In our previous studies, we examined the relationship between changes in mood, verbal (semantic) behavior, and non-verbal (skin temperature) activity induced by inhalation of essential oil fragrances, as well as linalool and its enantiomers. Sensory evaluation was a key component of these studies. We have found that perceived sensory attributes reported by participants can be represented via sensory spectrograph: A bar graph where the mean of the impression is plotted against descriptors of the setting for the semantic impression. In this paper, we present our latest attempts at assessing the taste of food using a sensory spectrograph. We conducted two studies: One in which participants assessed the taste of cookies with or without bean curd lees and one in which participants evaluated the taste of Miso soup and Sumashi soup as a function of salty concentration and soup stock consistency.
Sensory evaluation can be used to measure elements of consciousness. As a result, it has been a key element of experimental and mathematical psychology (Coombs, 1964; Guilford, 1954; Kling & Riggs, 1972; Stevens, 1951; Torgerson, 1958) . Sensory experiences can be reported using verbal (semantic) methods.
Previously, we conducted a series of studies to investigate the psychophysiological effects of inhaling essential oils, as well as linalool and its enantiomers ((R)-(−)-, (S)-(+)-, and (R, S)-(±)-forms). Specifically, we examined changes in mood, as well as verbal (semantic) and non-verbal (skin temperature) activity in humans after exposure to fragrant compounds (Satoh & Sugawara, 2003; Sugawara, 2001, 2008; Sugawara & Kawasaki, 2000; Sugawara et al., 1998a, 1998b, 1999, 2000, 2003, 2006, 2008, 2009a, 2009b, 2013, 2015a, 2015b; Yamagata & Sugawara, 2014) . Meanwhile, sensory evaluation has been a key component of our research activities (Sugawara, 2008; Sugawara et al., 2009a, 2009b, 2013, 2015a, 2015b; Yamagata & Sugawara, 2014) .
As a measure (sensory profile) of perceived odor quality, we asked participants to complete a sensory questionnaire after inhalation of a given aroma (Sugawara, 2008; Sugawara et al., 2009a, 2009b, 2013, 2015a, 2015b; Yamagata & Sugawara, 2014) . The questionnaire evaluated aroma perception using 13 descriptors in the form of paired contrasting adjectives: fresh - stale, soothing - activating, airy - heavy, plain - rich, natural - unnatural, elegant - unrefined, soft - strong, pleasant - unpleasant, warm - cool, comfortable - uncomfortable, woodsy - not woodsy, floral - peppery, lively - dull. The 13 descriptors were scored on an 11-point scale (−5 to +5), with 0 as the middle score. To test the effects of the aromas on behavior, we employed the Uchida-Kraepelin test as a mental arithmetic task and a task involving listening to environmental (natural) sounds as an auditory task. The sensory evaluation test (including exposure to the aroma and completion of the questionnaire mentioned above) was conducted twice, once before and once after the task. The perceived sensory attributes of a given aroma could be represented as a function of behavioral task performance using a sensory spectrograph, which is a bar graph in which the mean of the difference in score between pre- and post-task inquiry (post minus pre) was plotted against the impression descriptors. We were able to establish the sensory attributes of the following 21 essential oils, as well as linalool and its enantiomers, as a function of the two behavioral tasks (mental arithmetic and auditory): basil, bergamot, cardamom, chamomile, cinnamon, clove, cypress, geranium, ho leaf/wood, juniper, lavender, lemon, lime, marjoram, orange, palmarosa, peppermint, rosemary, sandalwood, spearmint, and ylangylang (Sugawara et al., 2015a) .
The resulting sensory spectra warranted particular interest (Sugawara et al., 2015a) . For instance, we observed three types of sensory spectra. One is an upward (positive) spectrum, where the descriptors regarded as significant via a t-test had a positive value and were shown above the horizontal axis, signifying a positive (or favorable) correlation between the fragrance of a given aroma and the type of task with respect to the positive descriptors (i.e., “fresh”, “airy”, “elegant”, “pleasant”, “comfortable”, etc.). The next is a downward (negative) spectrograph, in which negative values appeared below the axis, suggesting an unfavorable (negative) correlation between the fragrance and the type of task in terms of the negative descriptors (i.e., “stale”, “heavy”, “unrefined”, “unpleasant”, “uncomfortable”, etc.). The third was a “miscellaneous” type, where half of the significant descriptors were positive and the other half were negative. The sensory spectra classified as part of the first category (“favorable” type) were seen for bergamot, peppermint, sandalwood, ylangylang, and others if they were paired with the auditory task, while the spectra belonging to the second (“unfavorable” type) were observed for bergamot, peppermint, sandalwood, ylangylang, and others if they were paired with mental arithmetic. Moreover, the spectrographs classified as part of the third (“miscellaneous” type) were found for the following pairings: cardamom/mental arithmetic, cinnamon/mental arithmetic, lemon/auditory task, orange/mental arithmetic, orange/ auditory task, and so on.
