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Multisensory flavor perception: Assessing the influence of fruit acids and color cues on the perception of fruit-flavored beverages
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Food Quality and Preference 19 (2008) 335–343 www.elsevier.com/locate/foodqual
Multisensory flavor perception: Assessing the influence of fruit acids and color cues on the perception of fruit-flavored beverages Massimiliano Zampini a,b,c,*, Emma Wantling d, Nicola Phillips e, Charles Spence a a
Crossmodal Research Laboratory, Department of Experimental Psychology, University of Oxford, South Parks Road, Oxford OX1 3UD, United Kingdom b Department of Cognitive Sciences and Education, University of Trento, Corso Bettini 31, 38068 Rovereto (TN), Italy c Center for Mind/Brain Sciences, University of Trento, Rovereto, Italy d Unilever Research, Colworth House, Sharnbrook, England, United Kingdom e Unilever Research, Port Sunlight, Bebington, England, United Kingdom Received 10 May 2007; received in revised form 6 November 2007; accepted 6 November 2007 Available online 13 November 2007
Abstract We report a study designed to investigate the influence of fruit acids (in particular, citric and malic acid) on people’s perception of the identity and the intensity of a variety of different fruit-flavored solutions. Participants had to identify the flavor of fruit-flavored drinks that were colored yellow, grey, orange, red, or else were presented as colorless solutions. The participants also rated the intensity of flavor, sweetness, and sourness of each solution using a Labelled Magnitude Scale (LMS). The participants identified the flavors of the beverages more accurately when citric and malic acids were added to the solutions, and/or when the solutions were colored appropriately. Moreover, the perception of flavor intensity was modulated by the presence of the fruit acids in the solutions. Ó 2007 Elsevier Ltd. All rights reserved. Keywords: Flavor perception; Multisensory perception; Color; Citric and malic acid; Fruit-flavored beverages; Taster status
1. Introduction It is well-known that people’s perception of the flavor of many beverages can be influenced by their color (Alley & Alley, 1998; Clydesdale, 1993; DuBose, Cardello, & Maller, 1980; Johnson & Clydesdale, 1982; Morrot, Brochet, & Dubourdieu, 2001; Philipsen, Clydesdale, Griffin, & Stern, 1995; Roth, Radle, Gifford, & Clydesdale, 1988; Zellner & Durlach, 2003). In one frequently cited study, Dubose et al. showed that inappropriately coloring a cherry-flavored beverage (i.e., by using incongruent coloring) resulted in a significant decrease in participants’ ability to identify the cherry flavor correctly. For instance, 26% of the partic*
Corresponding author. Address: Department of Cognitive Sciences and Education & Center for Brain/Mind Sciences, University of Trento, Corso Bettini, 31, 38068 Rovereto (TN), Italy. Tel.: +39 0464 483661; fax: +39 0464 483554 (M. Zampini). E-mail address: [email protected] (M. Zampini). 0950-3293/$ - see front matter Ó 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodqual.2007.11.001
ipants in their study reported that they were drinking a lime-flavored beverage when the drink was colored green as compared to no lime-flavor responses when the drink was colored red. Maga (1974) suggested that those colors that are typically associated with the natural ripening of fruits (e.g., yellow, red, etc.) may be particularly effective in modulating sweetness perception (Strugnell, 1997). By contrast, researchers have reported that the addition of color has far less of an effect on the perceived saltiness of foods such as soups (Gifford & Clydesdale, 1986; Gifford, Clydesdale, & Damon, 1987; Maga, 1974), perhaps because (in contrast to sweet foods) there are no particular colors associated with the salt content of a food (i.e., salt is ubiquitous to many different kinds, and hence colors, of food; see Maga, 1974, see also Lavin & Lawless, 1998, on this point). A relatively independent line of food science research has demonstrated that the perception of flavor intensity in various fruit-flavored beverages can also be enhanced
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by adding the appropriate fruit acids (King & Duineveld, 1998; Kuo, Pangborn, & Noble, 1993; Pfeiffer, Hort, Hollowood, & Taylor, 2006; Sortwell & Woo, 1996; Valde´s, Simone, & Hinreiner, 1956b). For example, Sortwell and Woo have argued that adding the appropriate fruit acids (i.e., those that are naturally present in fruits) can result in participants judging flavors as being more ‘natural’. Pfeiffer et al. have also shown that increasing the citric and malic acid content results in an increase in the perceived intensity of strawberry flavored solutions. Therefore, it seemed plausible to us that the presence of the appropriate fruit acids might improve participants’ flavor identification performance since they may increase people’s perception of both the naturalness and the intensity of the flavor of fruit-flavored solutions (King & Duineveld, 1998; Sortwell & Woo, 1996). Alternatively, however, it also seemed possible that if people perceived the flavor of fruit more clearly then they might have a stronger association with the appropriate color (Maga, 1974), and thus color cues might exert a stronger influence on people’s flavor identification responses. The primary aim of the experiment reported in the present study was therefore to investigate whether the influence of fruit acids on people’s perception of flavor intensity would modulate their ability to correctly identify the various fruit-flavored solutions that were presented as a function of whether they were colored appropriately or not. The present study also investigated whether the welldemonstrated visual influence over flavor perception in colored drinks would be influenced by the addition of the appropriate fruit acids to flavored-colored solutions. To the best of our knowledge, no one has previously addressed the question of whether the influence of visual cues on flavor perception can be modulated by the presence versus absence of the appropriate fruit acid ‘signatures’ (i.e., the acids that are naturally and normally present in fruits). Our prediction was that color cues might become more effective in enhancing sweetness and flavor perception when the appropriate fruit signatures were added to the beverages tested in the present study (though note that the addition of fruit acids might also be expected to reduce the overall level of sweetness). In particular, researchers have demonstrated that the addition of citric acid suppresses the perception of sweetness in sucrose solutions (see Bonnans & Noble, 1993; McBride & Finlay, 1989, 1990; Pangborn, 1961, 1965; Schifferstein & Frijters, 1990; though see also Fabian & Blum, 1943; Kamen, Pilgrim, Gutman, & Kroll, 1961; Pangborn, 1960; Sjo¨stro¨m & Cairncross, 1953). 2. Methods 2.1. Participants Fourteen participants (9 females and 5 males; mean age of 36 years; range from 22 to 58 years) took part in this study. The participants were selected from a panel of
untrained individuals recruited from the staff at Unilever Research (Colworth House, Sharnbrook, UK). All of the participants had normal color-vision as assessed by means of the Ishihara test for color blindness (Ishihara, 1943). Individuals who were pregnant, smokers, diabetic, hypoglycaemic, and those who suffered from thyroid problems were excluded from the study. None of the participants reported having a cold or other respiratory tract infection either on the days of the testing sessions or in the week prior to testing. All of the participants completed each experimental session at the same time. All of the participants gave their informed consent prior to taking part in the study, and all received £30 (UK Sterling) in return for completing the study. The study had ethical approval from Unilever Research Colworth House Laboratory. The experiment consisted of three testing sessions each lasting 100 min. Each testing session was conducted on a different day. 2.2. Apparatus and materials The participants were seated comfortably in an individual testing booth in front of a computer screen at the Colworth House testing suite. During the experiment, each participant received a series of plastic cups of colored and/or flavored solutions. One transparent cup was dispensed on each trial through a small window in front of the participant by one of the experimenters. The plastic cups were presented at room temperature (20 ± 2 °C). The flavored solutions were prepared from 1 l of distilled water with 75 g pure cane sugar added (Tate and Lyle, Warrington, UK) stirred until dissolved, and from concentrated fruit flavors (Quest International, Naarden, The Netherlands). Orange flavoring (0.8 ml ) and 1 ml of blackcurrant flavoring were added to 1 l of solution to flavor them orange and blackcurrant, respectively (as suggested by Quest International). Yellow, orange, grey, and red food colorings (Supercook, Leeds, UK) were used to color the solutions: 1.6 ml of yellow food coloring was added to 1 l of distilled water to color solutions yellow; the orange color was created by adding 0.8 ml of red and 4 ml of yellow food coloring; the grey coloring was achieved by combining 0.8 ml of yellow, 0.8 ml of red, and 2 ml of blue food coloring; and the red color by adding 1.6 ml of red food coloring to 1 l of distilled water. The criteria for selecting these colors were that they should be the colors that participants typically associated with the flavors used (e.g. orange–orange; blackcurrant-grey). The particular colors used in the present study emerged from a previous study on visual-flavor interactions (Zampini, Sanabria, Phillips, & Spence, 2007). There were also colorless samples that were made from distilled water, flavorings, and sucrose (but no coloring). In order to ensure that the participants in the present study were not able to derive any potentially useful information concerning the likely flavor of a given solution from
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its color alone, each of the flavorings (orange, blackcurrant, or flavorless) was presented equiprobably with each of the different colors (yellow, grey, orange, red, or colorless). Flavorless samples were also presented to the participants, and these could either be colored or colorless, just as for the flavored solutions. In half of the solutions, 0.9 ml of citric acid and 0.1 ml of malic acid were added per litre of solution (Sortwell & Woo, 1996). The flavorings, colorings, and acids used in the present study were cleared for human consumption by the Safety and Environmental Assurance Centre at Unilever Research, Colworth House.1 The bottled solutions were prepared on the morning of each experimental session, used during the day of the session, and any remaining solutions were discarded at the end of each experimental session. The experimenters dispensed 40 ml of the solutions from the airtight glass bottles into the clear plastic cups immediately prior to the experimental testing session using sterile syringes. The participants were given 40 ml of a tasteless palate cleansing solution (‘artificial saliva’) between each trial to wash their mouths out before tasting the next solution. This palate cleansing solution was made from deionised water using the main ionic components of saliva, 1.865 g/l of potassium chloride (KCl), and 0.210 g/l of sodium bicarbonate (NaHCO3; O’Doherty, Rolls, Francis, Bowtell, & McGlone, 2001). All of the apparatus associated with the preparation of the solutions (except the bottles, which were rinsed with boiled water and fully dried) were discarded at the end of each experimental testing session. 2.3. Design There were three within-participants factors: Flavor of the solution (blackcurrant, orange, or flavorless), Color of the solution (yellow, grey, orange, red, or colorless), and Fruit acids (present vs. absent). These factors were fully crossed giving rise to 30 conditions in total, which were each presented twice in each of three experimental sessions. 60 randomly ordered trials were presented in each experimental session, giving rise to a total of 180 stimuli tasted by each participant.
