Introduction The taste and aroma of high quality coffee can vary considerably among samples from the same species and variety grown in different regions. In addition to the fact that geographic origin is embedded in coffee quality, marking of origin for product differentiation is highly demanded for traceability, authentication, and marketability purposes. In this study, we developed a mass spectrometry based set-up for the high-throughput characterisation of food samples. The aromatic profiles of six roasted C. arabica coffees (Brazil, Ethiopia, Guatemala, Costa Rica, Colombia, India) were analysed by Proton-Transfer-Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS) to characterise aromatic profiles of coffee powders and brews. Methods Commercially available medium roasted C. arabica coffees were used for the experiment. Coffee brewing was performed by steam pressure coffee extraction in a stove-top coffee maker known as “moka” in Italy. The headspace measurements of coffee powder and brews were performed by a commercial PTR-ToF-MS 8000 instrument connected to a multipurpose autosampler. The proton transfer reaction was controlled by drift voltage (550 V), drift temperature (110°C), drift pressure (2.30 mbar) and E/N=140 Td. Multivariate data analysis techniques were applied in order to visualize data and classify the coffees according to origin. Results The results showed that the volatile compositions of coffees were highly influenced by the geographic origin of the coffee beans. Significant differences were found among volatile concentrations of coffee powders and brews. Tentative identification of mass peaks aided characterisation of aroma fractions. Principal component analysis allowed separation of coffees according to origin both for powder and brew. Some mass peaks were increased in the brew whereas decreased maybe be due to the lower solubility of aroma compounds in the brew or degradation of them by hot water. Conclusions Six C. arabica from different geographical origins were successfully classified by their volatile profiles in powder and brew. PTR-ToF-MS spectra of the coffees contained almost five hundred mass peaks and the high mass resolution allowed the tentative identification of diverse volatile compounds useful for aroma fingerprints and origin discrimination. Novel Aspect PTR-ToF-MS has been used for the first time for the rapid classification of the origin of ground roasted coffee powder and brew

Yener, S.; Romano, A.; Cappellin, L.; Granitto, P.M.; Märk, T.D.; Gasperi, F.; Navarini, L.; Biasioli, F. (2014). PTR-ToF-MS characterization of roasted coffees (C. arabica) from different geographic origins. In: 20th IMSC: International Mass Spectrometry Conference, Genewa, Switzerland, August, 24-29, 2014: 75 (WOS24-04). ISBN: 978-2-8399-1514-4. url: http://www.imsc2014.ch/wp-content/uploads/2013/12/IMSC2014_AbstractBook_ISBN_978-2-8399-1514-4.pdf handle: http://hdl.handle.net/10449/25032

PTR-ToF-MS characterization of roasted coffees (C. arabica) from different geographic origins

Yener, Sine;Romano, Andrea;Cappellin, Luca;Gasperi, Flavia;Biasioli, Franco
2014-01-01

Abstract

Introduction The taste and aroma of high quality coffee can vary considerably among samples from the same species and variety grown in different regions. In addition to the fact that geographic origin is embedded in coffee quality, marking of origin for product differentiation is highly demanded for traceability, authentication, and marketability purposes. In this study, we developed a mass spectrometry based set-up for the high-throughput characterisation of food samples. The aromatic profiles of six roasted C. arabica coffees (Brazil, Ethiopia, Guatemala, Costa Rica, Colombia, India) were analysed by Proton-Transfer-Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS) to characterise aromatic profiles of coffee powders and brews. Methods Commercially available medium roasted C. arabica coffees were used for the experiment. Coffee brewing was performed by steam pressure coffee extraction in a stove-top coffee maker known as “moka” in Italy. The headspace measurements of coffee powder and brews were performed by a commercial PTR-ToF-MS 8000 instrument connected to a multipurpose autosampler. The proton transfer reaction was controlled by drift voltage (550 V), drift temperature (110°C), drift pressure (2.30 mbar) and E/N=140 Td. Multivariate data analysis techniques were applied in order to visualize data and classify the coffees according to origin. Results The results showed that the volatile compositions of coffees were highly influenced by the geographic origin of the coffee beans. Significant differences were found among volatile concentrations of coffee powders and brews. Tentative identification of mass peaks aided characterisation of aroma fractions. Principal component analysis allowed separation of coffees according to origin both for powder and brew. Some mass peaks were increased in the brew whereas decreased maybe be due to the lower solubility of aroma compounds in the brew or degradation of them by hot water. Conclusions Six C. arabica from different geographical origins were successfully classified by their volatile profiles in powder and brew. PTR-ToF-MS spectra of the coffees contained almost five hundred mass peaks and the high mass resolution allowed the tentative identification of diverse volatile compounds useful for aroma fingerprints and origin discrimination. Novel Aspect PTR-ToF-MS has been used for the first time for the rapid classification of the origin of ground roasted coffee powder and brew
978-2-8399-1514-4
2014
Yener, S.; Romano, A.; Cappellin, L.; Granitto, P.M.; Märk, T.D.; Gasperi, F.; Navarini, L.; Biasioli, F. (2014). PTR-ToF-MS characterization of roasted coffees (C. arabica) from different geographic origins. In: 20th IMSC: International Mass Spectrometry Conference, Genewa, Switzerland, August, 24-29, 2014: 75 (WOS24-04). ISBN: 978-2-8399-1514-4. url: http://www.imsc2014.ch/wp-content/uploads/2013/12/IMSC2014_AbstractBook_ISBN_978-2-8399-1514-4.pdf handle: http://hdl.handle.net/10449/25032
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