Given the opposite shape of the sensory spectrographs produced upon inhalation of bergamot, peppermint, sandalwood, or ylangylang depending on whether the participants completed the mental arithmetic or the auditory talk, our research indicates that different behavioral tasks can evoke different perceived odor quality of a given aroma.
The task-dependent responses seen in bergamot, peppermint, sandalwood, and ylangylang essential oils were also found in linalool and (RS)-(±)-linalool, which is refined from commercial linalool via repeated flash column chromatography with silica gel (Sugawara et al., 2015a) . Linalool and the associated refined (purified) material also produced opposite sensory spectra in a task dependent way. Additionally, a detailed inspection of the spectra of optically active linalools ((R)-(−)-, (S)-(+)-, and (R, S)-(±)-forms) revealed that the (R)-(−)- and (S)-(+)- forms of linalool produce different sensory spectra when participants are engaged in mental arithmetic, but identical spectra when the auditory task is employed. Given these findings and the suggestion by Ohloff and Klein (1962) that (+)- and (−)-linalool are petitgrain-like and lavender-like, respectively, we speculated that different enantiomers of linalool may evoke distinct odor percepts in a task-dependent manner.
When assessing perceived odor quality as a function of different behavioral tasks assigned to participants, we have been able to discern nuanced individual differences in the spectrograph for each participant. This implies that our method of sensory profiling via sensory spectrograph may be practical for multimodal methodologies (i.e., for multimodal sensory targets).
Based on our experiences conducting sensory profiling of aromas, in this paper, we sought to assess the perception of food flavor using sensory spectrographs. We conducted two flavor studies: 1) an evaluation of the taste of cookies with or without bean curd lees; and 2) an evaluation of the taste of Miso soup and Sumashi soup as a function of salty concentration and soup stock consistency.
We generated two recipes for making cookies: one with and one without bean curd lees. We found that both generally succeeded in producing “moist cookies”.
First, we will describe the process for making cookies fortified with bean curd lees.
First, we preheated an oven to 180˚C. We prepared 70 g bean curd lees by heating in a frying pan until most of the moisture had been evaporated. We then let the bean curd lees cool for 5 minutes. In a mixing bowl, we used electric beaters to cream 70 g of salt-free butter at room temperature. We then added 50 g sugar and blended well until the mixture turned white. We then separated 2 eggs, discarding the whites. We added the egg yolks to the mixing bowl one at a time, mixing well between eggs. We then added the bean curd lees along with 100 g sifted flour, and mixed the batter well using a spatula. Following that, we added 50 g raisins and then 6 g ground tea leaf, mixing well between the two. We then used a spoon to round out sections of dough, which were placed on to a parchment-lined baking sheet and baked for 22 minutes.
We used the same recipe for cookies without bean curd lees, except that the bean curd lees were replaced by an equivalent amount of flour. The recipe made approximately 26 cookies.
