# Perceptive interactions among fruity esters involved in red wine fruity aromas

G. LYTRA<fnref n="1" />,<fnref n="2" />*, S. TEMPERE<fnref n="1" />,<fnref n="2" />, A. LE FLOCH<fnref n="1" />,<fnref n="2" />, G. DE REVEL<fnref n="1" />,<fnref n="2" />, J.-C. BARBE<fnref n="1" />,<fnref n="2" />

Esters – aromatic reconstitution – olfactory threshold – red wine fruity aromas

## Introduction

Studies investigating fruity aromas in red wines over the past decade have revealed a certain number of compounds that are potentially involved [1, 2]. Although the importance of the variation of ester concentrations effecting red wine fruity aroma has already been highlighted [3], previous works did not investigate this further.

The goal of this work is to study the qualitative and quantitative impact of 12 red wine esters, in complex mixtures, on the perception of fruity aromas.

## Materials and methods

### Samples

Aromatic reconstitution using esters. For aromatic reconstitutions, the various esters were added individually or blended together at the average concentrations found in red wines (Table 1) to double-distilled ethanol and microfiltered water to obtain an ethanol level of 12% (v/v) (pH adjusted to 3.5 with tartaric acid). The mixtures containing all 12 esters consisted of the total aromatic reconstitution (TAR).

### Sensory analyses

Discriminative testing methods. Triangular tests were performed by panel 1 (18 judges, staff at ISVV) for various aromatic reconstitution samples (Table 1). A first set of triangular tests consisted of evaluating the individual perception of each compound in dilute alcohol solution. Each compound, present at the concentrations listed in Table 1, was compared to dilute alcohol solution alone. In the second phase, the same panel was subjected to triangular omission tests (Table 1): first the omission of each entire chemical family and then the omission of only one compound among the 12 esters. The results of all of the triangular tests were statistically analyzed, according to the tables given in the literature based on the binomial law corresponding to the distribution of answers in this type of test (NF EN ISO 4120: 2007).

Olfactory thresholds were determined by panel 1 (18 judges, staff at ISVV), in a three alternative, forced-choice presentation (3-AFC) in dilute alcohol solution (NF ISO 13301: 2002). The olfactory thresholds of ethyl propanoate, ethyl 3-hydroxybutanoate, butyl acetate, and 2-methylpropyl acetate were measured. The olfactory thresholds of specific mixtures were also established. Olfactory thresholds of aromatic reconstitutions were thus measured in different matrices: dilute alcohol solution, dilute alcohol solution containing a compound of interest, and dilute alcohol solution containing a compound at a fixed concentration only in the positive sample. The olfactory thresholds of the following mixtures were measured: total aromatic reconstitution (TAR) excluding ethyl propanoate, TAR excluding ethyl 3-hydroxybutanoate, TAR excluding butyl acetate, and TAR excluding 2-methylpropyl acetate. The results of all 3-AFC tests were statistically analyzed (NF ISO 13301: 2002). In addition, interaction effects for certain mixtures were evaluated using Feller's additive model [4].

Descriptive testing methods. Sensory profiles of aromatic reconstitutions were evaluated by panel 2 (21 judges, staff at ISVV) for overall aromatic intensity, red-berry, blackberry, fresh-, and jammy-fruit aroma intensity. Each sample was presented twice in each session. The subject rated the intensity of these

<footnote n="1">¹Univ. Bordeaux, ISVV, EA 4577 Œnologie, F 33140 Villenave d'Ornon, France</footnote>

<footnote n="2">²INRA, ISVV, USC 1366 Œnologie, F 33140 Villenave d'Ornon, France</footnote>
descriptors in each sample on a 100-mm scale. Statistical data were analyzed using the Mann-Whitney statistical non-parametric test (XLSTAT software). All descriptors are mean-centered per panelist and scaled to unit variance. The statistically significant level was 5% (p<0.05).

<table><caption>**Table 1** - Olfactory impact of the omission of various esters from complex aromatic reconstitutions</caption><thead><tr><th>C3C2</th><th>C4C2</th><th>C6C2</th><th>C8C2</th><th>2Me C3C2</th><th>2Me C4C2</th><th>2OH 4MeC5C2</th><th>3OH C4C2</th><th>C2C4</th><th>C2C6</th><th>C2iC4</th><th>C2iC5</th><th>difference observed</th></tr><tr><th>150</th><th>200</th><th>200</th><th>200</th><th>250</th><th>50</th><th>400</th><th>300</th><th>10</th><th>2</th><th>50</th><th>250</th><th>concentration (µg/L)</th></tr></thead><tbody><tr><td>-</td><td>-</td><td>-</td><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>***</td></tr><tr><td>x</td><td>x</td><td>x</td><td>x</td><td>-</td><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>*</td></tr><tr><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>-</td><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>**</td></tr><tr><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>-</td><td>x</td><td>x</td><td>x</td><td>**</td></tr><tr><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>-</td><td>x</td><td>**</td></tr><tr><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>***</td></tr><tr><td>x</td><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>***</td></tr><tr><td>x</td><td>x</td><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>**</td></tr><tr><td>x</td><td>x</td><td>x</td><td>x</td><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>*</td></tr><tr><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>=</td></tr><tr><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>***</td></tr><tr><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>***</td></tr><tr><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>***</td></tr><tr><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>-</td><td>x</td><td>x</td><td>x</td><td>***</td></tr><tr><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>**</td></tr><tr><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>-</td><td>x</td><td>x</td><td>**</td></tr><tr><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>***</td></tr><tr><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>***</td></tr><tr><td>x</td><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>***</td></tr><tr><td>x</td><td>x</td><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>**</td></tr></tbody></table>

## Results and discussion

### *Impact hierarchy of the compounds*

Perception of individual compounds. All compounds were identified by the panel, except ethyl propanoate, ethyl 3-hydroxybutanoate, butyl acetate, and 2-methylpropyl acetate, revealing that they were present in subthreshold concentrations. For all other compounds, the differences observed by the panel were significant, with a confidence interval of at least 1%.

The olfactory thresholds obtained for ethyl propanoate, ethyl 3-hydroxybutanoate, butyl acetate, and 2-methylpropyl acetate (662, 3244, 174, and 249 µg/L respectively) clearly confirmed that these four compounds in hydroalcoholic solution had no direct olfactory impact.

Effect of the omission of one or more compounds. The omission tests results are presented in Table 1. The omission of entire families of compounds resulted in a statistically significant modification in the odor of the aromatic reconstitution. With the exception of ethyl-2-methylpropanoate, the omission of each compound from the TAR was significantly perceived, showing that these compounds contribute to the overall fruity aroma of the complex mixture. Omission of each of the four compounds present at

<footnote>*** 0.1% significant level; ** 1% significant level; * 5% significant level; = no significant difference; x: presence of listed compounds; -: absence of listed compounds. C3C2, ethyl propanoate; C4C2, ethyl butanoate; C6C2, ethyl hexanoate; C8C2, ethyl octanoate; 2MeC3C2, ethyl 2-methylpropanoate; 2MeC4C2, ethyl 2-methylbutanoate; 2OH4MeC5C2, ethyl 2-hydroxy-4-methylpentanoate; 3OH4C4C2, ethyl 3-hydroxybutanoate; C2C4, butyl acetate; C2C6, hexyl acetate; C2iC4, 2-methylpropyl acetate; C2iC5, 3-methylbutyl acetate.</footnote>
subthreshold concentrations was conclusive. These results highlighted the existence of new perceptual interactions. The psychometric curve obtained using the olfactory threshold of each compound of interest was used to calculate the detection probability of each compound individually at the studied concentration: for respective concentrations of ethyl propanoate, ethyl-3-hydroxybutanoate, butyl acetate, and 2-methylpropyl acetate of 150, 300, 10, and 50 µg/L, the probability of detection was 0.2, 0.019, 0.016, and 0.092, respectively, i.e., 20%, 1.9%, 1.6%, and 9.2% of the panelists, respectively, were able to detect the presence of these compounds The most notable effects were attributable to ethyl 3-hydroxybutanoate and butyl acetate.

### Olfactory properties of compounds present at subthreshold concentrations

Quantitative effect. As shown in Figure 1, the presence of each compound, which omission at subthreshold levels could be perceived, resulted in a decrease in the "olfactory threshold" of the TAR, reflecting an individual quantitative contribution of these four compounds to overall aroma intensity. According to the esters tested, the addition of ethyl propanoate, ethyl-3-hydroxybutanoate, butyl acetate, or 2-methylpropyl acetate led to a 2.6 (confidence interval p<0.01), 2.09 (p<0.01), 3.36 (p<0.01), and 1.84 (p>0.05)-fold decrease, respectively, in the "olfactory threshold" of the fruity pool constituted by the other 11 compounds. These results clearly confirmed that these compounds, present at subthreshold concentrations, play an important role as fruity aroma enhancers, via perceptive interactions.

<figure><img src="image_419.png" /><figcaption>**Fig. 1** - Effect of ester addition on the detection probability of aromatic reconstitutions.
*Expressed in mL total aromatic reconstitution (TAR) diluted in 50mL matrix. MS, model wine solution (dilute alcohol solution). OT, olfactory threshold. The curves are drawn according to a sigmoid function.</figcaption></figure>
Interaction effects were evaluated using Feller's additive model, revealing a hyper-addition effect after the addition of ethyl 3-hydroxybutanoate and 2-methylpropyl acetate to the fruity pool and a simple additive effect after the addition of ethyl propanoate and butyl acetate to the fruity pool.

Qualitative effect. Besides ethyl-3-hydroxybutanoate, which had no qualitative impact, the omission of these subthreshold compounds from the fruity matrix had a significant attenuating effect on black-berry and fresh-fruit aroma intensity and enhanced red-berry fruit aroma intensity.

Conclusion

Taken together, these compounds with similar chemical structures have both quantitative and qualitative effects, modulating the fruity aromas of red wines [5]. This research revealed their role as natural enhancers of black-berry and fresh-fruit aromas and revealed four new perceptual interactions.

References

1. Kotseridis Y, Baumes R (2000) Identification of impact odorants in Bordeaux red grape juice, in the commercial yeast used for its fermentation and in the produced wine. *J Agric Food Chem* **48**: 400-406.

2. Lytra G, Tempere S, de Revel G et al (2012) Impact of perceptive interactions on red wine fruity aroma. *J Agric Food Chem* **60**: 12260-12269.

3. Pineau B, Barbe JC, van Leeuwen C et al (2009) Examples of perceptive interactions involved in specific "red- and blackberry" aromas in red wines. *J Agric Food Chem* **57**: 3702-3708.

4. Feller W (1968) *An introduction to probability theory and its applications*, Wiley Series in Probability and Mathematical Statistics.

5. Lytra G, Tempere S, Le Floch A et al (2013) Study of sensory interactions among red wine fruity esters in a model solution. *J Agric Food Chem* **61**: 8504-8513.
# 2-Methylisoborneol in wine, is it responsible for off-odours?

A. LOPEZ PINAR<fnref n="1" />*, R. GHADIRIASLI<fnref n="1" />, P. DARRIET<fnref n="2" />, A. BUETTNER<fnref n="1" />,<fnref n="3" />

2-Methylisoborneol – off-odours – wine – gas chromatography-olfactometry (GC-O)

## Introduction

Aroma is the predominant quality parameter of wine. It is therefore not surprising that avoiding the generation of off-odours is an issue of great concern in oenology. In this way, there have been numerous studies dealing with the clarification of off-odours in wine from different approaches, either identifying the compounds responsible for the defects, improving analytical techniques to facilitate an early detection, or developing prevention strategies and remedial treatments. Nevertheless, the wine industry still encounters problems in relation to off-odours whose origin cannot be addressed properly.

