><thead><tr><th></th><th>Termes</th></tr></thead><tbody><tr><td>1</td><td>Minéral</td></tr><tr><td>2</td><td>Fruits jaunes/fruits blancs</td></tr><tr><td>3</td><td>Herbe coupée</td></tr><tr><td>4</td><td>Floral</td></tr><tr><td>5</td><td>Agrume (citron et pamplemousse)</td></tr><tr><td>6</td><td>Miel/cire</td></tr><tr><td>7</td><td>Pierre-à-fusil/silex frotté/fumée</td></tr><tr><td>8</td><td>Soufré/réduit/œuf pourri</td></tr><tr><td>9</td><td>Craie/calcaire</td></tr><tr><td>10</td><td>Coquillages/iodé</td></tr><tr><td>11</td><td>Sucré</td></tr><tr><td>12</td><td>Amertume</td></tr><tr><td>13</td><td>Acidité/vivacité</td></tr><tr><td>14</td><td>Salinité</td></tr><tr><td>15</td><td>Fraîcheur</td></tr><tr><td>16</td><td>Densité/volume en bouche</td></tr></tbody></table>

## Résultats et discussion

Les résultats ont montré un désaccord entre les professionnels sur leur jugement de la minéralité (Fig. 1). Ces résultats sont en accord avec ceux montrées par Ballester et al. [8]. Deux groupes de dégustateurs se dégagent dans une analyse CAH (Fig. 2).

<figure><img src="image_415.png" /><figcaption>Fig. 1 - ACP avec la distribution des participants par leurs jugements de la minéralité.</figcaption></figure>

<figure><img src="image_416.png" /><figcaption>Fig. 2 - Analyse de classification ascendante hiérarchique (CAH).</figcaption></figure>

Afin de mieux comprendre comment ces deux groupes de dégustateurs voient l'association entre minéralité et oxydation nous avons fait une ACP sur les descripteurs et les vins pour chaque groupe. Le premier groupe (n=12) révèle une claire opposition entre le caractère minéral et les notes miel/cire, notes représentatives de l'oxydation (Fig. 3a) et ce caractère minéral est associé à de notes du goût comme *acidité* et *vivacité*, et un descripteur sensoriel d'origine somesthésique, la *fraîcheur*. Pour l'autre groupe (n=8), l'ACP montre une indépendance entre la minéralité et le caractère oxydatif des vins et une opposition avec les notes réductrices (Fig. 3b) et la minéralité pour ce groupe est associée aux descripteurs *craie* et *calcaire* et opposée aux notes de réduction. Pour ce dernier groupe, les résultats ne vont pas dans le sens attendu (l'opposition minéralité et miel/cire).
<figure><img src="image_417.png" /><figcaption>Fig. 3 - ACP avec la distribution des descripteurs par les groupes 1 (A) et 2 (B).</figcaption></figure>

Conclusion

Finalement, notre hypothèse de départ n'est que partiellement validée, puisque deux conceptions différentes de minéralité par rapport au mécanisme d'oxydoréduction ont étés mises en évidence. La minéralité est corrélée avec la réduction qui est opposée à l'oxydation (première conception) et la minéralité est opposée à la réduction et indépendante de l'oxydation (deuxième conception). Ces résultats préliminaires restent à confirmer en réitérant l'expérience avec un effective plus large de participants.

Remerciements

Les auteurs remercient le « Conselho Nacional de Desenvolvimento Cientifico e Tecnologico – CNPQ,
programa Ciência sem Fronteiras, Brasil », le Bureau Interprofessionnel de Vins de Bourgogne et le
Conseil Régional de Bourgogne pour le financement de ce projet de recherche.

Références

1. Peynaud É, Blouin J (2013) *Le goût du vin - 5e éd : Le grand livre de la dégustation*. Dunod.

2. Deneulin P, Le Bras G, Le Fur Y et al (2014) Minéralité du vin : représentations mentales de consommateurs suisses et français. *Rev Suisse Vitic Arboric Hortic* **46**: 174-180.

