- Email: [email protected]
Can odours acquire fat-like properties?
ARTICLE IN PRESS
Appetite 47 (2006) 91–99 www.elsevier.com/locate/appet
Research report
Can odours acquire fat-like properties? Nina C. Sundqvist, Richard J. Stevenson, Ian R.J. Bishop Department of Psychology, Macquarie University, Sydney, NSW 2109, Australia Received 25 November 2005; received in revised form 20 March 2006; accepted 20 March 2006
Abstract Odours can acquire taste-like properties via simultaneous pairing in the mouth with tastants like sucrose. The experiment reported here sought to test whether qualities other than taste may also be acquired. Participants received pairings between odour A and low-fat unsweetened milk (LFUN), odour B and low-fat sweetened milk (LFSW), odour C and high-fat unsweetened milk (HFUN) and odour D and high-fat sweetened milk (HFSW). On test, participants reported that odours paired with milks perceived as being fattier (i.e. LFSW, HFUN, HFSW) were judged to smell fattier than they did prior to conditioning. In a further test, participants were asked to sample each of the four odours in a slightly fatty-sweet milk target. Odours previously paired with high-fat milks enhanced perceived fattiness of the target, whilst odours previously paired with sweetened milks enhanced perceived sweetness. These results were not well accounted for by participants’ explicit knowledge of the odour-milk pairings and suggest that fat-like qualities may be acquired. r 2006 Elsevier Ltd. All rights reserved. Keywords: Odour; Associative learning; Cross-modal learning; Flavour
Introduction Flavour perception involves interactions between taste, tactile, trigeminal and olfactory senses (Lawless, 1996; Small & Prescott, 2005). One consequence of these interactions is that they can produce long-lasting changes in the way that the flavour’s elements are perceived (Stevenson, Prescott, & Boakes, 1995). The most wellexplored example of this, is that between taste and smell. Odours that have been repeatedly presented with sweet tastes by mouth, such as vanilla in ice-cream, strawberry in jam or chocolate in cake, are commonly described as ‘sweet’ smelling. This perceived sweetness does not result from any direct effect of such odours on taste receptors (e.g. Stevenson, Prescott, & Boakes, 1999), rather it reflects a central process which appears to be based upon simultaneous associations between the taste and the smell (Stevenson & Boakes, 2004). A considerable amount of research has explored both whether odour ‘sweetness’ is perceptually akin to tasted sweetness (e.g. Dalton, Doolittle, Nagata, & Breslin, 2000; Frank & Byram, Corresponding author. Tel.: +61 2 9850 8098; fax: +61 2 9850 8062.
E-mail address: [email protected] (R.J. Stevenson). 0195-6663/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.appet.2006.03.328
1988) and whether such relationships can be acquired in the laboratory (e.g. Stevenson, Boakes, & Prescott, 1998). Moreover, these type of learning effects have also been observed for sour and bitter tastants too, resulting in odours that come to smell ‘sour’ and ‘bitter’, respectively (e.g. Stevenson et al., 1995; Yeomans, Mobini, Elliman, Walker, & Stevenson, in press). At present, the evidence favours the following conclusions, taste-like properties of smells share many characteristics in common with their real taste equivalents, and a ‘tasty’ smell may be acquired under laboratory conditions (see Small & Prescott, 2005; Small et al., 2004). If odours can acquire taste-like properties, it is important to explore the generality of this effect, namely whether they can acquire other flavour attributes too. This formed the basis for the present study, where we examined whether odours could acquire fat-like properties. Certain odours are reported to smell ‘fatty’. In Dravnieks’s (1985) Atlas of odor character profiles, several fattyrelated terms appear amongst the 146 descriptors provided for odour profiling. These include 118—oily, fatty, 119— buttery, fresh butter, 123—fried chicken, 127—rancid and 129—cheesy. In fact Dravnieks’ (1985) participants described several odours as being primarily characterised by their ‘oily, fatty’ smell, such as Decadienal (which smells
ARTICLE IN PRESS 92
N.C. Sundqvist et al. / Appetite 47 (2006) 91–99
like chicken fat where it occurs naturally), Heptanal (an oxidative product of milk) and Furfuryl mercaptan (from cooked meats). Similarly, Aldrich’s Flavors and Fragrances catalogue lists over 100 compounds with fatty attributes, including sub-types grouped under the headings; ‘Butterlike’, ‘Cheese’, ‘Creamy’ and ‘Oily’. The widespread use of the ‘fatty’ odour quality label is also reflected in attempts to generate lists of primary olfactory qualities, where a ‘Rancid/Fatty’ dimension is frequently included (see Table IX in Boelens, 1974). The perception of a fat-like quality in an odour does not of course imply that all fat-like smells arise from the type of simultaneous associations suggested for sweet smelling odours. Nonetheless, the apparent ubiquity of fat-like qualities suggests that this type of learning is at least plausible. Whilst the perceptual basis of tasted sucrose as ‘sweet’ is well understood and would not be widely disputed, there is still some controversy surrounding how we perceive fats as ‘fatty’. Fat perception appears to rely primarily upon textural cues, but a role for fatty taste receptors has also been suggested. The latter has not, however, been conclusively established in humans, whilst the former enjoys considerable empirical support (e.g. Drewnowski, 1993; Lermer & Mattes, 1999; Tittelbach & Mattes, 2001). Before briefly reviewing the nature of fat perception, it is important to bear in mind that if odour-fat learning occurs, the modalities involved in fat perception are those that can potentially form associations with odours. If fat perception is multimodal, or has multiple dimensions within one modality, then this raises a number of interesting possibilities that do not apply to odour-taste learning. Namely, that fatty attributes could be acquired either as a ‘whole’ or as an ‘element’ from a range of possible ‘elements’. The evidence favouring a textural account of fat perception is robust. Mela (1988) found that when olfactory and visual cues were eliminated, participants were able to detect differences in the fat content of a variety of liquid dairy products. The strongest line of support for a textural mechanism arises from the work of Rolls and colleagues (e.g. De Araujo & Rolls, 2004; Rolls, 2004; Verhagen, Rolls, & Kadohisa, 2003). Electrophysiological data reported by Rolls, Critchley, Browning, Hernadi, and Lenard (1999), suggests that fat is detected primarily by textural cues, as cells within the primate orbitofrontal cortex were found to respond not only to dietary fats, but also to texturally similar, non-dietary fats such as paraffin and silicone oil. Textural fat cues may consist of a number elements, including viscosity, fat globule quantity, and globule size, lubricity, cohesiveness and greasy mouthcoating properties (Richardson & Booth, 1993; Schiffman, Graham, Sattely-Miller, & Warwick, 1998). These properties are presumed to be mediated via a network of oral trigeminal nerves, tactile fibres, and mechanoreceptors, located in the gums, tongue and soft-palate (Schiffman, et al., 1998; Tepper & Nurse, 1997). Thus, although fat perception likely relies upon texture, the textural cues
themselves and the way they are detected, are probably multimodal and certainly multidimensional. In the present study our primary focus was on whether odours could acquire all or any fat-like properties. Our experimental design involved pairing four odours with four different fat/sucrose dairy mixtures (low- vs high-fat by unsweetened vs sweetened). A naturalistic fat medium of milk was chosen, as dairy products have featured in several important studies of fat perception (e.g. Drewnowski, 1993; Drewnowski & Greenwood, 1983; Mela, 1988; Richardson & Booth, 1993). In addition to manipulating fat-level, sweetness-level was also manipulated for two reasons. First, there is some evidence that sucrose potentiates fat perception, possibly by enhancing the viscosity of the stimulus (Drewnowski & Greenwood, 1983; Drewnowski, Henderson, & Barratt-Fornell, 1998; Salbe, DelParigi, Pratley, Drewnowski, & Tataranni, 2004). Second, we were also interested in whether both taste and fat-like properties could be acquired simultaneously. We tested for any change in odour ‘fat’ perception in two ways. The first test utilised odour attribute ratings (e.g. ‘fatty’, ‘sweet’) obtained prior to and post-conditioning. These have been employed successfully in this type of role before (e.g. Stevenson et al., 1998, 1995). The second method employed an enhancement test. If an odour has acquired a fat-like smell, or a sweet one for that matter, it should, when mixed with a slightly fatty (and sweet) stimulus, enhance the degree to which that stimulus is judged fatty (and sweet). Again, this type of test has been successfully deployed before to measure odour-taste learning (e.g. Prescott, Johnstone, & Francis, 2004) and to assay the perceptual similarity of ‘sweet’ smells and sweet tastes (e.g. Schifferstein & Verlegh, 1996). Moreover, there is evidence that fatty smells, such as those with butter and coconut notes, can enhance the textural properties of yoghurts (thickness), when compared to odours with green notes, suggesting that an enhancement test might offer a sensitive assay of any acquired fatty property (Saint-Eve, Kora, & Martin, 2004). In addition to the conditioning tests described above, we also assessed participants’ fattiness and sweetness ratings of the unodourised milk stimuli prior to and postconditioning. This was to ensure that the milk stimuli were indeed perceived as appropriately fatty and sweet. Participants were also asked to complete a pairing knowledge test to assess the degree to which they could explicitly recall what each target odour had been paired with. Finally, we included measures of both liking and individual differences (gender, dieting history and milk use), as the latter might impact upon conditioning. Method Participants Forty-two Macquarie University students participated for course credit. All initial recruits completed the first
ARTICLE IN PRESS N.C. Sundqvist et al. / Appetite 47 (2006) 91–99
session, but only 38 returned for the second. Of these 38, two had mean scores greater than 1.96 standard deviations below the sample mean on odour intensity ratings in the pre-test (i.e. the average of the four odour intensity scores in Session 1), indicating some difficulty in smelling the target odours. In addition, these two participants could not discriminate between low and high-fat milk, suggesting that they were either poorly motivated, or insensitive to the test variables (odour, fat) manipulated in this study. The data from these two participants was excluded from further analysis. This left 36 participants, of whom 13 were males and 23 females, of primarily Caucasian origin. Participants’ ages ranged from 17 to 39 years (M ¼ 20.3, SD ¼ 5.6). All participants could smell normally and reported that they were lactose tolerant. The presence of either lactose intolerance or respiratory infection were exclusion criteria and these were indicated in our recruitment advertisement. The study was approved by the Macquarie University Human Ethics Committee. Materials Milks Four milk types were prepared, consisting of two concentrations of fat, by two concentrations of sucrose: low-fat unsweetened milk—‘LFUN’ (0.1% fat, 0% sucrose), high-fat unsweetened milk—‘HFUN’ (10% fat, 0% sucrose), low-fat sweetened milk—‘LFSW’ (0.1% fat, 10% sucrose) and high-fat sweetened milk—‘HFSW’ (10% fat, 10% sucrose). The low-fat milk was composed of Dairy Farmers skimmed milk (0.1% fat), and the high-fat milk was prepared by mixing a combination of 80% Dairy Farmers full cream milk (3.6% fat content), with 20% Dairy Farmers pure cream (35% fat content). Each sample was prepared 1 day before testing began, stored in glass bottles, shaken by hand and refrigerated below 4 1C prior to testing. Samples were kept for a maximum of 3 days. All stimuli were presented in aliquots of 10 mL, within 22 mL transparent disposable plastic cups, and were filled 30 min prior to each experimental session. The stimuli were presented at room temperature under white light, in a well-ventilated room. Odours The odours employed here were: Lychee—‘LY’ (0.5 g/L in water; Quest), Water-chestnut—‘WC’ (0.2 g/L in water; Quest), Oolong tea—‘OT’ (0.6 g/L in water; Quest) and Red bean—‘RB’ (0.6 g/L in water; Quest). All odours were approximately matched for intensity, were visually indistinguishable, and were presented in clear, plastic, squeezable bottles, at room temperature. Conditioning stimuli—the milk–odour mixtures Based upon pre-pilot work we suspected that using the same concentration of target odourant in low and high-fat stimuli would result in participants being less able to perceive the odour in the high-fat condition. To further
