Oil-water partition of odorant: Discrepancy between sensory and instrumental data

Food

PIIrS0950-3293(96)00024-9

Qpali!y and l’wfmnce Vol. 7, No. 3/4, pp. 299-303, 1996 Copyright0 1996 Elsevier Science Ltd Printed in Great Britain. All rights reserved 0950-3293/96 $I5.00+0.00

OIL-WATERPARTITION 0FODORANT:DlSCREPANCY BETWEENSENSORYANDINSTRUMENTALDATA F. Rousseau,* C. Castelain &J. P. Dumont Institut

National

de la Recherche

Agronomique, Laboratoire d’Etude des Interactions des Moltcules Gtraudiire, BP 1627, 44316, Nantes cedex 03, France

Alimentaires,

Rue de la

(Accepted 15 May 1996)

perceptions from physical or chemical stimuli to which they have been exposed. It is known that people differ in

ABSTRACT The aim of this study was to determine

their tastes and likings, but has a single objective a unique perception in humans?

odour compounds elicit sensory responses of the same intensity when presented at the same concentration in vapour phase over water or oil solutions. Oil-water partition coeficients of selected odorous molecules were calculated from experimental data obtained either by sensory measurements or by GLC headspace analysis of the corresponding samples. Oil-water partition coejicients calculated from sensory data were consistently higher than the related data obtained from instrumental measurements. Experiments carried out on aqueous solutions showed a trend amongst panelists to underestimate odour intensity of blind samples of low concentration, but the bias cannot account for the whole of the observed di$erence. It is suggested that concentration of the odorants in the headspace might not be the unique factor determining intensity of the perceived stimulus. Copyright 0 1996 Else&r Science Ltd whether

Aside from the formal dispute on the static model and the dynamic model (Bakker et al., 1994), the present study is designed to evaluate variability of the sensory response when facing changes in quality and intensity of the odor stimulus. As the starting point, the question was raised as to whether a putative sensorial effect could result when odorants are released from either oil or water.

MATERIALS

a

tremendous

amount

of

available

to whom correspondence

METHODS

Four test compounds (benzaldehyde, act l-en 3-01, lina1001 and acetophenone) were selected for investigation as they are common food odorants. Odour thresholds (Devos et al., 1990) and odour qualities are reported in Table 1. Monocomponent solutions were prepared using distilled water (Millipore system) or miglyol (International Flavors and Fragances, Longvic, France). It is a natural oil phase extracted from coprah, consisting of a mixture of triglycerides with fatty acids from Cs to C12. Compared to

literature,

there is an ongoing challenge to relate instrumental measurements and sensory data. It is generally assumed that analysis of headspace vapours represents more closely the organoleptic characteristics of the food than other methods of analysis (Delahunty et al., 1994). Presently, the trend to approach the volatile profile as it occurs in the nose or mouth of human beings eating foods (Taylor & Linforth, 1994) is gaining stronger support. Even so, there is a large gap to bridge before a reliable translation of a mixture composition into its corresponding hedonic picture can be achieved. Compared to scientific instruments that deliver calibrated signals showing a direct relationship with the applied stimulus, humans often find it difficult to describe and quantify *Author

AND

Sample preparation

INTRODUCTION Despite

aroused

sunflower oil, miglyol is a low-odour oil phase. The odorous compounds were directly dissolved in water or in miglyol. Dilution series were designed according to a geometrical progression and consisted of four solutions in water and three in miglyol (Table 2). The lower concentration in the studied series was set above or close to the odour threshold. Test solutions (20 ml) were poured in 100 ml odour-free brown glass bottles closed with screw caps. They were allowed to equilibrate for 15-20 hours either at room temperature (22°C) prior to sensory analysis or 50°C before instrumental measurements.

Sensory analysis 11 subjects 45-member

should be addressed. 299

(8 females, 3 males) were selected out of the sensory panel of our institute. All were

300

F. Rousseau et al.

TABLE 1. Characteristics

TABLE 2. Experimental

of odorants

concentrations

of odorants

in solution

(ppm) Odorant

Odour quality

Odour threshold in air (ppm)

Odorant

Medium Water

Benzaldehyde Acetophenone Ott-1 en 3-01 Linalool

Bitter almond Pungent-sweet Mushroom, sweet-earthy Bergamot, lavander

0.420 0.360 0.030 0.053

Benzaldehyde

0.32 1.60 8.00 40.00 0.32 1.60 8.00 40.00 0.08 0.40 2.00 10.00 0.32 1.60 8.00 40.00

