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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...

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Autores principales: Setoyama, Daiki, Iwasa, Keiko, Seta, Harumichi, Shimizu, Hiroaki, Fujimura, Yoshinori, Miura, Daisuke, Wariishi, Hiroyuki, Nagai, Chifumi, Nakahara, Koichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
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.
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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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