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Identification of markers of sensory quality in ground coffee: an untargeted metabolomics approach
INTRODUCTION: In the last years, consumers increased the demand for high-quality and healthy beverages, including coffee. To date, among the techniques potentially available to determine the overall quality of coffee beverages, metabolomics is emerging as a valuable tool. OBJECTIVE: In this study, 4...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736008/ https://www.ncbi.nlm.nih.gov/pubmed/33315148 http://dx.doi.org/10.1007/s11306-020-01751-6 |
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author | Rocchetti, Gabriele Braceschi, Gian Paolo Odello, Luigi Bertuzzi, Terenzio Trevisan, Marco Lucini, Luigi |
author_facet | Rocchetti, Gabriele Braceschi, Gian Paolo Odello, Luigi Bertuzzi, Terenzio Trevisan, Marco Lucini, Luigi |
author_sort | Rocchetti, Gabriele |
collection | PubMed |
description | INTRODUCTION: In the last years, consumers increased the demand for high-quality and healthy beverages, including coffee. To date, among the techniques potentially available to determine the overall quality of coffee beverages, metabolomics is emerging as a valuable tool. OBJECTIVE: In this study, 47 ground coffee samples were selected during the 2018 Edition of the “International coffee tasting” (ICT) in order to provide discrimination based on both chemical and sensory profiles. In particular, 20 samples received a gold medal (“high quality” group), while lower sensory scores characterized 27 samples (without medal). METHODS: Untargeted metabolomics based on ultra-high pressure liquid chromatography coupled with quadrupole-time-of-flight (UHPLC-QTOF) and head space-gas chromatography coupled with mass spectrometry platforms followed by multivariate statistical approaches (i.e., both supervised and unsupervised) were used to provide new insight into the searching of potential markers of sensory quality. RESULTS: Several compounds were identified, including polyphenols, alkaloids, diazines, and Maillard reaction products. Also, the headspace/GC-MS highlighted the most important volatile compounds. Polyphenols were scarcely correlated to the sensory parameters, whilst the OPLS-DA models built using typical coffee metabolites and volatile/Maillard compounds possessed prediction values > 0.7. The “high quality” group showed specific metabolomic signatures, thus corroborating the results from the sensory analysis. Overall, methyl pentanoate (ROC value = 0.78), 2-furfurylthiol (ROC value = 0.75), and L-Homoserine (ROC value = 0.74) established the higher number of significant (p < 0.05) correlations with the sensory parameters. CONCLUSION: Although ad-hoc studies are advisable to further confirm the proposed markers, this study demonstrates the suitability of untargeted metabolomics for evaluating coffee quality and the potential correlations with the sensory attributes. GRAPHIC ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s11306-020-01751-6) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7736008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-77360082020-12-17 Identification of markers of sensory quality in ground coffee: an untargeted metabolomics approach Rocchetti, Gabriele Braceschi, Gian Paolo Odello, Luigi Bertuzzi, Terenzio Trevisan, Marco Lucini, Luigi Metabolomics Original Article INTRODUCTION: In the last years, consumers increased the demand for high-quality and healthy beverages, including coffee. To date, among the techniques potentially available to determine the overall quality of coffee beverages, metabolomics is emerging as a valuable tool. OBJECTIVE: In this study, 47 ground coffee samples were selected during the 2018 Edition of the “International coffee tasting” (ICT) in order to provide discrimination based on both chemical and sensory profiles. In particular, 20 samples received a gold medal (“high quality” group), while lower sensory scores characterized 27 samples (without medal). METHODS: Untargeted metabolomics based on ultra-high pressure liquid chromatography coupled with quadrupole-time-of-flight (UHPLC-QTOF) and head space-gas chromatography coupled with mass spectrometry platforms followed by multivariate statistical approaches (i.e., both supervised and unsupervised) were used to provide new insight into the searching of potential markers of sensory quality. RESULTS: Several compounds were identified, including polyphenols, alkaloids, diazines, and Maillard reaction products. Also, the headspace/GC-MS highlighted the most important volatile compounds. Polyphenols were scarcely correlated to the sensory parameters, whilst the OPLS-DA models built using typical coffee metabolites and volatile/Maillard compounds possessed prediction values > 0.7. The “high quality” group showed specific metabolomic signatures, thus corroborating the results from the sensory analysis. Overall, methyl pentanoate (ROC value = 0.78), 2-furfurylthiol (ROC value = 0.75), and L-Homoserine (ROC value = 0.74) established the higher number of significant (p < 0.05) correlations with the sensory parameters. CONCLUSION: Although ad-hoc studies are advisable to further confirm the proposed markers, this study demonstrates the suitability of untargeted metabolomics for evaluating coffee quality and the potential correlations with the sensory attributes. GRAPHIC ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s11306-020-01751-6) contains supplementary material, which is available to authorized users. Springer US 2020-12-14 2020 /pmc/articles/PMC7736008/ /pubmed/33315148 http://dx.doi.org/10.1007/s11306-020-01751-6 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Original Article Rocchetti, Gabriele Braceschi, Gian Paolo Odello, Luigi Bertuzzi, Terenzio Trevisan, Marco Lucini, Luigi Identification of markers of sensory quality in ground coffee: an untargeted metabolomics approach |
title | Identification of markers of sensory quality in ground coffee: an untargeted metabolomics approach |
title_full | Identification of markers of sensory quality in ground coffee: an untargeted metabolomics approach |
title_fullStr | Identification of markers of sensory quality in ground coffee: an untargeted metabolomics approach |
title_full_unstemmed | Identification of markers of sensory quality in ground coffee: an untargeted metabolomics approach |
title_short | Identification of markers of sensory quality in ground coffee: an untargeted metabolomics approach |
title_sort | identification of markers of sensory quality in ground coffee: an untargeted metabolomics approach |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736008/ https://www.ncbi.nlm.nih.gov/pubmed/33315148 http://dx.doi.org/10.1007/s11306-020-01751-6 |
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