Rapid communications in mass spectrometry : RCM · 2026
Comparative Metabolomic Profiling of Roasted Coffee Beans From Taiwan and Brazil.
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Chien Han-Ju, Jian Jyun-Cih, Lai Chien-Chen
Аннотация
RATIONALE: Taiwan produces high-value specialty coffee on a limited scale, whereas Brazil is the largest global supplier and a major source of imports to Taiwan. For food authenticity, differentiation of roasted coffee from these origins is important. However, few metabolomics-based traceability studies have yet been conducted on Taiwan-roasted coffee.
METHODS: In this study, metabolic profiling was applied to evaluate origin-related chemical signatures in Arabica roasted coffee beans from Taiwan and Brazil. An untargeted metabolomic workflow of integrating full scan and data-dependent acquisition (IFSDDA) was implemented using UHPLC-QTOF-MS. Roasted coffee beans were extracted using optimized 50% ethanol, profiled by LC-MS/MS, and analyzed using multivariate statistics, ROC analysis, and spectral-library-based metabolite annotation.
RESULTS: Multivariate analyses revealed a clear separation of Taiwanese and Brazilian roasted coffee samples. Among 26 annotated metabolites, four compounds showed the highest discriminatory power (VIP > 1.0), including 4-(1H-indol-3-yl)butan-2-one, citrulline, 7-methanesulfinylheptanenitrile, and phytosphingosine. The four-potential markers achieved excellent classification performance (AUC > 0.98), reflecting consistent origin-associated patterns.
CONCLUSIONS: This study demonstrated that untargeted metabolic profiling can effectively distinguish roasted coffee from Taiwan and Brazil. Such profiling provided an approach for food safety surveillance by capturing chemical signatures linked to regional production environments and agricultural inputs. The annotated markers offer a practical framework for monitoring both imported and domestic roasted coffee.
METHODS: In this study, metabolic profiling was applied to evaluate origin-related chemical signatures in Arabica roasted coffee beans from Taiwan and Brazil. An untargeted metabolomic workflow of integrating full scan and data-dependent acquisition (IFSDDA) was implemented using UHPLC-QTOF-MS. Roasted coffee beans were extracted using optimized 50% ethanol, profiled by LC-MS/MS, and analyzed using multivariate statistics, ROC analysis, and spectral-library-based metabolite annotation.
RESULTS: Multivariate analyses revealed a clear separation of Taiwanese and Brazilian roasted coffee samples. Among 26 annotated metabolites, four compounds showed the highest discriminatory power (VIP > 1.0), including 4-(1H-indol-3-yl)butan-2-one, citrulline, 7-methanesulfinylheptanenitrile, and phytosphingosine. The four-potential markers achieved excellent classification performance (AUC > 0.98), reflecting consistent origin-associated patterns.
CONCLUSIONS: This study demonstrated that untargeted metabolic profiling can effectively distinguish roasted coffee from Taiwan and Brazil. Such profiling provided an approach for food safety surveillance by capturing chemical signatures linked to regional production environments and agricultural inputs. The annotated markers offer a practical framework for monitoring both imported and domestic roasted coffee.