ingredients | soup stock consistancy | |||||
---|---|---|---|---|---|---|
0% | 0.1% | 0.2% | 0.3% | |||
(without soup stock) | (half amount of ordinary used) | (amount ordinary used) | (a little more serving) | |||
salty concentration | 0.5% | soup stock cube (granulated) | 0 g | 2.1 g | 4.2 g | 6.3 g |
soybeam paste | 17.82 g | 17.82 g | 17.82 g | 17.82 g | ||
the content of salt originated from soybean paste used (estimated) | 1.853 g | 1.853 g | 1.853 g | 1.853 g | ||
cooking salt | 2.646 g | 1.764 g | 0.882 g | 0 g | ||
0.7% | soup stock cube (granulated) | 0 g | 2.1 g | 4.2 g | 6.3 g | |
soybeam paste | 17.82 g | 17.82 g | 17.82 g | 17.82 g | ||
the content of salt originated from soybean paste used (estimated) | 1.853 g | 1.853 g | 1.853 g | 1.853 g | ||
cooking salt | 4.446 g | 3.564 g | 2.682 g | 1.800 g | ||
0.9% | soup stock cube (granulated) | 0 g | 2.1 g | 4.2 g | 6.3 g | |
soybeam paste | 17.82 g | 17.82 g | 17.82 g | 17.82 g | ||
the content of salt originated from soybean paste used (estimated) | 1.853 g | 1.853 g | 1.853 g | 1.853 g | ||
cooking salt | 7.092 g | 5.364 g | 4.482 g | 3.600 g |
ingredients | soup stock consistancy | |||||
---|---|---|---|---|---|---|
0% | 0.1% | 0.2% | 0.3% | |||
(without soup stock) | (half amount of ordinary used) | (amount ordinary used) | (a little more serving) | |||
salty concentration | 0.5% | soup stock cube (granulated) | 0 g | 2.1 g | 4.2 g | 6.3 g |
soy sauce | 3.096 g | 3.096 g | 3.096 g | 3.096 g | ||
the content of salt originated from soy sauce used (estimated) | 1.344 g | 1.344 g | 1.344 g | 1.344 g | ||
cooking salt | 2.646 g | 1.764 g | 0.882 g | 0 g | ||
0.7% | soup stock cube (granulated) | 0 g | 2.1 g | 4.2 g | 6.3 g | |
soy sauce | 6.06 g | 6.06 g | 6.06 g | 6.06 g | ||
the content of salt originated from soy sauce used (estimated) | 2.64 g | 2.64 g | 2.64 g | 2.64 g | ||
cooking salt | 2.646 g | 1.764 g | 0.882 g | 0 g | ||
0.9% | soup stock cube (granulated) | 0 g | 2.1 g | 4.2 g | 6.3 g | |
soy sauce | 9 g | 9 g | 9 g | 9 g | ||
the content of salt originated from soy sauce used (estimated) | 3.96 g | 3.96 g | 3.96 g | 3.96 g | ||
cooking salt | 2.646 g | 1.764 g | 0.882 g | 0 g |
(
In preparing the twelve varieties of Miso soup (
To make Miso soup, we first placed the required amount (grams) of granulated bonito-fish soup stock, soybean paste, and cooking salt in a 1 L scaled stainless steel beaker equipped with a handle. We then poured hot water (just under the boiling point) into the beaker, mixed well with a whisk, and added more water to reach 1 L in total. We then brewed the soup for 3 - 5 minutes. We matched the amount of cooking salt in each sample to the estimated amount of saline ingredients in the soybean paste used for each specimen. We used HONDASHI as the granulated bonito-fish soup stock and SETO-NO-HONJIO (common mineral salt originating from the water of the Seto Sea) as the cooking salt, which are both produced by AJINOMOTO Co. (Tokyo, Japan). Our soybean paste (non-additive blend of Miso fermented with barley koji and Miso fermented with rice koji) was produced by SHINJYO MISO Co. (Hiroshima, Japan), and the light soy sauce was from HIGASHIMARU SHOYU Co. (Tatsuno, Japan).
For both the Miso soup and Sumashi soup, we prepared the four specimens for each experimental run at once, and kept these at approximately 90˚C using a thermal container equipped with a thermostatic controller. Prior to serving to participants, the salt concentration of each soup was monitored using a salt-concentration meter (PAL-SALT; a product of ATAGO Co., Tokyo, Japan). We utilized known concentrations of NaCl solutions (0.5%, 0.7%, and 0.9%) as a reference. The samples were served in paper cups at 55˚C - 60˚C to the panelists, and the tasting process progressed from low (0%) to high (3%) soup stock consistency.
