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Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum

Aroma is one of the main characteristics of coffee specimens. Different mixtures of Arabica and Robusta coffees are usually found in the market to offer specific aroma or flavor profiles to consumers. However, the mixed samples or their proportions are not always identified in the product labels. Si...

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Autores principales: Piotr Konieczka, Paweł, Aliaño-González, María José, Ferreiro-González, Marta, Barbero, Gerardo F., Palma, Miguel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309026/
https://www.ncbi.nlm.nih.gov/pubmed/32486481
http://dx.doi.org/10.3390/s20113123
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author Piotr Konieczka, Paweł
Aliaño-González, María José
Ferreiro-González, Marta
Barbero, Gerardo F.
Palma, Miguel
author_facet Piotr Konieczka, Paweł
Aliaño-González, María José
Ferreiro-González, Marta
Barbero, Gerardo F.
Palma, Miguel
author_sort Piotr Konieczka, Paweł
collection PubMed
description Aroma is one of the main characteristics of coffee specimens. Different mixtures of Arabica and Robusta coffees are usually found in the market to offer specific aroma or flavor profiles to consumers. However, the mixed samples or their proportions are not always identified in the product labels. Since the price of Arabica is much higher than that of Robusta, this lack of information is not only an economical issue but a possible fraud to consumers, besides the potential allergic reaction that these mixtures may trigger in some individuals. In this paper, two sample preparation techniques were compared before the analysis of the total volatile organic compounds (VOCs) found in Robusta, Arabica, and in the mixture from both coffee types. The comparison of the signals obtained from the analyses showed that the VOCs concentration levels obtained from the headspace (HS) analyses were clearly higher than those obtained from the pre-concentration step where an adsorbent, an active charcoal strip (ACS + HS), was used. In the second part of this study, the possibility of using the headspace gas-chromatography ion mobility spectrometry (HS-GC-IMS) for the discrimination between Arabica, Robusta, and mixed coffee samples (n = 30) was evaluated. The ion mobility sum spectrum (IMSS) obtained from the analysis of the HS was used in combination with pattern recognition techniques, namely linear discrimination analysis (LDA), as an electronic nose. The identification of individual compounds was not carried out since chromatographic information was not used. This novel approach allowed the correct discrimination (100%) of all of the samples. A characteristic fingerprint for each type of coffee for a fast and easy identification was also developed. In addition, the developed method is ecofriendly, so it is a good alternative to traditional approaches.
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spelling pubmed-73090262020-06-25 Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum Piotr Konieczka, Paweł Aliaño-González, María José Ferreiro-González, Marta Barbero, Gerardo F. Palma, Miguel Sensors (Basel) Article Aroma is one of the main characteristics of coffee specimens. Different mixtures of Arabica and Robusta coffees are usually found in the market to offer specific aroma or flavor profiles to consumers. However, the mixed samples or their proportions are not always identified in the product labels. Since the price of Arabica is much higher than that of Robusta, this lack of information is not only an economical issue but a possible fraud to consumers, besides the potential allergic reaction that these mixtures may trigger in some individuals. In this paper, two sample preparation techniques were compared before the analysis of the total volatile organic compounds (VOCs) found in Robusta, Arabica, and in the mixture from both coffee types. The comparison of the signals obtained from the analyses showed that the VOCs concentration levels obtained from the headspace (HS) analyses were clearly higher than those obtained from the pre-concentration step where an adsorbent, an active charcoal strip (ACS + HS), was used. In the second part of this study, the possibility of using the headspace gas-chromatography ion mobility spectrometry (HS-GC-IMS) for the discrimination between Arabica, Robusta, and mixed coffee samples (n = 30) was evaluated. The ion mobility sum spectrum (IMSS) obtained from the analysis of the HS was used in combination with pattern recognition techniques, namely linear discrimination analysis (LDA), as an electronic nose. The identification of individual compounds was not carried out since chromatographic information was not used. This novel approach allowed the correct discrimination (100%) of all of the samples. A characteristic fingerprint for each type of coffee for a fast and easy identification was also developed. In addition, the developed method is ecofriendly, so it is a good alternative to traditional approaches. MDPI 2020-05-31 /pmc/articles/PMC7309026/ /pubmed/32486481 http://dx.doi.org/10.3390/s20113123 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Piotr Konieczka, Paweł
Aliaño-González, María José
Ferreiro-González, Marta
Barbero, Gerardo F.
Palma, Miguel
Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum
title Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum
title_full Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum
title_fullStr Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum
title_full_unstemmed Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum
title_short Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum
title_sort characterization of arabica and robusta coffees by ion mobility sum spectrum
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7309026/
https://www.ncbi.nlm.nih.gov/pubmed/32486481
http://dx.doi.org/10.3390/s20113123
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