Coffee aroma—Statistical analysis of compositional data |
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Authors: | M. Korhoňová ,K. Hron,D. Klim?í ková ,P. Bedná ? |
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Affiliation: | a Department of Analytical Chemistry, Faculty of Science, Palacky University, 17. listopadu 12, 711 46 Olomouc, Czech Republic b Department of Mathematical Analysis and Applications of Mathematics, Faculty of Science, Palacky University, 17. listopadu 12, 771 46 Olomouc, Czech Republic |
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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. |
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Keywords: | Coffee aroma Solid-phase microextraction SPME Compositional data Principal component analysis Cluster analysis |
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