Literature DB >> 25230190

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

Sine Yener1, Andrea Romano, Luca Cappellin, Tilmann D Märk, José Sánchez Del Pulgar, Flavia Gasperi, Luciano Navarini, Franco Biasioli.   

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 three monoorigin 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.
Copyright © 2014 John Wiley & Sons, Ltd.

Entities:  

Keywords:  PTR-ToF-MS; coffee; geographic origin; multivariate analysis; volatile compounds

Year:  2014        PMID: 25230190     DOI: 10.1002/jms.3455

Source DB:  PubMed          Journal:  J Mass Spectrom        ISSN: 1076-5174            Impact factor:   1.982


  6 in total

1.  PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis.

Authors:  Vittorio Capozzi; Sine Yener; Iuliia Khomenko; Brian Farneti; Luca Cappellin; Flavia Gasperi; Matteo Scampicchio; Franco Biasioli
Journal:  J Vis Exp       Date:  2017-05-11       Impact factor: 1.355

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

Authors:  Giuseppe Procida; Corrado Lagazio; Francesca Cateni; Marina Zacchigna; Angelo Cichelli
Journal:  Food Sci Biotechnol       Date:  2020-06-04       Impact factor: 2.391

3.  Analysis of volatile fraction of sweetie (Citrus maxima × Citrus paradisi) and its parent fruit using proton transfer reaction mass spectrometry.

Authors:  Anna Różańska; Dorota Sieńska; Tomasz Dymerski; Jacek Namieśnik
Journal:  Monatsh Chem       Date:  2018-08-09       Impact factor: 1.451

4.  Identification of the volatile profiles of 22 traditional and newly bred maize varieties and their porridges by PTR-QiTOF-MS and HS-SPME GC-MS.

Authors:  Onu Ekpa; Vincenzo Fogliano; Anita Linnemann
Journal:  J Sci Food Agric       Date:  2020-09-21       Impact factor: 3.638

5.  From Extra Virgin Olive Oil to Refined Products: Intensity and Balance Shifts of the Volatile Compounds versus Odor.

Authors:  Jing Yan; Martin Alewijn; Saskia M van Ruth
Journal:  Molecules       Date:  2020-05-26       Impact factor: 4.411

6.  PTR-MS Characterization of VOCs Associated with Commercial Aromatic Bakery Yeasts of Wine and Beer Origin.

Authors:  Vittorio Capozzi; Salim Makhoul; Eugenio Aprea; Andrea Romano; Luca Cappellin; Ana Sanchez Jimena; Giuseppe Spano; Flavia Gasperi; Matteo Scampicchio; Franco Biasioli
Journal:  Molecules       Date:  2016-04-12       Impact factor: 4.411

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.