Among the compounds responsible for off-odours reminiscent of wet earth and mushroom in wine, the importance of 2-MIB must be pointed out. The origin of this compound is the gray mold, also known as bunch rot, a grape disease mainly produced by the fungus *Botrytis cinerea* (Figure 1). Interestingly, although 2-methylisoborneol (2-MIB) could be identified in wine in the frame of this study, its stability has been previously studied and it was concluded that this compound is not stable in wine; the reported degradation mechanism is dehydration of the alcohol function in acidic media, and has been related to the fermentation phase of the must [1]. The dehydration products are 2-methylenebornane (2-MB) and 2-methy-2-bornene (2-M-2-B).

The aim of this study was to address this paradoxical situation. For this aim, two different strategies were followed. On the one hand, in order to study the possibility that this odoriferous zone could be due not to 2-MIB, but to a potentially related substance which would be stable in acidic conditions, several 2-MIB related compounds were synthesized. On the other hand, a study of the 2-MIB stability in wine and in model solution was carried out.

<figure><img src="image_420.png" /><figcaption>Fig. 1 - Example of grape affected by gray mold.</figcaption></figure>

<footnote n="1">¹Department of Chemistry and Pharmacy, Emil Fischer Center, Friedrich-Alexander-Universität Erlangen-Nürnberg, Schuhstrasse 9, 91052 Erlangen, Germany</footnote>

<footnote n="2">²Université de Bordeaux, EA 4577 Œnologie, USC 1366 INRA, Institut des Sciences de la Vigne et du Vin, 210 Chemin de Leysotte, CS 50008, 33882 Villenave d'Ornon cedex, France</footnote>

<footnote n="3">³Fraunhofer Institute for Process Engineering and Packaging IVV, Giggenhauserstrasse 35, 85354 Freising, Germany</footnote>
# Materials and methods

## Synthesis of 2-MIB related compounds

The synthesis of the 2-MIB related compounds was performed according to the methods described in Schumann and Pendleton [2] and Napolitano et al [3].

## Extraction and analysis of volatile compounds

The extraction of the volatiles from the respective samples was carried out by Solvent Assisted Flavour Evaporation (SAFE) [4]. The main odour compounds were then investigated by GC-O. The analyses were further continued on a 2-Dimensional Gas Chromatography-Mass Spectrometry system (2DIM GC-MS) (Figure 2) to separate the target substance from other potentially coeluting compounds and to ensure clear mass spectrometric detection of the target compound.

## Stability of 2-MIB

In order to study the stability of 2-MIB, a French Pinot Noir (Nicolas Napoléon from 2012) and a model solution were spiked with 2-MIB reference and stored at room temperature. The concentration was regularly measured by Stable Isotope Dilution Analysis (SIDA) during 90 days. The analyses were performed per triplicate. This assay was also performed on the 2DIM GC-MS system.

<figure><img src="image_421.png" /><figcaption>Fig. 2 - Schema of the 2DIM GC-MS system.</figcaption></figure>

# Results and discussion

In total, six structurally related compounds of 2-MIB were synthesized. Some of them were earthy smelling, presenting very similar odour properties to 2-MIB. The odour thresholds in air were determined according to Ullrich and Grosch [5] and they were in a range from 1.96 to 1510.67 ng/L. Nevertheless, their retention indices and mass spectra were different from those of the earthy odoriferous zone detected in wine, so that these could be dismissed as being responsible for the earthy off-odour previously detected in wine.

In the frame of this study, it could also be confirmed that the dehydration products, 2-MB and 2-M-2-B, are not odour-active. This confirmation was achieved by means of sensory evaluation of the two synthesized references.

Additionally, several Pinot Noir wines from Burgundy from the year 2006 were investigated by GC-O. Special attention was paid to the presence of earthy smelling compounds. 2-MIB could be detected in two samples but could only be clearly identified in Mercurey 2006. This sample had been previously described as being the most affected by the earthy off-odour. The identification of the compound was performed by comparison with the reference substance on the basis of the following criteria: linear retention index on two capillary columns with different polarity, mass spectra and odour quality. All three parameters showed a very good correlation.
Regarding the results of the study of stability in wine and in model solution, although the concentration decreased with time, there was still 2-MIB that remained at the end of the assay; this observation might be related to the reaching of a steady state between degradation and reformation of the target substance as the decrease curve followed an exponential decrease curve rather than a linear one. The characteristic earthy off-odour could be clearly perceived in the samples after 90 days of storage since the final concentrations measured in wine and in model solution were well above the odour threshold of the substance.

## Conclusion

Since 2-MIB was not totally degraded, it was concluded that indeed, if the concentration is high enough in must, this substance can still be detected in wine, and contribute, in this case, to an earthy off-odour. Alternatively, it may be hypothesized that the continued presence of 2-MIB in mature wines (2006 Pinot Noir) could also be related to precursor forms, releasing 2-MIB during wine ageing. However, as the degradation rates observed in Nicolas Napoléon (2012 Pinot Noir) wine in the present study followed a comparable path as observed in the model solution, the latter case appears to be unlikely in this case.

## Acknowledgements

The project was funded by the Bavarian Research Foundation with the Project 152-12.

## Abbreviations

GC-O, Gas Chromatography-Olfactometry; 2-MIB, 2-methylisoborneol; SIDA, Stable Isotope Dilution Analysis; 2DIM GC-MS, 2 Dimensional Gas Chromatography-Mass Spectrometry; SAFE, Solvent Assisted Flavor Evaporation; 2-MB, 2-methylenebornane; 2-M-2-B, 2-methyl-2-bornene.

## References

1. La Guerche S, Dauphin B, Pons M et al (2006) Characterization of some mushroom and earthy off-odors microbially induced by the development of rot on grapes. *J Agric Food Chem* **54**: 9193-9200.

2. Schumann R, Pendleton P (1996) Dehydration products of 2-methylisoborneol. *Water Res* **31**: 1243-1246.

3. Napolitano E, Giovani E, Ceccarelli N et al (1996) Tertiary alcohols with earthy odor. *J Agric Food Chem* **44**: 2806-2809.

4. Engel W, Bahr W, Schieberle P (1999) Solvent assisted flavour evaporation - a new and versatile technique for the careful and direct isolation of aroma compounds from complex food matrices. *Eur Food Res Technol* **209**: 237-241.

5. Ullrich F, Grosch W (1987) Identification of the most intense volatile flavour compounds formed during autoxidation of linoleic acid. *Z Lebensm Unters Forsch* **184**: 277-282.
# Development of a picture book: a new tool for description of wine aromas

S. MARCHAND<sup>1,2*</sup>, M. DUFOIR<sup>1,2</sup>, S. TEMPERE<sup>1,2</sup>, G. DE REVEL<sup>1,2</sup>

Wine tasting – imagery – wine aromas – descriptors

## Introduction

The description of wine aromas is a complex and multifactorial task. It includes odor detection and extraction from the matrix baseline, stimulus recognition and at the end the proposition of an adequate word [1]. New tools must be proposed to the wine tasters who desire to enhance their performances. One of our propositions to optimize tasters’ performances is giving them the opportunity to simplify the odor description task. The question is now: how can we simplify this task?

One possible solution is to give the possibility to tasters to skip the verbalization step. The usefulness of the visual interface choice in replacement of odor description has been evoked and then studied mainly during medical studies. Some psychiatric or degenerative diseases can damage the capacities of patient to recognize and/or describe odors. Doty et al. used a visual tool to study olfactory dysfunction in three neurodegenerative diseases [2]. Then, Hamtat proposed to replace the descriptor of an odor by the choice of a picture representative of the odor [3]. On another hand, the mechanistic link between visual and olfactory capacities has been studied in the central system. Gottfried et al. showed that the use of images improves olfactory identification performances [4]. Later, neuroscience studies demonstrated visual cues activate olfactory and gustatory cortexes [5, 6]. Literature has been recently supplemented by functional data, indicating the occurrence of perceptual visual-olfactory interactions [7]. Demattè et al. demonstrated that both color and shape information play an important role in olfactory discrimination using pictures [8].

If scientific oenology wants to go further in sensory analysis science, it can be useful to explore the utility of visual interfaces during taster’s formation and training. The priority is to constitute a picture book containing one validated picture for each (of the most common) wine aroma and off-flavor. That is the aim of this study.

## Materials and methods

Our strategy for the validation of the “wine aroma picture book” was:

- First, to list 150 most used flavors and off-flavors of wines using scientific literature [9] and wine tasting comments in French oenological press and guides (“Revue du Vin de France”, “Guide Hachette”, etc.).

- Then, to select 10 to 20 pictures for each odor using the specificities proposed by Foroni et al. [10]; to class the pictures in 3 formal categories (cut or whole fruits, flowers with pot or not); and to select (intralab selection) one photograph for each formal odor/item category.

- After, to propose an online consultation in order to validate the picture for 3 criteria: hedonic level, representativeness, proximity with the mental representation of the odor. The study was limited to wine workers. Every Monday, during 7 weeks, wine workers (around 250 persons) answered two online questionnaires, each one dealing with 10 items. In each questionnaire, the items were randomized, and for each item, three orders of presentations of the pictures were proposed. The persons had to inquire personal data (gender, age, experience, skills and diploma) and had to answer the 3 questions on 3 successive pages:

<footnote n="1"><sup>1</sup>Univ. Bordeaux, ISVV, EA 4577 Œnologie, F-33140 Villenave d'Ornon, France</footnote>

<footnote n="2"><sup>2</sup>INRA, ISVV, USC 1366 Œnologie, F-33140 Villenave d'Ornon, France</footnote>
1/ Do you recognize the object on this picture?

2/ Does this picture evoke a pleasant odor?

3/ From your point of view, which one is the most representative of the "strawberry" (for example) smell in wines?

- Finally, to validate each odor for each criterion using a Khi² test using Monte-Carlo procedure and a contrast evaluation using the Marascuilo procedure; to place each picture into aroma or off-flavor category using the results of hedonic level test; and to class all the pictures into class and underclass according to the naturalist point of view (not a technological one).

## Results and discussion

Around 250 persons answered the online questionnaires, 59% were women. Most of the panel was between 25 and 49 years old (37% between 25 and 34; 42% between 35 and 49; 9% younger and 12% older). Seventy percent of the answerers had a master degree (or DNO) in technical oenology, only 10% were not graduates of oenology. Most of the answerers (72%) used to work in the south west of France. The panel was familiar with wine tasting, 25% declared tasting wine daily, 40% several times a week and 35% weekly.

For each item, at least one picture was easily recognized by the panel (question 1). The unrecognized pictures were never selected as representatives of the odor (question 3) and finally excluded from the study.

The result of the hedonic level (question 2) test allowed the categorization of the items into flavor and off-flavor. The off-flavors were: "ethyl acetate", "acetic", "cultivated mushroom (champignon de Paris)", "encaustic", "cork", "moldy/earthy", "brett character", "mousse", "styrene, vegetal"; the family of oxidation odors including "rancid nut", "oxidized apple" and "dried fruits"; and the family of reduction odors including "garlic", "rubber", "cabbage", "sewage treatment plant", "onion", "floorcloth". The categorization into flavors and off-flavors reflects the classical categorization proposed to the wine workers by oenology schools and highlights the importance of scientific and pedagogic strategies to the knowledge of wine defects [11-13].

To select the most representative picture of an item, several situations existed. One picture was significantly more representative than the two others; it was the one. Two or three pictures were equivalently designated as more representative than others; they were proposed to the "expert committee" of the project who elected the one. This alternative strategy concerned 17 items: "cream", "cherry", "ash", "vanilla", "game", "linden", "mousse", "white peach", "green olive", "flint", "candied fruit", "fig", "broom", "magnolia", "pineapple", "butter" and "leather". The limit is due to a too close resemblance between the pictures itself due to the absence of 3 picture series with real formal differences. Concerning fruits, most of the time the cut fruits were designated as more representative than the entire fruits. Concerning dairy, spices and others the presence of objects linked to the use of the product in the picture but without real odor seems to be a factor of choice as most representative of the odor (nutmeg grater, honey spoon, tobacco pipe, etc.). In the case of "petroleum" the gas pump was most representative of the odor than oil itself. These results open a new perspective on the link between visual representations and odor mental representation.

