Title of article :
Coffee aroma—Statistical analysis of compositional data
Author/Authors :
Korho?ov?، نويسنده , , M. and Hron، نويسنده , , K. and Klim??kov?، نويسنده , , D. and Müller، نويسنده , , L. and Bedn??، نويسنده , , P. and Bart?k، نويسنده , , P.، نويسنده ,
Issue Information :
ماهنامه با شماره پیاپی سال 2009
Abstract :
Solid-phase microextraction in headspace mode coupled with gas chromatography–mass spectrometry was applied to the determination of volatile compounds in 30 commercially available coffee samples. In order to differentiate and characterize Arabica and Robusta coffee, six major volatile compounds (acetic acid, 2-methylpyrazine, furfural, 2-furfuryl alcohol, 2,6-dimethylpyrazine, 5-methylfurfural) were chosen as the most relevant markers. Cluster analysis and principal component analysis (PCA) were applied to the raw chromatographic data and data processed by centred logratio transformation.
Keywords :
Coffee aroma , SPME , Solid-phase microextraction , compositional data , Principal component analysis , Cluster analysis