3. Maltman A (2013) Minerality in wine: a geological perspective. *J Wine Res* **24**: 169-181.

4. Coutier M (2007) *Dictionnaire de la langue du vin*. CNRS.

5. Dawson E (Oct. 7, 2009). Taking our vitamins and minerality. *Palate Press*.

6. Lund CM, Thompson M, Benkwitz F et al (2009) New Zealand Sauvignon blanc distinct flavor characteristics: sensory, chemical, and consumer aspects. *Am J Enol Vitic* **60**: 1-12.

7. Parr WV, Valentin D, Green JA et al (2010) Evaluation of French and New Zealand Sauvignon wines by experienced French wine assessors. *Food Qual Prefer* **21**: 56-64.

8. Ballester J, Mihnea M, Peyron D et al (2013) Exploring minerality of Burgundy Chardonnay wines: a sensory approach with wine experts and trained panellists. *Aust J Grape Wine Res* **19**: 140-152.

9. Le Fur Y, Gautier L (2013) De la minéralité dans les rosés ? *Rev Fr Oenol* **260**: 40-43.

10. Heymann H, Hopfer H, Bershaw D (2013) An exploration of the perception of minerality in white wines by projective mapping and descriptive analysis. *J Sens Stud* **29**: 1-13.

11. Parr WV, Green JA, White KG et al (2007) The distinctive flavour of New Zealand Sauvignon blanc: sensory characterisation by wine professionals. *Food Qual Prefer* **18**: 849-861.

12. Ribéreau-Gayon P, Glories Y, Maujean A et al (2012) *Traité d'œnologie - Tome 2 - 6e éd. - Chimie du vin.*
*Stabilisation et traitements*. Dunod.

13. Parr WV, Ballester J, Peyron D et al (2015) Perceived minerality in Sauvignon wines: influence of culture and perception mode. *Food Qual Prefer* **41**: 121-132.
# Varietal typicality of Riesling wines – unravelling universal and regional aspects

A. SCHÜTTLER<fnref n="1" />*, K. SIRÉN<fnref n="1" />,<fnref n="3" />, J.F. HARBERTSON<fnref n="2" />, R. JUNG<fnref n="3" />, C.-D. PATZ<fnref n="4" />,
T. HENICK-KLING<fnref n="2" />, P. DARRIET<fnref n="5" />,<fnref n="6" />, D. RAUHUT<fnref n="1" />

Sensory – Riesling typicality – PLS-VIP-CCA – RATA-JAR

## Introduction

The notion of typicality in the field of wine is based on its sensory properties and plays an important role in the concept of varietal definition of wines. The common methodology for measurement of typicality in wine science is based on the comparison of wine samples with an internal ideal held by wine experts being experienced with the product.

The aim of this research was to study universal as well as regional elements of Riesling wine typicality. In a first study the universal typical aromatic concept of Riesling wines was studied by determining sensory properties and chemical markers for typical Riesling wine aroma. In a second study, the regional concepts of typical Riesling wines from Rheingau and from Washington State were evaluated.

## Materials and methods

### Study one

41 wines from 2007 and 2008 vintages were submitted to rate only orthonasal sensory appreciation by two expert panels at two locations – of which 18 wines intersected in the two locations for comparison purpose. In each session, 30 wines were considered – of which ~20 % were non-Riesling wines (Panel Geisenheim: 5 Sauvignon blanc, 2 Chardonnay; Panel Bordeaux: 3 Sauvignon blanc, 1 Pinot gris, 1 Gewürztraminer). The panellists in Geisenheim and Bordeaux were asked to rate typicality orthonasally according to [1]. In addition to the rating of typicality, the judges were asked to name descriptors by using free comments.

**Statistical analysis:** Panel performance was monitored using the repeatability index proposed by [2]. Further panel comparison was done using Pearson correlation and General Procrustes Analysis (GPA). Finally Partial Least-Squares (PLS) regression was used for variable selection, and descriptive sensory data was linked to the so selected chemical compositional data as described in [3].