Finally, a picture was selected for each item. The organization of items and all the validated pictures are presented in figure 1.

## Conclusion

A procedure for validation of pictures associated to pleasant or unpleasant sensations has been proposed. An aroma picture book has been validated for both flavors and off-flavors of wines. These results can also teach us about the mental representations associated with wine aromas.

As a perspective, it could be interesting to repeat this study using different wine-drinker panels (geographical origins, diplomas, consumption style, etc.). Our tool could constitute the base of several works in scientific oenology and also for marketing investigations.
<figure><img src="image_422.png" /><figcaption>Fig. 1 - The picture book of wine aromas</figcaption></figure>
Acknowledgements

This work was performed in the framework of the PROGUSTO project with financial support from OSEO and the Région Aquitaine, engineering support from INNOVIN and technical support from the "Association des oenologues de Bordeaux". The authors also thank all the faithful wine workers who filled all the questionnaires.

References

1. Tempère S, Cuzange E, Schaaper MH et al (2014) ‘Brett character’ in wine: is there a consensus among professional assessors? A perceptual and conceptual approach. *Food Qual Prefer* **34**: 29-36.

2. Doty RL, Perl DP, Steele JC et al (1991) Olfactory dysfunction in three neurodegenerative diseases. *Geriatrics* **46**: 47-51.

3. Hamtat M-L (2011) Perception et représentation de l'odeur chez les patients souffrant de schizophrénie : création et exploitation d'un test olfacto-visuel. *Thèse de doctorat*, Bordeaux Segalen, Ecole Doctorale Sciences sociales. Société, Santé, Décision (Bordeaux).

4. Gottfried JA, Dolan RJ (2003) The nose smells what the eye sees: crossmodal visual facilitation of human olfactory perception. *Neuron* **39**: 375-386.

5. Morrot G, Bonny J-M, Lehallier B et al (2013) fMRI of human olfaction at the individual level: interindividual variability. *J Magn Reson Imaging* **37**: 92-100.

6. Mak YE, Simmons KB, Gitelman DR et al (2005) Taste and olfactory intensity perception changes following left insular stroke. *Behav Neurosci* **119**: 1693-1700.

7. Jadauji JB, Djordjevic J, Lundström JN et al (2012) Modulation of olfactory perception by visual cortex stimulation. *J Neurosci* **32**: 3095-3100.

8. Demattè ML, Sanabria D, Spence C (2006) Cross-modal associations between odors and colors. *Chem Senses* **31**: 531-538.

9. Noble A (2006) Describing the indescribable. *Food Sci Technol* **20**: 32-35.

10. Foroni F, Pergola G, Argiris G et al (2013) The foodcast research image database (FRIDa). *Front Hum Neurosci* **7**: 51.

11. Tempère S (2010) Métrologie sensorielle olfactive et apprentissage olfactif appliqués à l’œnologie. *Thèse de doctorat*, Université Lyon 2, Ecole Doctorale Neurosciences et Cognition.

12. Tempère S, Cuzange E, Jinana M et al (2011) The training level of experts influences their detection thresholds for key wine compounds. *Chemosens Percept* **4**: 99-115.

13. Franc C, David F, de Revel G (2009) Multi-residue off-flavour profiling in wine using stir bar sorptive extraction–thermal desorption–gas chromatography–mass spectrometry. *J Chromatogr A* **1216**: 3318-3327.
# Sensory evaluation of vescalagin, castalagin and acutissimin A in model solutions

Z. RASINES-PEREA<fnref n="1" />,<fnref n="2" />, R. JAQUET<fnref n="3" />, M. JOURDES<fnref n="1" />,<fnref n="2" />, S. QUIDEAU<fnref n="3" />, P.-L. TEISSEDRE<fnref n="1" />,<fnref n="2" />*

Ellagitannins – flavano-ellagitannins – sensory evaluation

## Introduction

C-Glucosidic ellagitannins, which are the main polyphenolic compounds in oak heartwood, are extracted by wine during aging in oak barrels. Although such maturing of alcoholic beverages in oak barrels is a multi-centennial practice, very little is known on the impact of these ellagitannins on the organoleptic properties of red wine. To date, only one study has been performed to estimate the astringency and bitterness threshold of purified ellagitannins, but the conditions of the sensory test used were unfortunately not appropriate to model the wine tasting conditions [1]. To understand the contribution of the ellagitannins on the aforementioned mouth-feel properties of red wines or spirits aged in oak barrels, further sensory studies are required to evaluate the organoleptic properties of each oak-native ellagitannin, as well as their derivatives formed during red wine aging [2].

In this context, the objectives of the present work were: (i) to isolate and purify oak ellagitannins (vescalagin and castalagin) from oak wood, (ii) to hemisynthesize some flavano-ellagitannins, such as acutissimin A, and (iii) to evaluate their sensory impact on the basis of their human threshold concentrations and dose/response relationships.

## Materials and methods

### Ellagitannin extraction and purification

The C-glucosidic ellagitannins, castalagin and vescalagin, were extracted and purified (>95% pure) from *Quercus robur* heartwood as previously described [3-4]. The hemisynthesis of acutissimin A (>95% pure) was performed in an acidic organic solution [1.5% (v/v) TFA/THF] at 60 °C as previously described [5]. Each pure compound was separately dissolved in aqueous model solutions containing 5 g/L of tartaric acid at pH 3.5 and 4.5, and in a wine model solution (12% ethanol, 5 g/L of tartaric acid at pH 3.5).

### Sensory analysis

Eighteen judges, 10 women and 8 men, from the Enology Department of the University of Bordeaux took part in this sensory study. They were all selected on the basis of their interest and availability, and were previously trained with aqueous solutions of quinine sulfate (0.25 g/L), aluminium sulfate (3 g/L) and sucrose (4 g/L) to set bitterness, astringency and sweetness, respectively. This panel of judges then passed different triangular tests using solutions of each ellagitannin with increasing concentrations in order to determine the concentration thresholds of each compound at two different pH values, i.e., pH 4.5 for comparison with Glasbania and Hofmann's results [1], and pH 3.5 as a closer approximation of standard wine pH.

## Results and discussion

The castalagin (Cg) astringency threshold (Table 1) was determined to correspond to a concentration of 5.7 mg/L at pH 4.5, whereas the same compound in the same aqueous solution adjusted at pH 3.5 (Table 2) has its astringency threshold at 9.2 mg/L. Remarkably, the astringency threshold of its C-1 epimer

<footnote n="1">¹Univ. Bordeaux, ISVV, EA 4577, Œnologie, 210 Chemin de Leysotte, F-33140 Villenave d'Ornon, France</footnote>

<footnote n="2">²INRA, ISVV, USC 1366 Œnologie, F-33140 Villenave d'Ornon, France</footnote>

<footnote n="3">³Univ. Bordeaux, Institut des Sciences Moléculaires (CNRS-UMR 5255), Institut Européen de Chimie et Biologie, 2 rue Robert Escarpit, 33607, Pessac Cedex, France</footnote>
vescalagin (Vg) (Tables 1 and 2) could not be determined in these solutions within the range of concentrations used. However, it was possible to estimate that Vg astringency threshold is higher than 6.5 mg/L and 15 mg/L at pH 4.5 and 3.5, respectively.

The results we obtained indicate threshold values that are much higher (>6.5 mg/L and 5.7 mg/L at pH 4.5 for Vg and Cg, respectively) than those obtained by the Hofmann's group using the half-tongue test (1.03 mg/L for both Vg and Cg at pH 4.5) [1]. The Cg threshold in a wine model solution (Table 2) was estimated to be at a concentration higher than 40 mg/L. The acutissimin A astringency threshold (Table 1) was also evaluated for the first time in an aqueous solution at pH 4.5 and appeared to be higher than 14.8 mg/L.

<table><caption>**Table 1** - Sensory triangular tests for vescalagin, castalagin and acutissimin A at pH 4.5</caption><thead><tr><th colspan="3">pH 4.5</th></tr><tr><th>Vg (mg/L)</th><th>Cg (mg/L)</th><th>Acutissimin A (mg/L)</th></tr></thead><tbody><tr><td>&gt;6.5</td><td>5.7</td><td>&gt;14.8</td></tr><tr><td>1.03<sup>a</sup></td><td>1.03<sup>a</sup></td><td>nd<sup>a</sup></td></tr></tbody></table>

Vg: Vescalagin; Cg: Castalagin.

<table><caption>**Table 2** - Sensory triangular tests for vescalagin and castalagin at pH 3.5 and wine model solution</caption><thead><tr><th colspan="2">pH 3.5</th><th>Wine model solution</th></tr><tr><th>Vg (mg/L)</th><th>Cg (mg/L)</th><th>Cg (mg/L)</th></tr></thead><tbody><tr><td>&gt;15</td><td>9.2</td><td>&gt;40</td></tr></tbody></table>

## Conclusion

These preliminary results on the determination of the astringency thresholds of found-in-wine C-glucosidic ellagitannins clearly reveal that the methodology used for such a sensory analysis is a crucial parameter and that the methodology chosen must mimic as closely as possible the conditions of real wine testing. Further investigations are in progress in order to clarify the role and perception of these ellagitannins and their flavanoid hybrid derivatives in wine for a better control of wine aging quality.

## Acknowledgements

The authors thank the Conseil Interprofessionnel du Vin de Bordeaux and France AgriMer for their financial support (grant # EC EDP0914000097).

## References

1. Glasbania A, Hofmann T (2006) Sensory-directed identification of taste-active ellagitannins in American (*Quercus alba* L.) and European oak wood (*Quercus robur* L.) and quantitative analysis in bourbon whiskey and oak-matured red wines. *J Agric Food Chem* **54**: 3380-3390.

2. Saucier C, Jourdes M, Glories Y et al (2006) Extraction, detection and quantification of flavan-ellagitannins and ethylvescalagin in a Bordeaux red wine aged in oak barrels. *J Agric Food Chem* **54**: 7349-7354.

3. Vilhelmova-Ilieva N, Jacquet R, Quideau S et al (2014) Ellagitannins as synergists of ACV on the replication of ACV-resistant strains of HSV 1 and 2. *Antiviral Res* **110**: 104-114;

4. Quideau S, Varadinova T, Karagiozova D et al (2004) Main structural and stereochemical aspects of the antiherpetic activity of nonahydroxyterphenoyl-containing C-glycosidic ellagitannins. *Chem Biodiv* **1**: 247-258.

5. Quideau S, Jourdes M, Lefeuvre D et al (2005) The chemistry of wine polyphenolic C-glycosidic ellagitannins targeting human topoisomerase II. *Chem Eur J* **11**: 6503-6513.

<footnote>ªResults from Glasbania and Hofmann [1].</footnote>

<footnote>nd: not determined.</footnote>
# Sensory profiling of Chenin Blanc wines matured in different oak wood products

A. BOTHA, J. BRAND, W.J. DU TOIT*

*Department of Viticulture and Oenology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa.*

Sensory – oak – maturation – Chenin Blanc

## Introduction

Traditionally, wooden barrels are used for oak maturation. In recent years the use of alternative oak products has increased options of oak maturation for winemakers [1], since new barrels are expensive, require a lot of cellar space, and have a limited lifetime [2]. Alternative methods of oak maturation that have been investigated in several studies include the use of oak chips, beans, shavings, staves and barrel inserts.

