Literature DB >> 28338254

Static and dynamic headspace analysis of instant coffee blends by proton-transfer-reaction mass spectrometry.

Andrea Romano1,2, Sylvia Gaysinsky3, Andreas Czepa4, José Sanchez Del Pulgar1, Luca Cappellin1, Franco Biasioli1.   

Abstract

Instant coffee is a widespread product, generally related to a high consumer acceptability, also because of its ease of preparation. The present work addresses the characterization of the headspace of freshly brewed instant coffees resulting from different blends, during and immediately after preparation. The sample set consisted of 10 coffees, obtained by mixing three different blends in different proportions. The employment of Proton Transfer Reaction-Mass Spectrometry (PTR-MS) allowed for direct and real-time sampling from the headspace, under conditions that mimic those that are encountered above the cup during and right after brewing. Different coffee brews were separated on the basis of the respective volatile profiles, and data showed good consistency with the respective blend compositions. When the headspace evolution was monitored during preparation, similar results were obtained in terms of blend separation; moreover, different blends displayed different and reproducible 'signatures' in terms of time evolution. A straightforward method for the prediction of headspace composition is proposed, allowing to predict the volatile profiles of two-component and three-component blends on the basis of the respective parent components. Overall, the results constitute a successful example of the applicability of PTR-MS as a tool for product development in food science.
Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Keywords:  PTR-MS; dynamic headspace; instant coffee; static headspace; volatile release

Year:  2015        PMID: 28338254     DOI: 10.1002/jms.3619

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


  1 in total

1.  HS-SPME-MS-Enose Coupled with Chemometrics as an Analytical Decision Maker to Predict In-Cup Coffee Sensory Quality in Routine Controls: Possibilities and Limits.

Authors:  Erica Liberto; Davide Bressanello; Giulia Strocchi; Chiara Cordero; Manuela Rosanna Ruosi; Gloria Pellegrino; Carlo Bicchi; Barbara Sgorbini
Journal:  Molecules       Date:  2019-12-10       Impact factor: 4.411

  1 in total

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