93
check this we conducted a pilot study. The study had two aims. First, to test whether an odour mixed with high-fat milk was judged less intense than when added to a low-fat milk. Second, to determine the approximate quantities of the odourant needed to compensate for any suppression effect. Ten participants took part in the pilot, which revealed two key findings. First, an odour suppression effect was apparent, with the odour of samples containing a higher concentration of fat rated significantly less intense than those with a lower concentration of fat (Mdiff ¼ 19.2% [high–low]; t(9) ¼ 2.71, po0.025), for the same odourant concentration. Second, doubling the concentration of the odourant appeared to compensate for this effect. High-fat samples containing 1.0 g/L of the test odourant were not significantly different on rated intensity from low-fat samples with the test odourant at 0.5 g/L (Mdiff ¼ 2.9% [high–low]; to1). These findings suggested that doubling the concentrations of the odourants paired with high-fat would provide for similar odour intensity across fat-levels. Each target odour (LY, WC, OT and RB) was mixed with each of the four milk solutions (LFUN, HFUN, LFSW and HFSW), resulting in 16 combinations. Samples containing low-fat milk were combined with the following concentrations of odourant: LY—0.5 g/L, WC—0.2 g/L, OT—0.6 g/L and RB—0.6 g/L. These concentrations were doubled for samples containing high-fat milk. In addition, samples of white rice flour mixed with water, comprised the filler stimuli. These were intended to visually mimic the appearance of the milk samples, but provide a non-fat, non-sweet, unodourised break during conditioning, without drawing undue attention to the milk stimuli, which plain water samples might have done. All samples were stored and presented in the same manner as the milk samples described above. Enhancement test stimuli Four milk mixtures containing an intermediate level of fat (3.5%) and sucrose (2%) were produced from 90% Dairy Farmer’s skim milk (0.1% fat), to which 10% Dairy Farmers pure cream (35% fat) was added. To each of these mixtures, one of each of the four odourants was added at the same concentrations used for low-fat milk in the conditioning stimuli. Storage and presentation of the stimuli is as described above for the milk samples. Procedure Each participant attended two sessions, separated by a 1-week interval. The first session contained a pre-test for the milk and odour samples, as well as a conditioning phase. The second session contained another conditioning phase, followed by a post-test for the milk and odour samples, an enhancement test, a pairing knowledge test, and a short post-experimental questionnaire. Participants were tested in groups of 3 or 4, seated so as to minimise observation of other subjects. Stimulus sampling occurred
ARTICLE IN PRESS 94
N.C. Sundqvist et al. / Appetite 47 (2006) 91–99
at precisely the same time, with 30 s inter-stimulus intervals. Session 1 Session 1 began with a tasting of each of the four milk samples (Milk Pre-test), LFUN, HFUN, LFSW and HFSW. Participants were instructed to take the entire sample into their mouth, swirl it around for 3 s (timed by the experimenter’s stop-watch) and expectorate. This procedure was demonstrated by the experimenter, prior to testing. Participants were also requested not to comment verbally on samples. Presentation order was counterbalanced, so that each sample (i.e. LFUN, HFUN, LFSW, HFSW) occurred an equal number of times in the first, second, third and fourth position for a predicted sample size of 44. This was not affected by the effectively random reduction in participant numbers, as each sample was still presented an approximately equal number of times in each position. Sample position had no detectable effect on participants ratings when analysed. After tasting the first sample, participants completed their first rating sheet. This contained three 9-point category scales in the following order: Sweetness (anchors, ‘Not at all sweet’—1 to ‘Extremely Sweet’—9), Fattiness (anchors, ‘Not at all fatty’—1 to ‘Extremely fatty’—9) and Liking/Disliking (anchors, ‘Dislike extremely’—1 to ‘Like extremely’—9, plus a central marker, ‘Indifferent’—5). Participants then rinsed their mouths thoroughly with tap water. This procedure was repeated for the remaining three solutions. Participants then commenced the Odour Pre-test, which involved sniffing and rating each of the four target odours. Participants were instructed to hold the tip of the nozzle approximately 7 cm from their nose and to squeeze the bottle three times whilst sniffing. This was demonstrated by the experimenter, prior to testing. Each of the four odours, (LY, WC, OT and RB) were presented in counterbalanced order, with a 30 s inter-stimulus interval between each. Once again, counterbalancing was not significantly impacted by the loss of participants. During the interstimulus interval participants rated each odour for sweetness, fattiness and liking, on 9-point category scales, as described above. In addition, odour intensity was also assessed by asking participants, ‘How strong do you think this sample smells?’ (anchors, ‘Not at all strong’—1 to ‘Extremely strong’—9). The conditioning phase of the experiment then commenced. Participants were reminded of the correct sampling procedure prior to testing, as described for the milk samples above. They were then presented with a tray of 30 samples, comprised of 16 target trials and 14 filler trials (milk-coloured water). Each participant received four Odour A-LFUN samples, four Odour B-LFSW samples, four Odour C-HFUN samples and four Odour D-HFSW samples. Presentation order of all stimuli was random. Each series of odour-milk combinations (per participant) was drawn from a master set of fully counterbalanced
odour/fat/sucrose combinations. These were assigned to participants by order of arrival. For example, the first participant was given the following combination: LYLFSW, WC-HFSW, RB-LFUN and OT-HFUN, each presented four times. Samples were counterbalanced such that each odour appeared an equal number of times with each fat/sucrose combination, across participants. Counterbalancing was not adversely affected by the smallerthan-anticipated final sample size, that is each odour-tastefat combination occurred with approximately equal frequency. A 30 s inter-stimulus interval was maintained between all samples, during which participants circled their level of liking/disliking for each sample (‘Dislike’, ‘Indifferent’ and ‘Like’). The purpose of this task was to ensure that participants attended to the solutions and to provide some face validity for the sampling procedure. Session 2 Participants returned 1 week later for Session 2, which commenced with a further conditioning phase. This was identical to the first in all respects, except that only 15 samples were used. These were composed of two Odour A-LFUN samples, two Odour B-LFSW samples, two Odour C-HFUN samples and two Odour D-HFSW samples, as well as 7 filler trials. The post-test phase of the experiment then began. This started with the Milk Post-test, identical to the Pre-test, followed by the Odour Post-test, which was also identical to the Odour Pre-test. Participants then completed the Enhancement test, in which they received each of the target odours in a slightly sweetened and slightly fatty milk. The procedure for this test was identical to that of the Milk Pre/ Post-test, including the rating scales for Sweetness, Fattiness and Liking. This was then followed by the Pairing Knowledge Test. Here, participants smelled each of the four target odours again, presented in the same order, as in the Odour Pre/Post-test. After smelling each odour participants were asked, ‘Was this odour ever presented with: (a) A fatty milk, (b) Low-fat milk or (c) Unsure’. This was followed by a second question, ‘Was this odour ever presented with: (a) A lot of sugar, (b) No sugar or (c) Unsure’. Participants’ task was to circle one response for each question. Finally, a short post-experimental questionnaire was presented to participants. Responses provided information about participants’ age, gender, the type of milk typically drunk, and whether they were (or had recently been) dieting. Results Milk pre/post-test ratings The analyses described below tested whether the unodourised milk samples were, as we intended, perceived as appropriately fatty and sweet (see Table 1 for mean values on pre- and post-test). A three-way repeated measures
ARTICLE IN PRESS N.C. Sundqvist et al. / Appetite 47 (2006) 91–99
95
Table 1 Mean sweetness, fattiness and liking ratings for the milk-fat and sugar combinations alone (LFUN—low fat unsweetened; LFSW—low fat sweetened; HFUN—high fat sweetened; HFSW—high fat sweetened) on the milk pre- and post-test
Table 2 Mean sweetness, fattiness and liking ratings for the odours alone by condition (LFUN—low fat unsweetened; LFSW—low fat sweetened; HFUN—high fat sweetened; HFSW—high fat sweetened) on the odour pre- and post-test
Stimulus
Rating
Milk pre-test Mean (SD)
Milk post-test Mean (SD)
Stimulus
Rating
Odour pre-test Mean (SD)
Odour post-test Mean (SD)
LFUN
Sweetness Fattiness Liking
2.7 (1.5) 3.9 (2.1) 4.2 (1.8)
2.6 (1.5) 3.9 (1.9) 4.7 (1.4)
LFUN
Sweetness Fattiness Liking
4.5 (2.3) 3.8 (2.3) 4.1 (1.7)
5.0 (2.3) 3.6 (2.2) 4.0 (1.5)
LFSW
Sweetness Fattiness Liking
7.9 (1.1) 5.5 (1.7) 5.4 (2.1)
7.2 (1.5) 4.7 (1.7) 5.8 (1.9)
LFSW
Sweetness Fattiness Liking
5.5 (2.5) 3.4 (2.1) 4.7 (2.4)
5.9 (2.4) 4.4 (2.3) 4.5 (1.9)
HFUN
Sweetness Fattiness Liking
3.3 (2.0) 6.4 (1.7) 4.2 (1.9)
3.0 (1.6) 6.9 (1.7) 4.4 (1.9)
HFUN
Sweetness Fattiness Liking
5.3 (2.6) 3.4 (2.1) 4.7 (2.2)
6.2 (1.9) 4.3 (2.3) 4.4 (2.0)
HFSW
Sweetness Fattiness Liking
7.8 (1.0) 6.1 (1.6) 5.4 (2.0)
7.2 (1.3) 7.0 (1.4) 5.1 (2.3)
HFSW
Sweetness Fattiness Liking
5.6 (2.3) 3.5 (2.4) 4.4 (1.7)
6.9 (2.1) 4.4 (2.1) 3.9 (1.9)
ANOVA was conducted, with Fattiness ratings as the dependent variable, and with Time (pre- vs post-test), Fatlevel (low- vs high-fat) and Sweetness-level (unsweetened vs sweetened) as within-participant factors. This ANOVA revealed a main effect of Fat-level (F(1,35) ¼ 87.77, po0.001), with high-fat milks (HFUN and HFSW) rated as more fatty than low-fat milks (LFUN and LFSW). There was also a main effect of Sweetness-level (F(1,35) ¼ 5.64, po0.025), with sweetened milk rated significantly more fatty than unsweetened milk. These variables interacted (F(1,35) ¼ 11.86, po0.005), and as can be seen in Table 1, low-fat sweetened milk (LFSW) was judged as fattier than low-fat unsweetened milk (LFUN), with little difference in perceived fattiness for the high-fat sweetened (HFSW) and unsweetened (HFUN) milks. Finally, there was a significant interaction between Time and Fat-level (F(1,35) ¼ 11.52, po0.005), in that the fattiness ratings of low-fat milk decreased from pre to post-test, whereas the fattiness ratings of high-fat milk increased. Sweetness ratings were analysed using the same ANOVA design (see Table 1 for means). As expected, participants rated the sweetened milks (LFSW and HFSW) as sweeter than the unsweetened milks (F(1,35) ¼ 386.72, po0.001). There was also a main effect of Time (F(1,35) ¼ 7.58, po0.01), indicating that on average, milk was rated as sweeter in the pre-test than in the post-test. There were no other effects. Finally, liking ratings were analysed in the same way. Only the main effect of Sweetness-level was significant (F(1,35) ¼ 14.315, po0.005), with sweetened milks liked more than unsweetened milks (see Table 1). Odour pre/post-test ratings Mean values, on pre- and post-test for each of the key attributes (fattiness, sweetness and liking) are presented in