### Study two

20 Riesling wines from Rheingau and Washington State (5 dry and 5 off-dry from each region) were selected and tasted two times in each region (one orthonasal tasting, one global tasting each) by local wine professionals, resulting in four data sets. They were asked to rate overall typicality and to rate in a combined ‘rate-all-that-apply’ (RATA)–‘just-about-right’ (JAR) approach descriptors which were identified during pre-selection of the wines. **Statistical analysis:** Panel performance was monitored using the repeatability index proposed by [2]. Data from JAR scales were analysed using penalty analysis and

<footnote n="1">¹Geisenheim University, Department of Microbiology & Biochemistry, 65366 Geisenheim, Germany</footnote>

<footnote n="2">²Washington State University, Viticulture and Enology Program, Wine Science Center,
359 University Drive, Richland, WA 99354-1671, United States of America</footnote>

<footnote n="3">³Geisenheim University, Department of Enology, Modeling & Systems Analysis,
65366 Geisenheim, Germany</footnote>

<footnote n="4">⁴Geisenheim University, Department of Wine Chemistry and Beverage Research,
65366 Geisenheim, Germany</footnote>

<footnote n="5">⁵Univ. de Bordeaux, Institut des Sciences de la Vigne et du Vin, Unité de recherche Œnologie,
EA 4577, 210 Chemin de Leysotte, 33882 Villenave d'Ornon, France</footnote>

<footnote n="6">⁶INRA, Institut des Sciences de la Vigne et du Vin, USC 1366 Œnologie,
33882 Villenave d'Ornon, France</footnote>
calculating mean drops for relative typicality scores for all data sets. Furthermore, typicality scores of the panels were analysed. Further panel comparison was done using Pearson correlation, Spearman correlation, and RV-values in PCA projections (build on Spearman correlations). Finally, MFA models were built in order to compare single panel configurations regarding chemical composition, perceived typicality and region. All statistical calculations were performed using XLStat and R-Data base.

### Chemical analysis

All wines in the two studies were analysed for chemical composition (higher alcohols, fatty acids, ethylic fatty acid esters, acetic acid esters, monoterpenes, C13-norisoprenoids, volatile sulfur compounds, polyfunctional thiols, phenolic compounds, organic acids, and sugars) as described in [3].

## Results and discussion

Study one investigated the global concept of Riesling wines' aromatic typicality. Therefore wines from different regions and varieties were tasted orthonasally by two different wine expert panels in two different countries and regions, one experienced in Riesling (Rheingau) and one in Sauvignon blanc (Bordeaux).

### Panel comparison

Both panels, the German and the French, were able to reproduce typicality measures by showing repeatability indexes ($r_{im}$) of $r_{im} = 0.16$ and $r_{im} = 0.37$, respectively. When considering that a $r_{im}$ of 0 represents the best possible result, whereas a rim of 1 indicates no repeatability, the German panel showed higher repeatability, probably due to being more frequently exposed to Riesling wines. For the descriptive task the French panel performed more reliable, showing a reproducibility index ($R_i$) of $R_i = 0.68$ compared to the German panel showing a $R_i$ of 0.59. A $R_i$ of 1 is considered as optimum. When comparing holistic typicality of the two panels, there was high agreement of both panels on which wines are typical Riesling wines upon their aromatic perception. Both panels' typicality scores were highly correlated in Pearson correlation ($r = 0.864$; $\alpha = 0.05$; confidence interval 0.95), indicating that there is a shared aromatic concept of Riesling wines. Regarding the descriptive task, contingency tables from both panels obtained by the FFC method were highly correlated, indicating that both panels agreed on the sensory descriptors attributed to the wines (RV coefficient 0.873).

