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

Yener, S.; Romano, A.; Cappellin, L.; Märk, T.; Sanchez Del Pulgar Rico, J.; Gasperi, F.; Navarini, L.; Biasioli, F. (2014). PTR-ToF-MS characterisation of roasted coffees (C. arabica) from different geographic origins. JOURNAL OF MASS SPECTROMETRY, 49 (9): 929-935. doi: 10.1002/jms.3455 handle: http://hdl.handle.net/10449/25033

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

Yener, Sine;Romano, Andrea;Cappellin, Luca;Sanchez Del Pulgar Rico, José;Gasperi, Flavia;Biasioli, Franco
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
PTR-ToF-MS
Geographic origin
Coffee
Volatile compounds
Multivariate analysis
Settore CHIM/01 - CHIMICA ANALITICA
2014
Yener, S.; Romano, A.; Cappellin, L.; Märk, T.; Sanchez Del Pulgar Rico, J.; Gasperi, F.; Navarini, L.; Biasioli, F. (2014). PTR-ToF-MS characterisation of roasted coffees (C. arabica) from different geographic origins. JOURNAL OF MASS SPECTROMETRY, 49 (9): 929-935. doi: 10.1002/jms.3455 handle: http://hdl.handle.net/10449/25033
File in questo prodotto:
File Dimensione Formato  
yener et al J. Mass Spectrom. 2014 49 929–935.pdf

non disponibili

Descrizione: pdf paper
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 333.64 kB
Formato Adobe PDF
333.64 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10449/25033
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 46
  • ???jsp.display-item.citation.isi??? 38
social impact