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Coffee Drinking and Emotions: Are There Key Sensory Drivers for Emotions?

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In the past couple of decades the coffee market has exploded, and to remain competitive, it is important to identify the key drivers for consumer acceptance of coffee. This study expanded on the previous emotion study on a population of coffee drinkers in Manhattan, Kansas, USA and focused on identifying the sensory drivers of emotional responses elicited during the coffee drinking experience (CDE). A trained coffee panel performed a descriptive analysis of six coffee samples and identified the key sensory attributes that discriminated each coffee. Utilizing Partial Least Square Regression (PLSR), the descriptive data were then mapped with the emotion data to identify sensory drivers for eliciting the emotional responses. The sensory characteristics of dark roast coffee (roast–aroma and flavor, burnt–aroma and flavor, bitter, and body) might elicit positive-high energy feelings for this population of coffee users. Tobacco (flavor) and cocoa (aroma) may also be responsible for positive emotions (content, good, and pleasant). Citrus and acidity seemed to be negative sensory drivers as they induced the feeling of off-balance. Sensory descriptive data could be useful to describe emotion profiles elicited by coffee drinking, which could help the coffee industry create coffee products for different segments of coffee drinkers.
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beverages
Article
Coffee Drinking and Emotions: Are There Key
Sensory Drivers for Emotions?
Natnicha Bhumiratana 1, Mona Wolf 2, Edgar Chambers IV 3and Koushik Adhikari 4,*
1Independent Restauranteur, 250/3 Sukhumvit 55/8, Bangkok 10110, Thailand; natnichab@gmail.com
2The Wolf Group, 10860 Kenwood Road, Cincinnati, OH 45242, USA; mwolf@wolfgrp.com
3Center for Sensory Analysis and Consumer Behavior, Kansas State University, Manhattan, KS 66506, USA;
eciv@ksu.edu
4Department of Food Science & Technology, University of Georgia, Griffin, GA 30223, USA
*Correspondence: koushik7@uga.edu; Tel.: +1-770-412-4736
Data for this manuscript was collected at Center for Sensory Analysis and Consumer Behavior, Kansas State
University, Manhattan, KS 66506, USA.
Received: 18 December 2018; Accepted: 1 March 2019; Published: 1 April 2019


Abstract:
In the past couple of decades the coffee market has exploded, and to remain competitive, it
is important to identify the key drivers for consumer acceptance of coffee. This study expanded on the
previous emotion study on a population of coffee drinkers in Manhattan, Kansas, USA and focused on
identifying the sensory drivers of emotional responses elicited during the coffee drinking experience
(CDE). A trained coffee panel performed a descriptive analysis of six coffee samples and identified
the key sensory attributes that discriminated each coffee. Utilizing Partial Least Square Regression
(PLSR), the descriptive data were then mapped with the emotion data to identify sensory drivers
for eliciting the emotional responses. The sensory characteristics of dark roast coffee (roast–aroma
and flavor, burnt–aroma and flavor, bitter, and body) might elicit positive-high energy feelings for this
population of coffee users. Tobacco (flavor) and cocoa (aroma) may also be responsible for positive
emotions (content,good, and pleasant). Citrus and acidity seemed to be negative sensory drivers as
they induced the feeling of off-balance. Sensory descriptive data could be useful to describe emotion
profiles elicited by coffee drinking, which could help the coffee industry create coffee products for
different segments of coffee drinkers.
Keywords: descriptive analysis; emotions; coffee
1. Introduction
Human senses are powerful elicitors of emotions and the interactions between the two are rarely
debated [
1
3
]. A number of studies have attempted to define and categorize human emotion, but
it is only recently that emotions have been linked to acceptance of food and beverage. Nowadays,
there is more awareness that the emotional experiences consumers receive from a product via sensory
perception determine acceptability and consumption [
4
,
5
]. Therefore, assessment of the emotional
responses elicited by the sensorial experience during product consumption is also vital. Several
researchers have developed emotion scales to measure the affective feelings evoked by product
consumption (EsSense Profile
) [
6
] or by olfactory stimulations from everyday odors (Geneva Emotion
and Odor Scale) [1].
The emotions elicited by the coffee drinking experience were identified in our previous work [
7
],
where they determined a list of 44 emotions suitable for defining the ‘Coffee Drinking Experience (CDE)’
and provided the emotion profiles for each segment of coffee drinkers. The consumers in the study
were clustered in six consumer segments. To have a complete understanding of consumers’ perceptions,
Beverages 2019,5, 27; doi:10.3390/beverages5020027 www.mdpi.com/journal/beverages
Beverages 2019,5, 27 2 of 13
it is important to understand the sensory characteristics that elicit those emotions experienced during
coffee consumption.
Coffee is well known for its complex sensory characteristics and is often consumed for the sensory
experience it provides, in addition to the physiological stimulation of the caffeine [
8
11
]. Coffee is
one of the few food products that utilizes specialized experts (cuppers) to ensure that the sensory
properties are up to standard. These experts are not trained sensory assessors but have a lot of
experience in determining the quality of coffee for commercial purposes [
12
]. Trained sensory panels
are used extensively for understanding the sensory characteristics of food products including coffee.
Bhumiratana et al. [
13
] conducted a descriptive analysis study on aroma evolution in coffee beans when
they are subjected to roasting to different levels of roast. Due to its high complexity, the descriptive
sensory panel may need training specifically for coffee, in addition to the usual intensive training
program on the sensory characteristics of food and beverage. Many studies support that the amount
of training and regular re-training correlate with panelist perception of the sensory attributes and
increases the quantification accuracy of attribute intensities [
14
17
]. Recently, a “living” lexicon for
descriptive analysis of brewed coffee was developed by Chambers IV et al. [
18
] that can be used by
sensory researchers for descriptive analysis of coffee.
The link between emotion profiles for a food product and its descriptive sensory profile to
understand drivers of positive and negative emotions during consumption has been explored to
a limited extent by sensory researchers. Interestingly, the two studies the authors found are on
dark chocolates but neither used the classic descriptive approach in their respective study [
4
,
19
].
Thomson et al. [
4
] utilized best–worst scaling to gather sensory information on nine dark chocolates
from consumers. They also asked the consumers to identify five emotion descriptors from a
pre-conceptualized list that come to their mind for each chocolate. The conceptual biplot between
the sensory data and the emotions revealed that the sensory differences in products could drive, in
part, conceptual differences due to the emotional response. In another study, Jager et al. [
19
] reported
the link between temporal dominance of sensation (TDS; analytical data) and temporal dominance of
emotions (TDE; affective data) using unflavored and flavored dark chocolates. The unflavored dark
chocolates (70% and 85% cocoa content) characterized by bitter, dry, and cocoa flavor were linked
to aggressive,bored,calm, and guilty emotions, while the fruit-flavored dark chocolates (orange and
blueberry) that were characterized by crunchy, fruit, and sweet elicited interested,happy, and loving
emotions. The fruit-flavored chocolates were liked more by the consumers as was evident through
their emotional response as well. The main objective of our study was to identify sensory drivers of
emotional response to the experience of coffee drinking. A trained coffee panel performed descriptive
analysis on the coffee samples that were used to elicit emotions in coffee drinkers. The sensory data
was then utilized to determine the sensory drivers for emotional responses in each segment (cluster) of
consumers as reported in Bhumiratana et al. [7].
2. Materials and Methods
2.1. Descriptive Panel
The descriptive coffee panel from the Wolf group (Cincinnati, OH, USA) was utilized to evaluate
the coffee samples. The panel consisted of six highly-trained members who had completed 120 h of
general training and had a minimum of 1200 h of sensory testing of food and beverages. The coffee
panelists also completed an additional 120 h of training on various coffee stimuli and key attributes
(coffee, robusta, roasted, burnt, earthy, rioy, acidity, bitter, and body). Performance of the panel is
evaluated every 3 months in the form of a blind reference sample or samples. This coffee panel has
been evaluating coffee products regularly for over 2 years before doing this study.