### Typicality concept

The concept of typicality can be divided into ‘inter-’ and ‘intra-categorical’ typicality. The ‘inter-categorical’ concept of Riesling wine’s typicality can be observed by significant differences between wines from different categories, such as varietal wines. The ‘intra-categorical’ concept of Riesling wines’ typicality can be studied by regarding significant differences in a group of Riesling wines. In order to gain a more comprehensive picture of Riesling wines’ typicality including chemical aspects a novel methodology in sensory science was applied. Regarding chemical composition, a very high number of volatile compounds were analysed – of which not every compound can be considered as impacting variable. Therefore variable selection is necessary in order to link chemical composition to sensory data. For this purpose a PLS-Model of rated typicality scores was constructed from all aroma compound concentrations analysed. In order to select the most important aroma compounds in the PLS-Model, the Variable Importance in Projection (VIP) procedure was applied and aroma compounds showing a VIP-value above 1 were selected for further analysis.

The selected aroma compounds were used together with sensory descriptor groups' contingency tables to perform Canonical Correspondence Analysis (CCA). For 'inter-categorical' effects the whole data set was used including Chardonnay and Sauvignon blanc wines. Wines from different varieties were clearly separated. The cluster of Sauvignon blanc wines was linked to vegetal, sauvignon and *Rubus* ssp. *Sambucus* ssp. descriptors, whereas Riesling was related to fruity, yellow fruit, and aging related descriptors (according to F1) as well as to fermentative and floral aroma (according to F2). Monoterpenes linalool, linalool- and nerol oxides, and $\alpha$-terpineol were linked to the cluster of Riesling wines and floral, fruity and aging descriptors. Higher TDN concentrations were linked to aging descriptors in Riesling wines, whereas 3-sulfanylhexanol concentration was linked to Sauvignon blanc wine cluster. When analysing the CCA map towards 'intra-categorical' Riesling wines' typicality high linalool concentration was linked to floral descriptors, but to low typicality scores. Concentrations of monoterpene oxides, ethyl esters, and TDN increased with aging descriptors. Aging descriptors and therefore TDN concentrations did not link to high typicality, whereas higher 3-sulfanylhexanol concentrations did.
<table><caption>**Table 1** - Aroma compounds impacting PLS-Model according to Variable Importance in Projection Value (VIP-Score) which were kept for Canonical Correspondence Analysis</caption><thead><tr><th>Name of Aroma Compound</th><th>VIP-Score</th></tr></thead><tbody><tr><td>HIGHER ALCOHOLS</td><td></td></tr><tr><td>hexan-1-ol</td><td>2.188</td></tr><tr><td>ACETATE ESTER</td><td></td></tr><tr><td>2-methylbutyl acetate</td><td>1.508</td></tr><tr><td>ETHYL ESTER</td><td></td></tr><tr><td>ethyl propionate</td><td>1.851</td></tr><tr><td>ethyl butanoate</td><td>1.385</td></tr><tr><td>diethyl succinate</td><td>1.207</td></tr><tr><td>MONOTERPENOLS</td><td></td></tr><tr><td>linalool</td><td>0.417</td></tr><tr><td>α-terpineol</td><td>1.367</td></tr><tr><td>geraniol</td><td>2.099</td></tr><tr><td>MONOTERPENE OXIDES</td><td></td></tr><tr><td>trans-linalool oxide</td><td>3.725</td></tr><tr><td>cis-linalool oxide</td><td>1.257</td></tr><tr><td>nerol oxide</td><td>2.369</td></tr><tr><td>C<sub>13</sub>-NORISOPRENOIDS</td><td></td></tr><tr><td>1,1,6-trimethyl-1,2-dihydronaphthalene (TDN)</td><td>1.717</td></tr><tr><td>α-lonone</td><td>1.117</td></tr><tr><td>SULFUR COMPOUNDS</td><td></td></tr><tr><td>dimethylsulfide (DMS)</td><td>4.732</td></tr><tr><td>ethyl 2-sulfanylpropionate</td><td>1.183</td></tr><tr><td>ethyl 2-sulfanylacetate</td><td>1.084</td></tr><tr><td>3-sulfanylhexan-1-ol (3-SH)</td><td>3.767</td></tr></tbody></table>

**Study two** compared regional Rieslings' typicality concepts from two different regions on two continents, namely Washington State and Rheingau. For that study 10 wines from both regions were pre-selected by wine professionals. Upon prior discussion with wine professionals two categories were chosen, dry (RS <9 g/L) and off-dry (RS >9 g/L to 20 g/L), due to being expected that typical Washington State Riesling would be higher in RS. For this study the decision was made to adapt the methodology and use a RATA approach in combination to JAR scales in order to understand more of the wine professionals' ideal concept [4]. This study focused on the comparison of two regional concepts of Riesling wine's typicality and the link between aromatic and overall typicality.