Table 2. Odour fattiness ratings were analysed using a three-way repeated measures ANOVA with Time (pre- vs post-test), Fat-level (low- vs high-fat) and Sweetness-level (unsweetened vs sweetened) as within-participant factors. The key finding from this analysis was a significant Time by Fat-level by Sweetness-level interaction (F(1,35) ¼ 5.06, po0.05). Odours paired with high-fat milks or with the sweetened low-fat milk, were judged to smell fattier on post-test than they did on pre-test. Importantly in this respect, there was little change in fattiness ratings for the odour paired with LFUN from pre- to post-test. These results provide support for our central hypothesis, that odours can acquire the fatty properties of foods they are associated with, and are complementary to the milk fattiness ratings, which revealed that milk was rated fattier when it contained either higher fat and/or low-fat with added sucrose. Finally, the ANOVA also revealed a main effect of Time (F(1,35) ¼ 11.42, po0.005), but this was of little interest given the interaction reported above. There were no other significant effects. Odour sweetness ratings were analysed in the same way. The ANOVA revealed only a main effect of Time (F(1,35) ¼ 5.26, po0.05) with the sweetness ratings of all odourants increasing from pre- to post-test (see Table 2). There was, therefore, no indication of any differential conditioning effect here for sweetness. Odour intensity ratings were also analysed in the same manner as described above. The only significant effect here was a Time by Fat-level interaction (F(1,35) ¼ 13.71, po0.005). This suggested that intensity ratings for odours paired with high-fat milks tended to increase from pre-test (M ¼ 6.1) to post-test (M ¼ 6.7), whilst odours paired with low-fat milk, tended to decrease in intensity from pre-test (M ¼ 6.5) to post-test (M ¼ 6.3). These results were of interest as all test odours were presented at a uniform concentration on the pre- and post-tests, however the
ARTICLE IN PRESS N.C. Sundqvist et al. / Appetite 47 (2006) 91–99
odours paired with high-fat milk in the conditioning phase had been presented at a higher concentration, than those paired with low-fat milk. Finally, odour hedonic ratings were also analysed in the same manner, but there were no significant effects (see Table 2 for means). Enhancement test Fattiness ratings obtained in the Enhancement test were analysed with a two-way repeated measures ANOVA, with Fat-pairing (low- vs high-fat) and Sweetness-pairing (sweetened vs unsweetened) as within-subject factors. The ANOVA revealed a main effect of Fat-pairing (F(1,35) ¼ 4.47, po0.05), indicating that milk containing an odour originally paired with high-fat, was rated fattier on average in the Enhancement test, than the same milk containing an odour originally paired with low-fat (see Fig. 1). There were no other significant effects. Sweetness ratings were analysed in the same manner. This ANOVA revealed a main effect of Sweetness-pairing (F(1,35) ¼ 9.58, po0.005). Milk containing an odour originally paired with sucrose, was rated as sweeter in the Enhancement test, than the same milk containing an odour which had not been paired with sucrose (see Fig. 2). There were no other significant effects. Finally, liking ratings were analysed in the same way, however there were no significant effects. Pairing knowledge test For each of the four odours, participants were asked to identify whether it had been paired with fat and sucrose. Three measures were derived from these scores in an attempt to assess participants’ overt knowledge about the pairing history of each odour. The first variable was a measure of participants’ ‘Fat Knowledge’. Here, partici9 8
Low-fat paired odours High-fat paired odours
Rated Fattiness
7 6 5 4 3 2 1 None sucrose paired odours
Sucrose paired odours
Fig. 1. Mean fattiness ratings (and SE) on the enhancement test where each of the four target odours were presented in the same milk stimulus.
9 Low-fat paired odours High-fat paired odours
8 7 Rated Sweetness
96
6 5 4 3 2 1 None sucrose paired odours
Sucrose paired odours
Fig. 2. Mean sweetness ratings (and SE) on the enhancement test where each of the four target odours were presented in the same milk stimulus.
pants received a score of ‘1’ if they chose the correct level of fat that had been paired with that odour, and a score of ‘0’ if they were either incorrect or unsure. The second variable was a measure of participants ‘Sweetness Knowledge’. Here, the same criterion was used, a score of ‘1’ for correctly identifying that an odour had or had not been paired with sucrose, and a score of ‘0’ for incorrect or unsure responses. The third variable ‘Net knowledge’, assessed whether participants were correct in both their judgement of Fat- and Sweetness-level for each particular odour. A score of ‘1’ was returned if they had the correct choice on both fattiness and sweetness. All other responses were scored ‘0’. Thus a perfect score would be 4/4 for Fat Knowledge, 4/4 for Sweetness Knowledge and 4/4 for Net Knowledge. As can be seen in Table 3, most participants had some level of Fat Knowledge and some level of Sweetness Knowledge, but Net Knowledge was rather poor. To ascertain whether knowledge of the odours’ reinforcement history impacted upon learning, we calculated three measures of conditioning based upon the significant effects obtained in this experiment (i.e. Odour Fattiness [from the three-way interaction of Time by Sweetnesslevel by Fat-level in the Odour Pre/post-test], Fattiness enhancement [from the main effect of Fat-pairing in the Enhancement test] and Sweetness enhancement [from the main effect of Sweetness-pairing in the Enhancement test]). The fat-related learning effects were then correlated with the Fat Knowledge score and the Net Knowledge score and all four Pearsons correlations were non-significant (r’so0.15, critical r ¼ 0.33, a ¼ 0.05). The sweetness-related learning effect was then correlated with the Sweetness Knowledge score and the Net Knowledge score. Both Pearsons correlations were again non-significant (r’so0.21, critical r ¼ 0.33, a ¼ 0.05).
ARTICLE IN PRESS N.C. Sundqvist et al. / Appetite 47 (2006) 91–99 Table 3 Results from the pairing knowledge test showing the number of participants correctly identifying the pairing history of the odour stimuli Number of odours correctly identified
0 1 2 3 4
Fat Knowledge n
Sweet Knowledge n
Net Knowledge n
(%) ¼
(%) ¼
(%) ¼
3 9 11 11 2
2 7 14 10 3
13 12 9 2 0
(8.3) (25.0) (30.6) (30.6) (5.6)
(5.6) (19.4) (38.9) (27.8) (8.3)
(36.1) (33.3) (25.0) (5.6) (0.0)
Individual differences Individual differences in milk use and dieting might all potentially impact upon participants’ evaluations of the stimuli used in this experiment. The questionnaire completed at the end of the experimental session revealed that milk usage did indeed differ across the sample. Seventeen participants reported typically using full-cream milk in their daily diet, two participants used no milk at all, six reported using skim milk, ten used lite milk and one participant used soy milk. As for dieting, five participants were currently dieting and 14 participants were either currently dieting or had dieted within the last 6 months. Of these 14, 11 had consciously reduced sugar in their diet, and 13 in fat. In order to determine whether there were any consistent effects of milk usage, dieting or gender, a series of exploratory post hoc analyses were conducted, using; current dieting status (dieters vs non-dieters), dieting status within the previous 6 months (dieters vs non-dieters), milk use (full cream milk drinkers vs all other groups) and gender (males vs females), as between-subject factors. Each of the fattiness, sweetness and liking ANOVAs described above were repeated with each of the between-subject factors included sequentially. Alpha was set at 0.01 in an attempt to minimise Type 1 errors. There were no differences in fattiness, sweetness or liking ratings across the milk, odour or enhancement test analyses for the dieters, different types of milk drinkers or by gender. Discussion The primary aim of this experiment was to determine whether odours could acquire ‘fat-like’ properties. The odour pre/post-test revealed that odours paired with either high- or low-fat and sucrose, were subsequently rated fattier on post-test than odours paired with low-fat and no sucrose. In the Enhancement test, however, only milks containing the odourants previously paired with high-fat were rated fattier. In terms of sweetness learning, no evidence was obtained on the odour pre/post-test. In the Enhancement test, however, milk containing an odour previously paired with sucrose was rated sweeter than milk
97
containing an odour previously paired with no sucrose. For all these findings, there was no significant association with what participants reportedly knew about the reinforcement history of the odours, suggesting that demand had not played a significant role in these results. Notwithstanding the interesting difference in test results, the current experiment provides suggestive evidence that odour-fat associations may be learnt and that this may occur in conjunction with odour-sweetness learning. We start by presenting our take on these results and then describe a number of problems which future attempts to explore this phenomenon will need to grapple with. It was suggested in the Introduction that if odour-fat learning arose, it would be the result of odour-texture associations, as fat appears to be perceived primarily through its textural attributes (e.g. Mela, 1988). Support for a textural account was provided in the present experiment in two ways. First, LFSW was rated significantly more ‘fatty’ than LFUN. Similar findings have been made by other researchers, who have found that sucrose can increase the viscosity of a low-fat milk, thus enhancing perceptions of fat (Drewnowski & Greenwood, 1983; Drewnowski et al., 1998; Salbe, et al., 2004). Second, on the odour pre/post-test, the odours paired with milks judged to be fattier (i.e. high-fat milks and the sweetened low-fat milk) were judged as fattier smelling. At least on this test, it would imply that the odours may have become associated with the viscous properties of the stimulus, leading to the enhanced fattiness ratings for these three odours. Although the odour pre/post-test data nicely aligns itself with the fattiness ratings obtained for the milk stimuli, the Enhancement test data present a rather different picture. Two puzzling features stand out. First, the presence of a sweetness conditioning effect here (given its absence on the odour pre/post-test). Second, the absence, of a fattyenhancement effect for the odour paired with sweetened low-fat milk (given its presence on the odour pre/post-test). A rather straightforward answer can be suggested for the sweetness result. The enhancement test is contextually much closer to the conditions of learning than the odour pre/post-test. On the Enhancement test, stimuli were presented in milk and sampled by mouth, just as they were during conditioning. This might be akin to ‘transferappropriate processing’, in that only the more similar context allowed for effective retrieval of the odour-taste memory, making this a more sensitive test of learning. Needless to say, we have detected odour-taste learning on odour pre/post-tests before, but this is the first attempt under conditions where other related sensory features were present during conditioning. One major problem with this account is that if the Enhancement test really did offer a more sensitive medium in which to recover experiences acquired during learning, why was the fatty conditioning effect obtained for the lowfat sweetened stimulus on the odour pre/post-test, absent? One possibility is that the measurement scale attributes
ARTICLE IN PRESS 98
N.C. Sundqvist et al. / Appetite 47 (2006) 91–99