The panels were composed of untrained individuals. Specifically, they were female students, aged 20 to 22, who were attending Prefectural University of Hiroshima. A total of 45 panelists assessed the flavor of cookies with or without bean curd lees, and 95 panelists evaluated the taste of Miso soup and Sumashi soup. For the cookie experiment, 21 participants composed panel A, and 24 formed panel B. Most of the members of panel A (n = 15) were assigned to be part of the pilot study, in which we tested the questionnaire with the 13 contrasting pairs of adjectives. The other 6 participants from panel A and all of the members of panel B (n = 24) evaluated the flavor of cookies with or without bean curd lees. The panelists assigned to evaluate the taste of Miso soup and Sumashi soup were assigned to groups as follows: 16 in panel C, 15 in panel D, 17 in panel E, 16 in panel F, 15 in panel G, and 16 in panel H. The participants in panels C, D, and E evaluated the taste of Miso soup, while those in panels F, G, and H assessed the taste of Sumashi soup. No participants participated in multiple components of the study.
As the sensory questionnaire was a key element of our study, we assigned most of panel A to the pilot study, where we tested the impression items, i.e., the 13 contrasting pairs of adjectives. We first screened five judges from the member constituents of panel A, and asked these judges to join a discussion where the goal was to screen 25 levels of contrasting pairs of adjectives after tasting a cookie either with or without bean curd lees. After this screening process was complete, we picked out an additional five judges from the remaining panelists in panel A. These individuals were asked to taste a cookie with bean curd lees and assign the following threshold values (scores) for each adjective pair, one at a time: 0―“unfavorable or unsuitable”; 1―“preferable if forced to choose”; or 2―“favorable or suitable”. Similarly, the final five participants in panel A were asked to taste a cookie without bean curd lees, and then assign the above-mentioned threshold values to each adjective pair, individually. In this way, the following 13 impression items comprising contrasting adjective pairs were determined: delicious - not delicious, plain - rich, proper sweetness - less sweet, harmonious - inharmonious or watery, good aftertaste - bad aftertaste, moist - dry, smooth - coarse, fluffy - tough, soft - hard, chewy - not chewy, melting - not melting, flavorful - not flavorful, a little tea flavoring - non tea flavoring.
In our questionnaire assessment, the 13 descriptors in the questionnaire were scored on an 11-point scale (−5 to +5), with 0 as the middle score. There were no symbolic representations associated with the numbers, as in the Likert scale (Likert 1932) . In each experimental run, the questionnaire assessment (sensory test) was conducted twice: 1) once for a cookie with bean curd lees; and 2) once for a cookie without bean curd lees.
In each experimental run, the scores recorded in the first inquiry were subtracted from the relevant values in the second (the first minus the second) for each panelist. For each descriptor, we calculated the total sum of the difference in the scores between the first- and second-inquiry in the panel. We then evaluated the statistical significance of the 13 descriptors using Student’s t-tests. Then, the mean difference in the score for each descriptor was plotted against the 13 descriptors, producing a sensory evaluation spectrum. The statistical significance of each descriptor was marked and scored as follows: a score was given an * (asterisk) and a significance score of 1 if the difference was significant such that p < 0.05; a ± and a significance score of 0.5 if the difference was significant such that p = 0.05 - 0.1; and no symbol and a significance score of 0 if the difference was not significant such that p ³ 0.1. The sum of these scores was the total significance score =
We used this value as an index of whether the relevant sensory spectrum could be considered to be statistically significant across the spectrograph (Sugawara, 2008; Sugawara et al., 2009a, 2013; Yamagata & Sugawara, 2014) . To confirm this, we used a sign test with n = 13, corresponding to the number of descriptors used in our sensory test. We found that the spectra could be expected to reach significance (p < 0.05) when the number of descriptors regarded as significant at a probability value of p < 0.05 (according to the t-test) was greater than 10 out of the 13 descriptors. In contrast, when this value was less than 3, the null hypothesis could be rejected.
As in the previous section, the taste of Miso soup was evaluated using the following 13 contrasting pairs of adjectives: mild taste - harsh taste, proper taste - tasteless or strong taste, rich taste - poor taste, taste delicious - taste unpalatable, heartfelt taste - shallow taste, good aftertaste - bad aftertaste, fair scent of Miso - nasty scent of Miso, relish flavor of Miso - unpleasant flavor of Miso, fair scent of soup stock - nasty scent of soup stock, relish flavor of soup stock - unpleasant flavor of soup stock, elegant - unrefined, wholehearted - empty, feel relief - feel restless.
Similarly, the taste of Sumashi soup was assessed using the following 13 descriptors: mild taste - harsh taste, proper taste - tasteless or strong taste, rich taste - poor taste, taste delicious - taste unpalatable, heartfelt taste - shallow taste, good aftertaste - bad aftertaste, fair scent of soy sauce - nasty scent of soy sauce, relish flavor of soy sauce - unpleasant flavor of soy sauce, fair scent of soup stock - nasty scent of soup stock, relish flavor of soup stock - unpleasant flavor of soup stock, elegant - unrefined, wholehearted - empty, feel relief - feel restless.
In the questionnaire assessment of both Miso soup and Sumashi soup, the 13 descriptors were scored on an 11-point scale (−5 to +5) with 0 as the middle score, as with the assessment of cookie flavor. The questionnaire was administered four times for each panelist such that they tasted four soup varieties with a constant salty concentration (i.e., 0.5%, 0.7%, or 0.9%): once each for the specimens with 0%, 0.1%, 0.2%, and 0.3% soup stock consistency.
We saw the need for a soup stock reference in our experimental design. Thus, we employed either the 0% (without soup stock) or 0.2% (ordinary amount) soup stock sample as a control. We then compared the differences in each descriptor for each panelist using the scores of the reference (the former minus the latter). Statistical evaluation of the descriptors was conducted using Student’s t-tests. The statistical procedures were identical to those used for the assessment of cookie flavor.
This study complied with the Declaration of Helsinki for Medical Research involving Human Subjects and all participants provided informed written or verbal consent. This study was approved by the Ethics Committee of the Institution of Health Science, Prefectural University of Hiroshima, Japan.
Panels A (n = 21) and B (n = 24) participated in this part of the study.
The pilot study led to the compilation of the following 13 impression items: delicious - not delicious, plain - rich, proper sweetness - less sweet, harmonious - inharmonious or watery, good aftertaste - bad aftertaste, moist - dry, smooth - coarse, fluffy - tough, soft - hard, chewy - not chewy, melting - not melting, flavorful - not flavorful, a little tea flavor - non tea flavor.
The other members of panel A (n = 6) and all of panel B (n = 24) assessed the flavor of cookies with or without bean curd lees, which we then expressed using a sensory spectrograph. To measure the flavor of cookies with or without bean curd lees, the 13 descriptors in the questionnaire were scored on an 11-point scale (−5 to +5), with 0 as the middle score. Inquiry assessment, either practiced by panel A (n = 6) or panel B (n = 24), was conducted twice. The first inquiry was for cookies with bean curd lees, while the second one was for cookies without. The scores recorded in the second inquiry were subtracted from the scores obtained in the first inquiry (the first minus the second).
In contrast, the obtained sensory spectrograph (
marked and scored in each sensory spectrograph as follows: 1.0 for items denoted with *; 0.5 for items denoted with ±; and 0.0 for items that are unmarked. The summation of these scores produces the total significance score (
This value can be used as an index of the statistical significance of a specific spectrum across the obtained spectrographs (Sugawara, 2008; Sugawara et al., 2009a, 2013; Yamagata & Sugawara, 2014) . As mentioned above, a sign test with n = 13, which corresponds with the number of descriptors used in our sensory test, would enable us to evaluate the changes in each spectrum: 1) it would be expected to reach significance (p < 0.05) when the value of the total significance score that corresponds to the number of descriptors regarded as significant at a probability value of p < 0.05 (according to the t-test) was greater than 10 out of the 13 descriptors; 2) if this value was less than 3, the null hypothesis could be rejected. Thus, the trend shown in
In connection with this issue, it is relevant to question how many panelists per group would be required to identify and quantify specific sensory attributes, if using untrained (inexperienced) individuals in this sensory study.
obtained sensory spectrographs (
We speculate that the spectrograph in
Under equivalent conditions to those established in above section, we attempted to visualize the assessment of Miso soup and Sumashi soup taste (
Three different panels of participants, panel C (n = 16), D (n = 15), and E (n = 17) evaluated the Miso soup,
while Panels F (n = 16), G (n = 15), and H (n = 16) assessed the Sumashi soup. For both the Miso soup and Sumashi soup, a sensory questionnaire with the 13 descriptors was completed four times in each experimental run for each panel: once each for the specimens with 0%, 0.1%, 0.2%, and 0.3% soup stock consistency.
In our experimental design, we decided to identify an eligible reference for constructing a sensory spectrograph. The candidates for a reference were the specimens with 0% (without soup stock) or 0.2% (ordinary amount) soup stock consistency.
