Characterisation of coffees according to their origins is of utmost importance for commercial qualification. In this study, the aroma profiles of different batches of threemonoorigin roasted Coffea arabica coffees (Brazil, Ethiopia and Guatemala) were analysed by Proton-Transfer-Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS). The measurements were performed with the aid of a multipurpose autosampler. Unsupervised and supervised multivariate data analysis techniques were applied in order to visualise data and classify the coffees according to origin. Significant differences were found in volatile profiles of coffees. Principal component analysis allowed visualising a separation of the three coffees according to geographic origin and further partial least square regression-discriminant analysis classification showed completely correct predictions. Remarkably, the samples of one batch could be used as training set to predict geographic origin of the samples of the other batch, suggesting the possibility to predict further batches in coffee production by means of the same approach. Tentative identification of mass peaks aided characterisation of aroma fractions. Classification pinpointed some volatile compounds important for discrimination of coffees

PTR-ToF-MS characterisation of roasted coffees (C. arabica) from different geographic origins / Yener, Sine; Romano, Andrea; Cappellin, Luca; Märk, T.; Sanchez Del Pulgar Rico, José; Gasperi, Flavia; Navarini, L.; Biasioli, Franco. - In: JOURNAL OF MASS SPECTROMETRY. - ISSN 1076-5174. - 49:9(2014), pp. 929-935. [10.1002/jms.3455]

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

Gasperi, Flavia;
2014-01-01

Abstract

Characterisation of coffees according to their origins is of utmost importance for commercial qualification. In this study, the aroma profiles of different batches of threemonoorigin roasted Coffea arabica coffees (Brazil, Ethiopia and Guatemala) were analysed by Proton-Transfer-Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS). The measurements were performed with the aid of a multipurpose autosampler. Unsupervised and supervised multivariate data analysis techniques were applied in order to visualise data and classify the coffees according to origin. Significant differences were found in volatile profiles of coffees. Principal component analysis allowed visualising a separation of the three coffees according to geographic origin and further partial least square regression-discriminant analysis classification showed completely correct predictions. Remarkably, the samples of one batch could be used as training set to predict geographic origin of the samples of the other batch, suggesting the possibility to predict further batches in coffee production by means of the same approach. Tentative identification of mass peaks aided characterisation of aroma fractions. Classification pinpointed some volatile compounds important for discrimination of coffees
2014
9
Yener, Sine; Romano, Andrea; Cappellin, Luca; Märk, T.; Sanchez Del Pulgar Rico, José; Gasperi, Flavia; Navarini, L.; Biasioli, Franco
PTR-ToF-MS characterisation of roasted coffees (C. arabica) from different geographic origins / Yener, Sine; Romano, Andrea; Cappellin, Luca; Märk, T.; Sanchez Del Pulgar Rico, José; Gasperi, Flavia; Navarini, L.; Biasioli, Franco. - In: JOURNAL OF MASS SPECTROMETRY. - ISSN 1076-5174. - 49:9(2014), pp. 929-935. [10.1002/jms.3455]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/263968
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