Beer and Consumer Response Using Biometrics: Associations Assessment of Beer Compounds and Elicited Emotions

Some chemical compounds, especially alcohol, sugars, and alkaloids such as hordenine, have been reported as elicitors of different emotional responses. This preliminary study was based on six commercial beers selected according to their fermentation type, with two beers of each type (spontaneous, bottom, and top). Chemometry and sensory analysis were performed for all samples to determine relationships and patterns between chemical composition and emotional responses from consumers. The results showed that sweeter samples were associated with higher perceived liking by consumers and positive emotions, which corresponded to spontaneous fermentation beers. There was high correlation (R = 0.91; R2 = 0.83) between hordenine and alcohol content. Beers presenting higher concentrations of both, and higher bitterness, were related to negative emotions. Further studies should be conducted, giving more time for emotional response analysis between beer samples, and comparing alcoholic and non-alcoholic beers with similar styles, to separate the effects of alcohol and hordenine. This preliminary study was a first attempt to associate beer compounds with the emotional responses of consumers using non-invasive biometrics.


Introduction
Beer is a complex alcoholic beverage in terms of its chemical composition and ingredients, such as barley, yeast, hops, and, in some beer products, includes adjuncts that may consist of other cereals or fruits [1,2]. The wide range of combinations that may be used from each of the ingredients, along with the differences in brewing methods, have a great influence on the development of beer's chemical
Hue angle = arctan b * a * × 180 3.14 (1) The density of samples was assessed based on weight and volume (50 mL). Total dissolved solids (TDS) were measured in triplicates using a Yuelong YL-TDS2-A digital water quality tester (Zhengzhou Yuelong Electronic Technology Co., Ltd., Zhengzhou City, Henan Province, China). Salt concentration was obtained using two drops of the sample in triplicates added to a digital salt-meter (PAL-SALT Mohr, Atago Co., Ltd. Saitama, Japan). On the other hand, alcohol content was assessed using 18 mL of the sample at room temperature (20 • C) injected to an Alcolyzer Wine M alcohol meter (Anton Paar GmbH, GRAZ, Austria) with the wine extension method found in the equipment settings; the instrument has a maximum error of 0.1% vv −1 .

Characterization of Simple Sugars by HPLC-Refractive Index
The simple sugars profile was measured as described by Heredia-Olea et al. [30] and Alonso-Gómez et al. [31] with slight modifications. The samples were filtered through a polyvinylidene fluoride (PVDF) syringe filter (0.2 µm) and injected into high-performance liquid chromatography (HPLC) equipment (Waters HPLC Breeze model, Waters, Milford, MA, USA) with a refractive index detector Foods 2020, 9,821 4 of 16 (Waters 2414) kept at 50 • C. The chromatographic separation was achieved using an ion-exclusion column Phenomenex Rezex ROA-organic acid h+ (250 × 4.6 mm, 8 µm particle size, Phenomenex, Torrance, CA, USA) at 60 • C. The mobile phase consisted of a 5 mM H 2 SO 4 solution with a 20 min isocratic flow rate of 0.4 mL min −1 and with an injection volume of 10 µL. Glucose, maltose, and fructose quantifications were performed with calibration curves of HPLC-grade standards (Sigma-Aldrich, St. Louis, MO, USA).

Determination of Bitterness
Bitterness was assessed by manual isooctane extraction as described in the American Society of Brewing Chemists (ASBC) Methods of Analysis with the following modifications [32]. A total of 5 mL of beer was acidified with hydrochloric acid (HCl; 0.5 mL, 3M) and isooctane (10 mL); subsequently, it was homogenized for 15 min using a mechanical shaker. The separation of organic and aqueous layers was performed by centrifugation at 400 g × 5 min. Finally, the isooctane phase (upper) was measured spectrophotometrically at 275 nm. A calculation of bitterness units (IBU) of beer was obtained, as shown in Equation (4).

Hordenine Determination by UPLC-MS/MS
Hordenine sample preparation was performed as described by Sommer et al. [35] with slight modifications. Beer samples were centrifuged for 15 min at 12,000× g and 4 • C; two dilution steps were followed. Dilution I (Dil. I): 50 µL of degassed beer were added to 450 µL of 0.1% formic acid. Dilution II (Dil. II): 20 µL of Dil. I were added to 980 µL of 0.1% formic acid. The solutions obtained after Dil. II were passed through a PVDF filter (0.2 µm, Thermo Scientific™, Waltham, MA, USA) prior to the analysis. For quantification, a calibration curve with a range of 0-0.1 ppm was developed using a stock solution (2 mg mL −1 ) of a hordenine commercial standard (Sigma-Aldrich, St. Louis, MO, USA) prepared in formic acid (0.1%).

Consumer Sensory Evaluation and Biometrics
A sensory session was carried out in Monterrey, NL, Mexico, which is the state with the highest alcoholic drinks consumption with beer as the leader [36,37]. The session was conducted with N = 61 beer consumers (frequency > three times a month; 54% males; 46% females) between 18 and 51 years old (mean age 25.6 ± 6.9 years). Participants were recruited via email and asked to participate in a graduate research project from the Department of Bioengineering, School on Engineering and Sciences of Tecnológico de Monterrey, Campus Monterrey, Mexico (Ethics ID: CSERDBT-0002). According to the Power analysis conducted using the Power and Sample Size Calculator from the SigmaXL ver. 8.15 software (SigmaXL Inc., Kitchener, ON, Canada), the number of participants was sufficient to find significant differences (1-β = 0.98) among the beer samples. The session was conducted at SensoLab Solutions SC, a sensory and consumer science laboratory center, located at the Technology Transfer and Innovation Center of Tecnológico de Monterrey, Mexico. The laboratory was equipped with eight individual sensory booths with uniform lighting. Each booth had an Android ® (Google, Mountain View, CA, USA) Samsung Galaxy Tab 4 tablet (Samsung, Seoul, South Korea) displaying the Bio-Sensory application (App; The University of Melbourne, Parkville, Vic, Australia). The App was able to present the questionnaire ( Table 2) and record videos from the participants while tasting the beer samples to further analyze their emotional responses [29]. Samples (30 mL) were served at refrigeration temperature (4 • C), and water was used as palate cleanser before and between each sample. To assess the visual descriptors of the beers, a video showing the pouring of the sample using the RoboBEER (The University of Melbourne, Parkville, Vic, Australia) was displayed in the App to avoid bias from the variability due to the pouring method and glass effects [22]. As shown in Table 2, two overall liking ratings were obtained at the start and end of the tasting to verify if there is a bias on this descriptor based on the evaluation of specific attributes.  Videos were analyzed using an application developed based on the Affectiva software development kit (SDK; Affectiva, Boston, MA, USA). This application uses the histogram of the oriented gradient to detect and track the micro-and macro-movements of face features and is able to evaluate all videos in batch. Furthermore, it is capable of assessing facial expressions using support vector machine algorithms to translate them into emotions such as i) contempt, ii) disgust, iii) sadness, iv) surprise, v) joy, vi) valence, vii) engagement, and viii) attention, as well as emojis related to facial expressions such as ix) smiley , x) relaxed , xi) winking face , xii) stuck out tongue , xiii) flushed , xiv) rage , xv) smirk , and xvi) disappointed [39].