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2.4. Procedure All of the participants were given both written and oral instructions to view the solution on each trial from above the plastic cup and then to taste the solution. They were instructed to ensure that they moved the liquid around their mouths while making sure not to swallow it.2 After tasting each of the solutions, the participants were asked to spit them into the bucket provided. The participants were then asked to rinse their mouths thoroughly with the palate cleansing solution (again without swallowing) and to spit this into the bucket as well. On each trial, the participants were first asked to identify the flavor of the solution by ticking a box on a list of possible flavors presented on the computer monitor in front of them. The possible flavors were: strawberry, pear, mango, melon, grapefruit, lime, orange, papaya, cherry, peach, raspberry, blackcurrant, pineapple, grape, plum, apple, flavorless, or other. If the participants indicated the ‘other’ option they were prompted to suggest the specific flavor that they had in mind. (Note that the ‘other’ option was used on less than 2% of trials overall). The participants were also asked to evaluate the flavor intensity, sweetness intensity, and sourness intensity of each solution using a Labelled Magnitude Scale (LMS; Green, Shaffer, & Gilmore, 1993) that appeared on the computer monitor (see Fig. 1). The participants were fully informed and trained (but not experienced) in the use of the scale. They were instructed as to how to interpret the verbal descriptors (e.g., ‘strongest imaginable sensation’ on the top of the scale). The three scales for rating the intensity of the flavor, its sweetness, and its sourness were presented sequentially, although in a random order for each trial after the participants had made their flavor identification response. The sensation to be rated (i.e., flavor, sweetness, or sourness) appeared on the computer monitor each time the participant had to make a rating response. The list of flavors and the three LMS scales were presented on the computer screen placed in front of them using the Fizz software (Biosystemes, Couternon, France). The participants were explicitly informed that the color of the solutions should not be considered to provide a reliable cue to identify the flavors of the solutions that they were about to taste since all of the flavors had been crossed equiprobably with each of the colors (cf. Zampini et al., 2007).
1
In a preliminary experiment, we investigated whether the food colorings or fruit acids used in the present study would add some additional flavor to the sucrose solutions. To this end, the participants (N = 14 participants) were blindfolded and then instructed to compare two sucrose solutions, one with fruit acids (citric and malic acid) added. The participants reported that the latter solutions tasted sourer than the former samples but they did not report any difference between the flavor of the two solutions. The participants were then presented with two sucrose solutions to compare with the food colorings used in the present study added to one of the solutions. The participants reported no difference between the two samples. These results show that, by themselves, the food coloring and fruit acids did not add any flavor to the solutions tested in the present study.
2 The main reason for instructing the participants not to swallow was that we thought that they would have found it rather unpleasant to drink such a large quantity of liquid. The participants actually tasted 180 cups 40 ml = about 7 l of liquid in total. However, it is important to note on this point that previous studies have shown that people vary quite considerably in terms of the retro-nasal delivery of odors/flavors when swallowing is prevented (see Buettner, Beer, Hannig, & Settles, 2001; Hodgson, Linforth, & Taylor, 2003). The fact that the participants did not swallow the drinks in the present study therefore represents something of a limitation in terms of the ecological validity of our experimental design given that people normally swallow the beverages/foodstuffs that they put in their mouths.
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Correct responses (%)
classified into one of three taster groups: non-tasters, medium tasters, and supertasters, based on the cut-off values (non-tasters < 10.90; 10.91 < medium tasters < 61.48; supertasters > 61.49; see Essick, Chopra, Guest, & McGlone (2003), for a similar criterion). Using this criterion, 4 of the participants were classified as non-tasters, 5 as medium tasters, and 5 as supertasters.
Blackcurrant
100
75
50
3. Results
25
0
yellow
grey
orange
red
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Color of the solutions
Orange
Correct responses (%)
100
75
50
25
0
yellow
grey
orange
red
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Color of the solutions
Correct responses (%)
100
Flavorless
75
50
25
0
yellow
grey
orange
red
colorless
Color of the solutions Fig. 1. Mean percentage of correct flavor identification for the blackcurrant, orange, and flavorless solutions. The black columns represent solutions where fruit acids had been added and the white columns indicate solutions without fruit acids. The error bars represent the betweenparticipants standard errors of the means.