(sweet and fatty) are far better defined in the Enhancement test than they are in the odour pre/post-test. In the Enhancement test the stimulus really is sweet and fatty, providing concrete definitions of the stimulus attributes. As fattiness is potentially defined by several textural properties (see Introduction), and some of these may have been absent within the LFUN, this may have resulted in an enhancement effect for only the high-fat paired odours, which may have acquired a relatively greater perceptual similarity to fat (i.e. a greater number of fat-like attributes). Thus, one might speculate whether the odour paired with LFSN acquired a fatty characteristic related to viscosity, whilst the odours paired with high-fat milks acquired a broader range of fatty characteristics. Not surprisingly, given that this is the first study to examine odour-fat associations, little is known about the neural mechanisms which might underpin it. Research conducted by Rolls and his colleagues (e.g. Rolls & Baylis, 1994; Rolls, et al., 1999) does, however, provide some clues. Multimodal neurons have been found within the orbitofrontal cortex which respond to a variety of sensory inputs (Rolls & Baylis, 1994). It is plausible that odour and fat inputs converge here to form new associations, which are learnt through repeated presentation during eating or drinking. On the basis of procedural similarity with odourtaste learning, and due to the finding that odour and taste information also converges in the orbitofrontal cortex, we suggest that odour-taste and -fat learning may share a similar explanation. Namely, that olfactory, tactile and other fat-related inputs are stored as a configuration (or unitary percept), which is recovered when the odour is encountered again. Consistent with the account above is the finding that participants’ explicit knowledge was unrelated to performance. This has been noted repeatedly in the odour-taste literature and we have argued that it relates directly to both the simultaneous nature of presentation and to the configural encoding of flavour stimuli (Stevenson & Boakes, 2004). However, we would like to stress that our test of pairing knowledge was both rudimentary and performed at the end of the experiment, factors likely to make it less sensitive to any explicit knowledge held by participants. It was rudimentary by necessity, as we could not reasonably expect participants to sample more of the dairy mixtures, which many of them found unpalatable. It was performed at the end of the experiment, as we felt that our primary variables of interest (i.e. the conditioning measures) needed to be assessed first. Clearly, this is an issue which warrants further investigation. So far we have taken our results at face value. The study set out to explore odour-fat learning and produced findings that were generally consistent with our expectations. However, the review process revealed a dissenting opinion about the merits of our conclusions and we feel these issues require serious consideration. The first point of concern is that when making odour-fattiness ratings, participants may not be sure what they are rating. One remedy would be to
include a standard fatty odour to compare the targets to. The effect this might have on our experiment is hard to gauge. The worse case scenario might be that participants relied upon explicit knowledge to make their ratings, but we did not detect any such effect. This, though may have arisen because of a second concern, that the measures of awareness lacked sufficient sensitivity. As we noted above, our measure of awareness was less than ideal—it occurred at the end of the experiment and did not use contextually identical stimuli. A more potent test would need to examine contingency awareness earlier on and using a more sensitive test. Nonetheless, any subsequent failure to detect awareness could still be counted as inadequate test sensitivity. A third concern relates to the failure to detect a sweetness effect on the odour pre/post-test. One possibility is that halo-dumping occurred in this experiment. That is participants attributed ‘sweetness’ to the ‘fattiness’ dimension of the scale, resulting in the apparent absence of an effect. This explanation, although plausible, does not explain why sweetness would be dumped into fattiness ratings (learning?), nor why this only occurred in the odour pre/post-test and not in the enhancement test. Finally, no statement can be made about the psychological magnitude of any putative conditioning effect, because of the type of scales that were used here. Future studies would probably be well advised to use magnitude estimation or some other direct scaling approach. Although we did not have high expectations of finding any conditioned changes in liking, we were surprised by participants’ general indifference, or in some cases, active dislike of fattier milks. Drewnowski and Greenwood (1983), for example, reported that higher fat milk was preferred to low-fat milk. Two factors may account for this. First, fats have, more recently, been linked in the public mind to high rates of obesity (Drewnowski & Schwartz, 1990). They have also been widely vilified in the popular press (Mattes, 2003; Taubes, 2001). Second, the rather unnatural laboratory setting may have led participants to treat all stimuli with some circumspection. In combination, these two factors may have led to a more negative appraisal of our high-fat stimuli when compared to earlier studies. Finally, we obtained one further result that warrants comment in the light of our interest in associative learning as it relates to flavour perception and olfaction. Participants received a higher concentration of the target odourants when they were mixed with high-fat stimuli, to compensate for the potential suppressive effect that fats have on the perception of volatile compounds. On test, the odours previously paired with high-fat stimuli were found to smell more intense than the odours previously paired with low-fat stimuli. This effect was not an artefact of the test odours, because these odours were appropriately counterbalanced, and the result was only apparent on the post-test, not the pre-test, suggesting that the conditioning phase was in some way responsible. One might be tempted to suggest that this effect arose from the judgemental
ARTICLE IN PRESS N.C. Sundqvist et al. / Appetite 47 (2006) 91–99
context. If this were the case, however, we would have expected the odours originally presented at a higher concentration to be judged as weaker (i.e. contrast effect), and this was not the case. A further and more intriguing possibility is that the effect was the result of learning. If participants found the higher concentration of odours in the high-fat stimuli somewhat stronger, this could have been encoded alongside other sensory information. Thus on test, and that when the odours were encountered at a lower concentration, the original ‘smell’ could have been recovered from memory—thus being experienced as somewhat more intense. This finding may share some similarity to the observation of a positive association between familiarity and intensity, a presumed effect of the retention of familiar odours in memory (e.g. Ayabe-Kanamura et al., 1998). In conclusion, this study provides preliminary evidence that odours can indeed acquire the perceived fatty properties of foods they are associated with. This would suggest that the phenomenon of cross-modal learning related to flavour is probably not restricted to just odours and tastes, but may extend more broadly into other sensory domains. Acknowledgements We would like to thank Fumi Asai and Mehmet Mahmut for their assistance with these experiments. This research was assisted by a grant from the Australian Research Council. References Ayabe-Kanamura, S., Schicker, I., Laska, M., Hudson, R., Distel, H., Kobayakawa, T., et al. (1998). Differences in perception of everyday odors: A Japanese–German cross cultural study. Chemical Senses, 23, 31–38. Boelens, H. (1974). Relationship between the chemical structure of compounds and their olfactive properties. Cosmetics and Perfumery, 89, 70–89. Dalton, P., Doolittle, N., Nagata, H., & Breslin, P. (2000). The merging of the senses: Integration of subthreshold taste and smell. Nature Neuroscience, 3, 431–432. De Araujo, I. E., & Rolls, E. T. (2004). Representation in the human brain of food texture and oral fat. The Journal of Neuroscience, 24, 3086–3093. Dravnieks, A. (1985). Atlas of odor character profiles. ASTM Data series DS61. ASTM Publishers: Philadelphia. Drewnowski, A. (1993). Individual differences in sensory preferences for fat in model sweet dairy products. Acta Psychologica, 84, 103–110. Drewnowski, A., & Greenwood, M. R. C. (1983). Cream and sugar: Human preferences for high-fat foods. Physiology and Behavior, 30, 629–633. Drewnowski, A., Henderson, S. A., & Barratt-Fornell, A. (1998). Genetic sensitivity to 6-n-propylthiouracil and sensory responses to sugar and fat mixes. Physiology and Behavior, 63, 771–777. Drewnowski, A., & Schwartz, M. (1990). Invisible fats: Sensory assessment of sugar/fat mixtures. Appetite, 14, 203–217. Frank, R. A., & Byram, J. (1988). Taste-smell interactions are tastant and odorant dependent. Chemical Senses, 13, 445–455. Lawless, H. T. (1996). Flavor. In M. P. Friedman, & E. C. Carterette (Eds.), Handbook of perception, Vol. 16, Cognitive ecology (pp. 325–380). California: A.P. San Diego.
99
Lermer, C. M., & Mattes, R. D. (1999). Perception of dietary fat: Ingestive and metabolic implications. Progress in Lipid Research, 38, 117–128. Mattes, R. D. (2003). Fat: The sixth taste—Implications for health. Food Australia, 55, 510–514. Mela, D. J. (1988). Sensory assessment of fat content in fluid dairy products. Appetite, 10, 37–44. Prescott, J., Johnstone, V., & Francis, J. (2004). Odor/taste interactions: Effects of different attentional strategies during exposure. Chemical Senses, 29, 331–340. Richardson, N. J., & Booth, D. A. (1993). Multiple physical patterns in judgments of the creamy texture of milks and creams. Acta Psychologica, 84, 93–101. Rolls, E. T. (2004). The functions of the orbitofrontal cortex. Brain and Cognition, 55, 11–29. Rolls, E. T., & Baylis, L. L. (1994). Gustatory, olfactory, and visual convergence within the primate orbitofrontal cortex. The Journal of Neuroscience, 14, 5437–5452. Rolls, E. T., Critchley, H. D., Browning, A. S., Hernadi, I., & Lenard, L. (1999). Responses to the sensory properties of fat of neurons in the primate orbitofrontal cortex. The Journal of Neuroscience, 19, 1532–1540. Saint-Eve, A., Kora, E. P., & Martin, N. (2004). Impact of the olfactory quality and chemical complexity of the flavouring agent on the texture of low fat stirred yoghurts assessed by three different sensory methodologies. Food Quality and Preference, 15, 655–668. Salbe, A. D., DelParigi, A., Pratley, R. E., Drewnowski, A., & Tataranni, A. (2004). Taste preferences and body weight changes in an obesityprone population. American Journal of Clinical Nutrition, 79, 372–378. Schiffman, S. S., Graham, B. G., Sattely-Miller, E. A., & Warwick, Z. S. (1998). Orosensory perception of dietary fat. Current Directions in Psychological Science, 7, 137–143. Schifferstein, H. N. J., & Verlegh, P. W. (1996). The role of congruency and pleasantness in odor-induced taste enhancement. Acta Psychologica, 94, 87–105. Small, D. M., & Prescott, J. (2005). Odor/taste integration and the perception of flavor. Experimental Brain Research, 166, 345–357. Small, D. M., Voss, J., Mak, Y. E., Simmons, K. B., Parrish, T., & Gitelman, D. (2004). Experience dependent neural integration of taste and smell in the human brain. Journal of Neurophysiology, 92, 1892–1903. Stevenson, R. J., & Boakes, R. A. (2004). Sweet and sour smells: Learned synesthesia between the senses of taste and smell. In G. Calvert, C. Spence, & B. Stein (Eds.), The handbook of multisensory processes (pp. 69–83). Cambridge, MA: MIT Press. Stevenson, R. J., Boakes, R. A., & Prescott, J. (1998). Changes in odor sweetness resulting from implicit learning of a simultaneous odorsweetness association: An example of learned synesthesia. Learning and Motivation, 29, 113–132. Stevenson, R. J., Prescott, J., & Boakes, R. A. (1995). The acquisition of taste properties by odors. Learning and Motivation, 26, 433–455. Stevenson, R. J., Prescott, J., & Boakes, R. A. (1999). Confusing tastes and smells: How odors can influence the perception of sweet and sour tastes. Chemical Senses, 24, 627–635. Taubes, G. (2001). Nutrition: The soft science of dietary fat. Science, 291, 2536–2545. Tepper, B. J., & Nurse, R. J. (1997). Fat perception is related to PROP taster status. Physiology and Behavior, 61, 949–954. Tittelbach, T. J., & Mattes, R. D. (2001). Oral stimulation influences postprandial triacylglycerol concentrations in humans: Nutrient specificity. Journal of the American College of Nutrition, 20, 485–493. Verhagen, J. V., Rolls, E. T., & Kadohisa, M. (2003). Neurons in the primate orbitofrontal cortex respond to fat texture independently of viscosity. Journal of Neurophysiology, 90, 1514–1525. Yeomans, M. R., Mobini, S., Elliman, T., Walker, H. C., & Stevenson, R. J., (in press). Hedonic and sensory characteristics of odors conditioned by pairing with tastants. Journal of Experimental Psychology: Animal Behavior Processes, (accepted 19/12/05).