Statistical analysis
All data were analyzed through ANOVA and least significant differences (LSD) as a post-hoc test (α = 0.05) using Minitab 17.2.1 (Minitab Inc., State College, Pennsylvania, USA). A linear correlation analysis was conducted for alcohol and hordenine values using Microsoft Excel (Microsoft, Redmond, WA, USA). Chemical, sensory (self-reported), and biometric responses were assessed using multivariate data analysis based on principal components analysis (PCA), and multiple factor analysis (MFA) with a customized code written in Matlab ® R2019b (Mathworks, Inc., Natick, MA, USA) and XLSTAT ver. 2020.1.1 (Addinsoft Inc., New York, NY, USA), respectively. Videos were analyzed using an application developed based on the Affectiva software development kit (SDK; Affectiva, Boston, MA, USA). This application uses the histogram of the oriented gradient to detect and track the micro-and macro-movements of face features and is able to evaluate all videos in batch. Furthermore, it is capable of assessing facial expressions using support vector machine algorithms to translate them into emotions such as (i) contempt, (ii) disgust, (iii) sadness, (iv) surprise, (v Videos were analyzed using an application developed based on the Affectiva software elopment kit (SDK; Affectiva, Boston, MA, USA). This application uses the histogram of the ented gradient to detect and track the micro-and macro-movements of face features and is able to luate all videos in batch. Furthermore, it is capable of assessing facial expressions using support tor machine algorithms to translate them into emotions such as i) contempt, ii) disgust, iii) ness, iv) surprise, v) joy, vi) valence, vii) engagement, and viii) attention, as well as emojis related acial expressions such as ix) smiley , x) relaxed , xi) winking face , xii) stuck out tongue , xiii) flushed , xiv) rage , xv) smirk , and xvi) disappointed [39].

. Statistical analysis
All data were analyzed through ANOVA and least significant differences (LSD) as a post-hoc t (α = 0.05) using Minitab 17.2.1 (Minitab Inc., State College, Pennsylvania, USA). A linear relation analysis was conducted for alcohol and hordenine values using Microsoft Excel icrosoft, Redmond, WA, USA). Chemical, sensory (self-reported), and biometric responses were essed using multivariate data analysis based on principal components analysis (PCA), and ltiple factor analysis (MFA) with a customized code written in Matlab ® R2019b (Mathworks, Inc., tick, MA, USA) and XLSTAT ver. 2020.1.1 (Addinsoft Inc., New York, NY, USA), respectively.

esults
. Physicochemical results Table 3 shows the mean values and results from the ANOVA for selected physicochemical rameters. There were significant differences (p < 0.05) between samples for all parameters. Sample ad the lowest mean value for L* (26.58) as this is the darkest beer, while C had the highest value .36). Similarly, the yellow index (YI) was higher for Z (200.40) than all other samples, C being the est (15.69 Videos were analyzed using an application developed based on the Affectiva software velopment kit (SDK; Affectiva, Boston, MA, USA). This application uses the histogram of the ented gradient to detect and track the micro-and macro-movements of face features and is able to aluate all videos in batch. Furthermore, it is capable of assessing facial expressions using support ctor machine algorithms to translate them into emotions such as i) contempt, ii) disgust, iii) ness, iv) surprise, v) joy, vi) valence, vii) engagement, and viii) attention, as well as emojis related facial expressions such as ix) smiley , x) relaxed , xi) winking face , xii) stuck out tongue , xiii) flushed , xiv) rage , xv) smirk , and xvi) disappointed [39].

. Statistical analysis
All data were analyzed through ANOVA and least significant differences (LSD) as a post-hoc t (α = 0.05) using Minitab 17.2.1 (Minitab Inc., State College, Pennsylvania, USA). A linear rrelation analysis was conducted for alcohol and hordenine values using Microsoft Excel icrosoft, Redmond, WA, USA). Chemical, sensory (self-reported), and biometric responses were essed using multivariate data analysis based on principal components analysis (PCA), and ltiple factor analysis (MFA) with a customized code written in Matlab ® R2019b (Mathworks, Inc., tick, MA, USA) and XLSTAT ver. 2020.1.1 (Addinsoft Inc., New York, NY, USA), respectively. Table 3 shows the mean values and results from the ANOVA for selected physicochemical rameters. There were significant differences (p < 0.05) between samples for all parameters. Sample ad the lowest mean value for L* (26.58) as this is the darkest beer, while C had the highest value .36). Similarly, the yellow index (YI) was higher for Z (200.40) than all other samples, C being the est (15.69 Videos were analyzed using an application developed based on the Affectiva software velopment kit (SDK; Affectiva, Boston, MA, USA). This application uses the histogram of the iented gradient to detect and track the micro-and macro-movements of face features and is able to aluate all videos in batch. Furthermore, it is capable of assessing facial expressions using support ctor machine algorithms to translate them into emotions such as i) contempt, ii) disgust, iii) dness, iv) surprise, v) joy, vi) valence, vii) engagement, and viii) attention, as well as emojis related facial expressions such as ix) smiley , x) relaxed , xi) winking face , xii) stuck out tongue , xiii) flushed , xiv) rage , xv) smirk , and xvi) disappointed [39].

Statistical analysis
All data were analyzed through ANOVA and least significant differences (LSD) as a post-hoc st (α = 0.05) using Minitab 17.2.1 (Minitab Inc., State College, Pennsylvania, USA). A linear rrelation analysis was conducted for alcohol and hordenine values using Microsoft Excel icrosoft, Redmond, WA, USA). Chemical, sensory (self-reported), and biometric responses were sessed using multivariate data analysis based on principal components analysis (PCA), and ultiple factor analysis (MFA) with a customized code written in Matlab ® R2019b (Mathworks, Inc., atick, MA, USA) and XLSTAT ver. 2020.1.1 (Addinsoft Inc., New York, NY, USA), respectively. Table 3 shows the mean values and results from the ANOVA for selected physicochemical rameters. There were significant differences (p < 0.05) between samples for all parameters. Sample had the lowest mean value for L* (26.58) as this is the darkest beer, while C had the highest value 9.36). Similarly, the yellow index (YI) was higher for Z (200.40) than all other samples, C being the west (15.69 Videos were analyzed using development kit (SDK; Affectiva, oriented gradient to detect and trac evaluate all videos in batch. Furthe vector machine algorithms to tran sadness, iv) surprise, v) joy, vi) vale to facial expressions such as ix) smi , xiii) flushed , xiv) rage

Statistical analysis
All data were analyzed throu test (α = 0.05) using Minitab 17. correlation analysis was conduct (Microsoft, Redmond, WA, USA). assessed using multivariate data multiple factor analysis (MFA) wit Natick, MA, USA) and XLSTAT ve Videos were analyzed using an application developed based on the Affectiva software evelopment kit (SDK; Affectiva, Boston, MA, USA). This application uses the histogram of the riented gradient to detect and track the micro-and macro-movements of face features and is able to valuate all videos in batch. Furthermore, it is capable of assessing facial expressions using support ector machine algorithms to translate them into emotions such as i) contempt, ii) disgust, iii) adness, iv) surprise, v) joy, vi) valence, vii) engagement, and viii) attention, as well as emojis related o facial expressions such as ix) smiley , x) relaxed , xi) winking face , xii) stuck out tongue , xiii) flushed , xiv) rage , xv) smirk , and xvi) disappointed [39].

.7. Statistical analysis
All data were analyzed through ANOVA and least significant differences (LSD) as a post-hoc est (α = 0.05) using Minitab 17.2.1 (Minitab Inc., State College, Pennsylvania, USA). A linear orrelation analysis was conducted for alcohol and hordenine values using Microsoft Excel Microsoft, Redmond, WA, USA). Chemical, sensory (self-reported), and biometric responses were ssessed using multivariate data analysis based on principal components analysis (PCA), and ultiple factor analysis (MFA) with a customized code written in Matlab ® R2019b (Mathworks, Inc., atick, MA, USA) and XLSTAT ver. 2020.1.1 (Addinsoft Inc., New York, NY, USA), respectively.
. Videos were analyzed using an application developed based on the Affectiva software evelopment kit (SDK; Affectiva, Boston, MA, USA). This application uses the histogram of the riented gradient to detect and track the micro-and macro-movements of face features and is able to valuate all videos in batch. Furthermore, it is capable of assessing facial expressions using support ector machine algorithms to translate them into emotions such as i) contempt, ii) disgust, iii) adness, iv) surprise, v) joy, vi) valence, vii) engagement, and viii) attention, as well as emojis related o facial expressions such as ix) smiley , x) relaxed , xi) winking face , xii) stuck out tongue , xiii) flushed , xiv) rage , xv) smirk , and xvi) disappointed [39].