Before starting the experiment, the taster status of the participants was evaluated using 6-n-propylthiouracil (PROP) filter paper strips (Bartoshuk, Duffy, & Miller, 1994). The participants were instructed to place a PROP filter paper strip on their tongue. Next, they were instructed to close their mouth and moisten the paper with saliva for 20 s. Finally, the participants had to remove the paper strips from their mouths, swallow the saliva residue and then rate the intensity of the sensation of bitterness they experienced on an LMS scale. The participants were then
The data on the accuracy of participants’ flavor identification responses are summarized in Fig. 1. In the analysis of the flavor identification data, the frequency of participants’ responses were calculated first. Next, the percentage of correct responses were submitted to a repeated-measures analysis of variance (ANOVA) with the factors of Flavor (blackcurrant, orange, and flavorless), Color (yellow, grey, orange, red, or colorless), and Fruit acids (present vs. absent). For all of the analyses reported here, post-hoc comparisons used Bonferroni-corrected t-tests (where p < .05 prior to correction). The data analysis revealed a significant main effect of Color [F(4, 48) = 5.49, p = .001], with participants identifying the correct flavor more frequently when the solutions were colored grey (Mean = 46% correct responses), orange (M = 42%), or yellow (M = 39%), than when they were either colorless (M = 35%), or else colored red (M = 32%; post-hoc comparisons between the means of the three former conditions and between the means of the two latter conditions revealed no significant differences). The analysis of the flavor identification data also revealed a significant interaction between Color and Flavor [F(8, 96) = 8.33, p < .001], reflecting the fact that the blackcurrant flavor was identified more accurately when the solutions were colored grey (M = 64%) than when they were colored red (M = 32%), colorless (M = 30%), yellow, or orange (both M = 28%; none of the other comparisons approached significance). This result presumably reflects the fact that many blackcurrant-flavored products (such as, for example, blackcurrant-flavored yoghurts) are typically given a greyish-purple color. The orange-flavored solutions were also identified more accurately when they were colored orange (M = 63%) than when they were colored yellow (M = 49%), grey (M = 39%), red (M = 33%), or when they were presented as colorless solutions (M = 36%). This result is consistent with DuBose et al.’s (1980) finding that people are more likely to report that a cherry-flavored drink tasted of orange when it was colored orange than when it was colored red, green, or colorless. Finally, the ability of our participants to identify the flavorless solutions correctly (i.e., as being flavorless) was not affected by the color of the solutions (Engen, 1972; Zellner & Kautz, 1990). The significant interaction between Flavor and Fruit acids [F(2, 24) = 8.65, p = .001] can be attributed to the fact the participants identified the blackcurrant and orange-flavored solutions more accurately when they contained fruit
1.8
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Blackcurrant
1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Perceived flavor intensity (log10)
Color of the solutions
Orange
1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Color of the solutions Perceived flavor intensity (log10)
acids (M = 38% and 48%, respectively) than when they did not (M = 32% and 38%, respectively). This pattern of results is consistent with the claim that adding the appropriate fruit acids to a fruit-flavored beverage will lead to an increase in correct flavor identification responses. By contrast, the flavorless solutions were identified less accurately when they contained fruit acids (M = 25%) than when they did not (M = 46%). It seems plausible that adding fruit acids resulted in participants tending to think that the flavorless solutions had a flavor (perhaps because they confused their perception of sourness in the solutions with the perception of fruit flavor). Finally, the three-way interaction between Flavor, Color and Fruit acids just failed to reach significance [F(8, 96) = 1.98, p = .057]. None of the other terms in the analysis of the flavor identification data approached significance. Given that just three possible flavored solution were used in the present study (i.e., orange, blackcurrant, and flavorless), one might suggest that our participants may have begun to realise that only those solutions were being presented over time. If they had, this might then have affected the results from the later sessions. We investigated this possibility in a further analysis of our data where the flavor identification results in the first session were compared with those collected in the last session. However, this further analysis showed that our participants’ performance did not change over the course of the experimental sessions. These results therefore provide evidence against the possibility that our participants learned that they were being presented with only a limited range of fruit flavors in our study. Similar ANOVAs were conducted on the flavor, sourness, and sweetness intensity LMS ratings. However, before submitting these data to analysis, the participants’ individual mean responses were transformed to log 10, because the distribution of LMS ratings is typically lognormal (Green & George, 2004). The analysis of the flavor intensity log 10 converted data (see Fig. 2) revealed a significant main effect of Flavor [F(2, 26) = 15.95, p < .001], reflecting the fact that participants rated the intensity of the flavorless solutions as lower (M = .99) than either the orange or blackcurrant-flavored solutions (mean ratings of 1.23 and 1.32, respectively; the comparison between the latter two solutions was also significant). There was also a significant main effect of Fruit acids [F(1, 13) = 24.95, p < .001], reflecting the fact that solutions containing fruit acids were rated as having a more intense flavor (M = 1.29) than those that did not (M = 1.07). The interaction between Color and Fruit acids was also significant [F(4, 52) = 3.32, p = .017]. This reflects the fact that the participants rated the grey (M = 1.09), orange (M = 1.10), and red (M = 1.13) solutions as having a more intense flavor than either the yellow (M = 1.03) or colorless (M = 1.02) solutions when fruit acids were absent. No difference was found between the differently colored solutions when fruit acids were present. There was a significant interaction between Flavor and Color [F(8, 104) = 2.21,
Perceived flavor intensity (log10)
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1.8
Flavorless
1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Color of the solutions Fig. 2. Mean flavor intensity ratings for the blackcurrant, orange, and flavorless solutions. The black columns represent solutions where fruit acids had been added and the white columns indicate solutions without fruit acids. The error bars represent the between-participants standard errors of the means.
p = .03], showing that participants rated the intensity of the flavor of the blackcurrant-flavored solutions as being more intense when the solutions were colored grey (M = 1.39) than when they were colored either yellow (M = 1.30), orange (M = 1.29), red (M = 1.31), or else were colorless (M = 1.32). Moreover, the flavor of the orange-flavored solutions was rated as having a more intense flavor when the solutions were colored orange (M = 1.29) than when they were colored either yellow
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Perceived sourness intensity (log10)
(M = 1.23), grey (M = 1.20), or else were colorless (M = 1.22; the ratings of the red solutions were no different from any of the other solutions, M = 1.26). None of the other terms reached significance. The data from the LMS ratings of sourness intensity (see Fig. 3) were submitted to a similar ANOVA. This analysis revealed a significant main effect of Flavor [F(2, 26) = 14.11, p < .001], with the blackcurrant and orange-flavored solutions being rated as more sour
Blackcurrant
1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Perceived sourness intensity (log10)
Color of the solutions
Orange
1.8 1.6 1.4
4. Discussion
1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Color of the solutions Perceived sourness intensity (log10)
(M = 1.20 and 1.23, respectively) than the flavorless solutions (M = 1.11). The main effect of Fruit acids was also significant [F(1, 13) = 67.18, p < .001], revealing that the solutions containing fruit acids were rated as being more sour (M = 1.49) than those that did not (M = 0.88), as expected (McBride & Finlay, 1990). The significant interaction between Flavor and Fruit acids [F(2, 26) = 9.02, p = .001], reflects the fact that the participants rated the blackcurrant and orange-flavored solutions as being more acidic (M = 0.94 and 0.96, respectively) than the flavorless solutions (M = 0.76) when the fruit acids were absent, whereas there was no significant difference in sourness ratings when the fruit acids were present. None of the other terms reached significance. Finally, a similar analysis of the sweetness intensity ratings (see Fig. 4) revealed a significant main effect of Flavor [F(2, 26) = 4.94, p = .01], attributable to the fact that participants rated the blackcurrant solutions as being sweeter (M = 1.35) than the flavorless solutions (M = 1.30). The ratings of the orange solutions (M = 1.33) were not significantly different from the ratings of either the blackcurrant or flavorless solutions. The significant interaction between Color and Flavor [F(8, 104) = 2.81, p = .007], revealed that the orange-colored solutions were rated as sweeter when they had an orange flavor (M = 1.36) than when they were flavorless (M = 1.30). None of the other terms reached significance.
Flavorless
1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Color of the solutions Fig. 3. Mean sourness intensity ratings for the blackcurrant, orange, and flavorless solutions. The black columns represent solutions where fruit acids had been added and the white columns indicate solutions without fruit acids. The error bars represent the between-participants standard errors of the means.
One of the most important findings to emerge from the experiment reported here was the significant improvement in the accuracy of flavor identification responses when fruit acids were added to the solutions than when they were absent. In particular, participants were able to identify the flavor of the blackcurrant and orange-flavored solutions significantly more accurately when citric and malic acids were present than they were absent. Furthermore, the presence of fruit acids in the flavorless solutions resulted in the participants incorrectly identifying a flavor more often than when the fruit acids were absent, perhaps because adding fruit acids may have resulted in participants tending to think that the flavorless solutions had a flavor (that is, they may have confused their perception of sourness in the solutions for the perception of fruit flavor). One possible explanation for the better identification of the flavors of the beverages with fruit acids might be related to the fact that fruit acids (such as citric and malic acid) are naturally present in many fruits (Henshall, 1998; Valde´s, Hinreiner, & Simone, 1956a). Adding the appropriate fruit acids to the artificial fruit flavors used in the present study might therefore have helped to simulate ‘natural’ fruit flavor, and thus enhance the ‘flavor profile’ of the fruit-flavored solutions (King & Duineveld, 1998; Sortwell & Woo, 1996). However, it is worth noting that the perception of sourness is typically increased by adding acids.
Perceived sweetness intensity (log10)
M. Zampini et al. / Food Quality and Preference 19 (2008) 335–343 1.8
Blackcurrant
1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Perceived sweetness intensity (log10)
Color of the solutions 1.8
Orange
1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Perceived sweetness intensity (log10)
Color of the solutions 1.8
Flavorless
1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Color of the solutions Fig. 4. Mean sweetness intensity ratings for the blackcurrant, orange, and flavorless solutions. The black columns represent solutions where fruit acids had been added and the white columns indicate solutions without fruit acids. The error bars represent the between-participants standard errors of the means.
