Coffee aroma--statistical analysis of compositional data
Language English Country Netherlands Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
19836541
DOI
10.1016/j.talanta.2009.07.054
PII: S0039-9140(09)00624-9
Knihovny.cz E-resources
- MeSH
- Furaldehyde analogs & derivatives analysis isolation & purification MeSH
- Principal Component Analysis MeSH
- Coffee chemistry classification MeSH
- Acetic Acid analysis isolation & purification MeSH
- Solid Phase Microextraction methods MeSH
- Gas Chromatography-Mass Spectrometry methods MeSH
- Pyrazines analysis isolation & purification MeSH
- Cluster Analysis MeSH
- Volatile Organic Compounds analysis isolation & purification MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- Furaldehyde MeSH
- 2,5-dimethylpyrazine MeSH Browser
- 5-methyl-2-furfural MeSH Browser
- Coffee MeSH
- Acetic Acid MeSH
- Pyrazines MeSH
- Volatile Organic Compounds MeSH
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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