.7. Statistical analysis
All data were analyzed through ANOVA and least significant differences (LSD) as a post-hoc est (α = 0.05) using Minitab 17.2.1 (Minitab Inc., State College, Pennsylvania, USA). A linear orrelation analysis was conducted for alcohol and hordenine values using Microsoft Excel Microsoft, Redmond, WA, USA). Chemical, sensory (self-reported), and biometric responses were ssessed using multivariate data analysis based on principal components analysis (PCA), and ultiple factor analysis (MFA) with a customized code written in Matlab ® R2019b (Mathworks, Inc., atick, MA, USA) and XLSTAT ver. 2020.1.1 (Addinsoft Inc., New York, NY, USA), respectively.
. Table 3 shows the mean values and results from the ANOVA for selected physicochemical arameters. There were significant differences (p < 0.05) between samples for all parameters. Sample had the lowest mean value for L* (26.58) as this is the darkest beer, while C had the highest value 59.36). Similarly, the yellow index (YI) was higher for Z (200.40) than all other samples, C being the owest (15.69). Spontaneous fermentation beers (LK and LF) were the highest in density (1.02 and .03 g mL −1 , respectively), and significantly different from the other samples. On the other hand, LK as the most viscous (2.16 mPa s), followed by Z and H (1.80 mPa s), with C as the least viscous (1.48 Pa s). On the other hand, the spontaneous fermentation samples were the most acidic (LF: pH = .94, TA = 0.32; LK: pH = 3.17, TA = 0.41), while Z was the least acidic (pH = 4.42, TA = 0.17). Videos were analyzed using an application developed based on the Affectiva software evelopment kit (SDK; Affectiva, Boston, MA, USA). This application uses the histogram of the riented gradient to detect and track the micro-and macro-movements of face features and is able to valuate all videos in batch. Furthermore, it is capable of assessing facial expressions using support ector machine algorithms to translate them into emotions such as i) contempt, ii) disgust, iii) adness, iv) surprise, v) joy, vi) valence, vii) engagement, and viii) attention, as well as emojis related o facial expressions such as ix) smiley , x) relaxed , xi) winking face , xii) stuck out tongue , xiii) flushed , xiv) rage , xv) smirk , and xvi) disappointed [39].

.7. Statistical analysis
All data were analyzed through ANOVA and least significant differences (LSD) as a post-hoc est (α = 0.05) using Minitab 17.2.1 (Minitab Inc., State College, Pennsylvania, USA). A linear orrelation analysis was conducted for alcohol and hordenine values using Microsoft Excel Microsoft, Redmond, WA, USA). Chemical, sensory (self-reported), and biometric responses were ssessed using multivariate data analysis based on principal components analysis (PCA), and ultiple factor analysis (MFA) with a customized code written in Matlab ® R2019b (Mathworks, Inc., atick, MA, USA) and XLSTAT ver. 2020.1.1 (Addinsoft Inc., New York, NY, USA), respectively.
. Table 3 shows the mean values and results from the ANOVA for selected physicochemical arameters. There were significant differences (p < 0.05) between samples for all parameters. Sample had the lowest mean value for L* (26.58) as this is the darkest beer, while C had the highest value 59.36). Similarly, the yellow index (YI) was higher for Z (200.40) than all other samples, C being the owest (15.69). Spontaneous fermentation beers (LK and LF) were the highest in density (1.02 and .03 g mL −1 , respectively), and significantly different from the other samples. On the other hand, LK as the most viscous (2.16 mPa s), followed by Z and H (1.80 mPa s), with C as the least viscous (1.  Videos were analyzed using an application developed based on the Affectiva software evelopment kit (SDK; Affectiva, Boston, MA, USA). This application uses the histogram of the riented gradient to detect and track the micro-and macro-movements of face features and is able to valuate all videos in batch. Furthermore, it is capable of assessing facial expressions using support ector machine algorithms to translate them into emotions such as i) contempt, ii) disgust, iii) adness, iv) surprise, v) joy, vi) valence, vii) engagement, and viii) attention, as well as emojis related o facial expressions such as ix) smiley , x) relaxed , xi) winking face , xii) stuck out tongue , xiii) flushed , xiv) rage , xv) smirk , and xvi) disappointed [39].

.7. Statistical analysis
All data were analyzed through ANOVA and least significant differences (LSD) as a post-hoc est (α = 0.05) using Minitab 17.2.1 (Minitab Inc., State College, Pennsylvania, USA). A linear orrelation analysis was conducted for alcohol and hordenine values using Microsoft Excel Microsoft, Redmond, WA, USA). Chemical, sensory (self-reported), and biometric responses were ssessed using multivariate data analysis based on principal components analysis (PCA), and ultiple factor analysis (MFA) with a customized code written in Matlab ® R2019b (Mathworks, Inc., atick, MA, USA) and XLSTAT ver. 2020.1.1 (Addinsoft Inc., New York, NY, USA), respectively.
. Table 3 shows the mean values and results from the ANOVA for selected physicochemical arameters. There were significant differences (p < 0.05) between samples for all parameters. Sample had the lowest mean value for L* (26.58) as this is the darkest beer, while C had the highest value 59.36). Similarly, the yellow index (YI) was higher for Z (200.40) than all other samples, C being the owest (15.69). Spontaneous fermentation beers (LK and LF) were the highest in density (1.02 and .03 g mL −1 , respectively), and significantly different from the other samples. On the other hand, LK as the most viscous (2.16 mPa s), followed by Z and H (1.80 mPa s), with C as the least viscous (1.48 Pa s). On the other hand, the spontaneous fermentation samples were the most acidic (LF: pH = .94, TA = 0.32; LK: pH = 3.17, TA = 0.41), while Z was the least acidic (pH = 4.42, TA = 0.17).

Statistical Analysis
All data were analyzed through ANOVA and least significant differences (LSD) as a post-hoc test (α = 0.05) using Minitab 17.2.1 (Minitab Inc., State College, PA, USA). A linear correlation analysis was conducted for alcohol and hordenine values using Microsoft Excel (Microsoft, Redmond, WA, USA). Chemical, sensory (self-reported), and biometric responses were assessed using multivariate data analysis based on principal components analysis (PCA), and multiple factor analysis (MFA) with a customized code written in Matlab ® R2019b (Mathworks, Inc., Natick, MA, USA) and XLSTAT ver. 2020.1.1 (Addinsoft Inc., New York, NY, USA), respectively. Table 3 shows the mean values and results from the ANOVA for selected physicochemical parameters. There were significant differences (p < 0.05) between samples for all parameters. Sample Z had the lowest mean value for L* (26.58) as this is the darkest beer, while C had the highest value (59.36). Similarly, the yellow index (YI) was higher for Z (200.40) than all other samples, C being the lowest (15.69). Spontaneous fermentation beers (LK and LF) were the highest in density (1.02 and 1.03 g mL −1 , respectively), and significantly different from the other samples. On the other hand, LK was the most viscous (2.16 mPa s), followed by Z and H (1.80 mPa s), with C as the least viscous (1.48 mPa s). On the other hand, the spontaneous fermentation samples were the most acidic (LF: pH = 2.94, TA = 0.32; LK: pH = 3.17, TA = 0.41), while Z was the least acidic (pH = 4.42, TA = 0.17). Figure 1 shows the means and ANOVA results of the total sugars, bitterness (Figure 1a), iso-alpha acids, and hordenine ( Figure 1b). The spontaneous fermentation beers had significantly higher (p < 0.05) total sugar content (LF: 31.23 mg mL −1 ; LK: 27.53 mg mL −1 ) than the samples from other types of fermentation; for C, the sugar concentration was non-detectable with the chromatographic conditions used. Sample Z was the highest in both bitterness (34.98 IBU) and total iso alpha-acids (21.41 mg L −1 ), while LF was the least bitter (bitterness: 5.08 IBU; total iso-alpha acids: 0.60 mg L −1 ). On the other hand, the top fermentation beers (Z and L) had the highest concentrations of hordenine  (a) , total Iso-α-acid concentration (mg L −1 ). Different letters above bars denote significant differences between beer samples, for the same chemical parameter, according to the least significant difference test (LSD; p < 0.05). * Total sugars not detected in beer C. All values are the mean ± SE (error bars) of independent determinations. n = 3, hordenine, and bitterness; n = 2, total sugars, and total-α-acids. Abbreviations of samples may be found in Table 1. Table 4 shows that the simple sugars from the spontaneous fermentation samples (LF and LK) were mainly composed of glucose (LF: 14.32 mg mL −1 ; LK: 13.91 mg mL −1 ), followed by fructose (LF: 13.51 mg mL −1 ; LK: 12.56 mg mL −1 ), and maltose (LF: 3.40 mg mL −1 ; LK: 1.06 mg mL −1 ). Sample H had higher values of maltose (0.79 mg mL −1 ) than glucose (0.60 mg mL −1 ) and fructose (0.50 mg mL −1 ), while L was higher in fructose (2.04 mg mL −1 ) than glucose (1.87 mg mL −1 ) and did not contain maltose. Spontaneous fermentation beers were the highest in salt concentration (LK and LF: 0.10%), while C was the lowest (0.05%). A similar trend was found for TDS with LF and LK; although being significantly different, both presented the highest values (LF: 1226 ppm; LK: 1148 ppm), while C had the lowest with 658 ppm. Top fermentation beers showed the highest alcohol content (Z: 9.47%; L: 6.68%), while spontaneous fermentation samples had the lowest (LF: 2.53%; LK: 3.53%). A similar trend was found for the content of trans-Isocohumulone and trans-Isohumulone parameters with Z Figure 1. Chemical characterization of commercial beers, including (a) total sugars (mg mL −1 ), bitterness (IBU), (b) hordenine (mg L −1 ), total Iso-α-acid concentration (mg L −1 ). Different letters above bars denote significant differences between beer samples, for the same chemical parameter, according to the least significant difference test (LSD; p < 0.05). * Total sugars not detected in beer C. All values are the mean ± SE (error bars) of independent determinations. n = 3, hordenine, and bitterness; n = 2, total sugars, and total-α-acids. Abbreviations of samples may be found in Table 1. Table 4 shows that the simple sugars from the spontaneous fermentation samples (LF and LK) were mainly composed of glucose (LF: 14.32 mg mL −1 ; LK: 13.91 mg mL −1 ), followed by fructose (LF: 13.51 mg mL −1 ; LK: 12.56 mg mL −1 ), and maltose (LF: 3.40 mg mL −1 ; LK: 1.06 mg mL −1 ). Sample H had higher values of maltose (0.79 mg mL −1 ) than glucose (0.60 mg mL −1 ) and fructose (0.50 mg mL −1 ), while L was higher in fructose (2.04 mg mL −1 ) than glucose (1.87 mg mL −1 ) and did not contain maltose. Spontaneous fermentation beers were the highest in salt concentration (LK and LF: 0.10%), while C was the lowest (0.05%). A similar trend was found for TDS with LF and LK; although being significantly different, both presented the highest values (LF: 1226 ppm; LK: 1148 ppm), while C had the lowest with 658 ppm. Top fermentation beers showed the highest alcohol content (Z: 9.47%; L: 6.68%), while spontaneous fermentation samples had the lowest (LF: 2.53%; LK: 3.53%). A similar trend was found for the content of trans-Isocohumulone and trans-Isohumulone parameters with Z   Table 5 shows the mean values and ANOVA results of the self-reported responses from the consumers' sensory tests. Significant differences (p < 0.05) between samples were observed for all attributes evaluated. In all samples, except for Z, the responses from overall liking were higher when rated at the end of the test after assessing each attribute, compared to the overall liking at the start (before assessing individual attributes). Spontaneous fermentation beers with raspberry (Framboise) and cherry (Kriek) flavors were the most liked overall (LF: 10.79; LK: 10.73) and also received the highest in bitterness (LF: 11.85; LK: 11.06), acidity (LF: 10.76; LK: 11.37) and aroma (LF: 9.50; LK: 9.53) liking scores. For sweetness liking, there were non-significant differences among the spontaneous (LK, LF) and bottom fermentation samples (C, H), but these were significantly different from the top fermentation beers (L, Z). On the other hand, C had the lowest liking of foam stability (6.79) compared to all other beers (10.20-11.14).      represented it on the negative side of the axis. Sugars such as fructose and glucose were positively related to overall liking, FaceScale and relaxed, with the spontaneous fermentation beers (LK and LF) associated with those components. On the contrary, hordenine presented a negative relationship with the latter descriptors and a positive relationship with alcohol content, iso-alpha acids, bitterness, smirk *Values represent the mean ± standard error N = 61. Different letters within a column indicate that values are significantly different according to the least significant difference test (LSD; p < 0.05). Abbreviations of samples may be found in  , and disappointed *Values represent the mean ± standard error N = 61. Different letters within a column indicate that values are significantly different according to the least significant difference test (LSD; p < 0.05). Abbreviations of samples may be found in  27) represented it on the negative side of the axis. Sugars such as fructose and glucose were sitively related to overall liking, FaceScale and relaxed, with the spontaneous fermentation beers K and LF) associated with those components. On the contrary, hordenine presented a negative lationship with the latter descriptors and a positive relationship with alcohol content, iso-alpha ids, bitterness, smirk , and disappointed , and beers such as H (bottom fermentation) and (top fermentation) were associated with these variables.

Consumer Sensory Evaluation and Biometrics
, and beers such as H (bottom fermentation) and Z (top fermentation) were associated with these variables.  Table 1. Figure 3 shows the MFA for all chemicals, liking, and check all that apply data using emojis ( Figure 3a) and emotion-terms (Figure 3b). In the MFA using emojis (Figure 3a), it can be observed that factors 1 and 2 (F1 and F2) represented 89.35% of total data variability (F1 = 68.86%; F2 = 20.49%).
According to FL, the   Table 1. Figure 3 shows the MFA for all chemicals, liking, and check all that apply data using emojis ( Figure 3a) and emotion-terms (Figure 3b). In the MFA using emojis (Figure 3a), it can be observed that factors 1 and 2 (F1 and F2) represented 89.35% of total data variability (F1 = 68.86%; F2 = 20.49%).
According to FL, the F1 was mainly represented by crying  Table 1. Figure 3 shows the MFA for all chemicals, liking, and check all that apply data using emojis ( Figure 3a) and emotion-terms (Figure 3b). In the MFA using emojis (Figure 3a), it can be observed that factors 1 and 2 (F1 and F2) represented 89.35% of total data variability (F1 = 68.86%; F2 = 20.49%).
According to FL, the   Table 1. Figure 3 shows the MFA for all chemicals, liking, and check all that apply data using emojis ( Figure 3a) and emotion-terms (Figure 3b). In the MFA using emojis (Figure 3a), it can be observed that factors 1 and 2 (F1 and F2) represented 89.35% of total data variability (F1 = 68.86%; F2 = 20.49%).
According to FL, the    Table 1. Figure 3 shows the MFA for all chemicals, liking, and check all that apply data using emojis ( Figure 3a) and emotion-terms (Figure 3b). In the MFA using emojis (Figure 3a), it can be observed that factors 1 and 2 (F1 and F2) represented 89.35% of total data variability (F1 = 68.86%; F2 = 20.49%).
According to FL, the   Table 1. Figure 3 shows the MFA for all chemicals, liking, and check all that apply data using emojis ( Figure 3a) and emotion-terms (Figure 3b). In the MFA using emojis (Figure 3a), it can be observed that factors 1 and 2 (F1 and F2) represented 89.35% of total data variability (F1 = 68.86%; F2 = 20.49%).
According to FL, the  hordenine had a positive relationship with alcohol content, iso-alpha acids, bitterness and emotionterms such as aggressive, disgusted and nostalgic. These were negatively related with overall liking, FaceScale, fructose, glucose, acidity, joyful, affectionate, and happy. Samples were clearly grouped according to the type of fermentation: top (Z and L), bottom (C and H) and spontaneous (LF and LK).