Therefore, it could be argued that the perception of sourness per se might have improved participants’ flavor identification responses. This might be particularly true for fruits flavors that are very acidic, such as the blackcurrant and orange used in the present study. In future research, it will therefore be important to investigate whether the presence of acids that are not naturally (or normally) present in fruits would also have a similar effect on people’s perception of fruit-flavored solutions as well.
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Another (already well-established) result to emerge from the present study is the impact of color cues on flavor identification responses. The ability of our participants to identify the flavor of the beverages correctly improved significantly when the solutions were colored appropriately than when they were colored inappropriately, or else when they were presented as colorless solutions. The identification of the blackcurrant-flavored solutions was enhanced when they were colored grey (as in many blackcurrant-flavored yoghurts) and the orange-flavored solutions were more often identified correctly when they were colored orange (cf. Clydesdale, 1993; DuBose et al., 1980; Johnson & Clydesdale, 1982; Morrot et al., 2001; Philipsen et al., 1995; Roth et al., 1988, for a selection of the previous studies that have highlighted the role of visual color cues on people’s flavor identification responses). It should be noted that the colors of the solutions influenced participants’ flavor identification responses despite the fact that the experimenters informed the participants that the colors of the solutions would often be inappropriate to the flavor of the beverage that they were tasting (see also Zampini et al. (2007), on this point). Therefore, these results show that the modulatory role of visual information on flavor identification responses is robust enough to override any awareness that participants may have concerning the appropriateness of the color–flavor link in the solutions presented. In order to assess whether the participants’ taster status modulated their multisensory flavor perception, we conducted a further post-hoc analysis of the data. In particular, the data regarding the accuracy of participants’ flavor identification responses (see Fig. 5) were submitted to a mixed between–within repeated-measures ANOVA with the factors of Taster status (non-tasters (4), medium tasters (5), and supertasters (5)), Flavor (blackcurrant, orange, and flavorless), Color (yellow, grey, orange, red, or colorless), and Fruit acids (present vs. absent). The analysis of the flavor identification data revealed a significant between-participants effect of Taster status [F(1, 10) = 22.67, p < .001], with the supertasters responding more accurately (M = 67% correct responses) than the medium tasters (M = 31%) who, in turn, were more accurate in their flavor identification responses that the non-tasters (M = 19%), as one might have expected (e.g., see Prescott, 2004). The three-way interaction between Flavor, Color, and Taster status was also significant [F(16, 80) = 1.99, p = .02], reflecting the fact that the nontasters responded more accurately when the blackcurrantflavored solutions were colored grey (53%) than when they were colored orange (7%), yellow (4%), red (3%), or colorless (5%). The non-tasters were also more accurate when the orange-flavored solutions were colored orange (51%) than when they were colored yellow (35%), grey (17%), red (2%), or else were colorless (12%). The medium tasters identified the blackcurrant solutions more accurately when they were colored grey (59%), than when they were colored red (21%), yellow (13%), orange
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Fig. 5. Mean percentage of correct flavor identification responses for the three groups of participants (non-tasters, medium tasters, and supertasters) for the blackcurrant, orange, and flavorless solutions. The black columns represent solutions where fruit acids had been added and the white columns solutions without fruit acids. The error bars represent the between-participants standard errors of the means.
(5%) or else were colorless (10%); They also identified the flavor of the orange-flavored solutions significantly more accurately when the solutions were colored orange, yellow (both 42%), or red (37%), than when they were colored grey (24%) or were colorless (25%). Interestingly, the supertasters were seemingly not influenced by the color of the solutions when identifying their flavors (as shown by the non-significance of all the t-test pairwise comparisons). The results of this post-hoc analysis therefore show that the modulatory effect of visual cues on people’s flavor identification responses are more pronounced in non-tasters than in medium tasters who in turn showed more of an influence of visual cues on their flavor identification responses than did the supertasters. To our knowledge, this result provides the first empirical demonstration that taster status can modulate the influence of visual cues on people’s flavor perception. However, this potentially very interesting result should really be investigated in further studies given the relatively small number of participants in each category.
Acknowledgement This study was supported by a research grant from Unilever Research and Development. M.Z. is currently supported by a ‘Rientro dei Cervelli’ returning grant. References Alley, R. L., & Alley, T. R. (1998). The influence of physical state and color on perceived sweetness. Journal of Psychology, 132, 561–568. Bartoshuk, L. M., Duffy, V. B., & Miller, I. J. (1994). PTC/PROP tasting: Anatomy, psychophysics, and sex effects. Physiology & Behavior, 56, 1165–1171. Bonnans, S., & Noble, A. C. (1993). Effect of sweetener type and of sweetener and acid levels on temporal perception of sweetness, sourness, and fruitiness. Chemical Senses, 18, 273–283. Buettner, A., Beer, A., Hannig, C., & Settles, M. (2001). Observation of the swallowing process by application of videofluoroscopy and realtime magnetic resonance imaging-consequences for retronasal aroma stimulation. Chemical Senses, 26, 1211–1219. Clydesdale, F. M. (1993). Color as a factor in food choice. Critical Reviews in Food Science and Nutrition, 33, 83–101.
M. Zampini et al. / Food Quality and Preference 19 (2008) 335–343 DuBose, C. N., Cardello, A. V., & Maller, O. (1980). Effects of colorants and flavorants on identification, perceived flavor intensity, and hedonic quality of fruit-flavored beverages and cake. Journal of Food Science, 45, 1393–1399, 1415. Engen, T. (1972). The effect of expectation on judgments of odour. Acta Psychologica, 36, 450–458. Essick, G. K., Chopra, A., Guest, S., & McGlone, F. (2003). Lingual tactile acuity, taste perception, and the density and diameter of fungiform papillae in female subjects. Physiology & Behavior, 80, 289–302. Fabian, F. W., & Blum, H. B. (1943). Relative taste potency of some basic food constituents and their competitive and compensatory action. Food Research, 8, 179–193. Gifford, S. R., & Clydesdale, F. M. (1986). The psychophysical relationship between color and sodium chloride concentrations in model systems. Journal of Food Protection, 49, 977–982. Gifford, S. R., Clydesdale, F. M., & Damon, R. A. Jr., (1987). The psychophysical relationship between color and salt concentration in chicken flavored broths. Journal of Sensory Studies, 2, 137–147. Green, B. G., & George, P. (2004). ‘Thermal taste’ predicts higher responsiveness to chemical taste and flavor. Chemical Senses, 29, 617–628. Green, B. G., Shaffer, G. S., & Gilmore, M. M. (1993). Derivation and evaluation of a semantic scale of oral sensation with apparent ratio properties. Chemical Senses, 18, 683–702. Henshall, A. (1998). Liquid chromatographic techniques for detecting economic adulteration of foods. Cereal Foods World, 43, 98–103. Hodgson, M., Linforth, R. S. T., & Taylor, A. J. (2003). Simultaneous real-time measurements of mastication, swallowing, nasal airflow, and aroma release. Journal of Agricultural and Food Chemistry, 51, 5052–5057. Ishihara, S. (1943). The series of plates designed as tests for color blindness (ninth ed. (Complete Edition)). London: H.K. Lewis & Co Ltd. Johnson, J., & Clydesdale, F. M. (1982). Perceived sweetness and redness in colored sucrose solutions. Journal of Food Science, 47, 747–752. Kamen, J. M., Pilgrim, F. J., Gutman, N. J., & Kroll, B. J. (1961). Interaction of suprathreshold taste stimuli. Journal of Experimental Psychology, 62, 348–356. King, B. M., & Duineveld, C. A. (1998). Factors affecting the perception of naturalness and flavor strength in citrus drinks. Annals of the New York Academy of Sciences, 855, 847–853. Kuo, Y. L., Pangborn, R. M., & Noble, A. C. (1993). Temporal patterns of nasal, oral and retronasal perception of citral and vanillin and interaction of these odourants with selected tastants. International Journal of Food Science and Technology, 28, 127–137. Lavin, J., & Lawless, H. T. (1998). Effects of color and odor on judgments of sweetness among children and adults. Food Quality and Preference, 9, 283–289. Maga, J. A. (1974). Influence of color on taste thresholds. Chemical Senses and Flavor, 1, 115–119. McBride, R. L., & Finlay, D. C. (1989). Perception of taste mixtures by experienced and novice assessors. Journal of Sensory Studies, 3, 237–248. McBride, R. L., & Finlay, D. C. (1990). Perceptual integration of tertiary taste mixtures. Perception & Psychophysics, 48, 326–330.
