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High-Throughput Metabolic Profiling of Diverse Green Coffea arabica Beans Identified Tryptophan as a Universal Discrimination Factor for Immature Beans
The maturity of green coffee beans is the most influential determinant of the quality and flavor of the resultant coffee beverage. However, the chemical compounds that can be used to discriminate the maturity of the beans remain uncharacterized. We herein analyzed four distinct stages of maturity (i...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3731347/ https://www.ncbi.nlm.nih.gov/pubmed/23936381 http://dx.doi.org/10.1371/journal.pone.0070098 |
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author | Setoyama, Daiki Iwasa, Keiko Seta, Harumichi Shimizu, Hiroaki Fujimura, Yoshinori Miura, Daisuke Wariishi, Hiroyuki Nagai, Chifumi Nakahara, Koichi |
author_facet | Setoyama, Daiki Iwasa, Keiko Seta, Harumichi Shimizu, Hiroaki Fujimura, Yoshinori Miura, Daisuke Wariishi, Hiroyuki Nagai, Chifumi Nakahara, Koichi |
author_sort | Setoyama, Daiki |
collection | PubMed |
description | The maturity of green coffee beans is the most influential determinant of the quality and flavor of the resultant coffee beverage. However, the chemical compounds that can be used to discriminate the maturity of the beans remain uncharacterized. We herein analyzed four distinct stages of maturity (immature, semi-mature, mature and overripe) of nine different varieties of green Coffea arabica beans hand-harvested from a single experimental field in Hawaii. After developing a high-throughput experimental system for sample preparation and liquid chromatography-mass spectrometry (LC-MS) measurement, we applied metabolic profiling, integrated with chemometric techniques, to explore the relationship between the metabolome and maturity of the sample in a non-biased way. For the multivariate statistical analyses, a partial least square (PLS) regression model was successfully created, which allowed us to accurately predict the maturity of the beans based on the metabolomic information. As a result, tryptophan was identified to be the best contributor to the regression model; the relative MS intensity of tryptophan was higher in immature beans than in those after the semi-mature stages in all arabica varieties investigated, demonstrating a universal discrimination factor for diverse arabica beans. Therefore, typtophan, either alone or together with other metabolites, may be utilized for traders as an assessment standard when purchasing qualified trading green arabica bean products. Furthermore, our results suggest that the tryptophan metabolism may be tightly linked to the development of coffee cherries and/or beans. |
format | Online Article Text |
id | pubmed-3731347 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37313472013-08-09 High-Throughput Metabolic Profiling of Diverse Green Coffea arabica Beans Identified Tryptophan as a Universal Discrimination Factor for Immature Beans Setoyama, Daiki Iwasa, Keiko Seta, Harumichi Shimizu, Hiroaki Fujimura, Yoshinori Miura, Daisuke Wariishi, Hiroyuki Nagai, Chifumi Nakahara, Koichi PLoS One Research Article The maturity of green coffee beans is the most influential determinant of the quality and flavor of the resultant coffee beverage. However, the chemical compounds that can be used to discriminate the maturity of the beans remain uncharacterized. We herein analyzed four distinct stages of maturity (immature, semi-mature, mature and overripe) of nine different varieties of green Coffea arabica beans hand-harvested from a single experimental field in Hawaii. After developing a high-throughput experimental system for sample preparation and liquid chromatography-mass spectrometry (LC-MS) measurement, we applied metabolic profiling, integrated with chemometric techniques, to explore the relationship between the metabolome and maturity of the sample in a non-biased way. For the multivariate statistical analyses, a partial least square (PLS) regression model was successfully created, which allowed us to accurately predict the maturity of the beans based on the metabolomic information. As a result, tryptophan was identified to be the best contributor to the regression model; the relative MS intensity of tryptophan was higher in immature beans than in those after the semi-mature stages in all arabica varieties investigated, demonstrating a universal discrimination factor for diverse arabica beans. Therefore, typtophan, either alone or together with other metabolites, may be utilized for traders as an assessment standard when purchasing qualified trading green arabica bean products. Furthermore, our results suggest that the tryptophan metabolism may be tightly linked to the development of coffee cherries and/or beans. Public Library of Science 2013-08-01 /pmc/articles/PMC3731347/ /pubmed/23936381 http://dx.doi.org/10.1371/journal.pone.0070098 Text en © 2013 Setoyama et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Setoyama, Daiki Iwasa, Keiko Seta, Harumichi Shimizu, Hiroaki Fujimura, Yoshinori Miura, Daisuke Wariishi, Hiroyuki Nagai, Chifumi Nakahara, Koichi High-Throughput Metabolic Profiling of Diverse Green Coffea arabica Beans Identified Tryptophan as a Universal Discrimination Factor for Immature Beans |
title | High-Throughput Metabolic Profiling of Diverse Green Coffea arabica Beans Identified Tryptophan as a Universal Discrimination Factor for Immature Beans |
title_full | High-Throughput Metabolic Profiling of Diverse Green Coffea arabica Beans Identified Tryptophan as a Universal Discrimination Factor for Immature Beans |
title_fullStr | High-Throughput Metabolic Profiling of Diverse Green Coffea arabica Beans Identified Tryptophan as a Universal Discrimination Factor for Immature Beans |
title_full_unstemmed | High-Throughput Metabolic Profiling of Diverse Green Coffea arabica Beans Identified Tryptophan as a Universal Discrimination Factor for Immature Beans |
title_short | High-Throughput Metabolic Profiling of Diverse Green Coffea arabica Beans Identified Tryptophan as a Universal Discrimination Factor for Immature Beans |
title_sort | high-throughput metabolic profiling of diverse green coffea arabica beans identified tryptophan as a universal discrimination factor for immature beans |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3731347/ https://www.ncbi.nlm.nih.gov/pubmed/23936381 http://dx.doi.org/10.1371/journal.pone.0070098 |
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