Beverages 2019,5, 27 3 of 13
2.2. Coffee Samples
The six single-serve coffee samples (K-Cup
®
Keurig, Inc.; Reading, MA, USA) were evaluated
by the descriptive sensory panel. These single-serve coffee samples represented the range of roast
levels from light to dark. Green Mountain Breakfast Blend represented the light roast. Green Mountain
Nantucket Blend represented the blend of medium roasted African and Indonesian beans mixed with
some French roast. Green Mountain Sumatra Reserved represented dark roasted organic Sumatra
coffee. Tully’s Kona represented the blend including the famous Hawaiian coffee from the Kona
Typica varietal, and was classified as medium roast. Tully’s Italian Roast represented a blend of dark
roast. Lastly, Newman’s Own Organic represented a blend of medium and dark roast organic coffee
beans. All coffee samples were stored at room temperature (20 C) until testing and were used in the
study within six weeks of their delivery.
2.3. Descriptive Sensory Analysis
2.3.1. Sample Preparation and Serving
Keurig
®
Special Edition B60 Brewing System (Keurig
®
, Inc.; Reading, MA, USA) was used to
brew the single-serve K-Cup
®
coffee samples. The machine was set up and cleaned following the
instructions in the user manual. A K-Cup was placed in the K-Cup holder and 157.5 mL of coffee was
brewed into a styrofoam cup (Dart J-cup, Dart Container Corp.; Mason, OH, USA). The coffee cups
were labeled with 3-digit random numbers prior to serving. After each brewing cycle was completed,
the K-Cup was removed and discarded immediately. Each coffee cup was covered with either a saucer
(Econo Rim, Syracuse China; Lyncourt, NY, USA) or a plastic lid (Dart Container Corp.; Mason, OH,
USA) and was then served immediately to the panelists monadically in random order.
2.3.2. Sample Evaluation
A 180 min orientation session was completed to familiarize the descriptive panel with the samples.
During orientation, the panel identified and defined aroma, flavor, and texture attributes present in
each sample (Table 1). Necessary references were determined to anchor and calibrate the intensity
measurement on a 0 to 15-point scale with 0.5 increments (0.0 = none; 15.0 = extremely high intensity).
Table 1. The list of aroma, flavor, and texture descriptors identified by the coffee panel.
Attributes. Definitions
Coffee Amount or strength of Arabica coffee aroma or flavor
Roast Degree to which the coffee is roasted; ranges from green/no
roast–low–medium–dark–very dark
Burnt Aromatics associated with blacked/acrid carbohydrates (e.g., burnt toast,
espresso coffee)
Rioy
Aromatic associated with iodine in water; is described as chlorine-like, brassy, metallic,
and chemical
Ashy Bark-like lingering aromatics associated with a cold campfire
Acidity A sour, sharp, puckering sensation in the mouth caused by acids
Tobacco Characteristic reminiscent of tobacco’s odor and taste, but should not be used for
burnt tobacco
Stale Not fresh, flat, bodied down or reduced; old
Citrus Aromatics associated with citrus fruits (e.g., lemon)
Cocoa Brown, sweet, dusty often biter aromatics associated with cocoa beans and powered
cocoa
Bitter The amount of bitter basic taste; (e.g., caffeine solutions)
Body (Mouthfeel) Viscosity of the coffee; heaviness on the tongue: thin to thick
Outlined in the following paragraph is the structured tasting protocol: Once the coffee was served,
panelists opened the lid and the temperature of the coffee was taken with a digital thermometer
(Model T220/38A Latte Thermometer, Comark; Hertfordshire, UK). When the temperature reached
Beverages 2019,5, 27 4 of 13
65.5
C, the lid was replaced, keeping one end slightly opened. The panelists took a sniff to identify
aroma descriptors belonging to that particular coffee. Panelists then slurped the sample and gently
manipulated it in the mouth for 10–20 s to evaluate flavor and body/mouthfeel attributes. A small
amount of sample was swallowed to discern bitterness on the back of the tongue. Afterward samples
were expectorated. A 10 min break was taken between each sample, during which buttered bread and
distilled water were used as palate cleansers. Buttered bread was prepared by spreading Land O’Lakes
Whipped Butter (Whipped Butter Sweet Cream, Salted, 45% less fat, Land O’Lakes, Inc.; Arden Hills,
MN, USA) on a 3
4cm slice of European Batard bread (Kroger; Cincinnati, OH, USA).
During testing, panelists evaluated four samples per 180 min panel session. Samples were served
one at a time and tasted individually by each panelist. A group discussion was then initiated by a panel
leader to determine attributes present, their strengths, and to identify which references were needed.
A new cup of the same sample was then served, along with references. The panel then individually
evaluated the sample on ballots. The ratings were collected and written on the board by the panel
leader. This was to identify any problem areas and whether other references should be reviewed. The
panelists then determined and recorded their final score for the first replication of the sample. The
next sample was served after a 10 min break and was evaluated following the same procedure. Two
replications were carried out for the entire descriptive study.
2.4. Emotion Data
The emotion data for the coffee samples were collected from 94 coffee drinkers (consumers) as
reported in Bhumiratana et al. [
7
]. The consumers were between the ages of 18–70 years and there
were 63 female and 31 male participants. In brief, the emotion profile data for each of the six coffees
for the 44 terms in CDE (Appendix A) were used. Intensity of emotion elicited by the coffee drinking
experience were measured before and during consumption using a 5-point numerical scale (1 = not at
all; 2 = slightly; 3 = moderately; 4 = very much; 5 = extremely). The emotion ratings prior to the coffee
evaluation were subtracted from the emotion ratings during the evaluation before analyzing the data.
Hierarchical cluster analysis (HCA) using Ward’s method was carried out on the overall liking data of
the six coffee samples. The emotion profiles for each coffee were then separated for the six consumer
clusters (Appendix B) and were used in this study. Appendix Balso shows the mean liking scores for
the coffee samples for each cluster.
2.5. Statistical Analyses
Randomized complete block design was used for the descriptive evaluation of the six coffee
samples. A two-way Analysis of Variance (ANOVA) using the GLIMMIX procedure (SAS
®
system
version 9.2; SAS institute; Cary, NC, USA) at a 5% level of significance was performed on the data set
to determine attributes significant in identifying differences among products. Coffee sample was the
fixed effect and panelist was set as a random effect. Post-hoc mean separation was carried out by using
Fisher’s Least Significant Difference. Principal component analysis (XLSTAT Sensory 19.01; Addinsoft,
NY, USA) with covariance matrix was performed on the sensory descriptors to understand the sensory
profile of the coffee samples.
To investigate the relationship between the sensory attributes and the emotional responses to the
drinking experience, partial least squares repression (XLSTAT Sensory 19.01) was conducted. Sensory
drivers associated with the emotional experiences were identified among the 94 coffee users and in
each consumer cluster.
3. Results and Discussion
3.1. Descriptive Sensory Data
The ANOVA followed by mean separation indicated significant differences among the six coffee
samples (p-value < 0.05) as shown in Table 2. The coffee descriptive panel differentiated sensory
Beverages 2019,5, 27 5 of 13
elements that were distinctive to each coffee sample. Ashy was identified in Nantucket and Sumatra
and was perceived to be more intense in Nantucket (a medium roast). Rioy was detected at the same
intensity level in Nantucket, Newman, and Sumatra, but was not present in the other samples. Tobacco
appeared in the Italian sample, stale underlined Newman, and cocoa aroma was unique to Kona.
Table 2. The mean scores of the descriptive analysis of the coffee samples.