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Morrot, G., Brochet, F., & Dubourdieu, D. (2001). The color of odors. Brain and Language, 79, 309–320. O’Doherty, J., Rolls, E. T., Francis, S., Bowtell, R., & McGlone, F. (2001). Representation of pleasant and aversive taste in the human brain. Journal of Neurophysiology, 85, 1315–1321. Pangborn, R. M. (1960). Taste interrelationships. Food Research, 25, 245–256. Pangborn, R. M. (1961). Taste interrelationships II. Suprathreshold solutions of sucrose and citric acid. Journal of Food Science, 26, 648–655. Pangborn, R. M. (1965). Taste interrelationships of organic acids and selected sugars. In J. M. Leitch (Ed.), Proceedings of the first international congress of food and science technology, London, 1962 (pp. 291–305). New York: Gordon and Breach Science Publisher. Pfeiffer, J. C., Hort, J., Hollowood, T. A., & Taylor, A. J. (2006). Taste– aroma interactions in a ternary system: A model of fruitiness perception in sucrose/acid solutions. Perception & Psychophysics, 68, 216–227. Philipsen, D. H., Clydesdale, F. M., Griffin, R. W., & Stern, P. (1995). Consumer age affects response sensory characteristics of a cherry flavored beverage. Journal of Food Science, 60, 364–368. Prescott, J. (2004). Psychological processes in flavour perception. In A. J. Taylor & D. Roberts (Eds.), Flavour perception (pp. 256–277). London: Blackwell Publishing. Roth, H. A., Radle, L. J., Gifford, S. R., & Clydesdale, F. M. (1988). Psychophysical relationships between perceived sweetness and color in lemon- and lime-flavored drinks. Journal of Food Science, 53, 1116– 1119, 1162. Schifferstein, H. N. J., & Frijters, J. E. R. (1990). Sensory integration in citric acid/sucrose mixtures. Chemical Senses, 15, 87–109. Sjo¨stro¨m, L. B., & Cairncross, S. E. (1953). Role of sweeteners in food flavor. Advances in Chemistry Series, 12, 108–113. Sortwell, D., & Woo, A. (1996). Improving flavor of fruit products with acidulants. Paper presented at the Expotecnoalimentaria’96, Mexico City, Mexico. (http://www.bartek.ca/pdfs/BulletinsFumaric (Downloaded on 20-01-2004). Strugnell, C. (1997). Colour and its role in sweetness perception. Appetite, 28, 85. Valde´s, R. M., Hinreiner, E. H., & Simone, M. J. (1956a). Effect of sucrose and organic acids on apparent flavor intensity. I. Aqueous solutions. Food Technology, 10, 282–285. Valde´s, R. M., Simone, M. J., & Hinreiner, E. H. (1956b). Effect of sucrose and organic acids on apparent flavor intensity. II. Fruit nectars. Food Technology, 10, 387–390. Zampini, M., Sanabria, D., Phillips, N., & Spence, C. (2007). The multisensory perception of flavor: Assessing the influence of color cues on flavor discrimination responses. Food Quality and Preference, 18, 975–984. Zellner, D. A., & Durlach, P. (2003). Effect of color on expected and experienced refreshment, intensity, and liking of beverages. American Journal of Psychology, 116, 633–647. Zellner, D. A., & Kautz, M. A. (1990). Color affects perceived odor intensity. Journal of Experimental Psychology: Human Perception and Performance, 16, 391–397.
Food Quality and Preference 19 (2008) 335–343 www.elsevier.com/locate/foodqual
Multisensory flavor perception: Assessing the influence of fruit acids and color cues on the perception of fruit-flavored beverages Massimiliano Zampini a,b,c,*, Emma Wantling d, Nicola Phillips e, Charles Spence a a
Crossmodal Research Laboratory, Department of Experimental Psychology, University of Oxford, South Parks Road, Oxford OX1 3UD, United Kingdom b Department of Cognitive Sciences and Education, University of Trento, Corso Bettini 31, 38068 Rovereto (TN), Italy c Center for Mind/Brain Sciences, University of Trento, Rovereto, Italy d Unilever Research, Colworth House, Sharnbrook, England, United Kingdom e Unilever Research, Port Sunlight, Bebington, England, United Kingdom Received 10 May 2007; received in revised form 6 November 2007; accepted 6 November 2007 Available online 13 November 2007
Abstract We report a study designed to investigate the influence of fruit acids (in particular, citric and malic acid) on people’s perception of the identity and the intensity of a variety of different fruit-flavored solutions. Participants had to identify the flavor of fruit-flavored drinks that were colored yellow, grey, orange, red, or else were presented as colorless solutions. The participants also rated the intensity of flavor, sweetness, and sourness of each solution using a Labelled Magnitude Scale (LMS). The participants identified the flavors of the beverages more accurately when citric and malic acids were added to the solutions, and/or when the solutions were colored appropriately. Moreover, the perception of flavor intensity was modulated by the presence of the fruit acids in the solutions. Ó 2007 Elsevier Ltd. All rights reserved. Keywords: Flavor perception; Multisensory perception; Color; Citric and malic acid; Fruit-flavored beverages; Taster status
1. Introduction It is well-known that people’s perception of the flavor of many beverages can be influenced by their color (Alley & Alley, 1998; Clydesdale, 1993; DuBose, Cardello, & Maller, 1980; Johnson & Clydesdale, 1982; Morrot, Brochet, & Dubourdieu, 2001; Philipsen, Clydesdale, Griffin, & Stern, 1995; Roth, Radle, Gifford, & Clydesdale, 1988; Zellner & Durlach, 2003). In one frequently cited study, Dubose et al. showed that inappropriately coloring a cherry-flavored beverage (i.e., by using incongruent coloring) resulted in a significant decrease in participants’ ability to identify the cherry flavor correctly. For instance, 26% of the partic*
Corresponding author. Address: Department of Cognitive Sciences and Education & Center for Brain/Mind Sciences, University of Trento, Corso Bettini, 31, 38068 Rovereto (TN), Italy. Tel.: +39 0464 483661; fax: +39 0464 483554 (M. Zampini). E-mail address: [email protected] (M. Zampini). 0950-3293/$ - see front matter Ó 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodqual.2007.11.001
ipants in their study reported that they were drinking a lime-flavored beverage when the drink was colored green as compared to no lime-flavor responses when the drink was colored red. Maga (1974) suggested that those colors that are typically associated with the natural ripening of fruits (e.g., yellow, red, etc.) may be particularly effective in modulating sweetness perception (Strugnell, 1997). By contrast, researchers have reported that the addition of color has far less of an effect on the perceived saltiness of foods such as soups (Gifford & Clydesdale, 1986; Gifford, Clydesdale, & Damon, 1987; Maga, 1974), perhaps because (in contrast to sweet foods) there are no particular colors associated with the salt content of a food (i.e., salt is ubiquitous to many different kinds, and hence colors, of food; see Maga, 1974, see also Lavin & Lawless, 1998, on this point). A relatively independent line of food science research has demonstrated that the perception of flavor intensity in various fruit-flavored beverages can also be enhanced
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by adding the appropriate fruit acids (King & Duineveld, 1998; Kuo, Pangborn, & Noble, 1993; Pfeiffer, Hort, Hollowood, & Taylor, 2006; Sortwell & Woo, 1996; Valde´s, Simone, & Hinreiner, 1956b). For example, Sortwell and Woo have argued that adding the appropriate fruit acids (i.e., those that are naturally present in fruits) can result in participants judging flavors as being more ‘natural’. Pfeiffer et al. have also shown that increasing the citric and malic acid content results in an increase in the perceived intensity of strawberry flavored solutions. Therefore, it seemed plausible to us that the presence of the appropriate fruit acids might improve participants’ flavor identification performance since they may increase people’s perception of both the naturalness and the intensity of the flavor of fruit-flavored solutions (King & Duineveld, 1998; Sortwell & Woo, 1996). Alternatively, however, it also seemed possible that if people perceived the flavor of fruit more clearly then they might have a stronger association with the appropriate color (Maga, 1974), and thus color cues might exert a stronger influence on people’s flavor identification responses. The primary aim of the experiment reported in the present study was therefore to investigate whether the influence of fruit acids on people’s perception of flavor intensity would modulate their ability to correctly identify the various fruit-flavored solutions that were presented as a function of whether they were colored appropriately or not. The present study also investigated whether the welldemonstrated visual influence over flavor perception in colored drinks would be influenced by the addition of the appropriate fruit acids to flavored-colored solutions. To the best of our knowledge, no one has previously addressed the question of whether the influence of visual cues on flavor perception can be modulated by the presence versus absence of the appropriate fruit acid ‘signatures’ (i.e., the acids that are naturally and normally present in fruits). Our prediction was that color cues might become more effective in enhancing sweetness and flavor perception when the appropriate fruit signatures were added to the beverages tested in the present study (though note that the addition of fruit acids might also be expected to reduce the overall level of sweetness). In particular, researchers have demonstrated that the addition of citric acid suppresses the perception of sweetness in sucrose solutions (see Bonnans & Noble, 1993; McBride & Finlay, 1989, 1990; Pangborn, 1961, 1965; Schifferstein & Frijters, 1990; though see also Fabian & Blum, 1943; Kamen, Pilgrim, Gutman, & Kroll, 1961; Pangborn, 1960; Sjo¨stro¨m & Cairncross, 1953). 2. Methods 2.1. Participants Fourteen participants (9 females and 5 males; mean age of 36 years; range from 22 to 58 years) took part in this study. The participants were selected from a panel of