Appetite 47 (2006) 91–99 www.elsevier.com/locate/appet
Research report
Can odours acquire fat-like properties? Nina C. Sundqvist, Richard J. Stevenson, Ian R.J. Bishop Department of Psychology, Macquarie University, Sydney, NSW 2109, Australia Received 25 November 2005; received in revised form 20 March 2006; accepted 20 March 2006
Abstract Odours can acquire taste-like properties via simultaneous pairing in the mouth with tastants like sucrose. The experiment reported here sought to test whether qualities other than taste may also be acquired. Participants received pairings between odour A and low-fat unsweetened milk (LFUN), odour B and low-fat sweetened milk (LFSW), odour C and high-fat unsweetened milk (HFUN) and odour D and high-fat sweetened milk (HFSW). On test, participants reported that odours paired with milks perceived as being fattier (i.e. LFSW, HFUN, HFSW) were judged to smell fattier than they did prior to conditioning. In a further test, participants were asked to sample each of the four odours in a slightly fatty-sweet milk target. Odours previously paired with high-fat milks enhanced perceived fattiness of the target, whilst odours previously paired with sweetened milks enhanced perceived sweetness. These results were not well accounted for by participants’ explicit knowledge of the odour-milk pairings and suggest that fat-like qualities may be acquired. r 2006 Elsevier Ltd. All rights reserved. Keywords: Odour; Associative learning; Cross-modal learning; Flavour
Introduction Flavour perception involves interactions between taste, tactile, trigeminal and olfactory senses (Lawless, 1996; Small & Prescott, 2005). One consequence of these interactions is that they can produce long-lasting changes in the way that the flavour’s elements are perceived (Stevenson, Prescott, & Boakes, 1995). The most wellexplored example of this, is that between taste and smell. Odours that have been repeatedly presented with sweet tastes by mouth, such as vanilla in ice-cream, strawberry in jam or chocolate in cake, are commonly described as ‘sweet’ smelling. This perceived sweetness does not result from any direct effect of such odours on taste receptors (e.g. Stevenson, Prescott, & Boakes, 1999), rather it reflects a central process which appears to be based upon simultaneous associations between the taste and the smell (Stevenson & Boakes, 2004). A considerable amount of research has explored both whether odour ‘sweetness’ is perceptually akin to tasted sweetness (e.g. Dalton, Doolittle, Nagata, & Breslin, 2000; Frank & Byram, Corresponding author. Tel.: +61 2 9850 8098; fax: +61 2 9850 8062.
E-mail address: [email protected] (R.J. Stevenson). 0195-6663/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.appet.2006.03.328
1988) and whether such relationships can be acquired in the laboratory (e.g. Stevenson, Boakes, & Prescott, 1998). Moreover, these type of learning effects have also been observed for sour and bitter tastants too, resulting in odours that come to smell ‘sour’ and ‘bitter’, respectively (e.g. Stevenson et al., 1995; Yeomans, Mobini, Elliman, Walker, & Stevenson, in press). At present, the evidence favours the following conclusions, taste-like properties of smells share many characteristics in common with their real taste equivalents, and a ‘tasty’ smell may be acquired under laboratory conditions (see Small & Prescott, 2005; Small et al., 2004). If odours can acquire taste-like properties, it is important to explore the generality of this effect, namely whether they can acquire other flavour attributes too. This formed the basis for the present study, where we examined whether odours could acquire fat-like properties. Certain odours are reported to smell ‘fatty’. In Dravnieks’s (1985) Atlas of odor character profiles, several fattyrelated terms appear amongst the 146 descriptors provided for odour profiling. These include 118—oily, fatty, 119— buttery, fresh butter, 123—fried chicken, 127—rancid and 129—cheesy. In fact Dravnieks’ (1985) participants described several odours as being primarily characterised by their ‘oily, fatty’ smell, such as Decadienal (which smells
ARTICLE IN PRESS 92
N.C. Sundqvist et al. / Appetite 47 (2006) 91–99
like chicken fat where it occurs naturally), Heptanal (an oxidative product of milk) and Furfuryl mercaptan (from cooked meats). Similarly, Aldrich’s Flavors and Fragrances catalogue lists over 100 compounds with fatty attributes, including sub-types grouped under the headings; ‘Butterlike’, ‘Cheese’, ‘Creamy’ and ‘Oily’. The widespread use of the ‘fatty’ odour quality label is also reflected in attempts to generate lists of primary olfactory qualities, where a ‘Rancid/Fatty’ dimension is frequently included (see Table IX in Boelens, 1974). The perception of a fat-like quality in an odour does not of course imply that all fat-like smells arise from the type of simultaneous associations suggested for sweet smelling odours. Nonetheless, the apparent ubiquity of fat-like qualities suggests that this type of learning is at least plausible. Whilst the perceptual basis of tasted sucrose as ‘sweet’ is well understood and would not be widely disputed, there is still some controversy surrounding how we perceive fats as ‘fatty’. Fat perception appears to rely primarily upon textural cues, but a role for fatty taste receptors has also been suggested. The latter has not, however, been conclusively established in humans, whilst the former enjoys considerable empirical support (e.g. Drewnowski, 1993; Lermer & Mattes, 1999; Tittelbach & Mattes, 2001). Before briefly reviewing the nature of fat perception, it is important to bear in mind that if odour-fat learning occurs, the modalities involved in fat perception are those that can potentially form associations with odours. If fat perception is multimodal, or has multiple dimensions within one modality, then this raises a number of interesting possibilities that do not apply to odour-taste learning. Namely, that fatty attributes could be acquired either as a ‘whole’ or as an ‘element’ from a range of possible ‘elements’. The evidence favouring a textural account of fat perception is robust. Mela (1988) found that when olfactory and visual cues were eliminated, participants were able to detect differences in the fat content of a variety of liquid dairy products. The strongest line of support for a textural mechanism arises from the work of Rolls and colleagues (e.g. De Araujo & Rolls, 2004; Rolls, 2004; Verhagen, Rolls, & Kadohisa, 2003). Electrophysiological data reported by Rolls, Critchley, Browning, Hernadi, and Lenard (1999), suggests that fat is detected primarily by textural cues, as cells within the primate orbitofrontal cortex were found to respond not only to dietary fats, but also to texturally similar, non-dietary fats such as paraffin and silicone oil. Textural fat cues may consist of a number elements, including viscosity, fat globule quantity, and globule size, lubricity, cohesiveness and greasy mouthcoating properties (Richardson & Booth, 1993; Schiffman, Graham, Sattely-Miller, & Warwick, 1998). These properties are presumed to be mediated via a network of oral trigeminal nerves, tactile fibres, and mechanoreceptors, located in the gums, tongue and soft-palate (Schiffman, et al., 1998; Tepper & Nurse, 1997). Thus, although fat perception likely relies upon texture, the textural cues
themselves and the way they are detected, are probably multimodal and certainly multidimensional. In the present study our primary focus was on whether odours could acquire all or any fat-like properties. Our experimental design involved pairing four odours with four different fat/sucrose dairy mixtures (low- vs high-fat by unsweetened vs sweetened). A naturalistic fat medium of milk was chosen, as dairy products have featured in several important studies of fat perception (e.g. Drewnowski, 1993; Drewnowski & Greenwood, 1983; Mela, 1988; Richardson & Booth, 1993). In addition to manipulating fat-level, sweetness-level was also manipulated for two reasons. First, there is some evidence that sucrose potentiates fat perception, possibly by enhancing the viscosity of the stimulus (Drewnowski & Greenwood, 1983; Drewnowski, Henderson, & Barratt-Fornell, 1998; Salbe, DelParigi, Pratley, Drewnowski, & Tataranni, 2004). Second, we were also interested in whether both taste and fat-like properties could be acquired simultaneously. We tested for any change in odour ‘fat’ perception in two ways. The first test utilised odour attribute ratings (e.g. ‘fatty’, ‘sweet’) obtained prior to and post-conditioning. These have been employed successfully in this type of role before (e.g. Stevenson et al., 1998, 1995). The second method employed an enhancement test. If an odour has acquired a fat-like smell, or a sweet one for that matter, it should, when mixed with a slightly fatty (and sweet) stimulus, enhance the degree to which that stimulus is judged fatty (and sweet). Again, this type of test has been successfully deployed before to measure odour-taste learning (e.g. Prescott, Johnstone, & Francis, 2004) and to assay the perceptual similarity of ‘sweet’ smells and sweet tastes (e.g. Schifferstein & Verlegh, 1996). Moreover, there is evidence that fatty smells, such as those with butter and coconut notes, can enhance the textural properties of yoghurts (thickness), when compared to odours with green notes, suggesting that an enhancement test might offer a sensitive assay of any acquired fatty property (Saint-Eve, Kora, & Martin, 2004). In addition to the conditioning tests described above, we also assessed participants’ fattiness and sweetness ratings of the unodourised milk stimuli prior to and postconditioning. This was to ensure that the milk stimuli were indeed perceived as appropriately fatty and sweet. Participants were also asked to complete a pairing knowledge test to assess the degree to which they could explicitly recall what each target odour had been paired with. Finally, we included measures of both liking and individual differences (gender, dieting history and milk use), as the latter might impact upon conditioning. Method Participants Forty-two Macquarie University students participated for course credit. All initial recruits completed the first
ARTICLE IN PRESS N.C. Sundqvist et al. / Appetite 47 (2006) 91–99
session, but only 38 returned for the second. Of these 38, two had mean scores greater than 1.96 standard deviations below the sample mean on odour intensity ratings in the pre-test (i.e. the average of the four odour intensity scores in Session 1), indicating some difficulty in smelling the target odours. In addition, these two participants could not discriminate between low and high-fat milk, suggesting that they were either poorly motivated, or insensitive to the test variables (odour, fat) manipulated in this study. The data from these two participants was excluded from further analysis. This left 36 participants, of whom 13 were males and 23 females, of primarily Caucasian origin. Participants’ ages ranged from 17 to 39 years (M ¼ 20.3, SD ¼ 5.6). All participants could smell normally and reported that they were lactose tolerant. The presence of either lactose intolerance or respiratory infection were exclusion criteria and these were indicated in our recruitment advertisement. The study was approved by the Macquarie University Human Ethics Committee. Materials Milks Four milk types were prepared, consisting of two concentrations of fat, by two concentrations of sucrose: low-fat unsweetened milk—‘LFUN’ (0.1% fat, 0% sucrose), high-fat unsweetened milk—‘HFUN’ (10% fat, 0% sucrose), low-fat sweetened milk—‘LFSW’ (0.1% fat, 10% sucrose) and high-fat sweetened milk—‘HFSW’ (10% fat, 10% sucrose). The low-fat milk was composed of Dairy Farmers skimmed milk (0.1% fat), and the high-fat milk was prepared by mixing a combination of 80% Dairy Farmers full cream milk (3.6% fat content), with 20% Dairy Farmers pure cream (35% fat content). Each sample was prepared 1 day before testing began, stored in glass bottles, shaken by hand and refrigerated below 4 1C prior to testing. Samples were kept for a maximum of 3 days. All stimuli were presented in aliquots of 10 mL, within 22 mL transparent disposable plastic cups, and were filled 30 min prior to each experimental session. The stimuli were presented at room temperature under white light, in a well-ventilated room. Odours The odours employed here were: Lychee—‘LY’ (0.5 g/L in water; Quest), Water-chestnut—‘WC’ (0.2 g/L in water; Quest), Oolong tea—‘OT’ (0.6 g/L in water; Quest) and Red bean—‘RB’ (0.6 g/L in water; Quest). All odours were approximately matched for intensity, were visually indistinguishable, and were presented in clear, plastic, squeezable bottles, at room temperature. Conditioning stimuli—the milk–odour mixtures Based upon pre-pilot work we suspected that using the same concentration of target odourant in low and high-fat stimuli would result in participants being less able to perceive the odour in the high-fat condition. To further
