Prediction of key aroma development in coffees roasted to different degrees by colorimetric sensor array
- Authors
- Kim, Su-Yeon; Ko, Jung-A; Kang, Bo-Sik; Park, Hyun-Jin
- Issue Date
- 1-2월-2018
- Publisher
- ELSEVIER SCI LTD
- Keywords
- Colorimetric artificial nose; Cross-responsive sensor; Multivariate analysis; Roast degree; Coffee roasting
- Citation
- FOOD CHEMISTRY, v.240, pp.808 - 816
- Indexed
- SCIE
SCOPUS
- Journal Title
- FOOD CHEMISTRY
- Volume
- 240
- Start Page
- 808
- End Page
- 816
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/77395
- DOI
- 10.1016/j.foodchem.2017.07.139
- ISSN
- 0308-8146
- Abstract
- 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 alpha-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 (r(p)(2)) 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.
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Collections - Graduate School > Department of Biotechnology > 1. Journal Articles
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