untrained individuals recruited from the staff at Unilever Research (Colworth House, Sharnbrook, UK). All of the participants had normal color-vision as assessed by means of the Ishihara test for color blindness (Ishihara, 1943). Individuals who were pregnant, smokers, diabetic, hypoglycaemic, and those who suffered from thyroid problems were excluded from the study. None of the participants reported having a cold or other respiratory tract infection either on the days of the testing sessions or in the week prior to testing. All of the participants completed each experimental session at the same time. All of the participants gave their informed consent prior to taking part in the study, and all received £30 (UK Sterling) in return for completing the study. The study had ethical approval from Unilever Research Colworth House Laboratory. The experiment consisted of three testing sessions each lasting 100 min. Each testing session was conducted on a different day. 2.2. Apparatus and materials The participants were seated comfortably in an individual testing booth in front of a computer screen at the Colworth House testing suite. During the experiment, each participant received a series of plastic cups of colored and/or flavored solutions. One transparent cup was dispensed on each trial through a small window in front of the participant by one of the experimenters. The plastic cups were presented at room temperature (20 ± 2 °C). The flavored solutions were prepared from 1 l of distilled water with 75 g pure cane sugar added (Tate and Lyle, Warrington, UK) stirred until dissolved, and from concentrated fruit flavors (Quest International, Naarden, The Netherlands). Orange flavoring (0.8 ml ) and 1 ml of blackcurrant flavoring were added to 1 l of solution to flavor them orange and blackcurrant, respectively (as suggested by Quest International). Yellow, orange, grey, and red food colorings (Supercook, Leeds, UK) were used to color the solutions: 1.6 ml of yellow food coloring was added to 1 l of distilled water to color solutions yellow; the orange color was created by adding 0.8 ml of red and 4 ml of yellow food coloring; the grey coloring was achieved by combining 0.8 ml of yellow, 0.8 ml of red, and 2 ml of blue food coloring; and the red color by adding 1.6 ml of red food coloring to 1 l of distilled water. The criteria for selecting these colors were that they should be the colors that participants typically associated with the flavors used (e.g. orange–orange; blackcurrant-grey). The particular colors used in the present study emerged from a previous study on visual-flavor interactions (Zampini, Sanabria, Phillips, & Spence, 2007). There were also colorless samples that were made from distilled water, flavorings, and sucrose (but no coloring). In order to ensure that the participants in the present study were not able to derive any potentially useful information concerning the likely flavor of a given solution from
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its color alone, each of the flavorings (orange, blackcurrant, or flavorless) was presented equiprobably with each of the different colors (yellow, grey, orange, red, or colorless). Flavorless samples were also presented to the participants, and these could either be colored or colorless, just as for the flavored solutions. In half of the solutions, 0.9 ml of citric acid and 0.1 ml of malic acid were added per litre of solution (Sortwell & Woo, 1996). The flavorings, colorings, and acids used in the present study were cleared for human consumption by the Safety and Environmental Assurance Centre at Unilever Research, Colworth House.1 The bottled solutions were prepared on the morning of each experimental session, used during the day of the session, and any remaining solutions were discarded at the end of each experimental session. The experimenters dispensed 40 ml of the solutions from the airtight glass bottles into the clear plastic cups immediately prior to the experimental testing session using sterile syringes. The participants were given 40 ml of a tasteless palate cleansing solution (‘artificial saliva’) between each trial to wash their mouths out before tasting the next solution. This palate cleansing solution was made from deionised water using the main ionic components of saliva, 1.865 g/l of potassium chloride (KCl), and 0.210 g/l of sodium bicarbonate (NaHCO3; O’Doherty, Rolls, Francis, Bowtell, & McGlone, 2001). All of the apparatus associated with the preparation of the solutions (except the bottles, which were rinsed with boiled water and fully dried) were discarded at the end of each experimental testing session. 2.3. Design There were three within-participants factors: Flavor of the solution (blackcurrant, orange, or flavorless), Color of the solution (yellow, grey, orange, red, or colorless), and Fruit acids (present vs. absent). These factors were fully crossed giving rise to 30 conditions in total, which were each presented twice in each of three experimental sessions. 60 randomly ordered trials were presented in each experimental session, giving rise to a total of 180 stimuli tasted by each participant.
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2.4. Procedure All of the participants were given both written and oral instructions to view the solution on each trial from above the plastic cup and then to taste the solution. They were instructed to ensure that they moved the liquid around their mouths while making sure not to swallow it.2 After tasting each of the solutions, the participants were asked to spit them into the bucket provided. The participants were then asked to rinse their mouths thoroughly with the palate cleansing solution (again without swallowing) and to spit this into the bucket as well. On each trial, the participants were first asked to identify the flavor of the solution by ticking a box on a list of possible flavors presented on the computer monitor in front of them. The possible flavors were: strawberry, pear, mango, melon, grapefruit, lime, orange, papaya, cherry, peach, raspberry, blackcurrant, pineapple, grape, plum, apple, flavorless, or other. If the participants indicated the ‘other’ option they were prompted to suggest the specific flavor that they had in mind. (Note that the ‘other’ option was used on less than 2% of trials overall). The participants were also asked to evaluate the flavor intensity, sweetness intensity, and sourness intensity of each solution using a Labelled Magnitude Scale (LMS; Green, Shaffer, & Gilmore, 1993) that appeared on the computer monitor (see Fig. 1). The participants were fully informed and trained (but not experienced) in the use of the scale. They were instructed as to how to interpret the verbal descriptors (e.g., ‘strongest imaginable sensation’ on the top of the scale). The three scales for rating the intensity of the flavor, its sweetness, and its sourness were presented sequentially, although in a random order for each trial after the participants had made their flavor identification response. The sensation to be rated (i.e., flavor, sweetness, or sourness) appeared on the computer monitor each time the participant had to make a rating response. The list of flavors and the three LMS scales were presented on the computer screen placed in front of them using the Fizz software (Biosystemes, Couternon, France). The participants were explicitly informed that the color of the solutions should not be considered to provide a reliable cue to identify the flavors of the solutions that they were about to taste since all of the flavors had been crossed equiprobably with each of the colors (cf. Zampini et al., 2007).