Discussion
Spontaneous fermentation beers resulted in the highest values for total sugars and lowest alcohol content, bitterness (expressed as IBU), and iso-alpha acids (Figure 1). This may be due to the addition of fruit juice (cherry in LK and raspberry in LF), and dried hops, which may also be old and oxidized to provide aromas and flavors but not bitterness [23,25,40].
There was a positive correlation (R = 0.91; R 2 = 0.83) between hordenine and alcohol content for all beer samples studied. The latter effect is in accordance with the study from Brauers et al. [16], who found higher hordenine content in strong beers (bock style), which have high alcohol content (6.6-7.5%; [41]), and lower hordenine values in alcohol-free beers. On the other hand, top fermentation beers were found to have higher concentrations of iso-alpha acids, hordenine, and bitterness (expressed as IBU) compared to the other samples ( Figure 3). Sensorial bitterness can be derived from several compounds, including polyphenols and alkaloids [42].
For beers, 80% of the perceived bitterness is originated from adding hops during the brewing process [43]. Hops from female plants contain glands with a resin that is rich in derivates of phloroglucinol, essential oils, and flavonoids [44]. In terms of the bitter compounds, there are two types of acids in the hops resins, alpha, and beta; however, these molecules are not bitter in their raw  Table 1.

Discussion
Spontaneous fermentation beers resulted in the highest values for total sugars and lowest alcohol content, bitterness (expressed as IBU), and iso-alpha acids (Figure 1). This may be due to the addition of fruit juice (cherry in LK and raspberry in LF), and dried hops, which may also be old and oxidized to provide aromas and flavors but not bitterness [23,25,40].
There was a positive correlation (R = 0.91; R 2 = 0.83) between hordenine and alcohol content for all beer samples studied. The latter effect is in accordance with the study from Brauers et al. [16], who found higher hordenine content in strong beers (bock style), which have high alcohol content (6.6-7.5%; [41]), and lower hordenine values in alcohol-free beers. On the other hand, top fermentation beers were found to have higher concentrations of iso-alpha acids, hordenine, and bitterness (expressed as IBU) compared to the other samples ( Figure 3). Sensorial bitterness can be derived from several compounds, including polyphenols and alkaloids [42].
For beers, 80% of the perceived bitterness is originated from adding hops during the brewing process [43]. Hops from female plants contain glands with a resin that is rich in derivates of phloroglucinol, essential oils, and flavonoids [44]. In terms of the bitter compounds, there are two types of acids in the hops resins, alpha, and beta; however, these molecules are not bitter in their raw forms. Before brewing, a thermal isomerization of the alpha-acids occurs during the boiling process, and iso-alpha acids are obtained, which are responsible for imparting the bitterness in beer. Two stereoisomers are generated during this isomerization process, trans-and cis-iso-alpha-acids, which are catalyzed by magnesium ions [45]. The perceived bitterness intensity is higher when there is a higher content of iso-alpha-acids. This compound provides a "harsh," "round," and "lingering" flavor to beer [43]. In the present study, the top fermentation beers (L and Z) had the lowest scores for the liking of bitterness compared to the other beer samples ( Table 5). The higher chemical bitterness (expressed as IBU) for these two samples can potentially explain the disliking of the bitterness in the tasting session by the participants. Besides, hordenine is known to impart bitterness [18], and the concentration of this compound was also higher in the top fermentation beers.
Similar results were found using the conscious responses with emojis and words, and from the subconscious responses using biometrics. According to the PCA and MFA presented in Figures 2 and 3, respectively, beers with higher sugar content (glucose and fructose) were associated with positive emotions such as joy, relaxed and iso-alpha acids are obtained, which are responsible for imparting the bitterness in beer. Two stereoisomers are generated during this isomerization process, trans-and cis-iso-alpha-acids, which are catalyzed by magnesium ions [45]. The perceived bitterness intensity is higher when there is a higher content of iso-alpha-acids. This compound provides a "harsh," "round," and "lingering" flavor to beer [43]. In the present study, the top fermentation beers (L and Z) had the lowest scores for the liking of bitterness compared to the other beer samples ( Table 5). The higher chemical bitterness (expressed as IBU) for these two samples can potentially explain the disliking of the bitterness in the tasting session by the participants. Besides, hordenine is known to impart bitterness [18], and the concentration of this compound was also higher in the top fermentation beers.
Similar results were found using the conscious responses with emojis and words, and from the subconscious responses using biometrics. According to the PCA and MFA presented in Figure 2 and Figure 3, respectively, beers with higher sugar content (glucose and fructose) were associated with positive emotions such as joy, relaxed , love , winking face with tongue , affectionate, and FaceScale in both subconscious and conscious responses (emojis and emotion-terms). This coincides with findings by Kim et al. [46], who reported that samples of beverages and biscuits with the highest sugar content elicited positive emotions such as affectionate, pleased, joyful, glad, and happy. On the other hand, bitterness has been associated with rejection due to genetic factors and the innate relationship of bitter products with poisonous compounds [24,47,48]. Overall taste liking is the result of the intrinsic balance among the basic tastes that are sensed by the receptors located in the gustative system [49]. Individual taste compounds can elicit discrete sensations in consumers. However, different tastes can interact with each other, which can result in suppression or enhancement effects of certain perceptions [50,51]. For instance, minor concentrations of sugar can enhance the sourness of citric acid solutions; or slight concentrations of salt can enhance the sweetness of sugar solutions. The opposite can also occur as slight concentrations of quinine (a bitter compound) mixed with saccharides can suppress the sweetness of the solutions [52,53]. This can potentially explain the overall taste perception by the consumers in the present study. As the sugar content of the spontaneous fermentation beers was higher compared to the other samples, the bitterness perception of those beers was somewhat suppressed, which produced higher hedonic and emotional responses. This effect can be observed for both responses (conscious and subconscious) measured in this study, as the sweet taste was the main factor responsible for the overall satisfaction of consumers.
Even though hordenine has been reported to stimulate the release of dopamine and is, therefore, associated with happiness [15,21], these studies have not evaluated these effects on consumers when drinking beer. In the present research, it was found that, as hordenine was positively related with bitterness and other bitter compounds such as iso-alpha acids, all these had a positive relationship with negative emotions such as disappointed (Figure 2), dizzy , sick , weary ( Figure  3a), disgusted, and aggressive (Figure 3b). This may be due to two main factors: i) the higher sugar concentration in beers LF and LK, which had a higher effect on consumers, and ii) the time of the sensory session, which may not have been long enough to increase hordenine concentration in the bloodstream significantly. Hence, since the effects of hordenine may be delayed, a sensory tasting session, including several sample beers, may not be appropriated to study the carry-over effects. This may be overcome by conducting further research allowing more time between beers for emotional assessments, so that there is enough hordenine level in the blood to more accurately assess the elicited emotional responses. Moreover, by comparing similar beer styles with alcoholic and non-alcoholic beers, it may render more information on the effects of hordenine and other compounds alone.