### Panel comparison

Average repeatability of the panels was 0.46 and 0.61 for the orthonasal panels and 0.73 and 0.77 for the global assessment panels from Rheingau and Washington State, respectively, indicating that the panels performed in both regions more reliable during global tastings. This effect was even more evident for the descriptor reproducibility of the panels, where the orthonasal panels scored 0.46 and 0.62 and the global panels 0.80 and 0.82 in Rheingau and Washington State, respectively. Typicality scores of all panels were compared using Spearman's rank correlation, showing significant correlation between Rheingau orthonasal and global results (r = 0.59; p < 0.005) and the two global tasting results from Rheingau and Washington State (r = 0.53; p < 0.01).

### JAR – mean drop and penalties

Regarding JAR analysis, the orthonasal panel from Rheingau rated the descriptors citrus and floral most frequently as 'too low' or 'just right', whereas petrol, vegetative and phenolic were considered most frequently to be 'too much'. Interestingly, 'too strong' petrol aroma did not play a detrimental role to typicality rating in penalty analysis at 95 % confidence intervals, which was observed for vegetative or phenolic descriptors. For the Washington State orthonasal panel a lack of citrus, floral, passion fruit, apricot, and mineral aroma showed a decreasing effect (low mean drop value) on typicality, whereas petrol and canned vegetative aroma showed a slightly decreasing effect when considered to be present
‘too much’. For global tastings the lack of cleanness (‘Reintönigkeit’), citrus, fruitiness and acidity were negatively linked to typicality as were ‘too much’ petrol, honey, and bitterness. Similar observations were made for Washington State global panel rating lower typicality to wines lacking balance, freshness, fruitiness, stone fruit, acidity, and citrus. Pronounced bitterness, astringency and sweetness was not considered to contribute to typical Washington State Rieslings.

*Comparison of aroma, global and regional configurations*

Regional elements were analysed using MFA build on PCA's based on Spearman correlations. When comparing the sensory space of the selected wines evaluated orthonasally by the Rheingau panel, the main separating descriptors between the regions, being more present in Rheingau Rieslings, were vegetal, SO₂, and grapefruit. Eisbonbon (candy) and honey descriptors were more pronounced in Washington State Riesling wines. The Washington State panel could clearly separate the Pinot gris as an outlier in orthonasal tasting, whereas no regional separation was achieved for Riesling wines. Regarding global testing, which included taste descriptors, the Rheingau panel discriminated dry Rheingau Rieslings from mixed Rheingau off-dry and Washington State Riesling by more pronounced citrus, acidity, and CO₂ descriptors and less sweetness, stone fruit, honey, and petrol. Generally Rheingau Rieslings were linked to citrus, acidity, and fruitiness. Washington State global tasting panel also linked Rheingau Riesling to stronger acidity and citrus perception, whereas fruitiness, sweetness, and balance were rated to be more pronounced in Washington State Riesling wines. In both global tasting, citrus was linked to acidity as were off-dry wines to sweetness. The fruity descriptor was linked more to stone fruit by the Washington wine experts, whereas for the Rheingau tasters citrus and stone fruit seemed to be involved into fruitiness. From final MFA the descriptors separating the four panels were apricot, fruitiness, pineapple, and honey, either upon poor panel performance or on different concepts of these descriptors. Bitterness was negatively linked to typicality in both regions, whereas citrus and acidity were positively related to typicality. Descriptors linked to Rheingau typicality were green and vegetal aromas, whereas Washington State Riesling typicality was linked to more intense floral, honey, apple, apricot, and phenolic aromas.