From a sensory point of view, one of the main functions of oak is to enrich the wine with new compounds. These compounds can be divided into two categories, namely wood polyphenols that will contribute to the structure and taste of the wine, and aromatic compounds such as oak lactones, vanillin, eugenol, furfural and guaiacol that will contribute to the aroma of the wine [3]. The concentration in which these compounds will be extracted during oak ageing can depend on various factors. These include the size of the pool of the compounds and their precursors contained within the matrix of the wood, the rate of release of these compounds from the wood, the rate at which such compounds are consumed by further chemical or biochemical transformation, as well as the temperature and the duration of storage [4].

Several studies have reported the sensory effect of alternative oak products [5], but few studies have investigated the evolution of oak derived aromas from alternative oak products, especially in white wine. Understanding how both experts and consumers react towards wines matured in different oak products would enable winemakers to make informed decisions about the application of alternative oak products, especially regarding the production of wines for certain price classes or market segments [6].

## Materials and methods

### Vinification

Chenin Blanc grapes were sourced from the Tygerberg region in the Western Cape of South Africa, and then vinified on large scale at a commercial cellar. The grapes were harvested at 25.4 °Brix, with a total acidity of 5.77 g/L and a pH of 3.77. In the settling tank the TA was adjusted to 7 g/L with tartaric acid and the total SO₂ was adjusted to 40 mg/L. The juice was also treated with 3 g/hL of settling enzyme. After 48 hours of settling the juice was racked and inoculated with a yeast preparation of *Saccharomyces cerevisiae* CY3079, D254, L2056 and D47 at a dosage of 7.5 g/hL each. After 48 hours and 96 hours of alcoholic fermentation 15 g/hL of nitrogen supplementation was added to the must. After 3 g/100 mL of sugar was consumed by the yeast, the must was moved to the respective oak maturation vessels.

### Maturation treatments

The maturation trial consisted of six experimental treatments. The first treatment, an unoaked tank wine of the same origin, served as the unoaked control for this study (TC1). The second treatment entailed the use of 5th fill barrels from the same cooperage, serving as the oaked control wines (BC). New French oak barrels, with the same toasting level, of different two different cooperages were used as two more treatment (B1 and B2). French oak barrel stave inserts from two different cooperages (S1 and S2) were used in 5th fill barrels of the same cooperage than for the second experimental treatment. The barrel inserts were customised to have a 40% contact ratio with the wine, thus replicating the effect of a new barrel. All of the treatments, except for the unoaked tank control, were performed in triplicate in 300L barrels.
## Wine sampling and storage

After intervals of respectively 4 months and 9 months of maturation, wine from all the treatments were sampled and sealed with screw capsules in 750 mL green Burgundy bottles (Consol, XPRS, South Africa). After bottling the wines were stored in a controlled environment with a temperature of 16°C, until the time of sensory analysis.

## Sensory analysis

The sensory analyses of the wines were performed by both an expert panel of 25 members and a trained panel of 20 members. Sensory evaluation of the wines was performed after respectively 4.5 and 9 months of oak maturation. Both the expert and trained panel evaluated the wines by means of the frequency of citation based method Pick-K-attributes. Experts did not receive any training prior to the sensory evaluation. Trained panellists were trained to recognise attributes on a list of set descriptors with the help of reference standards. During the formal sensory evaluation panellists received the list of set descriptors and had to mark the applicable aroma attributes. The expert panel only evaluated the wines once, whereas the trained panel evaluated the wines in two replicates.

## Data analysis and statistics

Sensory data were captured on paper ballots and entered into Microsoft excel (www.microsoft.co/excel). Statistical analysis was done on XLSTAT (www.xlstat.com) according to the protocol for analysing frequency data [7]. Contingency tables were constructed with wine samples as objects and attributes as variables. The number of citations of each attribute for a specific wine sample was counted; this was done for all wine samples. Correspondence analysis was conducted on the contingency tables. Hierarchical cluster analysis (HCA) with Euclidean distances and Ward's linkages was performed on the first two dimensions of the CA to identify clustering of samples.

# Results and discussion

Correspondence analysis was conducted to identify the clustering of samples, with F1 and F2 accounting for more than 50% of the variation between wines at each sampling stage. Clear separation was observed between the different treatments. The wines aged in new barrels correlated to aromatic descriptors such as oaky, caramel, toasted bread, vanilla, and marmalade, with an increase in oak related descriptors following maturation from 4.5 months to 9 months. At the 4.5 months ageing interval, treatment 1 of the staves (S1) showed little oak character, while S2 had more oak aromas being correlated to descriptors such as honey, nutty, vanilla and planky. At the 9 months ageing interval the stave treatments were correlated with similar descriptors, including toffee, toasted bread, nutty, and honey. This suggests that the release rate of oak derived aroma compounds differed for the two treatments. The unoaked tank control and barrel control treatments were correlated the strongest to fruity aromas and showed the least correlation to oak derived aromatic descriptors. Trends obtained for the trained and expert panel were in general in agreement (results not shown).

<figure><img src="image_423.png" /><figcaption>Fig. 1 - CA analysis of wines after 4.5 months</figcaption></figure>

<figure><img src="image_424.png" /><figcaption>Fig. 2 - CA analysis of wines after 9 months</figcaption></figure>
**Conclusion**

The expert panel and trained panel delivered results portraying the same trend of aromatic profiles for the different treatments. There were clear differences between the unoaked and oaked wines, and also between the oaked treatments itself. A clear discrimination between the wines aged in new barrels and the wines aged in old barrels with staves was also observed. There seems to exist a difference in the rate of release of oak derived compounds, and it is clear that longer maturation leads to more a more oaky profile.

**Acknowledgements**

We thank DGB (Pty) Ltd. and the NRF who funded this study; without their support this research would not have been possible. We acknowledge the panellists who participated in the tastings.

**References**

1. De Beer D, Joubert E, Marais J, Du Toit W et al (2008) Characterisation of Pinotage wine during maturation on different oak products. *S Afr J Enol Vitic* **29**: 39-49.

2. Rodriguez R, Gomez-Plaza E (2011) Differences in the extraction of volatile compounds from oak chips in wine and model solutions. *Am J Enol Vitic* **62**: 127-132.

3. Tiquet-Lavandier N, Mirabel M, De Beauregard D (2008) Functions and benefits of oak barrels for fermentation/élevage. *Winemaking November/December*: 46-49.

4. Spillman PJ, Iland PG, Sefton MA (1998) Accumulation of volatile oak compounds in a model wine stored in American and Limousin oak barrels. *Aust J Grape Wine Res* **4**: 67-74.

5. Du Toit WJ (2010) Micro-oxygenation, oak alternatives and added tannins and wine quality, pp 226-254. *In: A.G. Reynolds (ed.), Managing wine quality: Oenology and wine quality, Vol. 2*. Woodhead Publishing Limited.

6. Crump AM, Johnson TE, Wilkinson KL et al (2015) Influence of oak maturation regimen on composition, sensory properties, quality, and consumer acceptability of Cabernet Sauvignon wines. *J Agric Food Chem* **63**: 1593-1600.

7. 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.
# Study of sensory interactions among fruity and non-fruity compounds in various mixtures

M. CAMELEYRE<fnref n="1" />,<fnref n="2" />*, G. LYTRA<fnref n="1" />,<fnref n="2" />, S. TEMPERE<fnref n="1" />,<fnref n="2" />, G. DE REVEL<fnref n="1" />,<fnref n="2" />, J.-C. BARBE<fnref n="1" />,<fnref n="2" />

Red wine – perceptive interactions – higher alcohols – ethyl ester and acetate

## Introduction

Some ethyl esters and acetates may increase the perception of fruity aromas in wine, thanks to synergistic effects, even if these compounds are present at sub-thresholds concentrations [1, 2]. From a quantitative standpoint, higher alcohols (HA) represent the main group of volatiles in many alcoholic beverages. Some bibliographic data suggested their contribution to the aromatic complexity by either increasing or masking flavors of wine, depending on their concentrations [3]. The goal of this work was to highlight and study the impact of five higher alcohols on the perception of the fruity character of red wines' fruity pool.

## Materials and methods

### Aromatic reconstitution

Dilute alcohol solution was prepared with ethanol and microfiltered water (12% vol. (v/v)) and 5 g/L of tartaric acid (pH adjusted to 3.5 with sodium hydroxide). Dearomatized red wine (DRW) was prepared according to the method described by Lytra et al. [4]. Aromatic reconstitutions were also established in a *Vin de Pays d'Oc* (Cabernet Sauvignon).

The fruity reconstitution (FR) was prepared with thirteen ethyl esters and acetates in dilute alcohol solution or DRW at the average concentrations found in red wines (Table 1). Complete reconstitution (CR) was achieved by the mixture of these esters in dilute alcohol solution or DRW, with the five HA at representative levels of those found in wine (Table 1).

<table><caption>**Table 1** - Ethyl ester, acetate, and higher alcohol concentrations used for sensory analyses</caption><thead><tr><th colspan="11">Ethyl Esters and Acetates (µg/L)</th><th colspan="5">Higher Alcohols (mg/L)</th></tr></thead><tbody><tr><td>C<sub>3</sub>C<sub>2</sub></td><td>C<sub>4</sub>C<sub>2</sub></td><td>C<sub>6</sub>C<sub>2</sub></td><td>C<sub>8</sub>C<sub>2</sub></td><td>2MeC<sub>3</sub>C<sub>2</sub></td><td>(2S)-2MeC<sub>4</sub>C<sub>2</sub></td><td>(2S)- and (2R)-2OH4MeC<sub>5</sub>C<sub>2</sub>(95/5, m/m)</td><td>C<sub>2</sub>C<sub>4</sub></td><td>C<sub>2</sub>C<sub>6</sub></td><td>C<sub>2</sub>iC<sub>4</sub></td><td>C<sub>2</sub>iC<sub>5</sub></td><td>3OH<sub>C</sub>C<sub>4</sub>C<sub>2</sub></td><td>3MeC<sub>4</sub>C<sub>2</sub></td><td>2MB</td><td>3MB</td><td>2MP</td><td>P</td><td>B</td></tr><tr><td>150</td><td>200</td><td>200</td><td>200</td><td>250</td><td>50</td><td>400</td><td>10</td><td>2</td><td>50</td><td>250</td><td>300</td><td>50</td><td>50</td><td>200</td><td>100</td><td>30</td><td>4</td></tr></tbody></table>

C<sub>3</sub>C<sub>2</sub>, ethyl propanoate; C<sub>4</sub>C<sub>2</sub>, ethyl butanoate; C<sub>6</sub>C<sub>2</sub>, ethyl hexanoate; C<sub>8</sub>C<sub>2</sub>, ethyl octanoate; 2MeC<sub>3</sub>C<sub>2</sub>, ethyl 2-methylpropanoate; S-2MeC<sub>4</sub>C<sub>2</sub>, S-ethyl 2-methylbutanoate; 2OH4MeC<sub>5</sub>C<sub>2</sub>, ethyl 2-hydroxy-4-methylpentanoate; C<sub>2</sub>C<sub>4</sub>, butyl acetate; C<sub>2</sub>C<sub>6</sub>, hexyl acetate; C<sub>2</sub>iC<sub>4</sub>, 2-methylpropyl acetate; C<sub>2</sub>iC<sub>5</sub>, 3-methylbutyl acetate; 3OHC<sub>4</sub>C<sub>2</sub>, ethyl 3-hydroxybutanoate; 3MeC<sub>4</sub>C<sub>2</sub>, ethyl 3-methylbutanoate; 2MB, 2-methylbutan-1-ol; 3MB, 3-methylbutan-1-ol; 2MP, 2-methylpropan-1-ol; P, propan-1-ol; B, butan-1-ol.

