Characterization of Arabica and Robusta volatile coffees composition by reverse carrier gas headspace gas chromatography–mass spectrometry based on a statistical approach

Nineteen samples of Arabica and 14 of Robusta coming from various plantation were analysed by dynamic headspace capillary gas chromatography-mass spectrometry to characterize the volatile fraction of green and roasted samples and the relationships of the same species with geographical origin. As concerns green beans, Arabica species appear characterized by high content of n-hexanol, furfural and amylformate, while Robusta species by greater content of ethylpyrazine, dimethylsulfone and 2-heptanone. Four variables, 4-methyl-2,3-dihydrofuran, n-hexanol, limonene and nonanal, appear involved in the characterization of the geographical origin of the analysed samples. The volatile fraction of the roasted Arabica samples, appear characterized by high content of pyridine, diacetyl, propylformate, acetone and 2,3-pentanedione, while Robusta samples by high content of methylbutyrate, 2,3-dimethylpyrazine and 3-hexanone. Considering geographical origin of the analysed samples, four compounds appear involved, in particular 2-butanone, methylbutyrate, methanol and ethylformate. Very accurate (error rate lower than 5%) rules to classify samples as Arabica or Robusta according to their compounds profile were developed. furfural and amylformate, while Robusta species by greater content of ethylpyrazine, dimethylsulfone and 2-heptanone. Four variables, 4-methyl-2,3-dihydrofuran, n-hexanol, limonene and nonanal, appear involved in the characterization of the geographical origin of the analysed samples. The volatile fraction of the roasted Arabica samples, appear characterized by high content of pyridine, diacetyl, propylformate, acetone and 2,3-pentanedione, while Robusta samples by high content of methylbutyrate, 2,3- dimethylpyrazine and 3-hexanone. Considering geographical origin of the analysed samples, four compounds appear involved, in particular 2-butanone, methylbutyrate, methanol and ethylformate. Very accurate (error rate lower than 5%) rules to classify samples as Arabica or Robusta according to their compounds profile were developed.