93
check this we conducted a pilot study. The study had two aims. First, to test whether an odour mixed with high-fat milk was judged less intense than when added to a low-fat milk. Second, to determine the approximate quantities of the odourant needed to compensate for any suppression effect. Ten participants took part in the pilot, which revealed two key findings. First, an odour suppression effect was apparent, with the odour of samples containing a higher concentration of fat rated significantly less intense than those with a lower concentration of fat (Mdiff ¼ 19.2% [high–low]; t(9) ¼ 2.71, po0.025), for the same odourant concentration. Second, doubling the concentration of the odourant appeared to compensate for this effect. High-fat samples containing 1.0 g/L of the test odourant were not significantly different on rated intensity from low-fat samples with the test odourant at 0.5 g/L (Mdiff ¼ 2.9% [high–low]; to1). These findings suggested that doubling the concentrations of the odourants paired with high-fat would provide for similar odour intensity across fat-levels. Each target odour (LY, WC, OT and RB) was mixed with each of the four milk solutions (LFUN, HFUN, LFSW and HFSW), resulting in 16 combinations. Samples containing low-fat milk were combined with the following concentrations of odourant: LY—0.5 g/L, WC—0.2 g/L, OT—0.6 g/L and RB—0.6 g/L. These concentrations were doubled for samples containing high-fat milk. In addition, samples of white rice flour mixed with water, comprised the filler stimuli. These were intended to visually mimic the appearance of the milk samples, but provide a non-fat, non-sweet, unodourised break during conditioning, without drawing undue attention to the milk stimuli, which plain water samples might have done. All samples were stored and presented in the same manner as the milk samples described above. Enhancement test stimuli Four milk mixtures containing an intermediate level of fat (3.5%) and sucrose (2%) were produced from 90% Dairy Farmer’s skim milk (0.1% fat), to which 10% Dairy Farmers pure cream (35% fat) was added. To each of these mixtures, one of each of the four odourants was added at the same concentrations used for low-fat milk in the conditioning stimuli. Storage and presentation of the stimuli is as described above for the milk samples. Procedure Each participant attended two sessions, separated by a 1-week interval. The first session contained a pre-test for the milk and odour samples, as well as a conditioning phase. The second session contained another conditioning phase, followed by a post-test for the milk and odour samples, an enhancement test, a pairing knowledge test, and a short post-experimental questionnaire. Participants were tested in groups of 3 or 4, seated so as to minimise observation of other subjects. Stimulus sampling occurred
ARTICLE IN PRESS 94
N.C. Sundqvist et al. / Appetite 47 (2006) 91–99
at precisely the same time, with 30 s inter-stimulus intervals. Session 1 Session 1 began with a tasting of each of the four milk samples (Milk Pre-test), LFUN, HFUN, LFSW and HFSW. Participants were instructed to take the entire sample into their mouth, swirl it around for 3 s (timed by the experimenter’s stop-watch) and expectorate. This procedure was demonstrated by the experimenter, prior to testing. Participants were also requested not to comment verbally on samples. Presentation order was counterbalanced, so that each sample (i.e. LFUN, HFUN, LFSW, HFSW) occurred an equal number of times in the first, second, third and fourth position for a predicted sample size of 44. This was not affected by the effectively random reduction in participant numbers, as each sample was still presented an approximately equal number of times in each position. Sample position had no detectable effect on participants ratings when analysed. After tasting the first sample, participants completed their first rating sheet. This contained three 9-point category scales in the following order: Sweetness (anchors, ‘Not at all sweet’—1 to ‘Extremely Sweet’—9), Fattiness (anchors, ‘Not at all fatty’—1 to ‘Extremely fatty’—9) and Liking/Disliking (anchors, ‘Dislike extremely’—1 to ‘Like extremely’—9, plus a central marker, ‘Indifferent’—5). Participants then rinsed their mouths thoroughly with tap water. This procedure was repeated for the remaining three solutions. Participants then commenced the Odour Pre-test, which involved sniffing and rating each of the four target odours. Participants were instructed to hold the tip of the nozzle approximately 7 cm from their nose and to squeeze the bottle three times whilst sniffing. This was demonstrated by the experimenter, prior to testing. Each of the four odours, (LY, WC, OT and RB) were presented in counterbalanced order, with a 30 s inter-stimulus interval between each. Once again, counterbalancing was not significantly impacted by the loss of participants. During the interstimulus interval participants rated each odour for sweetness, fattiness and liking, on 9-point category scales, as described above. In addition, odour intensity was also assessed by asking participants, ‘How strong do you think this sample smells?’ (anchors, ‘Not at all strong’—1 to ‘Extremely strong’—9). The conditioning phase of the experiment then commenced. Participants were reminded of the correct sampling procedure prior to testing, as described for the milk samples above. They were then presented with a tray of 30 samples, comprised of 16 target trials and 14 filler trials (milk-coloured water). Each participant received four Odour A-LFUN samples, four Odour B-LFSW samples, four Odour C-HFUN samples and four Odour D-HFSW samples. Presentation order of all stimuli was random. Each series of odour-milk combinations (per participant) was drawn from a master set of fully counterbalanced
odour/fat/sucrose combinations. These were assigned to participants by order of arrival. For example, the first participant was given the following combination: LYLFSW, WC-HFSW, RB-LFUN and OT-HFUN, each presented four times. Samples were counterbalanced such that each odour appeared an equal number of times with each fat/sucrose combination, across participants. Counterbalancing was not adversely affected by the smallerthan-anticipated final sample size, that is each odour-tastefat combination occurred with approximately equal frequency. A 30 s inter-stimulus interval was maintained between all samples, during which participants circled their level of liking/disliking for each sample (‘Dislike’, ‘Indifferent’ and ‘Like’). The purpose of this task was to ensure that participants attended to the solutions and to provide some face validity for the sampling procedure. Session 2 Participants returned 1 week later for Session 2, which commenced with a further conditioning phase. This was identical to the first in all respects, except that only 15 samples were used. These were composed of two Odour A-LFUN samples, two Odour B-LFSW samples, two Odour C-HFUN samples and two Odour D-HFSW samples, as well as 7 filler trials. The post-test phase of the experiment then began. This started with the Milk Post-test, identical to the Pre-test, followed by the Odour Post-test, which was also identical to the Odour Pre-test. Participants then completed the Enhancement test, in which they received each of the target odours in a slightly sweetened and slightly fatty milk. The procedure for this test was identical to that of the Milk Pre/ Post-test, including the rating scales for Sweetness, Fattiness and Liking. This was then followed by the Pairing Knowledge Test. Here, participants smelled each of the four target odours again, presented in the same order, as in the Odour Pre/Post-test. After smelling each odour participants were asked, ‘Was this odour ever presented with: (a) A fatty milk, (b) Low-fat milk or (c) Unsure’. This was followed by a second question, ‘Was this odour ever presented with: (a) A lot of sugar, (b) No sugar or (c) Unsure’. Participants’ task was to circle one response for each question. Finally, a short post-experimental questionnaire was presented to participants. Responses provided information about participants’ age, gender, the type of milk typically drunk, and whether they were (or had recently been) dieting. Results Milk pre/post-test ratings The analyses described below tested whether the unodourised milk samples were, as we intended, perceived as appropriately fatty and sweet (see Table 1 for mean values on pre- and post-test). A three-way repeated measures
ARTICLE IN PRESS N.C. Sundqvist et al. / Appetite 47 (2006) 91–99
95
Table 1 Mean sweetness, fattiness and liking ratings for the milk-fat and sugar combinations alone (LFUN—low fat unsweetened; LFSW—low fat sweetened; HFUN—high fat sweetened; HFSW—high fat sweetened) on the milk pre- and post-test
Table 2 Mean sweetness, fattiness and liking ratings for the odours alone by condition (LFUN—low fat unsweetened; LFSW—low fat sweetened; HFUN—high fat sweetened; HFSW—high fat sweetened) on the odour pre- and post-test
Stimulus
Rating
Milk pre-test Mean (SD)
Milk post-test Mean (SD)
Stimulus
Rating
Odour pre-test Mean (SD)
Odour post-test Mean (SD)
LFUN
Sweetness Fattiness Liking
2.7 (1.5) 3.9 (2.1) 4.2 (1.8)
2.6 (1.5) 3.9 (1.9) 4.7 (1.4)
LFUN
Sweetness Fattiness Liking
4.5 (2.3) 3.8 (2.3) 4.1 (1.7)
5.0 (2.3) 3.6 (2.2) 4.0 (1.5)
LFSW
Sweetness Fattiness Liking
7.9 (1.1) 5.5 (1.7) 5.4 (2.1)
7.2 (1.5) 4.7 (1.7) 5.8 (1.9)
LFSW
Sweetness Fattiness Liking
5.5 (2.5) 3.4 (2.1) 4.7 (2.4)
5.9 (2.4) 4.4 (2.3) 4.5 (1.9)
HFUN
Sweetness Fattiness Liking
3.3 (2.0) 6.4 (1.7) 4.2 (1.9)
3.0 (1.6) 6.9 (1.7) 4.4 (1.9)
HFUN
Sweetness Fattiness Liking
5.3 (2.6) 3.4 (2.1) 4.7 (2.2)
6.2 (1.9) 4.3 (2.3) 4.4 (2.0)
HFSW
Sweetness Fattiness Liking
7.8 (1.0) 6.1 (1.6) 5.4 (2.0)
7.2 (1.3) 7.0 (1.4) 5.1 (2.3)
HFSW
Sweetness Fattiness Liking
5.6 (2.3) 3.5 (2.4) 4.4 (1.7)
6.9 (2.1) 4.4 (2.1) 3.9 (1.9)
ANOVA was conducted, with Fattiness ratings as the dependent variable, and with Time (pre- vs post-test), Fatlevel (low- vs high-fat) and Sweetness-level (unsweetened vs sweetened) as within-participant factors. This ANOVA revealed a main effect of Fat-level (F(1,35) ¼ 87.77, po0.001), with high-fat milks (HFUN and HFSW) rated as more fatty than low-fat milks (LFUN and LFSW). There was also a main effect of Sweetness-level (F(1,35) ¼ 5.64, po0.025), with sweetened milk rated significantly more fatty than unsweetened milk. These variables interacted (F(1,35) ¼ 11.86, po0.005), and as can be seen in Table 1, low-fat sweetened milk (LFSW) was judged as fattier than low-fat unsweetened milk (LFUN), with little difference in perceived fattiness for the high-fat sweetened (HFSW) and unsweetened (HFUN) milks. Finally, there was a significant interaction between Time and Fat-level (F(1,35) ¼ 11.52, po0.005), in that the fattiness ratings of low-fat milk decreased from pre to post-test, whereas the fattiness ratings of high-fat milk increased. Sweetness ratings were analysed using the same ANOVA design (see Table 1 for means). As expected, participants rated the sweetened milks (LFSW and HFSW) as sweeter than the unsweetened milks (F(1,35) ¼ 386.72, po0.001). There was also a main effect of Time (F(1,35) ¼ 7.58, po0.01), indicating that on average, milk was rated as sweeter in the pre-test than in the post-test. There were no other effects. Finally, liking ratings were analysed in the same way. Only the main effect of Sweetness-level was significant (F(1,35) ¼ 14.315, po0.005), with sweetened milks liked more than unsweetened milks (see Table 1). Odour pre/post-test ratings Mean values, on pre- and post-test for each of the key attributes (fattiness, sweetness and liking) are presented in