### Sensory analyses – Discriminative testing methods

A first set of triangular tests consisted of evaluating the individual perception of each HA in the FR and in dilute alcohol solution by an 18-member panel. Each HA, present at the concentrations listed in Table 1, was compared to FR or dilute alcohol solution alone. In the second phase, the same panel was subjected to triangular tests (Table 2). The results of all of the triangular tests were statistically analyzed. Olfactory

<footnote n="1">¹Univ. Bordeaux, ISVV, EA 4577 Œnologie, F 33140 Villenave d'Ornon, France</footnote>

<footnote n="2">²INRA, ISVV, USC 1366 Œnologie, F 33140 Villenave d'Ornon, France</footnote>

<footnote>*Corresponding author: margaux.cameleyre@wanadoo.fr</footnote>
thresholds were determined by an 18-member panel in dilute alcohol solution. The “olfactory thresholds” of specific mixtures were also established. “Olfactory thresholds” of aromatic reconstitutions were thus measured in different matrices: dilute alcohol solution, dilute alcohol solution containing a compound of interest, and dilute alcohol solution containing HA at various concentrations (Table 3). This statistical value was determined according to the ASTM-E1432 method [5]. In addition, interaction effects for certain mixtures were evaluated using Feller’s additive model.

<table><caption>**Table 2** - Olfactory impact of the omission of higher alcohols from the complete reconstitution</caption><thead><tr><th></th><th>13 ethyl esters and acetates</th><th>2MB</th><th>3MB</th><th>2MP</th><th>P</th><th>B</th><th>Difference observed</th></tr></thead><tbody><tr><td>Complete Reconstitution in Dilute Alcohol Solution</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td></td></tr><tr><td>Test 1</td><td>x</td><td>-</td><td>x</td><td>x</td><td>x</td><td>x</td><td>=</td></tr><tr><td>Test 2</td><td>x</td><td>x</td><td>-</td><td>x</td><td>x</td><td>x</td><td>***</td></tr><tr><td>Test 3</td><td>x</td><td>x</td><td>x</td><td>-</td><td>x</td><td>x</td><td>=</td></tr><tr><td>Test 4</td><td>x</td><td>x</td><td>x</td><td>x</td><td>-</td><td>x</td><td>=</td></tr><tr><td>Test 5</td><td>x</td><td>x</td><td>x</td><td>x</td><td>x</td><td>-</td><td>=</td></tr><tr><td>Test 6</td><td>x</td><td>-</td><td>-</td><td>x</td><td>x</td><td>x</td><td>***</td></tr><tr><td>Test 7</td><td>x</td><td>-</td><td>x</td><td>-</td><td>x</td><td>x</td><td>**</td></tr><tr><td>Test 8</td><td>x</td><td>-</td><td>x</td><td>x</td><td>-</td><td>x</td><td>=</td></tr><tr><td>Test 9</td><td>x</td><td>-</td><td>x</td><td>x</td><td>x</td><td>-</td><td>=</td></tr><tr><td>Test 10</td><td>x</td><td>x</td><td>-</td><td>-</td><td>x</td><td>x</td><td>***</td></tr><tr><td>Test 11</td><td>x</td><td>x</td><td>-</td><td>x</td><td>-</td><td>x</td><td>***</td></tr><tr><td>Test 12</td><td>x</td><td>x</td><td>-</td><td>x</td><td>x</td><td>-</td><td>***</td></tr><tr><td>Test 13</td><td>x</td><td>x</td><td>x</td><td>-</td><td>-</td><td>x</td><td>=</td></tr><tr><td>Test 14</td><td>x</td><td>x</td><td>x</td><td>-</td><td>x</td><td>-</td><td>=</td></tr><tr><td>Test 15</td><td>x</td><td>x</td><td>x</td><td>x</td><td>-</td><td>-</td><td>=</td></tr><tr><td>Test 16</td><td>x</td><td>-</td><td>-</td><td>-</td><td>x</td><td>x</td><td>***</td></tr><tr><td>Test 17</td><td>x</td><td>-</td><td>-</td><td>x</td><td>-</td><td>x</td><td>***</td></tr><tr><td>Test 18</td><td>x</td><td>-</td><td>-</td><td>x</td><td>x</td><td>-</td><td>***</td></tr><tr><td>Test 19</td><td>x</td><td>-</td><td>x</td><td>-</td><td>-</td><td>x</td><td>=</td></tr><tr><td>Test 20</td><td>x</td><td>-</td><td>x</td><td>-</td><td>x</td><td>-</td><td>**</td></tr><tr><td>Test 21</td><td>x</td><td>-</td><td>x</td><td>x</td><td>-</td><td>-</td><td>**</td></tr><tr><td>Test 22</td><td>x</td><td>x</td><td>-</td><td>-</td><td>-</td><td>x</td><td>***</td></tr><tr><td>Test 23</td><td>x</td><td>x</td><td>-</td><td>-</td><td>x</td><td>-</td><td>***</td></tr><tr><td>Test 24</td><td>x</td><td>x</td><td>-</td><td>x</td><td>-</td><td>-</td><td>***</td></tr><tr><td>Test 25</td><td>x</td><td>x</td><td>x</td><td>-</td><td>-</td><td>-</td><td>=</td></tr><tr><td>Test 26</td><td>x</td><td>x</td><td>-</td><td>-</td><td>-</td><td>-</td><td>*</td></tr><tr><td>Test 27</td><td>x</td><td>-</td><td>x</td><td>-</td><td>-</td><td>-</td><td>*</td></tr><tr><td>Test 28</td><td>x</td><td>-</td><td>-</td><td>x</td><td>-</td><td>-</td><td>***</td></tr><tr><td>Test 29</td><td>x</td><td>-</td><td>-</td><td>-</td><td>x</td><td>-</td><td>***</td></tr><tr><td>Test 30</td><td>x</td><td>-</td><td>-</td><td>-</td><td>-</td><td>x</td><td>***</td></tr></tbody></table>

## Sensory analyses – Descriptive testing methods

Various reconstitutions in dilute alcohol solution or DRW were presented to a 16-judge panel to evaluate sensory profiles for overall aroma, fresh- and jammy-fruit, solvent, and butyric notes. The first glass consisted of matrix (dilute alcohol solution or DRW) supplemented with the 13 ethyl esters and acetates at the concentrations indicated in Table 1. The second consisted of the same matrix supplemented with the 5 HA (individually or mixed) at the concentrations indicated in Table 3. The third consisted of the matrix supplemented with both the esters and the 5 HA (individually or mixed) at the concentrations indicated in Table 3. Four samples of aromatic reconstitutions in red wine were also presented. The first consisted of red wine alone. The other three glasses contained wine spiked with HA in order to achieve their low,

<footnote>***, 0.1% significant level; **, 1% significant; *, 5% significant level; =, no significant difference; x, presence of listed compounds; -, absence of listed compounds; 2MB, 2-methylbutan-1-ol; 3MB, 3-methylbutan-1-ol; 2MP, 2-methylpropan-1-ol; P, propan-1-ol; B, butan-1-ol</footnote>
medium and high concentrations in wines (Table 3). Experimental data were also reported on a graph based on two parameters for binary mixtures, as proposed by Patte and Laffort. Statistical data were analyzed using a non-parametric bilateral statistical test of Kruskal-Wallis (multiple pair wise comparisons using the Conover-Iman procedure).

<table><caption>**Table 3 - Amount of higher alcohols used for sensory profiles**</caption><thead><tr><th></th><th>2MB</th><th>3MB</th><th>2MP</th><th>P</th><th>B</th></tr></thead><tbody><tr><td>Low concentrations (mg/L)</td><td>60</td><td>200</td><td>50</td><td>15</td><td>133</td></tr><tr><td>Medium concentrations (mg/L)</td><td>85</td><td>290</td><td>80</td><td>20</td><td>2</td></tr><tr><td>High concentrations (mg/L)</td><td>100</td><td>350</td><td>115</td><td>40</td><td>2.7</td></tr></tbody></table>

2MB, 2-methylbutan-1-ol; 3MB, 3-methylbutan-1-ol; 2MP, 2-methylpropan-1-ol; P, propan-1-ol; B, butan-1-ol

# Results and discussion

## Organoleptic impact of HA on quantitative perception

The evaluation of individual perception of each HA in the FR and in dilute alcohol solution revealed that, in dilute alcohol solution, 2- and 3-methylbutan-1-ol were present in supra-threshold concentrations. These results also highlight the interesting role of butan-1-ol, which affected the aroma of the mixture, even when added at sub-threshold concentrations. When omission tests were realized (Table 3), all omissions involving 3-methylbutan-1-ol were significantly perceived by the panel, highlighting the importance of this compound in aromatic reconstitutions.

Olfactory thresholds for 3-methylbutan-1-ol and butan-1-ol were also determined. The olfactory threshold of 3-methylbutan-1-ol was evaluated at 29.6 mg/L in dilute alcohol solution and 30.6 mg/L in FR. These values highlighted that this compound had a direct olfactory impact at the concentration tested in both matrices. The olfactory threshold for butan-1-ol was evaluated at 368.6 mg/L in dilute alcohol solution and 458.5 mg/L in FR, indicating that this compound was tested at a concentration considerably lower than its olfactory threshold.

When 3-methylbutan-1-ol and butan-1-ol alone were added to the FR in dilute alcohol solution, their presence resulted in a significant decrease (p<0.05) in the “olfactory threshold” of FR (4.4- and 7.64-fold decrease, respectively). The behavior of butan-1-ol was particularly interesting leading to a decrease in the “threshold” of the FR, despite its sub-threshold concentration, revealing an enhancement of the perception of the fruity pool, via specific perceptual interactions. Similar effects were detected using a mixture of fruity esters [2]. To verify whether the quantitative contribution of butan-1-ol was due to a simple addition phenomenon or a hyper-addition effect, the impact of its presence on the odor of the mixture was evaluated according to Feller’s additive model. The result revealed a simple addition effect when FR was supplemented with this compound.

The impact of the mixture of HA at various concentrations was also studied. Adding low, medium, and high concentrations of a mixture of the five HA led to a 5-, 9-, and 4-fold increase (p<0.05), respectively, in the “olfactory threshold” of the fruity pool (Figure 1). These results showed that adding HA at concentrations corresponding to those found in red wine led to a decrease in the “olfactory threshold” of FR and underline the masking power of these components on the fruity pool perception. Similar effects have been described in the literature: adding isovaleric acid and isobutyric acid had a masking effect on “phenol character”: the olfactory threshold of this defect character was higher when red wine was supplemented with these carboxylic acids [6].

## Organoleptic impact of HA on qualitative odor perception

Sensory profile evaluation showed that the addition of 3-methylbutan-1-ol to the FR led to an increase in overall aroma and butyric notes, and adding butan-1-ol to the FR increased the intensity of fresh- and jammy-fruit, even if this compound was present at levels considerably below its olfactory threshold.

Adding the five HA at various levels to the FR in dilute alcohol solution (Figure 2) resulted in a significant increase in the intensity of solvent notes at all concentrations tested, and butyric notes were significantly higher when FR in dilute alcohol was supplemented with the HA mixture at medium and high concentrations. Moreover, this addition resulted in lower average scores for jammy- and fresh-fruit
intensity of the mixture, for medium and high concentrations, respectively. The same trends were observed for solvent notes in DRW and red wine and a significant difference was also noticed for the butyric descriptor in red wine.

<figure><img src="image_425.png" /><figcaption>**Fig. 1** - Detection probability of fruity reconstitution in different matrices: aromatic impact of higher alcohols at (a) low, (b) medium, and (c) high concentrations added to fruity reconstitution in dilute alcohol solution. \*expressed in mL total fruity reconstitution (FR) diluted in 50 mL matrix. DAS, Dilute Alcohol Solution; HA, Higher Alcohols. The curves are drawn according to a sigmoid function.</figcaption></figure>

<figure><img src="image_426.png" /></figure>
<figure><img src="image_427.png" /></figure>

**Fig. 2** - Aromatic impact of various concentrations of higher alcohols added to the fruity reconstitution in dilute alcohol solution.* p < 0.05 on the centered and scaled values; FR, Fruity Reconstitution. Histograms represent the non-centered and non-scaled values. Error bars indicate standard error deviation.