Descriptors Abbreviation
for Figures Breakfast Italian Kona Nantucket Newman Sumatra
Aroma
Coffee CoffeeA 7.79 ab 5.42 c8.33 a8.58 a7.50 ab 8.58 a
Roast RoastA 6.92 b8.50 a7.42 b8.50 a7.58 b8.58 a
Burnt BurntA 0.67 c4.50 a0.17 c2.92 b2.83 b4.33 a
Rioy RioyA 0.00 b0.00 b0.00 b1.33 a1.58 a1.58 a
Ashy AshyA 0.00 b0.00 b0.00 b2.75 a0.00 b1.92 a
Cocoa CocoaA 0.00 b0.00 b2.33 a0.00 b0.00 b0.00 b
Flavor
Coffee CoffeeF 8.25 c8.00 c11.75 a10.33 b11.75 a12.50 a
Roast RoastF 7.08 c10.17 a8.54 b8.92 b10.50 a10.08 a
Burnt BurntF 1.58 d6.67 b6.75 b3.75 c8.33 a8.50 a
Rioy RioyF 0.00 b0.00 b0.00 b2.04 a2.00 a1.58 a
Ashy AshyF 0.00 b0.00 b0.00 b2.92 a0.00 b2.83 a
Citrus Citrus 4.42 a0.00 b0.00 b0.00 b0.00 b0.00 b
Tobacco Tobacco 0.00 b8.08 a0.00 b0.00 b0.00 b0.00 b
Stale Stale 0.00 b0.00 b0.00 b0.00 b4.42 a0.00 b
Acidity Acidity 5.92 a4.83 c5.83 ab 5.92 a4.92 c4.92 c
Bitter Bitter 3.08 d9.50 a8.13 b5.42 c8.00 b8.42 b
Texture
Body Body 6.38 d8.67 ab 8.33 b7.63 c9.13 a8.83 ab
a,b,c Row means with common superscrits are not significantly different at p> 0.05.
Principal component analysis (PCA) was performed to visualize the product placements on the
sensory space based on the sensory attributes. Figure 1illustrates sensory profiles of the coffees created
by the coffee panel in the PCA biplot.
Beverages 2019, 5, x FOR PEER REVIEW 5 of 13
intensity level in Nantucket, Newman, and Sumatra, but was not present in the other samples. Tobacco
appeared in the Italian sample, stale underlined Newman, and cocoa aroma was unique to Kona.
Table 2. The mean scores of the descriptive analysis of the coffee samples.
Descriptors
Abbreviation
for Figures
Breakfast
Kona
Nantucket
Newman
Sumatra
Aroma
Coffee
CoffeeA
7.79 ab
8.33 a
8.58 a
7.50 ab
8.58 a
Roast
RoastA
6.92 b
7.42 b
8.50 a
7.58 b
8.58 a
Burnt
BurntA
0.67 c
0.17 c
2.92 b
2.83 b
4.33 a
Rioy
RioyA
0.00 b
0.00 b
1.33 a
1.58 a
1.58 a
Ashy
AshyA
0.00 b
0.00 b
2.75 a
0.00 b
1.92 a
Cocoa
CocoaA
0.00 b
2.33 a
0.00 b
0.00 b
0.00 b
Flavor
Coffee
CoffeeF
8.25c
11.75 a
10.33 b
11.75 a
12.50 a
Roast
RoastF
7.08 c
8.54 b
8.92 b
10.50 a
10.08 a
Burnt
BurntF
1.58 d
6.75 b
3.75 c
8.33 a
8.50 a
Rioy
RioyF
0.00 b
0.00 b
2.04 a
2.00 a
1.58 a
Ashy
AshyF
0.00 b
0.00 b
2.92 a
0.00 b
2.83 a
Citrus
Citrus
4.42 a
0.00 b
0.00 b
0.00 b
0.00 b
Tobacco
Tobacco
0.00 b
0.00 b
0.00 b
0.00 b
0.00 b
Stale
Stale
0.00 b
0.00 b
0.00 b
4.42 a
0.00 b
Acidity
Acidity
5.92 a
5.83 ab
5.92 a
4.92 c
4.92 c
Bitter
Bitter
3.08 d
8.13 b
5.42 c
8.00 b
8.42 b
Texture
Body
Body
6.38 d
8.33 b
7.63 c
9.13 a
8.83 ab
a,b,c Row means with common superscrits are not significantly different at p > 0.05.
Principal component analysis (PCA) was performed to visualize the product placements on the
sensory space based on the sensory attributes. Figure 1 illustrates sensory profiles of the coffees
created by the coffee panel in the PCA biplot.
Figure 1. Principal component analysis (PCA) biplot of the sensory profiles of the six coffees generated
by the coffee panel.
Breakfast
Italian
Kona
Nantucket
Newman
Sumatra
CoffeeA
RoastA
BurntA
RioyA
AshyA
CocoaA
Citrus Stale
Tobacco
CoffeeF
RoastF BurntF
Acidity
BitterF
RioyF
AshyF
Body
-1.2
0.0
1.2
-1.2 0.0 1.2
PC2 -33%
PC1 - 46%
Figure 1.
Principal component analysis (PCA) biplot of the sensory profiles of the six coffees generated
by the coffee panel.
Beverages 2019,5, 27 6 of 13
PC1 explained 46% of the data variation and seemed to reflect characteristics generated by roasting.
Acidity and citrus anchored the left side of PC1 and described Breakfast. Burnt,roast,bitter flavors
and body anchored the right side of PC1 and seemed to characterize Newman and Sumatra. Acidity,
bitter,burnt (flavor and aroma), roast flavor, coffee flavor (except for Italian) and body were influenced
by degree of roasting. Acidity was more intense in the lighter roasts, while bitter,burnt (flavor and
aroma), roast, and coffee flavors, and body increased with degree of roasting. The impact of degree of
roasting on aroma and flavor in coffee has been extensively studied [
11
,
13
,
20
22
] and is similar to what
was found in this research. However, degree of roasting was not the only factor affecting the sensory
characteristics of coffee. PC2 explained 33% of the data set and provided additional information on
sensory elements for Nantucket, Kona, and Italian. Coffee aroma and roast aroma did not seem to be
dependent on roast level. The intensities of these aroma attributes for Nantucket (medium roast) were
higher than Newman (medium-dark roast). The sensory profiles indicated some sensory attributes
might be independent of degree of roasting, which confirmed that other factors might be influencing
the sensory characteristics of coffee. The origins of coffee, including growing regions and variety of
bean, evidently have a noticeable impact on the sensory fingerprint of each coffee; this is supported by
numerous studies [11,13,2326].
The sensory data from the descriptive panel was then utilized in the next step to identify the
sensory drivers responsible for the emotional responses elicited by the coffee drinking experience.
3.2. Identifying Sensory Drivers for the Emotional Experience
The sensory descriptive data was studied with emotion responses for the same set of coffee
samples created by 94 coffee drinkers in the study done previously by Bhumiratana et al. [
7
]. Partial
Least Square Regression (PLSR) was used to identify sensory drivers of the emotion responses
(Figure 2). Coffee aroma, surprisingly, elicited a range of negative emotions (bored,disgusted,annoyed,
and disappointed) even though it is well known that ‘coffee aroma’ elicites positive feelings, including
alertness of the mental state, and is the driver of coffee consumption [
11
,
27
]. This may be because
the definition of coffee aroma used by the coffee panel and consumers could be different, a common
problem in the field of consumer research when integrating sensory and consumer data together. Coffee
aroma, by the definition listed in Table 1, was the aroma of pure Arabica beans, which consumers may
not be familiar with and might have led to a negative perception [5].
Beverages 2019, 5, x FOR PEER REVIEW 6 of 13
PC1 explained 46% of the data variation and seemed to reflect characteristics generated by
roasting. Acidity and citrus anchored the left side of PC1 and described Breakfast. Burnt, roast, bitter
flavors and body anchored the right side of PC1 and seemed to characterize Newman and Sumatra.
Acidity, bitter, burnt (flavor and aroma), roast flavor, coffee flavor (except for Italian) and body were
influenced by degree of roasting. Acidity was more intense in the lighter roasts, while bitter, burnt
(flavor and aroma), roast, and coffee flavors, and body increased with degree of roasting. The impact
of degree of roasting on aroma and flavor in coffee has been extensively studied [11,13,2022] and is
similar to what was found in this research. However, degree of roasting was not the only factor
affecting the sensory characteristics of coffee. PC2 explained 33% of the data set and provided
additional information on sensory elements for Nantucket, Kona, and Italian. Coffee aroma and roast
aroma did not seem to be dependent on roast level. The intensities of these aroma attributes for
Nantucket (medium roast) were higher than Newman (medium-dark roast). The sensory profiles
indicated some sensory attributes might be independent of degree of roasting, which confirmed that
other factors might be influencing the sensory characteristics of coffee. The origins of coffee, including
growing regions and variety of bean, evidently have a noticeable impact on the sensory fingerprint
of each coffee; this is supported by numerous studies [11,13,2326].