Table 2. Odour fattiness ratings were analysed using a three-way repeated measures ANOVA with Time (pre- vs post-test), Fat-level (low- vs high-fat) and Sweetness-level (unsweetened vs sweetened) as within-participant factors. The key finding from this analysis was a significant Time by Fat-level by Sweetness-level interaction (F(1,35) ¼ 5.06, po0.05). Odours paired with high-fat milks or with the sweetened low-fat milk, were judged to smell fattier on post-test than they did on pre-test. Importantly in this respect, there was little change in fattiness ratings for the odour paired with LFUN from pre- to post-test. These results provide support for our central hypothesis, that odours can acquire the fatty properties of foods they are associated with, and are complementary to the milk fattiness ratings, which revealed that milk was rated fattier when it contained either higher fat and/or low-fat with added sucrose. Finally, the ANOVA also revealed a main effect of Time (F(1,35) ¼ 11.42, po0.005), but this was of little interest given the interaction reported above. There were no other significant effects. Odour sweetness ratings were analysed in the same way. The ANOVA revealed only a main effect of Time (F(1,35) ¼ 5.26, po0.05) with the sweetness ratings of all odourants increasing from pre- to post-test (see Table 2). There was, therefore, no indication of any differential conditioning effect here for sweetness. Odour intensity ratings were also analysed in the same manner as described above. The only significant effect here was a Time by Fat-level interaction (F(1,35) ¼ 13.71, po0.005). This suggested that intensity ratings for odours paired with high-fat milks tended to increase from pre-test (M ¼ 6.1) to post-test (M ¼ 6.7), whilst odours paired with low-fat milk, tended to decrease in intensity from pre-test (M ¼ 6.5) to post-test (M ¼ 6.3). These results were of interest as all test odours were presented at a uniform concentration on the pre- and post-tests, however the
ARTICLE IN PRESS N.C. Sundqvist et al. / Appetite 47 (2006) 91–99
odours paired with high-fat milk in the conditioning phase had been presented at a higher concentration, than those paired with low-fat milk. Finally, odour hedonic ratings were also analysed in the same manner, but there were no significant effects (see Table 2 for means). Enhancement test Fattiness ratings obtained in the Enhancement test were analysed with a two-way repeated measures ANOVA, with Fat-pairing (low- vs high-fat) and Sweetness-pairing (sweetened vs unsweetened) as within-subject factors. The ANOVA revealed a main effect of Fat-pairing (F(1,35) ¼ 4.47, po0.05), indicating that milk containing an odour originally paired with high-fat, was rated fattier on average in the Enhancement test, than the same milk containing an odour originally paired with low-fat (see Fig. 1). There were no other significant effects. Sweetness ratings were analysed in the same manner. This ANOVA revealed a main effect of Sweetness-pairing (F(1,35) ¼ 9.58, po0.005). Milk containing an odour originally paired with sucrose, was rated as sweeter in the Enhancement test, than the same milk containing an odour which had not been paired with sucrose (see Fig. 2). There were no other significant effects. Finally, liking ratings were analysed in the same way, however there were no significant effects. Pairing knowledge test For each of the four odours, participants were asked to identify whether it had been paired with fat and sucrose. Three measures were derived from these scores in an attempt to assess participants’ overt knowledge about the pairing history of each odour. The first variable was a measure of participants’ ‘Fat Knowledge’. Here, partici9 8
Low-fat paired odours High-fat paired odours
Rated Fattiness
7 6 5 4 3 2 1 None sucrose paired odours
Sucrose paired odours
Fig. 1. Mean fattiness ratings (and SE) on the enhancement test where each of the four target odours were presented in the same milk stimulus.
9 Low-fat paired odours High-fat paired odours
8 7 Rated Sweetness
96
6 5 4 3 2 1 None sucrose paired odours
Sucrose paired odours
Fig. 2. Mean sweetness ratings (and SE) on the enhancement test where each of the four target odours were presented in the same milk stimulus.
pants received a score of ‘1’ if they chose the correct level of fat that had been paired with that odour, and a score of ‘0’ if they were either incorrect or unsure. The second variable was a measure of participants ‘Sweetness Knowledge’. Here, the same criterion was used, a score of ‘1’ for correctly identifying that an odour had or had not been paired with sucrose, and a score of ‘0’ for incorrect or unsure responses. The third variable ‘Net knowledge’, assessed whether participants were correct in both their judgement of Fat- and Sweetness-level for each particular odour. A score of ‘1’ was returned if they had the correct choice on both fattiness and sweetness. All other responses were scored ‘0’. Thus a perfect score would be 4/4 for Fat Knowledge, 4/4 for Sweetness Knowledge and 4/4 for Net Knowledge. As can be seen in Table 3, most participants had some level of Fat Knowledge and some level of Sweetness Knowledge, but Net Knowledge was rather poor. To ascertain whether knowledge of the odours’ reinforcement history impacted upon learning, we calculated three measures of conditioning based upon the significant effects obtained in this experiment (i.e. Odour Fattiness [from the three-way interaction of Time by Sweetnesslevel by Fat-level in the Odour Pre/post-test], Fattiness enhancement [from the main effect of Fat-pairing in the Enhancement test] and Sweetness enhancement [from the main effect of Sweetness-pairing in the Enhancement test]). The fat-related learning effects were then correlated with the Fat Knowledge score and the Net Knowledge score and all four Pearsons correlations were non-significant (r’so0.15, critical r ¼ 0.33, a ¼ 0.05). The sweetness-related learning effect was then correlated with the Sweetness Knowledge score and the Net Knowledge score. Both Pearsons correlations were again non-significant (r’so0.21, critical r ¼ 0.33, a ¼ 0.05).
ARTICLE IN PRESS N.C. Sundqvist et al. / Appetite 47 (2006) 91–99 Table 3 Results from the pairing knowledge test showing the number of participants correctly identifying the pairing history of the odour stimuli Number of odours correctly identified
0 1 2 3 4
Fat Knowledge n
Sweet Knowledge n
Net Knowledge n
(%) ¼
(%) ¼
(%) ¼
3 9 11 11 2
2 7 14 10 3
13 12 9 2 0
(8.3) (25.0) (30.6) (30.6) (5.6)
(5.6) (19.4) (38.9) (27.8) (8.3)
(36.1) (33.3) (25.0) (5.6) (0.0)
Individual differences Individual differences in milk use and dieting might all potentially impact upon participants’ evaluations of the stimuli used in this experiment. The questionnaire completed at the end of the experimental session revealed that milk usage did indeed differ across the sample. Seventeen participants reported typically using full-cream milk in their daily diet, two participants used no milk at all, six reported using skim milk, ten used lite milk and one participant used soy milk. As for dieting, five participants were currently dieting and 14 participants were either currently dieting or had dieted within the last 6 months. Of these 14, 11 had consciously reduced sugar in their diet, and 13 in fat. In order to determine whether there were any consistent effects of milk usage, dieting or gender, a series of exploratory post hoc analyses were conducted, using; current dieting status (dieters vs non-dieters), dieting status within the previous 6 months (dieters vs non-dieters), milk use (full cream milk drinkers vs all other groups) and gender (males vs females), as between-subject factors. Each of the fattiness, sweetness and liking ANOVAs described above were repeated with each of the between-subject factors included sequentially. Alpha was set at 0.01 in an attempt to minimise Type 1 errors. There were no differences in fattiness, sweetness or liking ratings across the milk, odour or enhancement test analyses for the dieters, different types of milk drinkers or by gender. Discussion The primary aim of this experiment was to determine whether odours could acquire ‘fat-like’ properties. The odour pre/post-test revealed that odours paired with either high- or low-fat and sucrose, were subsequently rated fattier on post-test than odours paired with low-fat and no sucrose. In the Enhancement test, however, only milks containing the odourants previously paired with high-fat were rated fattier. In terms of sweetness learning, no evidence was obtained on the odour pre/post-test. In the Enhancement test, however, milk containing an odour previously paired with sucrose was rated sweeter than milk
97
containing an odour previously paired with no sucrose. For all these findings, there was no significant association with what participants reportedly knew about the reinforcement history of the odours, suggesting that demand had not played a significant role in these results. Notwithstanding the interesting difference in test results, the current experiment provides suggestive evidence that odour-fat associations may be learnt and that this may occur in conjunction with odour-sweetness learning. We start by presenting our take on these results and then describe a number of problems which future attempts to explore this phenomenon will need to grapple with. It was suggested in the Introduction that if odour-fat learning arose, it would be the result of odour-texture associations, as fat appears to be perceived primarily through its textural attributes (e.g. Mela, 1988). Support for a textural account was provided in the present experiment in two ways. First, LFSW was rated significantly more ‘fatty’ than LFUN. Similar findings have been made by other researchers, who have found that sucrose can increase the viscosity of a low-fat milk, thus enhancing perceptions of fat (Drewnowski & Greenwood, 1983; Drewnowski et al., 1998; Salbe, et al., 2004). Second, on the odour pre/post-test, the odours paired with milks judged to be fattier (i.e. high-fat milks and the sweetened low-fat milk) were judged as fattier smelling. At least on this test, it would imply that the odours may have become associated with the viscous properties of the stimulus, leading to the enhanced fattiness ratings for these three odours. Although the odour pre/post-test data nicely aligns itself with the fattiness ratings obtained for the milk stimuli, the Enhancement test data present a rather different picture. Two puzzling features stand out. First, the presence of a sweetness conditioning effect here (given its absence on the odour pre/post-test). Second, the absence, of a fattyenhancement effect for the odour paired with sweetened low-fat milk (given its presence on the odour pre/post-test). A rather straightforward answer can be suggested for the sweetness result. The enhancement test is contextually much closer to the conditions of learning than the odour pre/post-test. On the Enhancement test, stimuli were presented in milk and sampled by mouth, just as they were during conditioning. This might be akin to ‘transferappropriate processing’, in that only the more similar context allowed for effective retrieval of the odour-taste memory, making this a more sensitive test of learning. Needless to say, we have detected odour-taste learning on odour pre/post-tests before, but this is the first attempt under conditions where other related sensory features were present during conditioning. One major problem with this account is that if the Enhancement test really did offer a more sensitive medium in which to recover experiences acquired during learning, why was the fatty conditioning effect obtained for the lowfat sweetened stimulus on the odour pre/post-test, absent? One possibility is that the measurement scale attributes
ARTICLE IN PRESS 98
N.C. Sundqvist et al. / Appetite 47 (2006) 91–99