The analysis by Patte and Laffort model showed that the addition of 3-methylbutan-1-ol, at supra-threshold concentrations, to FR in dilute alcohol solution resulted in a marked reduction in the intensity of the fruity notes, and that the addition of butan-1-ol to FR in dilute alcohol solution resulted in hypo-addition of fresh-fruit notes, with a partial-addition level. A tendency towards hyper-addition was observed for jammy-fruit notes, but it was not significant compared to the hypo-addition.

Moreover, when the 5 HA were added at various concentrations to FR in dilute alcohol solution and DRW, it generally resulted in hypo-addition of fresh- and jammy-fruit notes. Compounds having non-fruity note have been reported to affect the fruity aroma of FR [4].

## Conclusion

The addition of individual HA at concentrations found in red wines revealed the interesting behavior of two of them, 3-methylbutan-1-ol and butan-1-ol, in reducing the “olfactory threshold” and modifying the qualitative perception of FR.

Furthermore, adding the 5 HA to different matrices revealed remarkable, new, perceptual interactions, illustrating quantitative and qualitative changes in the perception of fruity aroma. These compounds contributed to a masking effect of fruity aromas in the mixture. Their simultaneous addition to the model solution also modified the qualitative perception of FR, depending on the concentration of HA.

Sensory profiles highlighted changes in the perception of fruity nuances in the presence of the mixture of HA, with specific perceptive interactions, including a relevant masking effect on fresh- and jammy-fruit notes of the fruity mixture in both dilute alcohol solution and dearomatized red wine matrices. These key observations were made following the addition of HA to a more complex matrix, such as a red wine, revealing the sensory consequences of the presence of HA at various concentrations under real conditions.

## References

1. Pineau B, Barbe J-C, Van Leeuwen C et al (2009) Examples of perceptive interactions involved in specific “red-” and “black-berry” aromas in red wines. *J Agric Food Chem* **57**: 3702-3708.

2. Lytra G, Tempere S, Le Floch A et al (2013) Study of sensory interactions among red wine fruity esters in a model solution. *J Agric Food Chem* **61**: 8504-8513.

3. Etievant PX (1991) Wine. In *Volatile Compounds of Foods and Beverages*; H. Maarse: New-York, pp 483-546.

4. Lytra G, Tempere S, de Revel G et al (2012) Impact of perceptive interactions on red wine fruity aroma. *J Agric Food Chem* **60**: 12260-12269.

5. AFNOR (2002) Sensory analysis - Methodology - General guidance for measuring odour, flavour and taste detection thresholds by a three-alternative forced-choice (3-AFC) procedure - ISO 13301. In *Analyse Sensorielle*, Paris.

6. Romano A, Perello MC, Lonvaud-Funel A et al (2009) Sensory and analytical re-evaluation of “Brett character”. *Food Chem* **114**: 15-19.
# Etude sensorielle, analytique et consommateur de la typicité aromatique poivrée des vins de Gamay N de l'AOP Côtes d'Auvergne

O. GEFFROY<fnref n="1" />*, C. BUISSIERE<fnref n="2" />, T. DUFOURCQ<fnref n="3" />, E. SERRANO<fnref n="1" />

## Gamay N – typicité – arôme poivré – rotundone

### Introduction

Avec près de 30 000 ha de vignoble en 2011, le Gamay N est le 8ème cépage rouge le plus planté en France. Parfois également dénommé « Gamay noir à jus blanc », cette variété originaire de Bourgogne résulte d'un croisement entre le Pinot Noir et le Gouais [1]. Il a trouvé une place de choix dans l'encépagement des vignobles de France et est principalement représenté aujourd'hui en Bourgogne, dans le Beaujolais, dans le Val de Loire et en Midi-Pyrénées. On le retrouve également dans de nombreux petits vignobles septentrionaux comme celui de l'AOP Côtes d'Auvergne où il est implanté pour sa précocité. Au sein de ce territoire, ce cépage exprime des notes typiques poivrées qui n'ont à ce jour jamais été étudiées. Ces notes pourraient être imputables à la présence de hauts niveaux de rotundone, une molécule identifiée en Australie dans des vins de Shiraz [2]. Afin d'étudier la typicité aromatique poivrée des vins de Gamay d'Auvergne, une étude comprenant 3 volets (sensoriel, analytique et consommateur) largement inspirée de travaux conduits sur Sauvignon blanc [3] a été menée par l'IFV Sud-Ouest en collaboration avec la Fédération Viticole du Puy de Dôme.

### Matériel et méthodes

#### Vins

Les 21 vins de l'étude du millésime 2013 ont été choisis sur la base qu'ils contenaient de manière prédominante du Gamay N (>85%) et qu'ils étaient représentatifs en termes de volume de production des régions considérées. Cette sélection comprend 12 vins des Côtes d'Auvergne, 6 du Beaujolais, 2 du Val de Loire et 1 de Gaillac.

#### Analyse sensorielle

Les vins ont été dégustés fin juin 2014 par le jury expert de l'IFV composé de 10 dégustateurs entraînés régulièrement. La notation a porté au total sur 32 descripteurs sensoriels au nez et en bouche à l'aide d'une échelle discontinue de 0 à 5. Plusieurs séances spécifiques de travail ont été organisées en amont de la dégustation, sur les descripteurs aromatiques les plus fréquemment perçus dans les vins de Gamay (Figure 1a). Deux dégustateurs soit 20% des membres du jury ont été évincés car ils étaient incapables de percevoir les arômes poivrés dans les vins. Des anosmies spécifiques touchant 20 à 25% de la population ont en effet été rapportées pour la rotundone [2].

#### Analyses classiques et rotundone

Les 21 vins de l'étude ont fait l'objet d'un suivi analytique dans le laboratoire de l'IFV Sud-Ouest sur des paramètres œnologiques classiques. Dans le cadre d'une prestation de service, la concentration en rotundone des vins a été déterminée par l'AWRI par chromatographie en phase gazeuse multidimensionnelle selon le protocole décrit par Geffroy et al [4].

#### Panel consommateur

Deux études consommateurs ont été organisées début juillet 2014 à Clermont-Ferrand (n=47) et à Paris (n=40). Les membres du panel ont été recrutés sur la base qu'ils étaient des consommateurs réguliers de

<footnote n="1">¹IFV Sud-Ouest, F-81310 Lisle Sur Tarn, France</footnote>

<footnote n="2">²IFV Sud-Ouest, F-32100 Caussens, France</footnote>

<footnote n="3">³Fédération viticole du Puy-de-Dôme, F-63170 Aubière, France</footnote>
vins rouges. Suite à l'évaluation sensorielle, 4 vins présentant des profils sensoriels distincts ont été choisis pour être dégustés par chacun des membres de ce panel. Ceux-ci étaient invités à classer les vins par ordre de préférence (de 1 le vin préféré, à 4 le moins apprécié) après examen olfactif puis examen gustatif. A l'issue de la séance, les membres du panel ont complété un formulaire de renseignements démographiques et d'habitude de consommation.

## Traitement statistique

Le traitement statistique des données a été réalisé grâce au logiciel XLstat (Addinsoft, Paris). Il comprend des régressions linéaires, une Analyse en Composantes Principales (ACP) et une Classification Hiérarchique Ascendante (CAH) des données sensorielles obtenues par voie orthonasale et moyennées pour les 8 dégustateurs retenus parmi le jury expert. La CAH a été utilisée afin de sélectionner les 4 vins proposés au jury consommateur.

# Résultats et discussion

L'ACP (Figure 1a) permet de mettre en évidence que 4 loadings (épicé/poivré, fermentaire lacté, fermentaire amylique et intensité aromatique) sont à même d'expliquer les principales différences entre les vins. Il est possible de constituer un groupe de vins d'Auvergne présentant des caractéristiques sensorielles proches et marquées par des notes poivrées. GAIL-1 et BEAU-4 se distinguent par des notes de type fermentaire amylique alors que les vins BEAU-1, BEAU-5 et BEAU-6 présentent des arômes fermentaires lactés. Les autres vins présentent quant à eux, des profils sensoriels moins différenciés.

<figure><img src="image_428.png" /><figcaption>Fig. 1 - Analyse en Composantes Principales (a) et Classification Hiérarchique Ascendante (b) des données sensorielles de l'examen olfactif.</figcaption></figure>

<figure><img src="image_429.png" /><figcaption>Fig. 2 - Concentration en rotundone des 21 vins de Gamay de l'étude groupés par région d'origine.</figcaption></figure>

Des concentrations en rotundone sensiblement équivalentes sont observées dans les cuvées provenant du Beaujolais, de la Loire et du Sud-Ouest (Figure 2). Les vins des Côtes d'Auvergne se distinguent par des concentrations supérieures en ce composé. Parmi les 12 vins d'Auvergne, 4 possèdent une concentration en rotundone supérieure ou égale à 100 ng/L avec un maximum enregistré à 142 ng/L pour la cuvée AUV-7. Une corrélation positive significative avec un coefficient de détermination de 0,66 est observée entre les
notes poivrées perçues au nez et la concentration en rotundone mesurée dans les vins. Une variabilité importante de concentrations en rotundone peut être mise en évidence au sein des 12 vins des Côtes d'Auvergne. Lorsqu'on localise et représente géographiquement sur une carte les parcelles majoritairement utilisées pour élaborer les 12 cuvées auvergnates, on constate que les variations de concentration en rotundone ne sont pas structurées spatialement ce qui suggère que l'effet terroir, notamment à travers sa composante climatique n'est pas dominant. Le paramètre qui permet le mieux d'expliquer cette variabilité est le degré alcoolique des vins. En effet, une corrélation positive et significative est observée entre ce paramètre et la concentration en rotundone (R² = 0.44). Ces résultats sont en cohérence avec les travaux menés dans le Sud-Ouest sur cépage Duras [4].

Sur la base de leur appartenance à des groupes distincts déterminés par CAH (Figure 1b), 4 vins ont été choisis pour participer à une étude consommateur : GAIL-1 (profil de type primeur avec de fortes notes amylique), BEAU-1 (profil plus complexe marqué par des arômes fermentaires de type lacté), AUV-6 (profil épicé/poivré), AUV-8 (profil tirant vers le végétal avec en bouche l'astringence la plus faible). Le vin AUV-8 marqué par des arômes végétaux est le préféré au nez (somme des rangs = 199) puisqu'il devance le vin GAIL-1 d'une courte tête (somme des rangs = 201). Ce dernier, très explosif et fruité, ne fait pas l'unanimité car même s'il possède un nombre important d'admirateurs (vin le plus apprécié de 37 dégustateurs sur 87), il connaît également beaucoup de détracteurs (le moins apprécié de 27 d'entre eux). Le vin au profil aromatique poivré (AUV-6) ne fait pas consensus. Il s'agit toutefois en fréquence de citation du deuxième vin le plus souvent préféré. Les 21 consommateurs qui ont le plus apprécié cette cuvée possèdent le « budget vin » le plus élevé (7,90 euros en moyenne) et parmi eux 57% n'ont pas du tout apprécié le vin GAIL-1. Ces constatations permettent de conclure à une certaine opposition entre les amateurs du vin GAIL-1 s'apparentant à des néophytes, et ceux du vin AUV-6 qui ont un profil d'amateurs éclairés.

## Conclusion

Ces résultats qui soulignent la typicité de leur production devraient aider les vignerons auvergnats à en faire la promotion. Ils leur donnent également la possibilité de s'approprier et de mettre en œuvre les connaissances acquises sur la rotundone dans d'autres régions et d'autres pays, dans l'objectif de piloter les notes poivrées de leurs vins. Les résultats de l'étude consommateur pourront également les aider à constituer leur gamme en mieux ciblant les profils de consommation.

