Coffee aroma--statistical analysis of compositional data

Talanta. 2009 Dec 15;80(2):710-5. doi: 10.1016/j.talanta.2009.07.054. Epub 2009 Aug 3.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acetic Acid / analysis
  • Acetic Acid / isolation & purification
  • Cluster Analysis
  • Coffee / chemistry*
  • Coffee / classification
  • Furaldehyde / analogs & derivatives
  • Furaldehyde / analysis
  • Furaldehyde / isolation & purification
  • Gas Chromatography-Mass Spectrometry / methods*
  • Principal Component Analysis
  • Pyrazines / analysis
  • Pyrazines / isolation & purification
  • Solid Phase Microextraction / methods*
  • Volatile Organic Compounds / analysis*
  • Volatile Organic Compounds / isolation & purification

Substances

  • Coffee
  • Pyrazines
  • Volatile Organic Compounds
  • 5-methyl-2-furfural
  • Furaldehyde
  • Acetic Acid
  • 2,5-dimethylpyrazine