Metabolomics fingerprint of Philippine coffee by SPME-GC-MS for geographical and varietal classification

Abstract

Volatile metabolites of Philippine Arabica and Robusta coffee beans in both forms standard (not-eaten by the Asian palm civet) and civet coffee grown in different Philippine regions were identified using the hyphenated technique headspace-solid phase microextraction-gas chromatography-mass spectrometry. A great number of volatile metabolites with a wide variety of functional groups were extracted and forty-seven prominent compounds were identified. The volatile metabolomics (volatilomics) fingerprint of Arabica coffees considerably differed from Robusta coffee and geographical origin slightly altered the fingerprint profile of coffee samples. Chemometric analysis such as principal component analysis (PCA) displayed a good classification between Arabica and Robusta coffee samples. Although Arabica coffee samples from different geographical origins were clustered separately from each other, the proximity of clusters between Arabica coffee samples which could be classified into one large group, indicated their close similarity of headspace metabolites. The distinction between Arabica samples and Robusta coffees was attributed through the PCA to several key volatile metabolites, in particular, higher quantities of acetic acid, furfural, 5-methylfurfural, 2-formylpyrrole and maltol and lower concentrations of 4-ethylguaiacol and phenol. These discriminating metabolites could represent useful quality markers to differentiate Arabica from Robusta coffee. Results revealed that the headspace metabolites in coffee provide significant information on its inherent aroma quality. Also, the findings suggested that the overall quality of Philippine coffee is variety and region-specific.

Keywords: Arabica; Asian palm civet; Civet coffee; Discriminant markers; Geographical origin; HS-SPME-GC-MS; Robusta; Volatile metabolites; Volatilomics.