Conclusions
This preliminary study was a first attempt to associate beer compounds with the emotional responses of consumers using non-invasive biometrics. Findings showed that there was a positive relationship between sugar content, acidity, and positive emotions. At the same time, alcohol, bitterness, and hordenine were associated with negative emotions, which explain the consumers' and iso-alpha acids are obtained, which are responsible for imparting the bitterness in beer. Two stereoisomers are generated during this isomerization process, trans-and cis-iso-alpha-acids, which are catalyzed by magnesium ions [45]. The perceived bitterness intensity is higher when there is a higher content of iso-alpha-acids. This compound provides a "harsh," "round," and "lingering" flavor to beer [43]. In the present study, the top fermentation beers (L and Z) had the lowest scores for the liking of bitterness compared to the other beer samples ( Table 5). The higher chemical bitterness (expressed as IBU) for these two samples can potentially explain the disliking of the bitterness in the tasting session by the participants. Besides, hordenine is known to impart bitterness [18], and the concentration of this compound was also higher in the top fermentation beers.
Similar results were found using the conscious responses with emojis and words, and from the subconscious responses using biometrics. According to the PCA and MFA presented in Figure 2 and Figure 3, respectively, beers with higher sugar content (glucose and fructose) were associated with positive emotions such as joy, relaxed , love , winking face with tongue , affectionate, and FaceScale in both subconscious and conscious responses (emojis and emotion-terms). This coincides with findings by Kim et al. [46], who reported that samples of beverages and biscuits with the highest sugar content elicited positive emotions such as affectionate, pleased, joyful, glad, and happy. On the other hand, bitterness has been associated with rejection due to genetic factors and the innate relationship of bitter products with poisonous compounds [24,47,48]. Overall taste liking is the result of the intrinsic balance among the basic tastes that are sensed by the receptors located in the gustative system [49]. Individual taste compounds can elicit discrete sensations in consumers. However, different tastes can interact with each other, which can result in suppression or enhancement effects of certain perceptions [50,51]. For instance, minor concentrations of sugar can enhance the sourness of citric acid solutions; or slight concentrations of salt can enhance the sweetness of sugar solutions. The opposite can also occur as slight concentrations of quinine (a bitter compound) mixed with saccharides can suppress the sweetness of the solutions [52,53]. This can potentially explain the overall taste perception by the consumers in the present study. As the sugar content of the spontaneous fermentation beers was higher compared to the other samples, the bitterness perception of those beers was somewhat suppressed, which produced higher hedonic and emotional responses. This effect can be observed for both responses (conscious and subconscious) measured in this study, as the sweet taste was the main factor responsible for the overall satisfaction of consumers.
Even though hordenine has been reported to stimulate the release of dopamine and is, therefore, associated with happiness [15,21], these studies have not evaluated these effects on consumers when drinking beer. In the present research, it was found that, as hordenine was positively related with bitterness and other bitter compounds such as iso-alpha acids, all these had a positive relationship with negative emotions such as disappointed (Figure 2), dizzy , sick , weary ( Figure  3a), disgusted, and aggressive (Figure 3b). This may be due to two main factors: i) the higher sugar concentration in beers LF and LK, which had a higher effect on consumers, and ii) the time of the sensory session, which may not have been long enough to increase hordenine concentration in the bloodstream significantly. Hence, since the effects of hordenine may be delayed, a sensory tasting session, including several sample beers, may not be appropriated to study the carry-over effects. This may be overcome by conducting further research allowing more time between beers for emotional assessments, so that there is enough hordenine level in the blood to more accurately assess the elicited emotional responses. Moreover, by comparing similar beer styles with alcoholic and non-alcoholic beers, it may render more information on the effects of hordenine and other compounds alone.

Conclusions
This preliminary study was a first attempt to associate beer compounds with the emotional responses of consumers using non-invasive biometrics. Findings showed that there was a positive relationship between sugar content, acidity, and positive emotions. At the same time, alcohol, bitterness, and hordenine were associated with negative emotions, which explain the consumers' , winking face with tongue and iso-alpha acids are obtained, which are responsible for imparting the bitterness in beer. Two stereoisomers are generated during this isomerization process, trans-and cis-iso-alpha-acids, which are catalyzed by magnesium ions [45]. The perceived bitterness intensity is higher when there is a higher content of iso-alpha-acids. This compound provides a "harsh," "round," and "lingering" flavor to beer [43]. In the present study, the top fermentation beers (L and Z) had the lowest scores for the liking of bitterness compared to the other beer samples ( Table 5). The higher chemical bitterness (expressed as IBU) for these two samples can potentially explain the disliking of the bitterness in the tasting session by the participants. Besides, hordenine is known to impart bitterness [18], and the concentration of this compound was also higher in the top fermentation beers.
Similar results were found using the conscious responses with emojis and words, and from the subconscious responses using biometrics. According to the PCA and MFA presented in Figure 2 and Figure 3, respectively, beers with higher sugar content (glucose and fructose) were associated with positive emotions such as joy, relaxed , love , winking face with tongue , affectionate, and FaceScale in both subconscious and conscious responses (emojis and emotion-terms). This coincides with findings by Kim et al. [46], who reported that samples of beverages and biscuits with the highest sugar content elicited positive emotions such as affectionate, pleased, joyful, glad, and happy. On the other hand, bitterness has been associated with rejection due to genetic factors and the innate relationship of bitter products with poisonous compounds [24,47,48]. Overall taste liking is the result of the intrinsic balance among the basic tastes that are sensed by the receptors located in the gustative system [49]. Individual taste compounds can elicit discrete sensations in consumers. However, different tastes can interact with each other, which can result in suppression or enhancement effects of certain perceptions [50,51]. For instance, minor concentrations of sugar can enhance the sourness of citric acid solutions; or slight concentrations of salt can enhance the sweetness of sugar solutions. The opposite can also occur as slight concentrations of quinine (a bitter compound) mixed with saccharides can suppress the sweetness of the solutions [52,53]. This can potentially explain the overall taste perception by the consumers in the present study. As the sugar content of the spontaneous fermentation beers was higher compared to the other samples, the bitterness perception of those beers was somewhat suppressed, which produced higher hedonic and emotional responses. This effect can be observed for both responses (conscious and subconscious) measured in this study, as the sweet taste was the main factor responsible for the overall satisfaction of consumers.
Even though hordenine has been reported to stimulate the release of dopamine and is, therefore, associated with happiness [15,21], these studies have not evaluated these effects on consumers when drinking beer. In the present research, it was found that, as hordenine was positively related with bitterness and other bitter compounds such as iso-alpha acids, all these had a positive relationship with negative emotions such as disappointed (Figure 2), dizzy , sick , weary ( Figure  3a), disgusted, and aggressive (Figure 3b). This may be due to two main factors: i) the higher sugar concentration in beers LF and LK, which had a higher effect on consumers, and ii) the time of the sensory session, which may not have been long enough to increase hordenine concentration in the bloodstream significantly. Hence, since the effects of hordenine may be delayed, a sensory tasting session, including several sample beers, may not be appropriated to study the carry-over effects. This may be overcome by conducting further research allowing more time between beers for emotional assessments, so that there is enough hordenine level in the blood to more accurately assess the elicited emotional responses. Moreover, by comparing similar beer styles with alcoholic and non-alcoholic beers, it may render more information on the effects of hordenine and other compounds alone.