*Link between sensory and chemical data*

Rheingau Riesling typicality scores, from both orthonasal and global tasting, were linked to 3-SH concentrations (Pearson correlation, $\alpha$ = 0.05, r = 0.447, $p$ < 0.05; r = 0.538, $p$ < 0.05). Furthermore mean 3-SH concentrations were significantly higher in Riesling wines from Rheingau (557 ng/L) compared to those from Washington State (244 ng/L) and therefore could explain the more pronounced citrus and grapefruit descriptors in Rheingau Rieslings. A candidate marker compound, possibly implicated in green, vegetal aromas contributing to Rheingau Riesling typicality is hexanol. The C6-alcohol showed significant higher concentrations in Rheingau Rieslings (1493 µg/L) than in Washington State Rieslings (783 µg/L). Washington State Rieslings showed higher TDN concentrations compared to Rheingau Rieslings (2.4 µg/L and 0.9 µg/L) without any clear effect on typicality.

Conclusion

The two studies prove a universal typicality of Riesling wines compared to other varietal wines. Riesling wine typicality is aromatically linked to fruity and citrus descriptors, whereas it is chemically linked to 3-sulfanylhexanol concentrations. The C13-norisoprenoid TDN and monoterpene linalool play a less significant role in aromatic typicality of Riesling wines. Despite an agreed universal aromatic Riesling wine concept, regional differences occur and were demonstrated through investigating Rheingau and Washington State Rieslings typicality. The importance of taste and retronasal aroma perception was demonstrated for the typicality concept. Whereas citrus and acidity were considered as typical for both regions, Rheingau Riesling typicality also tended to be defined by green and vegetative descriptors. Washington Riesling typicality tended to be defined by floral, honey, apple, apricot, and phenolic descriptors. These differences could be traced back to chemical composition. The results regarding Riesling wines' fruitiness indicated possible regional differences in descriptor concepts.

Acknowledgements

The authors would like to acknowledge the Conseil Régional Aquitaine and the Ministry of Science and Art of the State of Hessen for financial support of the first study.
References

1. Ballester J, Dacremont C, Le Fur Y et al (2005) The role of olfaction in the elaboration and use of the Chardonnay wine concept. *Food Qual Prefer* **16**: 351-359.

2. Campo E, Ballester J, Langlois J et al (2010) Comparison of conventional descriptive analysis and a citation frequency-based descriptive method for odor profiling: an application to Burgundy Pinot noir wines. *Food Qual Prefer* **21**: 44-55.

3. Schüttler A, Friedel M, Jung R et al (2015) Characterizing aromatic typicality of Riesling wines: merging volatile compositional and sensory aspects. *Food Res Int* **69**: 26-37.

4. Cadot Y, Caillé S, Samson A et al (2010) Sensory dimension of wine typicality related to a terroir by Quantitative Descriptive Analysis, Just About Right analysis and typicality assessment. *Anal Chim Acta* **660**: 53-62.
# Holistic approach to the characterization of three South African Chenin blanc wine styles. Comprehensive chemical volatile composition and sensory evaluation using Polarized Projective Mapping method

J. BRAND, C. WILSON, A. BUICA*

Department of Viticulture and Oenology, Stellenbosch University, P/Bag X1, Matieland, Stellenbosch, South Africa

Chenin blanc wine styles – volatile composition – Polarized Projective Mapping – holistic evaluation

## Introduction

Both chemistry and sensory can offer what could be called “descriptive profiling”, but each approach does it in its own terms. Chemical analysis can detect ultra-trace levels (ng/L), but this performance is not always relevant to the consumer. The link between the data generated by the two evaluation approaches is usually difficult to establish, as many chemical compounds work either synergistically or have a masking effect on each other.

One of the so-called “rapid methods” has drawn our attention. Polarized Projective Mapping (PPM) is a hybrid of Projective Mapping and Polarized Sensory Positioning [1-3]. It is a reference-based method in which poles are used for the evaluation of similarities and dissimilarities between samples and the poles. It is an intuitive method in the sense that the closer a sample is to the reference, the closer that sample will be physically placed to the pole. Additionally, the judges give a description of the samples, generating a short list of attributes.