(sweet and fatty) are far better defined in the Enhancement test than they are in the odour pre/post-test. In the Enhancement test the stimulus really is sweet and fatty, providing concrete definitions of the stimulus attributes. As fattiness is potentially defined by several textural properties (see Introduction), and some of these may have been absent within the LFUN, this may have resulted in an enhancement effect for only the high-fat paired odours, which may have acquired a relatively greater perceptual similarity to fat (i.e. a greater number of fat-like attributes). Thus, one might speculate whether the odour paired with LFSN acquired a fatty characteristic related to viscosity, whilst the odours paired with high-fat milks acquired a broader range of fatty characteristics. Not surprisingly, given that this is the first study to examine odour-fat associations, little is known about the neural mechanisms which might underpin it. Research conducted by Rolls and his colleagues (e.g. Rolls & Baylis, 1994; Rolls, et al., 1999) does, however, provide some clues. Multimodal neurons have been found within the orbitofrontal cortex which respond to a variety of sensory inputs (Rolls & Baylis, 1994). It is plausible that odour and fat inputs converge here to form new associations, which are learnt through repeated presentation during eating or drinking. On the basis of procedural similarity with odourtaste learning, and due to the finding that odour and taste information also converges in the orbitofrontal cortex, we suggest that odour-taste and -fat learning may share a similar explanation. Namely, that olfactory, tactile and other fat-related inputs are stored as a configuration (or unitary percept), which is recovered when the odour is encountered again. Consistent with the account above is the finding that participants’ explicit knowledge was unrelated to performance. This has been noted repeatedly in the odour-taste literature and we have argued that it relates directly to both the simultaneous nature of presentation and to the configural encoding of flavour stimuli (Stevenson & Boakes, 2004). However, we would like to stress that our test of pairing knowledge was both rudimentary and performed at the end of the experiment, factors likely to make it less sensitive to any explicit knowledge held by participants. It was rudimentary by necessity, as we could not reasonably expect participants to sample more of the dairy mixtures, which many of them found unpalatable. It was performed at the end of the experiment, as we felt that our primary variables of interest (i.e. the conditioning measures) needed to be assessed first. Clearly, this is an issue which warrants further investigation. So far we have taken our results at face value. The study set out to explore odour-fat learning and produced findings that were generally consistent with our expectations. However, the review process revealed a dissenting opinion about the merits of our conclusions and we feel these issues require serious consideration. The first point of concern is that when making odour-fattiness ratings, participants may not be sure what they are rating. One remedy would be to
include a standard fatty odour to compare the targets to. The effect this might have on our experiment is hard to gauge. The worse case scenario might be that participants relied upon explicit knowledge to make their ratings, but we did not detect any such effect. This, though may have arisen because of a second concern, that the measures of awareness lacked sufficient sensitivity. As we noted above, our measure of awareness was less than ideal—it occurred at the end of the experiment and did not use contextually identical stimuli. A more potent test would need to examine contingency awareness earlier on and using a more sensitive test. Nonetheless, any subsequent failure to detect awareness could still be counted as inadequate test sensitivity. A third concern relates to the failure to detect a sweetness effect on the odour pre/post-test. One possibility is that halo-dumping occurred in this experiment. That is participants attributed ‘sweetness’ to the ‘fattiness’ dimension of the scale, resulting in the apparent absence of an effect. This explanation, although plausible, does not explain why sweetness would be dumped into fattiness ratings (learning?), nor why this only occurred in the odour pre/post-test and not in the enhancement test. Finally, no statement can be made about the psychological magnitude of any putative conditioning effect, because of the type of scales that were used here. Future studies would probably be well advised to use magnitude estimation or some other direct scaling approach. Although we did not have high expectations of finding any conditioned changes in liking, we were surprised by participants’ general indifference, or in some cases, active dislike of fattier milks. Drewnowski and Greenwood (1983), for example, reported that higher fat milk was preferred to low-fat milk. Two factors may account for this. First, fats have, more recently, been linked in the public mind to high rates of obesity (Drewnowski & Schwartz, 1990). They have also been widely vilified in the popular press (Mattes, 2003; Taubes, 2001). Second, the rather unnatural laboratory setting may have led participants to treat all stimuli with some circumspection. In combination, these two factors may have led to a more negative appraisal of our high-fat stimuli when compared to earlier studies. Finally, we obtained one further result that warrants comment in the light of our interest in associative learning as it relates to flavour perception and olfaction. Participants received a higher concentration of the target odourants when they were mixed with high-fat stimuli, to compensate for the potential suppressive effect that fats have on the perception of volatile compounds. On test, the odours previously paired with high-fat stimuli were found to smell more intense than the odours previously paired with low-fat stimuli. This effect was not an artefact of the test odours, because these odours were appropriately counterbalanced, and the result was only apparent on the post-test, not the pre-test, suggesting that the conditioning phase was in some way responsible. One might be tempted to suggest that this effect arose from the judgemental
ARTICLE IN PRESS N.C. Sundqvist et al. / Appetite 47 (2006) 91–99
context. If this were the case, however, we would have expected the odours originally presented at a higher concentration to be judged as weaker (i.e. contrast effect), and this was not the case. A further and more intriguing possibility is that the effect was the result of learning. If participants found the higher concentration of odours in the high-fat stimuli somewhat stronger, this could have been encoded alongside other sensory information. Thus on test, and that when the odours were encountered at a lower concentration, the original ‘smell’ could have been recovered from memory—thus being experienced as somewhat more intense. This finding may share some similarity to the observation of a positive association between familiarity and intensity, a presumed effect of the retention of familiar odours in memory (e.g. Ayabe-Kanamura et al., 1998). In conclusion, this study provides preliminary evidence that odours can indeed acquire the perceived fatty properties of foods they are associated with. This would suggest that the phenomenon of cross-modal learning related to flavour is probably not restricted to just odours and tastes, but may extend more broadly into other sensory domains. Acknowledgements We would like to thank Fumi Asai and Mehmet Mahmut for their assistance with these experiments. This research was assisted by a grant from the Australian Research Council. References Ayabe-Kanamura, S., Schicker, I., Laska, M., Hudson, R., Distel, H., Kobayakawa, T., et al. (1998). Differences in perception of everyday odors: A Japanese–German cross cultural study. Chemical Senses, 23, 31–38. Boelens, H. (1974). Relationship between the chemical structure of compounds and their olfactive properties. Cosmetics and Perfumery, 89, 70–89. Dalton, P., Doolittle, N., Nagata, H., & Breslin, P. (2000). The merging of the senses: Integration of subthreshold taste and smell. Nature Neuroscience, 3, 431–432. De Araujo, I. E., & Rolls, E. T. (2004). Representation in the human brain of food texture and oral fat. The Journal of Neuroscience, 24, 3086–3093. Dravnieks, A. (1985). Atlas of odor character profiles. ASTM Data series DS61. ASTM Publishers: Philadelphia. Drewnowski, A. (1993). Individual differences in sensory preferences for fat in model sweet dairy products. Acta Psychologica, 84, 103–110. Drewnowski, A., & Greenwood, M. R. C. (1983). Cream and sugar: Human preferences for high-fat foods. Physiology and Behavior, 30, 629–633. Drewnowski, A., Henderson, S. A., & Barratt-Fornell, A. (1998). Genetic sensitivity to 6-n-propylthiouracil and sensory responses to sugar and fat mixes. Physiology and Behavior, 63, 771–777. Drewnowski, A., & Schwartz, M. (1990). Invisible fats: Sensory assessment of sugar/fat mixtures. Appetite, 14, 203–217. Frank, R. A., & Byram, J. (1988). Taste-smell interactions are tastant and odorant dependent. Chemical Senses, 13, 445–455. Lawless, H. T. (1996). Flavor. In M. P. Friedman, & E. C. Carterette (Eds.), Handbook of perception, Vol. 16, Cognitive ecology (pp. 325–380). California: A.P. San Diego.
99
Lermer, C. M., & Mattes, R. D. (1999). Perception of dietary fat: Ingestive and metabolic implications. Progress in Lipid Research, 38, 117–128. Mattes, R. D. (2003). Fat: The sixth taste—Implications for health. Food Australia, 55, 510–514. Mela, D. J. (1988). Sensory assessment of fat content in fluid dairy products. Appetite, 10, 37–44. Prescott, J., Johnstone, V., & Francis, J. (2004). Odor/taste interactions: Effects of different attentional strategies during exposure. Chemical Senses, 29, 331–340. Richardson, N. J., & Booth, D. A. (1993). Multiple physical patterns in judgments of the creamy texture of milks and creams. Acta Psychologica, 84, 93–101. Rolls, E. T. (2004). The functions of the orbitofrontal cortex. Brain and Cognition, 55, 11–29. Rolls, E. T., & Baylis, L. L. (1994). Gustatory, olfactory, and visual convergence within the primate orbitofrontal cortex. The Journal of Neuroscience, 14, 5437–5452. Rolls, E. T., Critchley, H. D., Browning, A. S., Hernadi, I., & Lenard, L. (1999). Responses to the sensory properties of fat of neurons in the primate orbitofrontal cortex. The Journal of Neuroscience, 19, 1532–1540. Saint-Eve, A., Kora, E. P., & Martin, N. (2004). Impact of the olfactory quality and chemical complexity of the flavouring agent on the texture of low fat stirred yoghurts assessed by three different sensory methodologies. Food Quality and Preference, 15, 655–668. Salbe, A. D., DelParigi, A., Pratley, R. E., Drewnowski, A., & Tataranni, A. (2004). Taste preferences and body weight changes in an obesityprone population. American Journal of Clinical Nutrition, 79, 372–378. Schiffman, S. S., Graham, B. G., Sattely-Miller, E. A., & Warwick, Z. S. (1998). Orosensory perception of dietary fat. Current Directions in Psychological Science, 7, 137–143. Schifferstein, H. N. J., & Verlegh, P. W. (1996). The role of congruency and pleasantness in odor-induced taste enhancement. Acta Psychologica, 94, 87–105. Small, D. M., & Prescott, J. (2005). Odor/taste integration and the perception of flavor. Experimental Brain Research, 166, 345–357. Small, D. M., Voss, J., Mak, Y. E., Simmons, K. B., Parrish, T., & Gitelman, D. (2004). Experience dependent neural integration of taste and smell in the human brain. Journal of Neurophysiology, 92, 1892–1903. Stevenson, R. J., & Boakes, R. A. (2004). Sweet and sour smells: Learned synesthesia between the senses of taste and smell. In G. Calvert, C. Spence, & B. Stein (Eds.), The handbook of multisensory processes (pp. 69–83). Cambridge, MA: MIT Press. Stevenson, R. J., Boakes, R. A., & Prescott, J. (1998). Changes in odor sweetness resulting from implicit learning of a simultaneous odorsweetness association: An example of learned synesthesia. Learning and Motivation, 29, 113–132. Stevenson, R. J., Prescott, J., & Boakes, R. A. (1995). The acquisition of taste properties by odors. Learning and Motivation, 26, 433–455. Stevenson, R. J., Prescott, J., & Boakes, R. A. (1999). Confusing tastes and smells: How odors can influence the perception of sweet and sour tastes. Chemical Senses, 24, 627–635. Taubes, G. (2001). Nutrition: The soft science of dietary fat. Science, 291, 2536–2545. Tepper, B. J., & Nurse, R. J. (1997). Fat perception is related to PROP taster status. Physiology and Behavior, 61, 949–954. Tittelbach, T. J., & Mattes, R. D. (2001). Oral stimulation influences postprandial triacylglycerol concentrations in humans: Nutrient specificity. Journal of the American College of Nutrition, 20, 485–493. Verhagen, J. V., Rolls, E. T., & Kadohisa, M. (2003). Neurons in the primate orbitofrontal cortex respond to fat texture independently of viscosity. Journal of Neurophysiology, 90, 1514–1525. Yeomans, M. R., Mobini, S., Elliman, T., Walker, H. C., & Stevenson, R. J., (in press). Hedonic and sensory characteristics of odors conditioned by pairing with tastants. Journal of Experimental Psychology: Animal Behavior Processes, (accepted 19/12/05).