With these two samples as references, Figures 4-7 summarize the obtained sensory spectrographs for the taste assessment of the 12 varieties of Miso and Sumashi soup. For both Miso soup and Sumashi soup,
This signifies a positive (or favorable) inclination toward the taste of a given sample against the reference sensory test data (0% soup stock consistency) in regard to the “positive” descriptors (i.e., “mild taste”, “proper taste”, “rich taste”, “taste delicious”, “heartfelt taste”, etc.). With respect to the total significance scores for these spectrographs, almost all samples were significant for more than 10 out of 13 descriptors, with the exception of
In the present study, we aimed to visualize the assessment of food flavor in terms of a sensory spectrograph. Accordingly, we conducted two studies. In the first study, we assessed the flavor of cookies with or without bean curd lees. In the second study, we evaluated the taste of Miso soup and Sumashi soup as a function of salt concentration and soup stock consistency.
We hoped that the obtained sensory spectra would exhibit satisfactory-to-good agreement with the data that could be obtained from the traditional descriptive sensory analysis in terms of reproducibility and consistency as well as statistical significance. This is because a traditional descriptive sensory analysis involves a group of trained individuals (generally 6 - 12) who identify and quantify specific sensory attributes with the goal of reproducibility and consistency (Drake, 2004, 2007; Lawless & Heymann, 1988; Meilgaard et al., 1999) . On the
other hand, we chose to employ untrained individuals as panelists. Thus, our sensory study is subject to variations in the obtained data based on varying levels of participant interest in the sensory target, sensitivity to the stimuli, susceptibility to fatigue, and so on.
This was evident from the outcome of our first experiment, as shown in
Regardless, the outcome of the first experiment (
In this context, we conducted a series of computer-generated graphics experiments while taking the sensory test data attained from both panels A (n = 6) and B (n = 24) regarding cookie taste assessment as the foundation of this work (
sensory spectra with respect to reproducibility and consistency, both in terms of the shape and characteristics of the total significance score.
In our second study, we used groups of panelists that were larger than 15. Figures 4-7 show the results of a taste assessment for Miso soup and Sumashi soup as a function of salt concentration and soup stock consistency.
For the sensory spectra shown in
We believe that the above-mentioned phenomenon relates to the sensory characteristics shown in
We are currently developing an application to use our sensory spectrum method to characterize the taste of commercially available foods, especially commodities that have been developed in recent years for elderly persons. Our findings imply that sensory spectrographs can be used to access the finer nuances of taste profiles. Thus, this method of sensory profiling has practical applications for assessing food flavors. Indeed, this method may represent a new and different approach to the assessment of flavor from the view of semantics.
Based on the experiences conducting sensory profiling of aromas, in this paper, we sought to assess the perception of food flavor via sensory spectrograph: a bar graph where the mean of the impression is plotted against descriptors of the setting for the semantic impression.
For this objective, we conducted two studies: the first study assessed the flavor of cookies with or without bean curd lees; and the second study evaluated the taste of Miso soup and Sumashi soup as a function of salt concentration and soup stock consistency.
As a result, the obtained data of both studies demonstrate that our sensory spectrum method could represent sensory attributes at a level of quality that was equal to that of the traditional (conventional) descriptive analyses in terms of reproducibility and consistency, although we chose to employ untrained individual as panellists.
Specifically, a series of computer-generated graphics experiments in the first study while taking the sensory test data attained from both panels A (n = 6) and B (n = 24) regarding cookie taste assessment as the foundation of this work revealed that we would obtain satisfactory-to-good agreement in the shape and characteristics of the statistical significance, if the number of participants were greater than 15.
The outcomes in the second study, in which we used groups of panellists that were larger than 15, suggest that sensory spectrographs could access the finer nuances of taste profiles, if we can choose an eligible reference for constructing a sensory spectrograph.
Thus, we believe that our sensory spectrum method may represent a new and different approach to the assessment of flavour from the view of semantics.
Naomi Sano,Ayaka Miyamoto,Mao Igasaki,Shiori Itoh,Haruna Ohkaji,Yoshie Yamagata,Jun Kayashita,Sumi Sugiyama,Yoshiaki Sugawara, (2016) Food Flavor Perception as Expressed via Sensory Spectrograph. Psychology,07,223-237. doi: 10.4236/psych.2016.72025