The sensory data from the descriptive panel was then utilized in the next step to identify the
sensory drivers responsible for the emotional responses elicited by the coffee drinking experience.
3.2. Identifying Sensory Drivers for the Emotional Experience
The sensory descriptive data was studied with emotion responses for the same set of coffee
samples created by 94 coffee drinkers in the study done previously by Bhumiratana et al. [7]. Partial
Least Square Regression (PLSR) was used to identify sensory drivers of the emotion responses (Figure
2). Coffee aroma, surprisingly, elicited a range of negative emotions (bored, disgusted, annoyed, and
disappointed) even though it is well known that ‘coffee aroma’ elicites positive feelings, including
alertness of the mental state, and is the driver of coffee consumption [11,27]. This may be because the
definition of coffee aroma used by the coffee panel and consumers could be different, a common
problem in the field of consumer research when integrating sensory and consumer data together.
Coffee aroma, by the definition listed in Table 1, was the aroma of pure Arabica beans, which
consumers may not be familiar with and might have led to a negative perception [5].
Figure 2. Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for 94 consumers.
CoffeeA
RoastA
BurntA
RioyA
AshyA
Citrus
Tobacco
Stale
CocoaA
CoffeeF
RoastF
BurntF
Acidity
Bitter
RioyF
AshyF
Body
Active
Annoyed
Awake
Balanced
Boosted
Bored
Clear-minded
Comfortable
Content
Curious
Disappointed
Disgusted
Educated
Empowering
Energetic
Free
Fulfilled
Fun
Good
Grouchy
Guilty
In control
Jolted
Joyful
Jump start
Merry
Motivated
Nervous
Off balance
Peaceful
Pleasant
Pleased
Productive
Relaxed
Rested
Rewarded
Satisfied
Social
Soothing
Special
Understanding
Warm
Wild
Worried
Breakfast
Italian
Kona
Nantucket
Newman
Sumatra
-1.2
0.0
1.2
-1.2 0.0 1.2
Dim 2 (X: 24%, Y: 24%)
Dim 1 (X:42%, Y:20%)
Figure 2.
Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for 94 consumers.
Beverages 2019,5, 27 7 of 13
Positive emotions seemed to be driven by cocoa aroma, bitter,tobacco,roast,burnt, and body.Cocoa
aroma may elevate good and pleasant emotions, which was consistent with previous studies. King and
Meiselman [
6
] found that among the five food categories evaluated, chocolate was reported to have the
highest ratings for 15 of the positive emotions (out of 24 positive emotions on a list of 39 terms). Macht
and Mueller [
28
] reported consumption of chocolate could immediately reduce negative mood state,
although the effect was temporary. It is also common knowledge that chocolate and its resemblance
usually induces positive feelings in the general population. Tobacco flavor evoked the feelings of jolted
and content. Coffee users may initially be surprised (i.e., jolted) by the unfamiliar tobacco attribute that
was not commonly found in all coffee (only one coffee sample in this study exhibited this sensory
attribute). However, they were accepting of the experience (i.e., content), which indicates that having a
tobacco attribute in coffee could potentially enhance the drinking experience for general coffee users.
Bitter aroused energetic and productive feelings. Roast and burnt (flavor and aroma), and body texture
made consumers feel jump start,satisfied,boosted, and special. On the contrary, citrus,hay-like, and acidity
appeared to elicit a feeling of off-balance. Like tobacco, consumers may not be familiar with experiencing
these sensory characteristics in coffee and were caught off-guard by them. Unlike tobacco, they may not
find these attributes appropriate for coffee, hence the off-balance emotion. Because emotions are context
specific [
29
], it seems that citrus and acidity attributes may not fit well with the concept of coffee, which
caused negative feelings to develop.
It seems the characteristics of dark roast coffee (roasted,burnt,bitter, and body) elicited positive-high
energy feelings. This is likely because there were more participants who preferred darker roasts since
coffee preference was not one of the criteria during recruitment. This finding identified tobacco,roasted,
burnt,bitter, and body as the sensory drivers for this population of 94 coffee users. Since consumers
have varying preferences and are affected differently by sensory stimuli, the 94 coffee users were
examined more closely in our previous study [
7
] through clustering the consumers in six segments.
The entire set of 94 coffee drinkers was clustered into six groups based on their acceptability scores
for the coffee samples and emotion profiles were generated for each set of consumers. We conducted
PLSR analysis on each consumer cluster to determine whether relationships can be drawn between the
sensory characteristics and emotions elicited by the perceived attributes for each consumer cluster.
For coffee drinkers in Cluster 1 (n= 20), who liked all the coffees [
7
], the tobacco attribute seemed
to elicit social,jump start, and special feelings, while the characteristics of dark roasts (high intensity of
roast,burnt, and body/mouthfeel) appeared to make them feel empowering and relaxed (Figure 3). Acidity
was associated with awake and disgusted and may be a negative attribute for this group. Cluster 2
(n= 17; Figure 4) consisted of consumers who dislike Breakfast (classified as light roast) [
7
]. The
PLSR map indicated that attributes citrus and acidity elicited negative emotions (e.g., disappointed,
disgusted,annoyed), and dark roast characteristics (roast,burnt,bitter, and body) were driving positive
emotions (e.g., satisfied,energetic,rewarded,boosted,in control,empowering). This group of coffee drinkers
seem to relate the coffee aroma to a grouchy emotion and the tobacco attribute to clear-minded,wild, and
good feelings.
Cluster 3 (n= 24) was identified to like Nantucket and Breakfast but dislike Sumatra [
7
]. The
PLSR bi-plot (Figure 5) illustrated that hay-like,citrus, and acidity brought out positive emotions
(e.g., merry,pleasant,understanding,relaxed,rewarded) for this group of coffee drinkers. Empowering and
boosted emotions seemed to be induced by coffee flavor, ashy, and rioy, while tobacco elicited feelings
of off-balance,jolted, and social. Negative emotions (disappointed and disgusted) were driven by roast,
burnt, and body characteristics. Coffee drinkers grouped into Cluster 4 (n= 13) were those that did not
prefer any of the six coffees [
7
]. Nantucket was liked the most by this group, and that might be the
reason that peaceful,energetic,pleased, and awake are somewhat encircling this sample in Figure 6. Since
they did not have any firm preferences, the coffees may have elicited mixed emotions for this group
(Figure 6), which are not easily discernible.
Beverages 2019,5, 27 8 of 13
Beverages 2019, 5, x FOR PEER REVIEW 8 of 13
Figure 3. Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 1.
Figure 4. Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 2.
CoffeeA
RoastA
BurntA
RioyA
AshyA
Citrus
Tobacco
Stale
CocoaA
CoffeeF
RoastF
BurntF
Acidity
Bitter
RioyF
AshyF
Body
Active
Annoyed
Awake
Balanced
Boosted
Bored
Clear-minded
Comfortable
Content
Curious
Disappointed
Disgusted
Educated
Empowering
Energetic
Free
Fulfilled
Fun
Good
Grouchy
Guilty
In control
Jolted
Joyful
Jump start
Merry
Motivated
Nervous
Off balance
Peaceful
Pleasant
Pleased
Productive
Relaxed
Rested
Rewarded
Satisfied
Social
Soothing
Special
Understanding
Warm
Wild
Worried
Breakfast
Italian
Kona
Nantucket
Newman
Sumatra
-1.2
0.0
1.2
-1.2 0.0 1.2
DIM 2 (X: 24%, Y: 21%)
DIM 1 (X: 45%, Y: 24%)
CoffeeA
RoastA
BurntA
RioyA
AshyA
Citrus
Tobacco
Stale
CocoaA
CoffeeF
RoastF
BurntF
Acidity
Bitter
RioyF
AshyF
Body
Active
Annoyed
Awake
Balanced
Boosted
Bored
Clear-minded
Comfortable
Content
Curious
Disappointed
Disgusted Educated Empowering
Energetic
Free
Fulfilled
Fun
Good
Grouchy
Guilty
In control
Jolted
Joyful
Jump start
Merry
Motivated
Nervous
Off balance
Peaceful
Pleasant
Pleased
Productive
Relaxed
Rested
Rewarded
Satisfied
Social
Soothing
Special
Understanding
Warm
Wild
Worried
Breakfast
Italian
Kona
Nantucket
Newman
Sumatra
-1.2
0.0
1.2
-1.2 0.0 1.2
DIM 2 (X: 24%, Y: 18%)
DIM (X: 45%, Y: 40%)
Cluster 1
Cluster 2
Figure 3.
Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 1.
Beverages 2019, 5, x FOR PEER REVIEW 8 of 13
Figure 3. Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 1.
Figure 4. Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 2.
CoffeeA
RoastA
BurntA
RioyA
AshyA
Citrus
Tobacco
Stale
CocoaA
CoffeeF
RoastF
BurntF
Acidity
Bitter
RioyF
AshyF
Body
Active
Annoyed
Awake
Balanced
Boosted
Bored
Clear-minded
Comfortable
Content
Curious
Disappointed
Disgusted
Educated
Empowering
Energetic
Free
Fulfilled
Fun
Good
Grouchy
Guilty
In control
Jolted
Joyful
Jump start
Merry
Motivated
Nervous
Off balance
Peaceful
Pleasant
Pleased
Productive
Relaxed
Rested
Rewarded
Satisfied
Social
Soothing
Special
Understanding
Warm
Wild
Worried
Breakfast
Italian
Kona
Nantucket
Newman
Sumatra
-1.2
0.0
1.2
-1.2 0.0 1.2
DIM 2 (X: 24%, Y: 21%)
DIM 1 (X: 45%, Y: 24%)
CoffeeA
RoastA
BurntA
RioyA
AshyA
Citrus
Tobacco
Stale
CocoaA
CoffeeF
RoastF
BurntF
Acidity
Bitter
RioyF
AshyF
Body
Active
Annoyed
Awake
Balanced
Boosted
Bored
Clear-minded
Comfortable
Content
Curious
Disappointed
Disgusted Educated Empowering
Energetic
Free
Fulfilled
Fun
Good
Grouchy
Guilty
In control
Jolted
Joyful
Jump start
Merry
Motivated
Nervous
Off balance
Peaceful
Pleasant
Pleased
Productive
Relaxed
Rested
Rewarded
Satisfied
Social
Soothing
Special
Understanding
Warm
Wild
Worried
Breakfast
Italian
Kona
Nantucket
Newman
Sumatra
-1.2
0.0
1.2
-1.2 0.0 1.2
DIM 2 (X: 24%, Y: 18%)
DIM (X: 45%, Y: 40%)
Cluster 1
Cluster 2
Figure 4.
Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 2.
Beverages 2019,5, 27 9 of 13
Beverages 2019, 5, x FOR PEER REVIEW 9 of 13
Figure 5. Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 3.
Figure 6. Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 4.
Cluster 5 (n = 10) was composed of coffee drinkers who gave a high liking rating for Breakfast
and disliked the dark roasts (Newman, Italian, and Sumatra) [7]. Citrus and acidity were shown to
explain positive emotions (e.g., relaxed, soothing, understanding, peaceful), and coffee aroma explained
fun, rewarded, and pleased (Figure 7). On the other hand, coffee flavor and rioy appeared to describe
negative emotions, including nervous, disgusted, and annoyed. Coffee drinkers in Cluster 6 (n = 10)
CoffeeA
RoastA
BurntA
RioyA AshyA
CocoaA
CoffeeF
RoastF BurntF
Acidity
Bitter
RioyF
AshyF
Citrus
Tobacco
Stale
Body
Active
Annoyed
Awake Balanced
Boosted
Bored
Clear-minded
Comfortable
Content
Curious
Disappointed
Disgusted
Educated
Empowering
Energetic
Free
Fulfilled
Fun
Good
Grouchy
Guilty
In control
Jolted
Joyful
Jump start
Merry
Motivated
Nervous
Off balance
Peaceful
Pleasant
Pleased
Productive
Relaxed
Rested
Rewarded
Satisfied
Social
Soothing
Special
Understanding
Warm
Wild
Worried
Breakfast
Italian
Kona
Nantucket
Newman
Sumatra
-1.2
0.0
1.2
-1.2 0.0 1.2
DIM 2 (X: 23%, Y: 16%)
DIM 1 (X: 45%, Y: 19%)
CoffeeA
RoastA
BurntA
RioyA
AshyA
CocoaA
CoffeeF
RoastF
BurntF
Acidity
Bitter
RioyF
AshyF
Citrus
Tobacco
Stale
Body
Active
Annoyed
Awake
Balanced Boosted
Bored
Clear-minded
Comfortable
Content
Curious
Disappointed Disgusted
Educated
Empowering
Energetic
Free
Fulfilled
Fun
Good
Grouchy
Guilty
In control
Jolted
Joyful
Jump start
Merry
Motivated
Nervous
Off balance
Peaceful
Pleasant
Pleased
Productive
Relaxed
Rested Rewarded
Satisfied
Social
Soothing
Special
Understanding
Warm
Wild
Worried
Breakfast
Italian
Kona
Nantucket
Newman
Sumatra
-1.2
0.0
1.2
-1.2 0.0 1.2
DIM 2 (X: 25% , Y: 17%)
DIM 1 (X: 43%, Y: 28%)
Cluster 3
Cluster 4
Figure 5.
Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 3.
Beverages 2019, 5, x FOR PEER REVIEW 9 of 13
Figure 5. Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 3.
Figure 6. Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 4.
Cluster 5 (n = 10) was composed of coffee drinkers who gave a high liking rating for Breakfast
and disliked the dark roasts (Newman, Italian, and Sumatra) [7]. Citrus and acidity were shown to
explain positive emotions (e.g., relaxed, soothing, understanding, peaceful), and coffee aroma explained
fun, rewarded, and pleased (Figure 7). On the other hand, coffee flavor and rioy appeared to describe
negative emotions, including nervous, disgusted, and annoyed. Coffee drinkers in Cluster 6 (n = 10)
CoffeeA
RoastA
BurntA
RioyA AshyA
CocoaA
CoffeeF
RoastF BurntF
Acidity
Bitter
RioyF
AshyF
Citrus
Tobacco
Stale
Body
Active
Annoyed
Awake Balanced
Boosted
Bored
Clear-minded
Comfortable
Content
Curious
Disappointed
Disgusted
Educated
Empowering
Energetic
Free
Fulfilled
Fun
Good
Grouchy
Guilty
In control
Jolted
Joyful
Jump start
Merry
Motivated
Nervous
Off balance
Peaceful
Pleasant
Pleased
Productive
Relaxed
Rested
Rewarded
Satisfied
Social
Soothing
Special
Understanding
Warm
Wild
Worried
Breakfast
Italian
Kona
Nantucket
Newman
Sumatra
-1.2
0.0
1.2
-1.2 0.0 1.2
DIM 2 (X: 23%, Y: 16%)
DIM 1 (X: 45%, Y: 19%)
CoffeeA
RoastA
BurntA
RioyA
AshyA
CocoaA
CoffeeF
RoastF
BurntF
Acidity
Bitter
RioyF
AshyF
Citrus
Tobacco
Stale
Body
Active
Annoyed
Awake
Balanced Boosted
Bored
Clear-minded
Comfortable
Content
Curious
Disappointed Disgusted
Educated
Empowering
Energetic
Free
Fulfilled
Fun
Good
Grouchy
Guilty
In control
Jolted
Joyful
Jump start
Merry
Motivated
Nervous
Off balance
Peaceful
Pleasant
Pleased
Productive
Relaxed
Rested Rewarded
Satisfied
Social
Soothing
Special
Understanding
Warm
Wild
Worried
Breakfast
Italian
Kona
Nantucket
Newman
Sumatra
-1.2
0.0
1.2
-1.2 0.0 1.2
DIM 2 (X: 25% , Y: 17%)
DIM 1 (X: 43%, Y: 28%)
Cluster 3
Cluster 4
Figure 6.
Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 4.
Cluster 5 (n= 10) was composed of coffee drinkers who gave a high liking rating for Breakfast
and disliked the dark roasts (Newman, Italian, and Sumatra) [
7
]. Citrus and acidity were shown to
explain positive emotions (e.g., relaxed,soothing,understanding,peaceful), and coffee aroma explained
fun,rewarded, and pleased (Figure 7). On the other hand, coffee flavor and rioy appeared to describe
negative emotions, including nervous,disgusted, and annoyed. Coffee drinkers in Cluster 6 (n= 10)
were classified as preferring Kona coffee [
7
]. The PLSR bi-plot (Figure 8) reflects that this group of
consumers were attracted to the cocoa aroma as most positive emotions (i.e., balanced,productive,fulfilled,
Beverages 2019,5, 27 10 of 13
awake,motivated, and energetic). Tobacco also described good and soothing emotions, while acidity seemed
to generate mixed emotions of rewarded,free,jolted, and nervous.
Beverages 2019, 5, x FOR PEER REVIEW 10 of 13
were classified as preferring Kona coffee [7]. The PLSR bi-plot (Figure 8) reflects that this group of
consumers were attracted to the cocoa aroma as most positive emotions (i.e., balanced, productive,
fulfilled, awake, motivated, and energetic). Tobacco also described good and soothing emotions, while
acidity seemed to generate mixed emotions of rewarded, free, jolted, and nervous.
Figure 7. Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 5.
Figure 8. Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 6.
CoffeeA
RoastA
BurntA
RioyA
AshyA
CocoaA
CoffeeF
RoastF
BurntF
Acidity
Bitter
RioyF
AshyF
Citrus
Tobacco
Stale
Body
Active
Annoyed
Awake
Balanced
Boosted
Bored
Clear-minded
Comfortable
Content
Curious
Disappointed
Disgusted
Educated
Empowering
Energetic
Free
Fulfilled
Fun
Good
Grouchy
Guilty
In control
Jolted
Joyful
Jump start
Merry
Motivated
Nervous
Off balance
Peaceful
Pleasant
Pleased
Productive
Relaxed
Rested
Rewarded
Satisfied
Social
Soothing
Special
Understanding
Warm
Wild
Worried
Breakfast
Italian
Kona
Nantucket
Newman
Sumatra
-1.2
0.0
1.2
-1.2 0.0 1.2
DIM 2 (X: 27%, Y: 24%)
DIM 1 (X:42%, Y: 32%)
CoffeeA
RoastA
BurntA
RioyA
AshyA
CocoaA
CoffeeF
RoastF
BurntF
Acidity
Bitter
RioyF
AshyF
Citrus
Tobacco
Stale
Body
Active
Annoyed
Awake
Balanced
Boosted
Bored
Clear-minded
Comfortable
Content
Curious
Disappointed
Disgusted
Educated Empowering
Energetic
Free
Fulfilled
Fun
Good
Grouchy
Guilty
In control
Jolted
Joyful
Jump start
Merry
Motivated
Nervous
Off balance
Peaceful
Pleasant
Pleased
Productive
Relaxed
Rested
Rewarded
Satisfied
Social
Soothing
Special
Understanding
Warm
Wild
Worried
Breakfast
Italian
Kona
Nantucket
Newman
Sumatra
-1.2
0.0
1.2
-1.2 0.0 1.2
DIM 2 (X: 20% , Y: 37%)
DIM 1 (X: 36%, Y: 27%)
Cluster 5
Cluster 6
Figure 7.
Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 5.
Beverages 2019, 5, x FOR PEER REVIEW 10 of 13
were classified as preferring Kona coffee [7]. The PLSR bi-plot (Figure 8) reflects that this group of
consumers were attracted to the cocoa aroma as most positive emotions (i.e., balanced, productive,
fulfilled, awake, motivated, and energetic). Tobacco also described good and soothing emotions, while
acidity seemed to generate mixed emotions of rewarded, free, jolted, and nervous.
Figure 7. Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 5.
Figure 8. Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 6.
CoffeeA
RoastA
BurntA
RioyA
AshyA
CocoaA
CoffeeF
RoastF
BurntF
Acidity
Bitter
RioyF
AshyF
Citrus
Tobacco
Stale
Body
Active
Annoyed
Awake
Balanced
Boosted
Bored
Clear-minded
Comfortable
Content
Curious
Disappointed
Disgusted
Educated
Empowering
Energetic
Free
Fulfilled
Fun
Good
Grouchy
Guilty
In control
Jolted
Joyful
Jump start
Merry
Motivated
Nervous
Off balance
Peaceful
Pleasant
Pleased
Productive
Relaxed
Rested
Rewarded
Satisfied
Social
Soothing
Special
Understanding
Warm
Wild
Worried
Breakfast
Italian
Kona
Nantucket
Newman
Sumatra
-1.2
0.0
1.2
-1.2 0.0 1.2
DIM 2 (X: 27%, Y: 24%)
DIM 1 (X:42%, Y: 32%)
CoffeeA
RoastA
BurntA
RioyA
AshyA
CocoaA
CoffeeF
RoastF
BurntF
Acidity
Bitter
RioyF
AshyF
Citrus
Tobacco
Stale
Body
Active
Annoyed
Awake
Balanced
Boosted
Bored
Clear-minded
Comfortable
Content
Curious
Disappointed
Disgusted
Educated Empowering
Energetic
Free
Fulfilled
Fun
Good
Grouchy
Guilty
In control
Jolted
Joyful
Jump start
Merry
Motivated
Nervous
Off balance
Peaceful
Pleasant
Pleased
Productive
Relaxed
Rested
Rewarded
Satisfied
Social
Soothing
Special
Understanding
Warm
Wild
Worried
Breakfast
Italian
Kona
Nantucket
Newman
Sumatra
-1.2
0.0
1.2
-1.2 0.0 1.2
DIM 2 (X: 20% , Y: 37%)
DIM 1 (X: 36%, Y: 27%)
Cluster 5
Cluster 6
Figure 8.
Partial least square regression analysis of descriptive sensory and CDE emotion lexicon of
the six coffee samples for consumer Cluster 6.
Beverages 2019,5, 27 11 of 13
This study presented the useful interaction of sensory and emotion data. Using the emotion
profiles generated by the 44 emotions on the coffee drinking experience lexicon, we were able to
identify some sensory drivers for specific emotions elicited by coffee drinking.
4. Conclusions
The PLSR maps indicated that sensory descriptive data might be used to describe emotions
profiles elicited by coffee drinking. The PLSR maps were used to identify which attributes had an
impact on positive or negative emotional responses from various groups of coffee drinkers. In general,
coffee aroma, citrus, and acidity elicited negative feelings while cocoa aroma, tobacco,bitter,roast,burnt,
and body generated positive emotions. As consumers have differing likes and dislikes, this study also
examined each consumer cluster based on their preferences and identified sensory drivers for the
emotions experienced by each cluster. These insights generated by the interaction of sensory and
emotion data are valuable to both marketers and product developers by explaining acceptability data
and change in consumption or purchase behavior.
Author Contributions:
N.B. conceptualized and designed the study with the help of K.A. and E.C.I.; N.B. ran the
descriptive analysis under the guidance of M.W.; The data analysis and manuscript preparation were done by
N.B. with the help of K.A. and E.C.I.
Funding: This research received no external funding.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A
The emotion lexicon for Coffee Drinking Experience (CDE) [7].
Active Disgusted Jolted Relaxed
Annoyed Educated Joyful Rested
Awake Empowering Jumpstart Rewarded
Balanced Energetic Merry Satisfied
Boosted Free Motivated Social
Bored Fulfilling Nervous Soothing
Clear-minded Fun Off-balance Special
Comfortable Good Peaceful Understanding
Content Grouchy Pleasant Warm
Curious Guilty Pleased Wild
Disappointed In-control Productive Worried
Appendix B
Mean liking scores on a 9-point Hedonic scale for each consumer cluster and coffee sample [7].
