Discrimination of complex mixtures by a colorimetric sensor array: coffee aromas.

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 r

SUBMITTER: Suslick BA 

PROVIDER: S-EPMC2947826 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature