## 3 Results and Discussion
### Cluster Analysis of Consumers  
Based on overall liking scores, three consumer groups were identified (Figure 3). These consumer segments were differed in their overall liking ranges and ranking of their preference. For cluster 1 (\(n=56\)), the most-liked samples were BaristaRTD (6.6) followed by TwosomeplaceCS (6.0) and BabinskiRTD (5.8). They preferred TwosomeplaceCS to StarbucksCS, and their least-liked samples were Colombia and Kenya samples. Cluster 2 (\(n=36\)) preferred BabinskiRTD (5.7), followed by ColombiaCB and BlendingCM (5.1). They preferred StarbucksCS to TwosomeplaceCS and disliked the Folgers samples. Mean overall liking scores for cluster 3 (\(n=28\)) were lower than that of other clusters. The most-liked samples were BaristaRTD (5.0) and BabinskiRTD (4.9) and cluster 3 showed the same liking scores for both StarbucksCS and TwosomeplaceCS. [PERSON] and [PERSON] [26] also showed that high consumption group of wine discriminated wine samples based on flavor attributes better than low wine consumption group. In this study, specifically, cluster 2 demonstrated the highest frequency of cold black coffee consumption at 22.2%, followed by cluster 3 (14.3%) and cluster 1 (5.36%). Considering the distinct liking patterns of cluster 2, the frequency of consumption might affect acceptability ranking based on their flavor perception of coffee. Comparison between Consumer Sensory Perception and Instrumental Analysis--Multi-Factor Analysis (MFA)  
Multi-factor analysis (MFA) was conducted to illustrate the relationship among multiple variables, such as sensory liking data, instrumental data (36 volatile and 3 non-volatile compounds), and coffee samples (Figure 4a). F1 and F2 explained 78.4% of total variance. The MFA results were similar to those of the correspondence analysis from the CATA, indicating similarity in line with brewing methods, except for blending samples. This may suggest that volatile compounds affect the position of samples on a CA plot (Figure 1) to some degree. Figure 3: Overall liking of coffee by three consumer clusters. Figure 4: Multi-factor analysis of instrumental and sensory data (**a**) and superimposed map of coffee samples (**b**). (C), (N), and (V) stands for consumer acceptability, non-volatiles compounds, and volatile compounds, respectively. CS and Folgers samples were positioned in quadrant 1 where most volatile compounds were positioned including guaiaicol (V20) and 4-ethylguaiaicol (V29), which indicates spice and clove, smoke, sweet, and medicine characteristics [27]. On the contrary, other samples such as RTD samples were positioned in quadrants 2 and 3, showing no specific relationship with most volatile compounds. Colombia and Kenya samples were placed roughly in quadrant 4 with furfural (V3), 5-methyl-2-furaldehyde (V7), 3,5-ocatadien-2-one (V15), and tetradecanoic acid (V36) suggesting they were distinct indicators of these coffee samples. Caffeine is an alkaloid that has bitter taste [28], and chlorogenic acids has both bitterness and astringent characteristics [9]. Trigonelline is known to influence aroma perception of coffee [29]. Caffeine is close to CS and Folgers samples and to most volatile compounds. Thus, the most volatile compounds and caffeine seemed unrelated with sensory liking data, whereas chlorogenic acid and trigonelline had a slightly inversed relationship with sensory liking data. Contrary to this result, [PERSON] _et al._[30] showed that although there was a slightly positive correlation between coffee quality and chlorogenic acid content, but still there were no consistent relationship between coffee cup quality and chlorogenic acid content. They were associated with 4-vinylguaiaicol (V31), 3,4-dimethoxystyrene (V33), and dodecanoic acid (V35). Additionally, blended samples were not explained by specific variables, positioned near the RTD samples. Aroma and flavors of coffee can be balanced by blending and coffee including diverse variety can maintain its quality even if when ingredients undergo changes [31].