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, 82 (5), 2067-73

Discrimination of Complex Mixtures by a Colorimetric Sensor Array: Coffee Aromas

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Discrimination of Complex Mixtures by a Colorimetric Sensor Array: Coffee Aromas

Benjamin A Suslick et al. Anal Chem.

Abstract

The analysis of complex mixtures presents a difficult challenge even for modern analytical techniques, and the ability to discriminate among closely similar such mixtures often remains problematic. Coffee provides a readily available archetype of such highly multicomponent systems. The use of a low-cost, sensitive colorimetric sensor array for the detection and identification of coffee aromas is reported. The color changes of the sensor array were used as a digital representation of the array response and analyzed with standard statistical methods, including principal component analysis (PCA) and hierarchical clustering analysis (HCA). PCA revealed that the sensor array has exceptionally high dimensionality with 18 dimensions required to define 90% of the total variance. In quintuplicate runs of 10 commercial coffees and controls, no confusions or errors in classification by HCA were observed in 55 trials. In addition, the effects of temperature and time in the roasting of green coffee beans were readily observed and distinguishable with a resolution better than 10 degrees C and 5 min, respectively. Colorimetric sensor arrays demonstrate excellent potential for complex systems analysis in real-world applications and provide a novel method for discrimination among closely similar complex mixtures.

Figures

Figure 1
Figure 1
Color change profiles after 2 min of array exposure to the saturated vapors from 10 representative commercial coffees. While the overall patterns are all similar, a close examination shows highly reproducible differences between brands. A full digital database is provided in the Supporting Information, Table S2. For display purposes, the color range of these difference maps are expanded from 4 to 8 bits per color (RGB range of 4–19 expanded to 0–255).
Figure 2
Figure 2
Hierarchical cluster analysis (HCA) for 10 commercial coffees and a control. All experiments were run in quintuplet trials; no confusions or errors in classification were observed in 55 trials, as shown. The HCA used minimum variance (i.e., “Ward’s Method”) for clustering. Abbreviations: Maxwell House Original Roast, MHOR; Folgers Grande Supreme Decaf, FGSD; Eight O’Clock Hazel Nut, EOHN; Maxwell House Original Roast Decaf, MHORD; Starbucks Sumatra Roast, SSR; Starbucks Columbian Roast, SCR; Starbucks Espresso Roast, SER; Folgers Columbian Roast, FCR; Café Mai Traditional, CMT; Eight O’Clock Columbian Roast, EOCR; the number indicates nth trial. Control = no coffee present.
Figure 3
Figure 3
Scree plot of the principal components from PCA of 55 trials using 10 coffees and a control. The colorimetric sensor array has an extremely high level of dispersion: for centered, standardized color difference vectors, 18 dimensions are required to define 90% of the total variance and 25 dimensions are required to define 95%.
Figure 4
Figure 4
Color change profiles after 2 min of array exposure to Columbian Huila green coffee beans roasted for 15 min at 180, 200, 210, 220, 230, and 240 °C. A full digital database is provided in the Supporting Information, Table S2. For display purposes, the color range of these difference maps are expanded from 4 to 8 bits per color (RGB range of 4–19 expanded to 0–255).
Figure 5
Figure 5
Hierarchical cluster analysis (HCA) for Columbian Huila green coffee beans roasted for 15 min at temperatures ranging from 180 to 240 °C. All experiments were run in quintuplet trials; no confusions or errors in classification were observed in 40 trials, as shown. NR = green coffee, not roasted; the number indicates nth trial. Control = no coffee present.
Figure 6
Figure 6
Color change profiles after 2 min of array exposure to Columbian Huila green coffee beans roasted at 220 °C for times ranging from 1 min to 3 h. A full digital database is provided in the Supporting Information, Table S2. For display purposes, the color range of these difference maps are expanded from 4 to 8 bits per color (RGB range of 4–19 expanded to 0–255).
Figure 7
Figure 7
Hierarchical cluster analysis (HCA) for Columbian Huila green coffee beans roasted at 220 °C for times ranging from 1 min to 3 h. All experiments were run in quintuplet trials; no confusions or errors in classification were observed in 45 trials, as shown. NR = green coffee, not roasted; the number indicates nth trial. Control = no coffee present.

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