1
In a preliminary experiment, we investigated whether the food colorings or fruit acids used in the present study would add some additional flavor to the sucrose solutions. To this end, the participants (N = 14 participants) were blindfolded and then instructed to compare two sucrose solutions, one with fruit acids (citric and malic acid) added. The participants reported that the latter solutions tasted sourer than the former samples but they did not report any difference between the flavor of the two solutions. The participants were then presented with two sucrose solutions to compare with the food colorings used in the present study added to one of the solutions. The participants reported no difference between the two samples. These results show that, by themselves, the food coloring and fruit acids did not add any flavor to the solutions tested in the present study.
2 The main reason for instructing the participants not to swallow was that we thought that they would have found it rather unpleasant to drink such a large quantity of liquid. The participants actually tasted 180 cups 40 ml = about 7 l of liquid in total. However, it is important to note on this point that previous studies have shown that people vary quite considerably in terms of the retro-nasal delivery of odors/flavors when swallowing is prevented (see Buettner, Beer, Hannig, & Settles, 2001; Hodgson, Linforth, & Taylor, 2003). The fact that the participants did not swallow the drinks in the present study therefore represents something of a limitation in terms of the ecological validity of our experimental design given that people normally swallow the beverages/foodstuffs that they put in their mouths.
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Correct responses (%)
classified into one of three taster groups: non-tasters, medium tasters, and supertasters, based on the cut-off values (non-tasters < 10.90; 10.91 < medium tasters < 61.48; supertasters > 61.49; see Essick, Chopra, Guest, & McGlone (2003), for a similar criterion). Using this criterion, 4 of the participants were classified as non-tasters, 5 as medium tasters, and 5 as supertasters.
Blackcurrant
100
75
50
3. Results
25
0
yellow
grey
orange
red
colorless
Color of the solutions
Orange
Correct responses (%)
100
75
50
25
0
yellow
grey
orange
red
colorless
Color of the solutions
Correct responses (%)
100
Flavorless
75
50
25
0
yellow
grey
orange
red
colorless
Color of the solutions Fig. 1. Mean percentage of correct flavor identification for the blackcurrant, orange, and flavorless solutions. The black columns represent solutions where fruit acids had been added and the white columns indicate solutions without fruit acids. The error bars represent the betweenparticipants standard errors of the means.
Before starting the experiment, the taster status of the participants was evaluated using 6-n-propylthiouracil (PROP) filter paper strips (Bartoshuk, Duffy, & Miller, 1994). The participants were instructed to place a PROP filter paper strip on their tongue. Next, they were instructed to close their mouth and moisten the paper with saliva for 20 s. Finally, the participants had to remove the paper strips from their mouths, swallow the saliva residue and then rate the intensity of the sensation of bitterness they experienced on an LMS scale. The participants were then
The data on the accuracy of participants’ flavor identification responses are summarized in Fig. 1. In the analysis of the flavor identification data, the frequency of participants’ responses were calculated first. Next, the percentage of correct responses were submitted to a repeated-measures analysis of variance (ANOVA) with the factors of Flavor (blackcurrant, orange, and flavorless), Color (yellow, grey, orange, red, or colorless), and Fruit acids (present vs. absent). For all of the analyses reported here, post-hoc comparisons used Bonferroni-corrected t-tests (where p < .05 prior to correction). The data analysis revealed a significant main effect of Color [F(4, 48) = 5.49, p = .001], with participants identifying the correct flavor more frequently when the solutions were colored grey (Mean = 46% correct responses), orange (M = 42%), or yellow (M = 39%), than when they were either colorless (M = 35%), or else colored red (M = 32%; post-hoc comparisons between the means of the three former conditions and between the means of the two latter conditions revealed no significant differences). The analysis of the flavor identification data also revealed a significant interaction between Color and Flavor [F(8, 96) = 8.33, p < .001], reflecting the fact that the blackcurrant flavor was identified more accurately when the solutions were colored grey (M = 64%) than when they were colored red (M = 32%), colorless (M = 30%), yellow, or orange (both M = 28%; none of the other comparisons approached significance). This result presumably reflects the fact that many blackcurrant-flavored products (such as, for example, blackcurrant-flavored yoghurts) are typically given a greyish-purple color. The orange-flavored solutions were also identified more accurately when they were colored orange (M = 63%) than when they were colored yellow (M = 49%), grey (M = 39%), red (M = 33%), or when they were presented as colorless solutions (M = 36%). This result is consistent with DuBose et al.’s (1980) finding that people are more likely to report that a cherry-flavored drink tasted of orange when it was colored orange than when it was colored red, green, or colorless. Finally, the ability of our participants to identify the flavorless solutions correctly (i.e., as being flavorless) was not affected by the color of the solutions (Engen, 1972; Zellner & Kautz, 1990). The significant interaction between Flavor and Fruit acids [F(2, 24) = 8.65, p = .001] can be attributed to the fact the participants identified the blackcurrant and orange-flavored solutions more accurately when they contained fruit
1.8
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Blackcurrant
1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Perceived flavor intensity (log10)
Color of the solutions
Orange
1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Color of the solutions Perceived flavor intensity (log10)
acids (M = 38% and 48%, respectively) than when they did not (M = 32% and 38%, respectively). This pattern of results is consistent with the claim that adding the appropriate fruit acids to a fruit-flavored beverage will lead to an increase in correct flavor identification responses. By contrast, the flavorless solutions were identified less accurately when they contained fruit acids (M = 25%) than when they did not (M = 46%). It seems plausible that adding fruit acids resulted in participants tending to think that the flavorless solutions had a flavor (perhaps because they confused their perception of sourness in the solutions with the perception of fruit flavor). Finally, the three-way interaction between Flavor, Color and Fruit acids just failed to reach significance [F(8, 96) = 1.98, p = .057]. None of the other terms in the analysis of the flavor identification data approached significance. Given that just three possible flavored solution were used in the present study (i.e., orange, blackcurrant, and flavorless), one might suggest that our participants may have begun to realise that only those solutions were being presented over time. If they had, this might then have affected the results from the later sessions. We investigated this possibility in a further analysis of our data where the flavor identification results in the first session were compared with those collected in the last session. However, this further analysis showed that our participants’ performance did not change over the course of the experimental sessions. These results therefore provide evidence against the possibility that our participants learned that they were being presented with only a limited range of fruit flavors in our study. Similar ANOVAs were conducted on the flavor, sourness, and sweetness intensity LMS ratings. However, before submitting these data to analysis, the participants’ individual mean responses were transformed to log 10, because the distribution of LMS ratings is typically lognormal (Green & George, 2004). The analysis of the flavor intensity log 10 converted data (see Fig. 2) revealed a significant main effect of Flavor [F(2, 26) = 15.95, p < .001], reflecting the fact that participants rated the intensity of the flavorless solutions as lower (M = .99) than either the orange or blackcurrant-flavored solutions (mean ratings of 1.23 and 1.32, respectively; the comparison between the latter two solutions was also significant). There was also a significant main effect of Fruit acids [F(1, 13) = 24.95, p < .001], reflecting the fact that solutions containing fruit acids were rated as having a more intense flavor (M = 1.29) than those that did not (M = 1.07). The interaction between Color and Fruit acids was also significant [F(4, 52) = 3.32, p = .017]. This reflects the fact that the participants rated the grey (M = 1.09), orange (M = 1.10), and red (M = 1.13) solutions as having a more intense flavor than either the yellow (M = 1.03) or colorless (M = 1.02) solutions when fruit acids were absent. No difference was found between the differently colored solutions when fruit acids were present. There was a significant interaction between Flavor and Color [F(8, 104) = 2.21,
Perceived flavor intensity (log10)
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1.8
Flavorless
1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Color of the solutions Fig. 2. Mean flavor intensity ratings for the blackcurrant, orange, and flavorless solutions. The black columns represent solutions where fruit acids had been added and the white columns indicate solutions without fruit acids. The error bars represent the between-participants standard errors of the means.