Cluster Breakfast Italian Kona Nantucket Newman Sumatra
C1 (n= 20) 7.7 6.9 7.3 7.7 7.5 7.2
C2 (n= 17) 4.4 6.9 6.7 6.1 7.2 6.5
C3 (n= 24) 7.0 6.0 5.8 7.5 5.3 3.7
C4 (n= 13) 4.6 3.5 5.7 6.0 5.5 5.4
C5 (n= 10) 7.1 3.3 3.5 4.1 2.2 2.1
C6 (n= 10) 5.9 6.4 7.0 3.6 5.1 6.1
References
1.
Chrea, C.; Grandjean, D.; Delplanque, S.; Cayeux, I.; Le Calve, B.; Aymard, L.; Velazco, M.I.; Sander, D.;
Scherer, K. Mapping the semantic space for the subjective experience of emotional responses to odors. Chem.
Senses 2009,34, 49–62. [CrossRef] [PubMed]
Beverages 2019,5, 27 12 of 13
2.
Porcherot, C.; Delplanque, S.; Raviot-Derrien, S.; Le Calve, B.; Chrea, C.; Gaudreau, N.; Cayeux, I. How do
you feel when you smell this? Optimization of a verbal measurement of odor-elicited emotions. Food Qual.
Prefer. 2010,21, 938–947. [CrossRef]
3.
Thomson, D.M.H. Sensory Cues for Emotional Responses to Foods & Drinks. International Union of Food
Science and Technology (IUFoST), 2006. Available online: http://dx.doi.org/10.1051/IUFoST:20061091
(accessed on 1 December 2018).
4.
Thomson, D.M.H.; Crocker, C.; Marketo, C.G. Linking sensory characteristics to emotions: An example using
dark chocolate. Food Qual. Prefer. 2010,21, 1117–1125. [CrossRef]
5.
Gibson, E.L. Emotional influences on food choice: Sensory, physiological and psychological pathways.
Physiol. Behav. 2006,89, 53–61. [CrossRef] [PubMed]
6.
King, S.C.; Meiselman, H.L. Development of a method to measure consumer emotions associated with foods.
Food Qual. Prefer. 2009,21, 168–177. [CrossRef]
7.
Bhumiratana, N.; Adhikari, K.; Chambers, E., IV. The development of an emotion lexicon for the coffee
drinking experience. Food Res. Int. 2014,61, 83–92. [CrossRef]
8. Illy, E. The complexity of coffee. Sci. Am. 2002,286, 86–91. [CrossRef]
9. Grosch, W. Flavour of coffee: A review. Nahrung 1998,42, 344–350. [CrossRef]
10.
Czerny, M.; Mayer, F.; Grosch, W. Sensory study on the character impact odorants of roasted Arabica coffee.
J. Agric. Food Chem. 1999,47, 695–699. [CrossRef]
11. Illy, A.; Viani, R. Espresso Coffee: The Science of Quality, 2nd ed.; Elsevier Academic Press: London, UK, 2005.
12.
Di Donfrancesco, B.; Gutierrez Guzman, N.; Chambers, E., IV. Comparison of results from cupping and
descriptive sensory analysis of Colombian brewed coffee. J. Sens. Stud. 2014,29, 301–311. [CrossRef]
13.
Bhumiratana, N.; Adhikari, K.; Chambers, E., IV. Green coffee beans to brewed coffee: Evolution of coffee
aroma. LWT-Food Sci. Technol. 2011,44, 2185–2192. [CrossRef]
14.
Chambers, D.H.; Allison, A.; Chambers, E., IV. Training effects on performance of descriptive panelists. J.
Sens. Stud. 2004,19, 486–499. [CrossRef]
15.
Chambers, E., IV; Smith, E.A. Effects of testing experience on performance of trained sensory panelists. J.
Sens. Stud. 1993,8, 155–166.
16.
Wolters, C.J.; Allchurch, E.M. Effect of training procedure on the performance of descriptive panels. Food
Qual. Prefer. 1994,5, 203–214. [CrossRef]
17.
Bitnes, J.; Ueland, O.; Moller, P.; Martens, M. Reliability of sensory assessors: Issues of retention and learning.
J. Sens. Stud. 2008,23, 852–870. [CrossRef]
18.
Chambers, E., IV; Sanchez, K.; Phan, U.T.X.; Miller, R.; Civille, G.V.; Di Donfrancesco, B. Development of a
“living” lexicon for descriptive sensory analysis of brewed coffee. J. Sens. Stud.
2016
,31, 465–480. [CrossRef]
19.
Jager, G.; Schlich, P.; Tijjsen, I.; Yao, J.; Visalli, M.; de Graaf, C.; Steiger, M. Temporal dominance of emotions:
Measuring dynamics of food-related emotions during consumption. Food Qual. Prefer.
2014
,37, 87–99.
[CrossRef]
20.
Schenker, S.; Heinemann, C.; Huber, M.; Pompizzi, R.; Perren, R.; Escher, F. Impact of roasting conditions on
the formation of aroma compounds in coffee beans. J. Food Sci. 2002,67, 60–66. [CrossRef]
21.
Yeretzian, C.; Jordan, A.; Badoud, R.; Lindinger, W. From the green bean to the cup of coffee: Investigating
coffee roasting by on-line monitoring of volatiles. Eur. Food Res. Technol. 2002,214, 92–104. [CrossRef]
22.
Baggenstoss, J.; Poisson, L.; Kaegi, R.; Perren, R.; Escher, F. Coffee roasting and aroma formation: Application
of different time and temperature conditions. J. Agric. Food Chem. 2008,56, 5836–5846. [CrossRef]
23.
Mayer, F.; Czerny, M.; Grosch, W. Influence of provenance and roast degree on the composition of potent
odorants in Arabica coffees. Eur. Food Res. Technol. 1999,209, 242–250. [CrossRef]
24.
Decazy, F.; Avelino, J.; Guyot, B.; Perriot, J.J.; Pineda, C.; Cilas, C. Quality of different Honduran coffees in
relation to several environments. J. Food Sci. 2003,68, 2356–2361. [CrossRef]
25.
Nebesny, E.; Budryn, G. Evaluation of sensory attributes of coffee brews from robusta coffee roasted under
different conditions. Eur. Food Res. Technol. 2006,224, 159–165. [CrossRef]
26.
Ross, C.F.; Pecka, K.; Weller, K. Effect of storage conditions on the sensory quality of ground Arabica coffee.
J. Food Qual. 2006,29, 596–606. [CrossRef]
27.
Seo, H.S.; Hirano, M.; Shibato, M.; Rakwal, R.; Hwang, I.K.; Masuo, Y. Effect of coffee bean aroma on the rat
brain stressed by sleep deprivation: A selected transcript and 2D get-based proteome analysis. J. Agric. Food
Chem. 2008,56, 4665–4673. [CrossRef] [PubMed]
Beverages 2019,5, 27 13 of 13
28.
Macht, M.; Mueller, J. Immediate effects of chocolate on experimentally induced mood states. Appetite
2007
,
49, 667–674. [CrossRef] [PubMed]
29.
Richins, M.L. Measuring emotions in the consumption experience. J. Cons. Res.
1997
,24, 127–146. [CrossRef]
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... The objective of this phase was to identify how trained judges and consumers use the memories vocabulary to characterize coffee samples as well as its relationship with sensory attributes and emotions at the trained panel and consumers' level. Coffee was used as a stimulus due to its sensory complexity and the experiences it generates (Bhumiratana et al., 2019). Additionally, coffee is very well known worldwide making it an excellent candidate to serve as a model for the development of our memories vocabulary as it is very probable consumers to have memories associated to this product. ...