Acetophenone and had previous sensory experience but were not familiar with the evaluation of pure odorants. During a preliminary round, they were trained in evaluating typicality and intensity of food odorants, and they were also familiarized with the method and testing procedure. During an experimental session, panelists were first provided with the complete set (four samples) of water solutions of the studied odorants ranked in order of increasing concentration. These solutions coded from 1 to 4 were spotted on an unanchored structured axis. Subjects were instructed to sniff samples and aim to memorize progression of odour intensity. Thereafter, three miglyol solutions of the odorant (coded with a three-digit random number) were presented to the panelists in order of increasing concentration. Panelists had to mark the samples on the axis on the grounds of the perceived intensity. Subjects were requested to swirl the bottles, unscrew the cap and sniff. Resniffing was not allowed in order to prevent olfactory fatigue and modification of the composition of the headspace. A 35 second pause was imposed on panel members before they were allowed to test the next sample to avoid adaptation effects. Before testing each set of solutions (water and miglyol), assessors were asked to sniff samples of the pure solvent as reference (without any tested odorant). From the position of the mark, the equivalent concentration of odorant in water was calculated for each miglyol solution. Sensorial miglyol-water partition coefficients (I&-SA) were then calculated as the ratio of solute concentration in miglyol to equivalent concentration in water. Three values of sensorial miglyol-water partition coefficients were determined for each panelist in each session and mean and standard deviation were calculated. Two different odorants were investigated in a session. Four or five experimental replications were carried out for such odorant. Accuracy of panelist responses was assessed and occurence of systematic bias was tested for three other sessions. Three blind samples of water solutions of act len 3-01 were substituted to miglyol solutions. volunteers

Ott-1 en 3-01

Linalool

30 150 750 48 240 1200 20 100 500 100 500 2500

equipped with an 800 pl insert on a DB5 capillary column (30 m, diameter: 0.32 mm, film thickness: 0.52 p) in splitless mode with FID detection. Programmated temperature was 50°C for 2 minutes then lO”C/minute. For each tested odorant, duplicated measurements were carried out on the four water samples and the three miglyol samples. Detector response was related to odorant concentration in water by linear regression calculated on data available from the eight water samples. In turn, detector responses obtained over the six miglyol samples were converted into their equivalent concentrations in water. Instrumental miglyol-water partition coefficients (K,,--GLC) were then calculated as the ratio of solute concentration in miglyol to equivalent concentration in water. Six values of instrumental miglyol-water partition coefficients were determined in each session on each odorant and mean and standard deviation were calculated. Due to the low concentrations of samples involved in sensory analysis, instrumental analysis proved rather unreliable when carried out on samples equilibrated at 22°C. Equilibration at 50°C was preferred with the aim to increase odorant concentration in the headspace. Possible effect of this difference in temperature was investigated for each odorant performing a complete set of measurements at both 22°C and 50°C on water and TABLE 3. Mean partition coefficients (*SD) of odorants obtained from GLC analysis at 22°C and GLC analysis at 50°C (n = 6) Odorant

Instrumental analysis Odorant concentration in the headspace of samples submitted for sensory evaluation was estimated by means of GLC. A 500 pl of headspace sample, equilibrated at 50°C was manually injected in an HP 5890 apparatus

Miglyol

Benzaldehyde Acetophenone Ott-1 en 3-01 Linalool **:p

co.01

GLC analysis 22°C

GLC analysis 50°C

38*8 3365 54f 17 136f48

251t4 35*7 72f 16 172*26

t values

5.845** 0.202 1.400 1.651

Oil-Water miglyol

solutions

centrations.

prepared

Instrumental

cients calculated

mental

miglyol-water

odorant partition

at 22°C

except

for benzaldehyde.

partition

component

coefficients

were corrected

1.52) when comparing

instrumental

concoeffi-

and 50°C

3 with t-test values. Results

difference

miglyol-water

the latter

higher

from data obtained

are shown in Table significant

with

show no Instru-

obtained

(correction

for

to geometrical

in case of over-estimation under-estimation. Means each panelist

of -I]

and [ I-(C/Ceq)] in case of and standard deviations for

(for all the samples) and for each sample or

RESULTS

AND

DISCUSSION

analysis

of sensory and instrumental

were calculated

for each odorant,

of the sessions.

formed using Student

Figure

1 shows the matching

partition

Except

coefficients

each session and the

Comparison

of means

was per-

t-test (p < 0.05).

higher data

for

linalool,

calculated

miglyol-water

from

sensory

than corresponding for almost

instrumental

from the position

of the mark and compared

to actual

values calculated Results

coeffi-

significantly from GLC

for t-tests are

the difference

data

was significant

(p cO.05)

highest

and benzaldehyde

ratio was obtained

the ratio for benzaldehyde

T

300-

sensory

only for aceto-

(p
for acetophenone

The

(4) while

was below 2.

Acetophenone

Kow 350

between

*:* 1i!h.L

phenone was calculated

partition were

reported in Table 4 together with corresponding calculated sensory/instrumental ratios. When the whole of the and

in water (Ceq)

data

all the sessions.

sessions was considered,

concentration

of sensory vs. instrumental

data.