Chenin blanc is considered a “neutral grape”, a canvas on which winemaking can put its mark with very different outcomes. South African Chenin blanc wine styles range from fresh and fruity, rich and ripe to wooded. The styles chosen for this project are fresh and fruity (FF), rich and ripe (RR), and wooded. The reason for this choice is that there are possible chemical drivers for each of these styles: thiols, esters, terpenes and wood-derived compounds.

## Materials and methods

The sample set consisted of 10 commercial Chenin blanc wines, vintages 2013 and 2014, from the three representative styles, chosen according to the description offered by the tasting notes.

### Chemical analysis

All the methods used were the in-house methods and they were as follows: major volatiles (esters, higher alcohols and fatty acids) liquid-liquid extraction followed by GC-FID; terpenes SPE followed by GC-FID; wood-derived compounds HS-SPME-GC-MS/MS.

### Sensory analysis

One session for projective mapping and one for PPM, 2 repeats, 15 judges. For the projective mapping the sample set consisted of 12 wines (2 of them duplicates). For PPM, the sample set also had 12 wines, with one of the poles and one other sample duplicated.

### Data analysis

The data generated was evaluated statistically by means of multivariate techniques: multiple factor analysis (MFA), principal component analysis (PCA), separately for the two sets of results, sensory and chemistry, respectively.
**Results and discussion**

Chemical analysis also focused on the volatile compounds. Various classes of analytes have been determined: terpenes, esters, volatile acids, higher alcohols, wood-derived compounds. The results are shown in Figure 1.

<figure><img src="image_418.png" /><figcaption>Fig. 1 - PCA of chemical data. Classes of compounds are colour-coded: major volatiles, terpenes and wood-derived compounds.</figcaption></figure>

The explained variance for the chemistry PCA was lower than expected (58.46 %). The thiol data is not included in this result set and it could improve the percentage.

The selection of the poles is a key point in this method. As previously presented in the literature, projective mapping was used for the selection of the poles [2].

Better RV coefficients were obtained for PPM. This could be explained partially because assessors are forced to a certain extent to use the A2 in a similar way, since the poles are fixed at the same positions for everyone, which is not the case for projective mapping.

The higher explained variance could also be due to the fact that the poles are given and fixed for PPM (47.92 % for projective mapping and 57.06 % for PPM, bi-plots not shown). The explained variance differs for the two techniques but it is still relatively low and the values are close.

**Conclusion**

Before implementing in practice, new methods should be tested against already established ones. In this way, limitations and advantages can be tested, modifications suggested and sometimes improvements added to existing methods. Also, the type of sample used can influence the success or failure rate of a new method. A method such as PPM for wine evaluation can be advantageous due to the use of poles, and as shown here, the results look promising.
Once again, the link between chemical composition and sensory attributes was proved difficult. Chemical composition can be used as a possible base for explaining some differences in the perception of samples. Additional chemical data could help improve the determination of the drivers for the various Chenin blanc styles.

## Abbreviations

GC-FID, gas chromatography – flame ionization detection; HS-SPME-GC-MS/MS, headspace-solid phase microextraction – gas chromatography – tandem mass spectrometry; MFA, multiple factor analysis; PCA, principal component analysis; PPM, polarized projective mapping; SPE, solid phase extraction.

## References

1. Valentin D, Chollet S, Lelièvre M et al (2012) Quick and dirty but still pretty good: a review of new descriptive methods in food science. *Int J Food Sci Technol* **47**: 1563-1578.

2. Ares G, de Saldamando L, Vidal L et al (2013) Polarized projective mapping: comparison with polarized sensory positioning approaches. *Food Qual Prefer* **28**: 510-518.

3. Varela P, Ares G (2012) Sensory profiling, the blurred line between sensory and consumer science. A review of novel methods for product characterization. *Food Res Int* **48**: 893-908.