## Remerciements

Ces travaux ont été financés par la Région Auvergne et FranceAgriMer dans le cadre du dispositif régional d'aide à la promotion collective et du Contrat de Plan Etat-Région. Les auteurs tiennent tout particulièrement à remercier Tracey Siebert, Randell Taylor de l'AWRI, Bertrand Chatelet et Valérie Lempereur de l'IFV, les vignerons, les caves qui ont mis à disposition les échantillons, Romain Renard, Maurice Chassin sans oublier l'ensemble des consommateurs pour leur participation.

## Références

1. Bowers J, Boursiquot J-M, This P et al (1999) Historical genetics: the parentage of Chardonnay, Gamay, and other wine grapes of Northeastern France. *Science* **285**: 1562-1565.

2. Wood C, Siebert TE, Parker M et al (2008) From wine to pepper: rotundone, an obscure sesquiterpene, is a potent spicy aroma compound. *J Agric Food Chem* **56**: 3738-3744.

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

4. Geffroy O, Dufourcq T, Carcenac D et al (2014) Effect of ripeness and viticultural techniques on the rotundone concentration in red wine made from *Vitis vinifera* L. cv. Duras. *Aust J Grape Wine Res* **20**: 401-408.
# Unveiling the “wine-like” feature - a sensory driven approach

C.S. TEIXEIRA<fnref n="1" />, A.R. MONFORTE<fnref n="1" />, J. DOMINGUES<fnref n="1" />, S. FAIRBAIRN<fnref n="2" />, M.J. SOUSA<fnref n="3" />, A.C. DA SILVA FERREIRA<fnref n="1" />,<fnref n="2" />*

Alcoholic fermentation – sensory – “wine-like” feature – nitrogen

## Introduction

The most basic “wine-like” concept may be formed exclusively with aroma without the contribution of other senses. That is, the trivial human experience of realizing that “it smells like wine”: a pattern recognition event. Humans generally struggle with identifying the components of a mixture, even when they are able to identify the components alone, and this difficulty becomes insurmountable as the complexity of the odours increases [1-4]. This limitation is suppressed by an extraordinary capability of discriminating one mixture from another. Mixtures containing hundreds of different volatile molecules, such as wine or coffee, are associated with unique olfactory percepts [5, 6]. This is possible as the olfactory system treats odorant mixtures as single synthetic objects and not as an analytical combination of components. Several studies have shown that the cortical patterns of neural activity induced by a mixture are unique, and not a combination of neural activities induced by the mixtures’ components [7]. Therefore, in order to reveal the volatile “wine-like feature”, pattern recognition techniques are required.

The aim of this study is to determine the temporal onset of the sensory space responsible for the “wine-like aroma” using a novel “bottom up” approach. This “bottom up” approach uses yeast to create the “wine-like” feature by fermenting a synthetic medium only containing the ingredients essential for creating this “wine-like” perception. This study provides insights with regard to what is common to all wines, i.e. what is responsible for the cognitive “wine-like” recognition. The chemical reconstruction of the volatile sensometabolome has previously been done using a “top down” strategy in order to reconstruct varietal aromas via the addition of aromatic compounds to a synthetic solution [8]. Ultimately, if these “bottom up” and “top down” aroma construction methods are used in unison, they would greatly aid sensory studies as the “wine-like” feature would provide the correct “wine-like” context for sensory analysis.

## Materials and methods

*Strain, media and culture conditions*

The yeast strain used in this study was *Saccharomyces cerevisiae* Lalvin QA23 (Lallemand Inc, Montreal, Canada). The yeast pre-cultures were grown in each of the fermentation medium. In order to obtain robust results, two independent sets of experiments were performed. Each set of fermentations was performed in triplicate. Fermentation vessels were inoculated with pre-culture in the logarithmic growth phase (OD640≈1) to an OD640 of 0.1 (final cell density of approximately 10⁶ cfu/mL). Fermentations were conducted in synthetic grape juice (SGJ) adapted from [9] with a slight modification in Solution C that only contained YNB (yeast nitrogen base without amino acids and ammonium sulphate) (Difco), CaCl₂, 0.2, and a nitrogen source according to the experiment aim: the composition of nitrogen and lipid treatments applied to an initial screening of the minimal fermentation medium formulation was NH₄Cl (200 mg/L, ≈ 52.373 mg/L Yeast Assimilable Nitrogen (YAN)) for M1 and M2 and NH₄Cl (300 mg/L, ≈ 78.56 mg/L YAN) for M3 and M4. M1 and M3 were absent of ergosterol. The nitrogen treatments applied to a minimal synthetic medium to evaluate the “wine-like” feature contained: for media NH - NH₄Cl (300 mg/L, ≈ 78.56 mg/L YAN) or, for media AA - NH₄Cl (200 mg/L, ≈ 52.38 mg/L YAN)

<footnote n="1">¹CBQF – Centro de Biotecnologia e Química Fina, Escola Superior de Biotecnologia, Universidade Católica Portuguesa/Porto, Rua Arquiteto Lobão Vital, Apartado 2511, 4202-401 Porto, Portugal</footnote>

<footnote n="2">²IWBT – DVO University of Stellenbosch, Private Bag X1, Matieland 7602, South Africa</footnote>

<footnote n="3">³CBMA – Centro de Biologia Molecular e Ambiental, Universidade do Minho, Campus de Gualtar, Departamento de Biologia, 4710-057, Braga, Portugal</footnote>
and cysteine, alanine, arginine, asparagine, aspartic acid, glutamine, glutamic acid, glycine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, proline, serine, threonine, tryptophan, tyrosine and valine (total 100 mg/L, ≈ 9.95 mg/L YAN). All fermentations were performed in Schott bottles modified with a plastic tube and a syringe in order to allow the sampling without opening the flask, thus avoiding the media aeration. The ratio liquid/gas was maintained (1:1) in all replicates in order to avoid any deviation. All fermentations were conducted in an incubator at a controlled temperature (22°C) and were agitated (300 rpm) before sampling.

### Growth measurement

Yeast growth was monitored by measuring the optical density using a UV/VIS spectrophotometer Nicolet evolution 100, Thermo electron corporation (Cambridge, UK). The absorbance of the homogenized sample was read at 640 nm in acrylic cuvettes with 1 cm of light path length.

### Sensory analysis

Seven ranking tests were performed according to [10]. The panellists received a given number of samples in coded black glasses covered with a watch glass and they were asked to rank them for the intensity of the “wine-like” aroma. The results were transformed from ranks to scores according to Fisher and Yates, 1942. An analysis of variance (ANOVA) was applied to the experimental data; results were considered significant if the associated p value was below 0.05. The significant differences were determined by Tukey tests. All statistical analysis was performed using SPSS for Windows, Version 10.0 (SPSS Inc., Chicago, IL), IBM SPSS Statistics 22.

## Results and discussion

### Fermentation kinetic parameters

In order to clarify the relationships between must composition and the fermentation end-products, the complexity of the fermentation medium was minimized such as to obtain the “threshold” for the production of the “wine-like aroma”. In a first approach we determined the influence of the quantity of nitrogen and lipids on yeast fermentation kinetics. The results showed that the amount of nitrogen (N) has the greatest impact on the fermentation profile and kinetics and that the yeast was able to ferment in a media containing only 52.37 mg/L of YAN and without lipids. However, since highest concentrations of YAN and the presence of lipid factors favoured the fermentation kinetics, 78.56 mg/L of nitrogen and lipid factors were included in the composition of minimal medium required by yeast to perform alcoholic fermentation, in order to reduce the risk of sluggish and stuck fermentations. The quality of the nitrogen source also greatly influences yeast growth, fermentation kinetics and flavour metabolism, and therefore in subsequent fermentations different nitrogen sources: only NH₄Cl (300 mg/L) and NH₄Cl (200 mg/L) plus 20 amino acids (100 mg/L total) were tested. Overall, both nitrogen treatments resulted in similar rates of glucose and fructose consumption, however, the CO₂ and biomass production profiles clearly illustrate that the medium containing only ammonium fermented faster than medium containing amino acids. This may be attributed to slightly higher levels of available YAN or ammonia being more readily metabolized in contrast with amino acids, which require additional biochemical modifications in order to be used in the same metabolic pathways [11].

### Sensory determination of the temporal onset of the wine-like aroma

Fermentation samples were presented to panellists, who were asked whether the aroma of the fermentation products resembled wine or not. Results from both experiments showed that 35-65% of the panellists already identified the wine-like aroma in AA fermentations at day 1 while only 15-40% associated this aroma to NH fermentations at the same fermentation time. On day 2 more than 80% of the panellists agreed that the AA fermentations had a wine-like aroma, whereas on day 3 the NH fermentations were unanimously described as wine-like. This suggests that amino acids influenced the production of some compounds that contribute to the wine-like feature during the early stages of fermentation. In fermentations lacking amino acids the same feature is only perceived hours later probably due to some metabolic differences.

### Ranking tests

The same fermentation samples were also ranked from least to most “wine-like”. The results of the statistical analysis of the 7 ranking tests are presented in table 1.
<table><caption>**Table 1** - Ranking of fermentation products to determine which ones resemble wine. *Saccharomyces cerevisiae*, QA23, fermented a minimal synthetic medium containing either ammonium (NH) or a combination of ammonium and amino acids (AA) in 2 independent experiments (F1 and F2). The letter denotes a significant difference (p ≤ 0.05).</caption><thead><tr><th rowspan="2">Ranking test</th><th colspan="5">Sample (Tukey Multiple Comparison test)</th><th colspan="2">ANOVA</th></tr><tr><th></th><th></th><th></th><th></th><th></th><th>Samples</th><th>Panellists</th></tr></thead><tbody><tr><td>1</td><td>F1_AA_t0<sup>a</sup></td><td>F1_AA_t1<sup>b</sup></td><td>F1_AA_t2<sup>c</sup></td><td>F1_AA_t3<sup>c</sup></td><td>F1_AA_t4<sup>d</sup></td><td>p&lt;0.05</td><td>p&gt;0.05</td></tr><tr><td>2</td><td>F1_NH_t0<sup>a</sup></td><td>F1_NH_t1<sup>b</sup></td><td>F1_NH_t2<sup>cd</sup></td><td>F1_NH_t3<sup>d</sup></td><td>F1_NH_t4<sup>de</sup></td><td>p&lt;0.05</td><td>p&gt;0.05</td></tr><tr><td>3</td><td>F1_NH_t2<sup>a</sup></td><td>F1_NH_t3<sup>b</sup></td><td>F1_NH_t4<sup>b</sup></td><td>F1_AA_t2<sup>a</sup></td><td>F1_AA_t3<sup>b</sup></td><td>F1_AA_t4<sup>b</sup></td><td>p&gt;0.05</td></tr><tr><td>4</td><td>F2_AA_t0<sup>a</sup></td><td>F2_AA_t1<sup>b</sup></td><td>F2_AA_t2<sup>cd</sup></td><td>F2_AA_t3<sup>d</sup></td><td>F2_AA_t4<sup>de</sup></td><td>diluted white wine (1:1)<sup>e</sup></td><td>p&gt;0.05</td></tr><tr><td>5</td><td>F2_NH_t0<sup>a</sup></td><td>F2_NH_t1<sup>a</sup></td><td>F2_NH_t2<sup>b</sup></td><td>F2_NH_t3<sup>cd</sup></td><td>F2_NH_t4<sup>c</sup></td><td>diluted white wine (1:1)<sup>ce</sup></td><td>p&lt;0.05</td></tr><tr><td>6</td><td>F2_NH_t3</td><td>F2_NH_t4</td><td>F2_AA_t3</td><td>F2_AA_t4</td><td>diluted white wine (1:1)</td><td></td><td>p&gt;0.05</td></tr><tr><td>7</td><td>F1_AA_t4<sup>a</sup></td><td>F1_AA_t11<sup>a</sup></td><td>F1_NH_t4<sup>a</sup></td><td>F1_NH_t11<sup>b</sup></td><td>reconstructed Alvarinho aroma<sup>a</sup></td><td></td><td>p&lt;0.05</td></tr></tbody></table>

The results show that over time, the fermentative aromas resemble the wine-like feature more closely in both NH and AA fermentations (ranking tests 1, 2, 4 and 5). Additionally, a diluted wine sample was perceived to be as “wine-like” as the fermentation samples with or without amino acids (ranking tests 4 and 5). When comparing fermentations with different sources of nitrogen at time 3 and 4 with a diluted white wine sample (ranking test 6) no significant differences were found between all samples. This result suggests that the wine-like feature is mainly affected by the quality of the volatiles that compose it and not by the quantity.