Accuracy of panel responses Equivalent

progression as [(Ceq/C)

the three samples (the whole panel) were calculated.

cients

whole

Due

to sensorial miglyol-

Comparison between sensory and instrumental analysis Means

(C).

relative error was calculated

301

factor:

water coefficients.

Statistical

concentration references,

Partition of Odorant

USA

T

q GLC

*

25020060 150IOO50-

*

‘.

./I .

o-

I

Session number

Linalool

___Kow 400 t

500 USA q GLC

Kow

g:.

2 Session

Ott

3 number

4

I -en 3-01

0 GLC

400 300

Session

number

Session

number

FIG. 1. Miglyol/water partition coefficients of odorants calculated from sensory (SA) and instrumental (GLC) analysis of headspaces. Instrumental coefficients for benzaldehyde were corrected for difference in temperature. Error bar: standard deviation. *: means are significantly different (p < 0.05).

302

F. Rousseau et al.

~”

Pl

~2

P3

P4

P5

P6

P7

P8

P9

PI0

PI I

Panel

Panelists or panel FIG. 2. Relative error on estimation of act l-en 3-01 concentration

TABLE 4. Mean partition coefficients ( f SD) of odorants obtained from sensory and GLC analysis Odorant

Benzaldehyde Acetophenone Ott-1 en 3-01 Linalool

n

5 4 4 5

Sensory

GLC analysis

t values

Ratio

analysis 62f7 148f49 185f53 200*65

45*9” 35i7 75 f 21 163*34

6.337** 4.449* 3.050 1.347

1.4 4.2

a : corrected values for difference in temperature ; * : p < 0.05 ; **: p CO.01

As a first hypothesis, occurrence of a systematic bias in the notation of the panel was considered. The probability of such an effect was tested for act l-en 3-01 over three sessions, replacing test miglyol samples by blind water samples. Seven panelists out of eleven tended to underestimate concentration of blind samples (Fig. 2) and results showed that discrepancy of the panel and individual differences became less and less important as odorant concentration increased (Table 5). For each blind sample, such a dispersion is observed that no significant under-estimation or over-estimation of concentration has to be considered (p < 0.05). Mean deviation of the panel (-0.44f 1.88) is too small to account for the whole difference evidenced between sensory and instrumental data for this odorant. Similar effects are currently being investigated for the three other odorant molecules. It should be remembered that headspace over oil does not contain water vapour, whereas headspace over aqueous solution does, and that water vapour is often overlooked by instrumental measurements as it is not detected by FID. As a second hypothesis, it is postulated that water vapour in the headspace of odorant solutions is involved in some way in the overall process of odorant perception. The assumption is supported by previous data reported by Rothe et al. (1994). The authors stressed that 2 heptanone showed an odour threshold twice as high in 70% fat processed cheese as in 45% fat product (35 vs. 19 mg/kg), but they missed that related con-

in headspaces over water solutions in the range 0.2 to 5 ppm.

TABLE 5. Deviation of the whole panel for blind act l-en 3-01 solutions in water (three sessions, n = 30) Concentration

0.2 ppm

1 PPm

5 ppm

Bulked samples

Mean Standard deviation

-1.213 2.53 1

-0.309 1.314

0.204 1.282

-0.44 1.88

centrations of 2 heptanone in fat were respectively (50 and 41 mg/kg). From the proposed equations it has been calculated that odorant concentration in fat must be 20% higher in the 70% fat processed cheese than in the 45% fat product in order to produce the same odour score. If we assume that water vapour can be released more freely by the 45% fat product than by the 70% fat cheese, it looks reasonable to admit that water vapour had added to the sensory impact of 2 heptanone. Whether such an effect deals with transportation or trapping of the odour component is still not understood. At the present time, attention should be given to the fact that, contrary to the tested odorants, water vapour has a higher coefficient of diffusion in air than nitrogen and oxygen. It is assumed that water vapour could have helped, particularly in the event of a noticeable affinity for the compound under test, the transportation of organic vaporized molecules.

CONCLUSION The use of oil-water partition coefficient of selected compounds as the criterion to evaluate the fit between the instrument and human perception of odour intensity detection has shown that the relationship between the two modes is not straightforward. Equality of odorant concentration over oil and water does not imply equivalent sensory responses from the panel and the evolved correction factor appears very different from one compound to the other.

Oil-Water

Moderate ability in memorizing odour intensity, as well as an active involvement of water vapour in the course of odour transfer or perception, probably account for most of the evidenced discrepancy.

Delahunty,

Low-fat

Cheddar

mouth.

In Treads in Flavour Research,

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Science

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&

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pp. 53-57.

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of flavour

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(1990).

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