... In the same sense, Excess negative memory could have been mentioned by consumers because it is related to hypersensitivity to food stimuli that influence the formation of people's preferences, for example, consumers that have a tendency for the consumption of foods rich in fat or fast foods (Moreno-Padilla et al., 2018;Blau et al., 2020). The word Addiction could be mentioned by consumers due to the dependence on products of alcoholic beverages, cola drinks, coffee, among others (Yamada et al., 2014;Bhumiratana et al., 2019). Finally, the negative memories, Stench or unpleasant odors is also of importance according to Jiménez (2014) who mentioned that this smell can influence acceptance or rejection of interpersonal relationships and is linked to feelings, sensations, or images such as food (e.g., cheese, fermented food, egg, among others), aspects of personal hygiene, state of conservation of objects or places (e.g., shoes, clothing, closed premises, among others). ...
... Positive and negative memories of industrialized coffees could have been evoked by different sensory attributes considered as negative such as spicy, rancidity, wood and earthy that after the mentioned memories evoked negative emotions (e.g., Bored, Aggressive, Guilty, Disgusted, Nostalgic, Worried and Wild). Both, emotions, and sensory attributes mentioned above were also reported in the studies of Bhumiratana et al. (2019) and Ramírez-Rivera et al. (2021) who evaluated coffee samples. Results from this study suggest that this first approximation of the memories vocabulary can be further evaluated with more emphasis in different situations such as 1) relationship of memories with preference data to explore in depth the possible memories that have the greatest influence on the purchase intent; 2) intra and inter-cultural studies to verify if the vocabulary of memories of this research is understood and used in the same way between different cultures; 3) to verify how the memories generated by the consumption of food at different times of the year can vary, since it has been shown that seasonality influences people's attitudes; 4) analysis of the duration of memories during consumption in real time using dynamic sensory techniques such as Temporal Dominance of Sensations; 5) the application of this memories vocabulary in other products where sensory evaluation has been used, such as cosmetics, medicines, automobiles, among others. ...
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Multiple references in sensory science indicate that foods evoke memories during consumption, however, research regarding those memories is still limited. The objective of this study was to develop a vocabulary and implement it in a memories vocabulary related to food as a complement for the evaluation of sensory attributes and emotions, using coffee as a model. The memories vocabulary was generated with a series of successive studies that involved assigning positive and negative memories to different food groups and applying mathematical algorithms (WordCountAna and Factorial Approach) and contrasting memories with the scientific literature. Subsequently, the vocabulary was used to determine the profile of memories and their association with sensory attributes and emotions in coffee samples evaluated by trained judges and consumers. The memories vocabulary consisted of a total of 14 and 12 positive and negative memories terms, respectively. The vocabulary of memories was used in a similar way by both panels allowing them to differentiate between artisanal and industrial coffees. The memories vocabulary of the coffees showed a positive association with sensory attributes and emotions, thus achieving a more robust explanation of the samples used in the research.
... First, participants read a story about a fictitious coffee brand. Coffee was selected because it is a product that, when consumed, elicits positive emotions in consumers, such as nostalgia (Bhumiratana et al., 2019;Labbe et al., 2015). The story was constructed by the researchers, based on the narrative structure theory. ...
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Given that previous studies have supported the idea that brand storytelling has a significant impact on consumer behaviour, brand stories are increasingly becoming a part of companies' marketing communications tools. The present study investigates the effect of nostalgic corporate storytelling on consumer responses to the brand. Its originality lies in the fact that it is the first attempt to explore nostalgic storytelling, and its effect on consumer responses. A survey was conducted with a sample of 233 respondents; the telling of a story for a fictitious brand was used. The main findings reveal that attitude toward this particular storytelling mediates the relationship between fantasies about past eras and brand attitude, brand attitude mediates the relationship between attitude toward storytelling and brand heritage, the relationship between fantasies about past eras and brand heritage is mediated by brand attitude, whereas the association between fantasies about past eras and brand heritage is sequentially mediated by attitude toward the storytelling and attitude toward the brand.
... The resultant bi-plot is later utilized to determine the drivers for the dependent variables. Sample identities are also anchored in the bi-plot so that their correlation with independent and dependent variables is described [23,24]. In this study, the dependent variables (Ys) were FRSA (expressed as a percentage of inhibition) and cytotoxicity (expressed as IC50), and the independent variables (Xs) were isoflavone data. ...
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Tempeh is nutritious food prepared through solid-state fermentation of cooked and dehulled soybeans with Rhizopus sp. for about 48 h. Fermentation beyond 48 h resulted in over-fermented tempeh. There may or may not have been similar research done before, especially related to its antioxidant and cytotoxicity. This study aims to determine the characteristics of fermented tempeh for up to 156 h. Samples were fermented at 0, 24, 48, 60, 72, 84, 96, 108, 120, and 156 h. Samples were dried, grounded, and extracted with acetone, followed by defatting with n‑hexane. Extracts were dissolved in organic solvents for free radical scavenging activity (FRSA) and cytotoxicity assays. The 120-h tempeh extract, at the concentration of 1,000 μg/mL, demonstrated the highest FRSA (81.31% inhibition) against 100 µM 2,2-diphenyl-1-picrylhydrazyl (DPPH) solution. Meanwhile, the 108-h tempeh extract at 1,000 μg/mL possessed the highest cytotoxicity (IC50 of 2.54 μg/mL) against MCF-7 breast cancer cell lines. Liquid Chromatography-Mass Spectrometry/Mass Spectroscopy (LC-MS/MS) analysis revealed the presence of daidzin, genistin, daidzein, and genistein in all extracts. Extracts prepared from 108 h and 120 h tempeh stood out from other extracts in the Partial Least Square (PLS) bi-plot due to their high percentage of inhibition, low response of daidzin, and high responses of the other three isoflavones. The cytotoxicity assays of the standard isoflavones showed that genistein had the lowest IC50 value at 4.82 ± 0.11 μg/mL. Standard genistein showed a low percentage of inhibition at 29.79 ± 9.10.
... The most outstanding characteristic of coffee is the peculiarity of its aromas and flavors formed during the roasting process. These generate in the consumer an excellent and stimulating sensory experience, increasing day by day its consumption worldwide (Bhumiratana et al., 2019). According to the International Coffee Organization (ICO), the world coffee export was 126.96 million bags in 2019/2020, with Brazil, Vietnam and Colombia being the largest producers and exporters worldwide with 40, 28 and 13 million bags exported, respectively (about 60% of production). ...
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s Background Neo-formed contaminants (NFCs) occurrence in coffee, a highly consumed beverage worldwide, has raised concern among different food safety agencies because a high intake of these toxic compounds may represent a long-term risk for the consumer health. The mechanisms responsible of NFCs formation in roasted coffee also trigger the generation of its desirable aroma and flavor characteristics. Hence their mitigation in coffee beverage while preserving these organoleptic properties represent a food safety challenge. Scope and approach This article performs a systematic review of the different strategies proposed for the NFCs mitigation in roasted coffee considering their effect on the bioactive compounds content and the sensory characteristics of the final product. The mechanisms of NFCs formation are addressed as the main axis for the rational design of technologies for their mitigation. Key findings and conclusions Available technologies for decreasing the NFCs (acrylamide, furfuryl alcohol, furan and 5-hydroxymethylfulfural) levels in roasted coffee were grouped in two main categories: (i) mitigation (before or during roasting) and (ii) reduction (after roasting). The understanding of the mechanisms responsible of NFCs formation allowed to establish different alternatives for their mitigation in roasted coffee. However, the greatest challenge still lies in guaranteeing a final product low in NFCs with desirable sensory and bioactive characteristics. The rational design of strategies that decrease the occurrence NFCs in roasted coffee without affecting its nutritional and sensory quality must consider the inclusion of pre-roasting stages such as fermentation and drying into the mitigation technology.
... A, aroma; BT, basic taste; F, flavor spicy, and smoky, respectively. These attributes are consistent with studies of Chambers IV et al. (2016), Bhumiratana et al. (2019) and ...
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... The purpose was to understand if certain PB alternatives are more similar/different to other product offerings such that inspiration for strategies to reducing consumption barriers could be based hereupon. Finally, variation regarding emotional, conceptual and situational product characteristics was sought across the beverage stimuli (e.g., Ng, Chaya, Hort, 2013;Waehrens, Grønbeck, Olsen, & Byrne, 2018;Bhumiratana, Wolf, Chambers, & Adhikari, 2019;Samant & Seo, 2020). ...
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