Conclusions
This preliminary study was a first attempt to associate beer compounds with the emotional responses of consumers using non-invasive biometrics. Findings showed that there was a positive relationship between sugar content, acidity, and positive emotions. At the same time, alcohol, bitterness, and hordenine were associated with negative emotions, which explain the consumers' , affectionate, and FaceScale in both subconscious and conscious responses (emojis and emotion-terms). This coincides with findings by Kim et al. [46], who reported that samples of beverages and biscuits with the highest sugar content elicited positive emotions such as affectionate, pleased, joyful, glad, and happy. On the other hand, bitterness has been associated with rejection due to genetic factors and the innate relationship of bitter products with poisonous compounds [24,47,48]. Overall taste liking is the result of the intrinsic balance among the basic tastes that are sensed by the receptors located in the gustative system [49]. Individual taste compounds can elicit discrete sensations in consumers. However, different tastes can interact with each other, which can result in suppression or enhancement effects of certain perceptions [50,51]. For instance, minor concentrations of sugar can enhance the sourness of citric acid solutions; or slight concentrations of salt can enhance the sweetness of sugar solutions. The opposite can also occur as slight concentrations of quinine (a bitter compound) mixed with saccharides can suppress the sweetness of the solutions [52,53]. This can potentially explain the overall taste perception by the consumers in the present study. As the sugar content of the spontaneous fermentation beers was higher compared to the other samples, the bitterness perception of those beers was somewhat suppressed, which produced higher hedonic and emotional responses. This effect can be observed for both responses (conscious and subconscious) measured in this study, as the sweet taste was the main factor responsible for the overall satisfaction of consumers.
Even though hordenine has been reported to stimulate the release of dopamine and is, therefore, associated with happiness [15,21], these studies have not evaluated these effects on consumers when drinking beer. In the present research, it was found that, as hordenine was positively related with bitterness and other bitter compounds such as iso-alpha acids, all these had a positive relationship with negative emotions such as disappointed and iso-alpha acids are obtained, which are responsible for imparting the bitterness in beer. Two stereoisomers are generated during this isomerization process, trans-and cis-iso-alpha-acids, which are catalyzed by magnesium ions [45]. The perceived bitterness intensity is higher when there is a higher content of iso-alpha-acids. This compound provides a "harsh," "round," and "lingering" flavor to beer [43]. In the present study, the top fermentation beers (L and Z) had the lowest scores for the liking of bitterness compared to the other beer samples ( Table 5). The higher chemical bitterness (expressed as IBU) for these two samples can potentially explain the disliking of the bitterness in the tasting session by the participants. Besides, hordenine is known to impart bitterness [18], and the concentration of this compound was also higher in the top fermentation beers.
Similar results were found using the conscious responses with emojis and words, and from the subconscious responses using biometrics. According to the PCA and MFA presented in Figure 2 and Figure 3, respectively, beers with higher sugar content (glucose and fructose) were associated with positive emotions such as joy, relaxed , love , winking face with tongue , affectionate, and FaceScale in both subconscious and conscious responses (emojis and emotion-terms). This coincides with findings by Kim et al. [46], who reported that samples of beverages and biscuits with the highest sugar content elicited positive emotions such as affectionate, pleased, joyful, glad, and happy. On the other hand, bitterness has been associated with rejection due to genetic factors and the innate relationship of bitter products with poisonous compounds [24,47,48]. Overall taste liking is the result of the intrinsic balance among the basic tastes that are sensed by the receptors located in the gustative system [49]. Individual taste compounds can elicit discrete sensations in consumers. However, different tastes can interact with each other, which can result in suppression or enhancement effects of certain perceptions [50,51]. For instance, minor concentrations of sugar can enhance the sourness of citric acid solutions; or slight concentrations of salt can enhance the sweetness of sugar solutions. The opposite can also occur as slight concentrations of quinine (a bitter compound) mixed with saccharides can suppress the sweetness of the solutions [52,53]. This can potentially explain the overall taste perception by the consumers in the present study. As the sugar content of the spontaneous fermentation beers was higher compared to the other samples, the bitterness perception of those beers was somewhat suppressed, which produced higher hedonic and emotional responses. This effect can be observed for both responses (conscious and subconscious) measured in this study, as the sweet taste was the main factor responsible for the overall satisfaction of consumers.
Even though hordenine has been reported to stimulate the release of dopamine and is, therefore, associated with happiness [15,21], these studies have not evaluated these effects on consumers when drinking beer. In the present research, it was found that, as hordenine was positively related with bitterness and other bitter compounds such as iso-alpha acids, all these had a positive relationship with negative emotions such as disappointed ( Figure 2), dizzy , sick , weary ( Figure  3a), disgusted, and aggressive (Figure 3b). This may be due to two main factors: i) the higher sugar concentration in beers LF and LK, which had a higher effect on consumers, and ii) the time of the sensory session, which may not have been long enough to increase hordenine concentration in the bloodstream significantly. Hence, since the effects of hordenine may be delayed, a sensory tasting session, including several sample beers, may not be appropriated to study the carry-over effects. This may be overcome by conducting further research allowing more time between beers for emotional assessments, so that there is enough hordenine level in the blood to more accurately assess the elicited emotional responses. Moreover, by comparing similar beer styles with alcoholic and non-alcoholic beers, it may render more information on the effects of hordenine and other compounds alone.

Conclusions
This preliminary study was a first attempt to associate beer compounds with the emotional responses of consumers using non-invasive biometrics. Findings showed that there was a positive relationship between sugar content, acidity, and positive emotions. At the same time, alcohol, bitterness, and hordenine were associated with negative emotions, which explain the consumers' and iso-alpha acids are obtained, which are responsible for imparting the bitterness in beer. Two stereoisomers are generated during this isomerization process, trans-and cis-iso-alpha-acids, which are catalyzed by magnesium ions [45]. The perceived bitterness intensity is higher when there is a higher content of iso-alpha-acids. This compound provides a "harsh," "round," and "lingering" flavor to beer [43]. In the present study, the top fermentation beers (L and Z) had the lowest scores for the liking of bitterness compared to the other beer samples ( Table 5). The higher chemical bitterness (expressed as IBU) for these two samples can potentially explain the disliking of the bitterness in the tasting session by the participants. Besides, hordenine is known to impart bitterness [18], and the concentration of this compound was also higher in the top fermentation beers.
Similar results were found using the conscious responses with emojis and words, and from the subconscious responses using biometrics. According to the PCA and MFA presented in Figure 2 and Figure 3, respectively, beers with higher sugar content (glucose and fructose) were associated with positive emotions such as joy, relaxed , love , winking face with tongue , affectionate, and FaceScale in both subconscious and conscious responses (emojis and emotion-terms). This coincides with findings by Kim et al. [46], who reported that samples of beverages and biscuits with the highest sugar content elicited positive emotions such as affectionate, pleased, joyful, glad, and happy. On the other hand, bitterness has been associated with rejection due to genetic factors and the innate relationship of bitter products with poisonous compounds [24,47,48]. Overall taste liking is the result of the intrinsic balance among the basic tastes that are sensed by the receptors located in the gustative system [49]. Individual taste compounds can elicit discrete sensations in consumers. However, different tastes can interact with each other, which can result in suppression or enhancement effects of certain perceptions [50,51]. For instance, minor concentrations of sugar can enhance the sourness of citric acid solutions; or slight concentrations of salt can enhance the sweetness of sugar solutions. The opposite can also occur as slight concentrations of quinine (a bitter compound) mixed with saccharides can suppress the sweetness of the solutions [52,53]. This can potentially explain the overall taste perception by the consumers in the present study. As the sugar content of the spontaneous fermentation beers was higher compared to the other samples, the bitterness perception of those beers was somewhat suppressed, which produced higher hedonic and emotional responses. This effect can be observed for both responses (conscious and subconscious) measured in this study, as the sweet taste was the main factor responsible for the overall satisfaction of consumers.
Even though hordenine has been reported to stimulate the release of dopamine and is, therefore, associated with happiness [15,21], these studies have not evaluated these effects on consumers when drinking beer. In the present research, it was found that, as hordenine was positively related with bitterness and other bitter compounds such as iso-alpha acids, all these had a positive relationship with negative emotions such as disappointed ( Figure 2), dizzy , sick , weary ( Figure  3a), disgusted, and aggressive (Figure 3b). This may be due to two main factors: i) the higher sugar concentration in beers LF and LK, which had a higher effect on consumers, and ii) the time of the sensory session, which may not have been long enough to increase hordenine concentration in the bloodstream significantly. Hence, since the effects of hordenine may be delayed, a sensory tasting session, including several sample beers, may not be appropriated to study the carry-over effects. This may be overcome by conducting further research allowing more time between beers for emotional assessments, so that there is enough hordenine level in the blood to more accurately assess the elicited emotional responses. Moreover, by comparing similar beer styles with alcoholic and non-alcoholic beers, it may render more information on the effects of hordenine and other compounds alone.