An additional ranking test was performed (ranking test 7) in order to evaluate the differences between the reconstructed “wine-like” aroma using a bottom up approach (fermentations) and a top down approach (reconstructed Alvarinho varietal aroma). Statistical treatment of the results demonstrates that there are no significant differences between the reconstructed Alvarinho varietal aroma and the aroma of fermentation with or without amino acids at time 3 and 4 and the fermentation with amino acids at time 11, although these treatments were significantly different from fermentation without amino acids at time 11. The transformation of ranks to scores [12] allowed the quantification of the differences between samples: the smallest the score (more negative), the highest the “wine-like” aroma of the sample. Results show that the reconstructed Alvarinho wine aroma is the sample that panellists consider less “wine-like” and that the fermentation without amino acids at day 11 is clearly the more “wine-like” with a score much more negative than all other samples.

These results clearly demonstrate that in the tested conditions the “bottom up” approach is more efficient in “wine-like” aroma reconstruction than a “top down” approach.

## Sensory validation

In order to validate the “bottom up” results the samples collected on day 4 were analysed by GC-MS and GC-FID for the identification and quantification of the headspace compounds (data not shown). In order to evaluate if those compounds when presented in a complex solution were recognized by a sensory panel as having a “wine-like aroma”, a synthetic solution was produced by adding the quantified compounds to an acidic solution (6 g/L tartaric acid, 3 g/L malic acid, 0.5 g/L citric acid) and buffered at pH 3.5. The panellists were asked if they recognized the wine-like aroma in the presented sample. Results show that 63% of the panellists recognized the “wine-like” aroma in the reconstructed solution. The results were statistically relevant (z-test, p<0.0001).
## Conclusion

The results showed that the amount of nitrogen has the greatest impact on the fermentation profile and kinetics and that the yeast was able to ferment in a media containing only 52.37 mg/L of YAN and without lipids. The medium containing only ammonium fermented faster than medium containing amino acids.

The amino acids influenced the production of some compounds that contribute to the wine-like feature during the early stages of fermentation. In fermentations lacking amino acids the same feature is only perceived hours later probably due to some metabolic differences.

The performed sensory tests suggest that the wine-like feature is mainly affected by the quality of the volatiles that compose it and not by the quantity.

It was demonstrated that in the tested conditions the “bottom up” approach is more efficient in “wine-like” aroma reconstruction than a “top down” approach.

The aroma obtained on day 4 with a “bottom up” strategy was reconstructed and a statistical relevant percentage of the panellists recognized the “wine-like” aroma in the synthetic solution. In order to validate this data, omission sensory tests are being done.

## Acknowledgements

This research was funded by the project "Wine Metrics: Revealing the Volatile Molecular Feature Responsible for the Wine-Like Aroma - a Critical Task toward the Wine Quality Definition." (PTDC/AGR-ALI/121062/2010) and partially supported by ESB/UCP pluriannual funds through the POS-Conhecimento Program that includes FEDER funds through the program COMPETE (Programa Operacional Factores de Competitividade), national funds through FCT (Fundação para a Ciência e a Tecnologia) and Winetech, the Technology and Human Resources Program and the South African National Science Foundation.

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# Characterization of the "Brett" character masking effect

S. TEMPERE<fnref n="1" />,<fnref n="2" />*, M.H. SCHAAPER<fnref n="1" />,<fnref n="2" />, E. CUZANGE<fnref n="3" />, R. DE LESCAR<fnref n="3" />, G. SICARD<fnref n="4" />, G. DE REVEL<fnref n="1" />,<fnref n="2" />

Wine defects – odor masking – psychophysiological test – perceptive interactions

## Introduction

Many of the compounds responsible for wine off-flavors have already been identified. To date, most of the sensory studies concerning off-flavors have focused on their hedonic valence and detection and/or rejection thresholds [1]. Few studies have examined how these compounds affect the aromatic profile of wine. This study reports on experiments where wine experts were asked to evaluate the impact of ethylphenols at sub- and supraliminal concentrations on wine fruity notes, in order to determine the effect responsible for this quality depreciation. The aim was to deepen our understanding of the perceptive phenomenon and examine whether the interaction had a chemical, or a peripheral or central physiological origin.

## Materials and methods

The sensory tests were conducted in a ventilated tasting-room.

### Experiment 1: fruity and "Brett character" evaluation

In the first experiment, different concentrations of ethylphenols (a mixture 10:1 of 4-ethylphenol and 4-ethylguaiacol in proportions as found in Bordeaux red wines contaminated by *Brettanomyces bruxellensis*) were added in a Merlot wine in order to evaluate the changes in wine fruity notes (subliminal concentration: 9 µg/l; supraliminal concentration: 466 µg/l).

One hundred and eighty-nine wine experts were required to rate the fruity intensity and the "Brett character" intensity on six-point scales (from 0 = not at all to 5 = very strong). Samples were evaluated in individual booths at controlled room temperature (20 °C) and in covered ISO glasses coded with three-digit number. All samples were only evaluated orthonasally.

### Experiment 2: detection ability and hedonic perception relationship

The purpose of the second experiment was to test the relationship between the detection ability and hedonic perception of a wine spiked with ethylphenols, on the basis of the olfactory segmentation ability among the odoriferous source of the participants. The cohort for this test consisted of 83 expert subjects. Two different psychophysical tests were used: detection (an ascending procedure, 10 perithreshold concentrations, 3-AFC presentation) and rejection threshold measurements (an ascending procedure, 10 perithreshold concentrations, and paired-comparison preference test). Solutions for measuring the thresholds were prepared using a Bordeaux red wine. The stimulus concentration range used was from 4 to 4000 µg/l of a mixture 10:1 of 4-ethylphenol and 4-ethylguaiacol.

### Experiment 3: fruity aroma modeling

In a third part, complementary experiments were carried out to better understand the perceptive phenomenon and to explore whether this interaction has a chemical, a peripheral or a central physiological origin: the fruity aroma was modeled by a wine fruity ester, the ethyl heptanoate (strawberry, pineapple note). This study included chemical measurements (SPME-GC-MS) [2, 3] as well as psychophysiological test, using olfactory mental imagery. Effects of perceived (objective) and imagined (subjective) odors were

<footnote n="1">¹Univ. de Bordeaux, ISVV, EA 4577, Unité de recherche OENOLOGIE, 33882 Villenave d'Ornon, France</footnote>

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

<footnote n="3">³Quali-Bordeaux, 33370 Artigues-près-Bordeaux, France</footnote>

<footnote n="4">⁴Univ. d'Aix - Marseille, NICN-UMR 7259, 13000 Marseille, France</footnote>

<footnote>*Corresponding author: sophie.tempere@u-bordeaux.fr</footnote>
used in order to evaluate whether the sensory effect observed is primarily mediated by peripheral or central mechanisms. In a first part, 12 participants evaluated the fruity intensity of 3 aqueous solutions of ethyl heptanoate (219 - 439 - 659 µg/l), and then completed the same task in presence of ethylphenols at supraliminal concentration (915 µg/l). Finally, we evaluated whether imagined odor of "Brett character" would bring forth the same effect. Subjects were required to spend two minutes imagining "Brett character" before sniffing the solutions of ethyl heptanoate. They were advised to sniff actively during the training phase as this sensorimotor activity seems to facilitate the evocation of olfactory images [4]. Subjects rated the intensities of the fruity character on 100 mm scales printed on paper.

# Results and discussion

## Perception of wine fruity notes: influence of ethylphenol concentrations

The results showed that both sub- and supraliminal concentrations of ethylphenols could interfere with the perception of the fruity notes. Actually, this test evidenced that a subliminal concentration of ethylphenols significantly decreases the intensity of wine fruity notes (Kruskal-Wallis test - Steel-Dwass-Critchlow-Fligner post-hoc test; p<0.05) (Figure 1).

<figure><img src="image_430.png" /><figcaption>**Fig. 1** - Olfactory evaluation of the same Merlot wine spiked with two different concentrations of ethylphenols. Comparisons of the mean perceived intensities for fruity notes ± standard error. Values marked with different letters are significantly different (Steel-Dwass-Critchlow-Fligner post-hoc test; p<0.05).</figcaption></figure>

## Relationship between the detection ability and hedonic perception of a wine spiked with ethylphenols

A significant difference (difference>one-dilution step or intra-individual fluctuations observed) was observed between the absolute detection threshold (345µg/l) and the rejection threshold (124 µg/l). Thus, the rejection threshold was significantly lower, by a factor of 2.8 (p<0.05) (Figure 2). This wine was rejected although its ethylphenol content was below the subjects' detection thresholds. This result highlights a perceived change in wine quality even at subliminal concentrations of ethylphenols.

<figure><img src="image_431.png" /><figcaption>**Fig. 2** - Comparison between detection and rejection of ethylphenols (n = 83 experts). Curves represent the stimulus-response function and sigmoid modeling for rejection (solid lines) and detection (broken lines) thresholds.</figcaption></figure>
*Origin of the "Brett character" masking effect*

The GC-MS measurements showed no difference of headspace concentrations for esters in presence of ethylphenols.

Complementary experiments were carried out to deepen our understanding of the perceptive phenomenon and explore whether the fruity note-ethylphenol interaction had a peripheral or central physiological origin. The fruity perception is significantly decreased in presence of ethylphenols or during "Brett character" imagery task. The interaction between concentration and condition is not significant (p>0.05) (Figure 3).

<figure><img src="image_432.png" /><figcaption>**Fig. 3** - Fruity note intensity as a function of condition (without ethylphenols, in conditions of objective or subjective ethylphenol perception). Bars show confidence interval (α=0.05). \*\* p<0.01. In both conditions, the presence of ethylphenols decreases the intensity of the fruity note.</figcaption></figure>

The results are consistent with the assumption that the interaction between the perception of ethylphenols and ethyl heptanoate takes place at a central locus.

**Acknowledgements**

The authors would like to thank the Conseil Interprofessionnel du Vin de Bordeaux for their financial support, as well as the wine tasters for their enthusiastic participation.

**References**

1. Tempere S, Cuzange E, Schaaper MH et al (2014) Brett character in wine: is there a consensus among professional assessors? A perceptual and conceptual approach. *Food Qual Prefer* **34**: 29-36.

2. Romano A, Perello MC, Lonvaud-Funel A et al (2009) Sensory and analytical re-evaluation of Brett character. *Food Chem* **114**: 15-19.

3. Antalick A, Perello MC, de Revel G (2010) Development, validation and application of a specific method for the quantitative determination of wine esters by headspace-solid-phase microextraction-gas chromatography-mass spectrometry. *Food Chem* **121**: 1236-1245.

4. Arshamian A, Olofsson JK, Jönsson FU et al (2008) Sniff your way to clarity: the case of olfactory imagery. *Chemosens Percept* **1**: 242-246.