p = .03], showing that participants rated the intensity of the flavor of the blackcurrant-flavored solutions as being more intense when the solutions were colored grey (M = 1.39) than when they were colored either yellow (M = 1.30), orange (M = 1.29), red (M = 1.31), or else were colorless (M = 1.32). Moreover, the flavor of the orange-flavored solutions was rated as having a more intense flavor when the solutions were colored orange (M = 1.29) than when they were colored either yellow
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Perceived sourness intensity (log10)
(M = 1.23), grey (M = 1.20), or else were colorless (M = 1.22; the ratings of the red solutions were no different from any of the other solutions, M = 1.26). None of the other terms reached significance. The data from the LMS ratings of sourness intensity (see Fig. 3) were submitted to a similar ANOVA. This analysis revealed a significant main effect of Flavor [F(2, 26) = 14.11, p < .001], with the blackcurrant and orange-flavored solutions being rated as more sour
Blackcurrant
1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Perceived sourness intensity (log10)
Color of the solutions
Orange
1.8 1.6 1.4
4. Discussion
1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Color of the solutions Perceived sourness intensity (log10)
(M = 1.20 and 1.23, respectively) than the flavorless solutions (M = 1.11). The main effect of Fruit acids was also significant [F(1, 13) = 67.18, p < .001], revealing that the solutions containing fruit acids were rated as being more sour (M = 1.49) than those that did not (M = 0.88), as expected (McBride & Finlay, 1990). The significant interaction between Flavor and Fruit acids [F(2, 26) = 9.02, p = .001], reflects the fact that the participants rated the blackcurrant and orange-flavored solutions as being more acidic (M = 0.94 and 0.96, respectively) than the flavorless solutions (M = 0.76) when the fruit acids were absent, whereas there was no significant difference in sourness ratings when the fruit acids were present. None of the other terms reached significance. Finally, a similar analysis of the sweetness intensity ratings (see Fig. 4) revealed a significant main effect of Flavor [F(2, 26) = 4.94, p = .01], attributable to the fact that participants rated the blackcurrant solutions as being sweeter (M = 1.35) than the flavorless solutions (M = 1.30). The ratings of the orange solutions (M = 1.33) were not significantly different from the ratings of either the blackcurrant or flavorless solutions. The significant interaction between Color and Flavor [F(8, 104) = 2.81, p = .007], revealed that the orange-colored solutions were rated as sweeter when they had an orange flavor (M = 1.36) than when they were flavorless (M = 1.30). None of the other terms reached significance.
Flavorless
1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Color of the solutions Fig. 3. Mean sourness intensity ratings for the blackcurrant, orange, and flavorless solutions. The black columns represent solutions where fruit acids had been added and the white columns indicate solutions without fruit acids. The error bars represent the between-participants standard errors of the means.
One of the most important findings to emerge from the experiment reported here was the significant improvement in the accuracy of flavor identification responses when fruit acids were added to the solutions than when they were absent. In particular, participants were able to identify the flavor of the blackcurrant and orange-flavored solutions significantly more accurately when citric and malic acids were present than they were absent. Furthermore, the presence of fruit acids in the flavorless solutions resulted in the participants incorrectly identifying a flavor more often than when the fruit acids were absent, perhaps because adding fruit acids may have resulted in participants tending to think that the flavorless solutions had a flavor (that is, they may have confused their perception of sourness in the solutions for the perception of fruit flavor). One possible explanation for the better identification of the flavors of the beverages with fruit acids might be related to the fact that fruit acids (such as citric and malic acid) are naturally present in many fruits (Henshall, 1998; Valde´s, Hinreiner, & Simone, 1956a). Adding the appropriate fruit acids to the artificial fruit flavors used in the present study might therefore have helped to simulate ‘natural’ fruit flavor, and thus enhance the ‘flavor profile’ of the fruit-flavored solutions (King & Duineveld, 1998; Sortwell & Woo, 1996). However, it is worth noting that the perception of sourness is typically increased by adding acids.
Perceived sweetness intensity (log10)
M. Zampini et al. / Food Quality and Preference 19 (2008) 335–343 1.8
Blackcurrant
1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Perceived sweetness intensity (log10)
Color of the solutions 1.8
Orange
1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Perceived sweetness intensity (log10)
Color of the solutions 1.8
Flavorless
1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0
yellow
grey
orange
red
colorless
Color of the solutions Fig. 4. Mean sweetness intensity ratings for the blackcurrant, orange, and flavorless solutions. The black columns represent solutions where fruit acids had been added and the white columns indicate solutions without fruit acids. The error bars represent the between-participants standard errors of the means.
Therefore, it could be argued that the perception of sourness per se might have improved participants’ flavor identification responses. This might be particularly true for fruits flavors that are very acidic, such as the blackcurrant and orange used in the present study. In future research, it will therefore be important to investigate whether the presence of acids that are not naturally (or normally) present in fruits would also have a similar effect on people’s perception of fruit-flavored solutions as well.
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Another (already well-established) result to emerge from the present study is the impact of color cues on flavor identification responses. The ability of our participants to identify the flavor of the beverages correctly improved significantly when the solutions were colored appropriately than when they were colored inappropriately, or else when they were presented as colorless solutions. The identification of the blackcurrant-flavored solutions was enhanced when they were colored grey (as in many blackcurrant-flavored yoghurts) and the orange-flavored solutions were more often identified correctly when they were colored orange (cf. Clydesdale, 1993; DuBose et al., 1980; Johnson & Clydesdale, 1982; Morrot et al., 2001; Philipsen et al., 1995; Roth et al., 1988, for a selection of the previous studies that have highlighted the role of visual color cues on people’s flavor identification responses). It should be noted that the colors of the solutions influenced participants’ flavor identification responses despite the fact that the experimenters informed the participants that the colors of the solutions would often be inappropriate to the flavor of the beverage that they were tasting (see also Zampini et al. (2007), on this point). Therefore, these results show that the modulatory role of visual information on flavor identification responses is robust enough to override any awareness that participants may have concerning the appropriateness of the color–flavor link in the solutions presented. In order to assess whether the participants’ taster status modulated their multisensory flavor perception, we conducted a further post-hoc analysis of the data. In particular, the data regarding the accuracy of participants’ flavor identification responses (see Fig. 5) were submitted to a mixed between–within repeated-measures ANOVA with the factors of Taster status (non-tasters (4), medium tasters (5), and supertasters (5)), Flavor (blackcurrant, orange, and flavorless), Color (yellow, grey, orange, red, or colorless), and Fruit acids (present vs. absent). The analysis of the flavor identification data revealed a significant between-participants effect of Taster status [F(1, 10) = 22.67, p < .001], with the supertasters responding more accurately (M = 67% correct responses) than the medium tasters (M = 31%) who, in turn, were more accurate in their flavor identification responses that the non-tasters (M = 19%), as one might have expected (e.g., see Prescott, 2004). The three-way interaction between Flavor, Color, and Taster status was also significant [F(16, 80) = 1.99, p = .02], reflecting the fact that the nontasters responded more accurately when the blackcurrantflavored solutions were colored grey (53%) than when they were colored orange (7%), yellow (4%), red (3%), or colorless (5%). The non-tasters were also more accurate when the orange-flavored solutions were colored orange (51%) than when they were colored yellow (35%), grey (17%), red (2%), or else were colorless (12%). The medium tasters identified the blackcurrant solutions more accurately when they were colored grey (59%), than when they were colored red (21%), yellow (13%), orange
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Fig. 5. Mean percentage of correct flavor identification responses for the three groups of participants (non-tasters, medium tasters, and supertasters) for the blackcurrant, orange, and flavorless solutions. The black columns represent solutions where fruit acids had been added and the white columns solutions without fruit acids. The error bars represent the between-participants standard errors of the means.
(5%) or else were colorless (10%); They also identified the flavor of the orange-flavored solutions significantly more accurately when the solutions were colored orange, yellow (both 42%), or red (37%), than when they were colored grey (24%) or were colorless (25%). Interestingly, the supertasters were seemingly not influenced by the color of the solutions when identifying their flavors (as shown by the non-significance of all the t-test pairwise comparisons). The results of this post-hoc analysis therefore show that the modulatory effect of visual cues on people’s flavor identification responses are more pronounced in non-tasters than in medium tasters who in turn showed more of an influence of visual cues on their flavor identification responses than did the supertasters. To our knowledge, this result provides the first empirical demonstration that taster status can modulate the influence of visual cues on people’s flavor perception. However, this potentially very interesting result should really be investigated in further studies given the relatively small number of participants in each category.
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