Conclusions
This preliminary study was a first attempt to associate beer compounds with the emotional responses of consumers using non-invasive biometrics. Findings showed that there was a positive relationship between sugar content, acidity, and positive emotions. At the same time, alcohol, bitterness, and hordenine were associated with negative emotions, which explain the consumers' , sick and iso-alpha acids are obtained, which are responsible for imparting the bitterness in beer. Two stereoisomers are generated during this isomerization process, trans-and cis-iso-alpha-acids, which are catalyzed by magnesium ions [45]. The perceived bitterness intensity is higher when there is a higher content of iso-alpha-acids. This compound provides a "harsh," "round," and "lingering" flavor to beer [43]. In the present study, the top fermentation beers (L and Z) had the lowest scores for the liking of bitterness compared to the other beer samples ( Table 5). The higher chemical bitterness (expressed as IBU) for these two samples can potentially explain the disliking of the bitterness in the tasting session by the participants. Besides, hordenine is known to impart bitterness [18], and the concentration of this compound was also higher in the top fermentation beers.
Similar results were found using the conscious responses with emojis and words, and from the subconscious responses using biometrics. According to the PCA and MFA presented in Figure 2 and Figure 3, respectively, beers with higher sugar content (glucose and fructose) were associated with positive emotions such as joy, relaxed , love , winking face with tongue , affectionate, and FaceScale in both subconscious and conscious responses (emojis and emotion-terms). This coincides with findings by Kim et al. [46], who reported that samples of beverages and biscuits with the highest sugar content elicited positive emotions such as affectionate, pleased, joyful, glad, and happy. On the other hand, bitterness has been associated with rejection due to genetic factors and the innate relationship of bitter products with poisonous compounds [24,47,48]. Overall taste liking is the result of the intrinsic balance among the basic tastes that are sensed by the receptors located in the gustative system [49]. Individual taste compounds can elicit discrete sensations in consumers. However, different tastes can interact with each other, which can result in suppression or enhancement effects of certain perceptions [50,51]. For instance, minor concentrations of sugar can enhance the sourness of citric acid solutions; or slight concentrations of salt can enhance the sweetness of sugar solutions. The opposite can also occur as slight concentrations of quinine (a bitter compound) mixed with saccharides can suppress the sweetness of the solutions [52,53]. This can potentially explain the overall taste perception by the consumers in the present study. As the sugar content of the spontaneous fermentation beers was higher compared to the other samples, the bitterness perception of those beers was somewhat suppressed, which produced higher hedonic and emotional responses. This effect can be observed for both responses (conscious and subconscious) measured in this study, as the sweet taste was the main factor responsible for the overall satisfaction of consumers.
Even though hordenine has been reported to stimulate the release of dopamine and is, therefore, associated with happiness [15,21], these studies have not evaluated these effects on consumers when drinking beer. In the present research, it was found that, as hordenine was positively related with bitterness and other bitter compounds such as iso-alpha acids, all these had a positive relationship with negative emotions such as disappointed ( Figure 2), dizzy , sick , weary ( Figure  3a), disgusted, and aggressive (Figure 3b). This may be due to two main factors: i) the higher sugar concentration in beers LF and LK, which had a higher effect on consumers, and ii) the time of the sensory session, which may not have been long enough to increase hordenine concentration in the bloodstream significantly. Hence, since the effects of hordenine may be delayed, a sensory tasting session, including several sample beers, may not be appropriated to study the carry-over effects. This may be overcome by conducting further research allowing more time between beers for emotional assessments, so that there is enough hordenine level in the blood to more accurately assess the elicited emotional responses. Moreover, by comparing similar beer styles with alcoholic and non-alcoholic beers, it may render more information on the effects of hordenine and other compounds alone.

Conclusions
This preliminary study was a first attempt to associate beer compounds with the emotional responses of consumers using non-invasive biometrics. Findings showed that there was a positive relationship between sugar content, acidity, and positive emotions. At the same time, alcohol, bitterness, and hordenine were associated with negative emotions, which explain the consumers' , weary and iso-alpha acids are obtained, which are responsible for imparting the bitterness in beer. Two stereoisomers are generated during this isomerization process, trans-and cis-iso-alpha-acids, which are catalyzed by magnesium ions [45]. The perceived bitterness intensity is higher when there is a higher content of iso-alpha-acids. This compound provides a "harsh," "round," and "lingering" flavor to beer [43]. In the present study, the top fermentation beers (L and Z) had the lowest scores for the liking of bitterness compared to the other beer samples ( Table 5). The higher chemical bitterness (expressed as IBU) for these two samples can potentially explain the disliking of the bitterness in the tasting session by the participants. Besides, hordenine is known to impart bitterness [18], and the concentration of this compound was also higher in the top fermentation beers.
Similar results were found using the conscious responses with emojis and words, and from the subconscious responses using biometrics. According to the PCA and MFA presented in Figure 2 and Figure 3, respectively, beers with higher sugar content (glucose and fructose) were associated with positive emotions such as joy, relaxed , love , winking face with tongue , affectionate, and FaceScale in both subconscious and conscious responses (emojis and emotion-terms). This coincides with findings by Kim et al. [46], who reported that samples of beverages and biscuits with the highest sugar content elicited positive emotions such as affectionate, pleased, joyful, glad, and happy. On the other hand, bitterness has been associated with rejection due to genetic factors and the innate relationship of bitter products with poisonous compounds [24,47,48]. Overall taste liking is the result of the intrinsic balance among the basic tastes that are sensed by the receptors located in the gustative system [49]. Individual taste compounds can elicit discrete sensations in consumers. However, different tastes can interact with each other, which can result in suppression or enhancement effects of certain perceptions [50,51]. For instance, minor concentrations of sugar can enhance the sourness of citric acid solutions; or slight concentrations of salt can enhance the sweetness of sugar solutions. The opposite can also occur as slight concentrations of quinine (a bitter compound) mixed with saccharides can suppress the sweetness of the solutions [52,53]. This can potentially explain the overall taste perception by the consumers in the present study. As the sugar content of the spontaneous fermentation beers was higher compared to the other samples, the bitterness perception of those beers was somewhat suppressed, which produced higher hedonic and emotional responses. This effect can be observed for both responses (conscious and subconscious) measured in this study, as the sweet taste was the main factor responsible for the overall satisfaction of consumers.
Even though hordenine has been reported to stimulate the release of dopamine and is, therefore, associated with happiness [15,21], these studies have not evaluated these effects on consumers when drinking beer. In the present research, it was found that, as hordenine was positively related with bitterness and other bitter compounds such as iso-alpha acids, all these had a positive relationship with negative emotions such as disappointed ( Figure 2), dizzy , sick , weary ( Figure  3a), disgusted, and aggressive (Figure 3b). This may be due to two main factors: i) the higher sugar concentration in beers LF and LK, which had a higher effect on consumers, and ii) the time of the sensory session, which may not have been long enough to increase hordenine concentration in the bloodstream significantly. Hence, since the effects of hordenine may be delayed, a sensory tasting session, including several sample beers, may not be appropriated to study the carry-over effects. This may be overcome by conducting further research allowing more time between beers for emotional assessments, so that there is enough hordenine level in the blood to more accurately assess the elicited emotional responses. Moreover, by comparing similar beer styles with alcoholic and non-alcoholic beers, it may render more information on the effects of hordenine and other compounds alone.

Conclusions
This preliminary study was a first attempt to associate beer compounds with the emotional responses of consumers using non-invasive biometrics. Findings showed that there was a positive relationship between sugar content, acidity, and positive emotions. At the same time, alcohol, bitterness, and hordenine were associated with negative emotions, which explain the consumers' (Figure 3a), disgusted, and aggressive (Figure 3b). This may be due to two main factors: (i) the higher sugar concentration in beers LF and LK, which had a higher effect on consumers, and (ii) the time of the sensory session, which may not have been long enough to increase hordenine concentration in the bloodstream significantly. Hence, since the effects of hordenine may be delayed, a sensory tasting session, including several sample beers, may not be appropriated to study the carry-over effects. This may be overcome by conducting further research allowing more time between beers for emotional assessments, so that there is enough hordenine level in the blood to more accurately assess the elicited emotional responses. Moreover, by comparing similar beer styles with alcoholic and non-alcoholic beers, it may render more information on the effects of hordenine and other compounds alone.

Conclusions
This preliminary study was a first attempt to associate beer compounds with the emotional responses of consumers using non-invasive biometrics. Findings showed that there was a positive relationship between sugar content, acidity, and positive emotions. At the same time, alcohol, bitterness, and hordenine were associated with negative emotions, which explain the consumers' preference for spontaneous fermentation samples, which are sweeter and less bitter than other beer styles. The strong correlation between alcohol and hordenine, along with the effect that time may have in terms of increasing the hordenine levels in the bloodstream, leads to the need to conduct further studies, which may allow giving more time between samples to assess emotional responses and to compare alcoholic and non-alcoholic beers with similar styles to separate the effects of alcohol and hordenine. Additionally, further studies may include the assessment of differences in emotional responses among consumers from different cultural backgrounds. Results from these studies may be useful for brewing companies to modify their products for different markets and satisfy the needs of distinct target consumers.