Su-Yeon Kima,c, Jung-A Koa, Bo-Sik Kangb,*, Hyun-Jin Parka,*
a Department of Biotechnology, College of Life Sciences and Biotechnology, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, Republic of Korea
b Department of Wine and Coffee, Daekyeung University, Jain-myeon, Gyeongsan-Si, Gyeongbuk 38547, Republic of Korea c World Institute of Kimchi, Gwangju 61755, Republic of Korea
*Corresponding authors : Bo-Sik Kang, Hyun-Jin Park
We developed a colorimetric sensor array (CSA) that is sensitive to highly contributory volatile compounds of coffee aroma for discrimination of coffee samples roasted to different roast degrees. Strecker aldehydes and α-diketones were significantly higher for the medium roast than the other roast degrees. The development of several sulfur compounds was pronounced in the medium-dark and dark roasts, except for dimethyl sulfide, which was only detected in the light roast. The CSA method coupled with principal component analysis or hierarchical cluster analysis successfully distinguished the roasted coffee samples according to roast degree. Partial least squares regression results showed that the CSA responses were well-correlated with the concentrations of volatile compounds in the coefficient of determination (rp2) range of 0.686?0.955. These results demonstrate that the CSA rapidly responded to coffee aroma compounds and was capable of predicting coffee aroma development.
Keywords : Colorimetric artificial nose, Cross-responsive sensor, Multivariate analysis, Roast degree, Coffee roasting