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<p>Philippine single-origin coffee is gaining international recognition and local interest, yet domestic production is declining, and scientific research remains limited. This study applies untargeted metabolomics to uncover the chemical diversity of Philippine <i>Coffea sp.</i> beans. Molecular profiles of green and roasted <i>Coffea arabica</i>, <i>C. canephora</i>, and <i>C. liberica</i> var. <i>liberica</i> beans collected across the Philippines were generated using UHPLC-QToF-MS. Key metabolite classes – alkaloids, hydroxycinnamic acids, triglycerides, diterpene esters, and carboxylic acid-5-hydroxytryptamides – were putatively identified through molecular networking. Multivariate analyses (PCA and PLS-DA) revealed species and location associated trends primarily driven by caffeine, trigonelline, and triglycerides. Notably, kahweol palmitate, caffeoyl tryptophan, and methylliberine emerged as potential species-specific markers for Arabica, Robusta, and Liberica, respectively. As the first LC-MS-based untargeted metabolomics study on Philippine coffee beans, this work establishes a molecular baseline to support future efforts toward improving the value and origin traceability of local coffee.</p>

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Metabolomics of major Philippine coffee species: chemical signature and comparative analysis

  • 期刊论文

  • 发表日期：

    2026年5月6日

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  • Camille V. Rodriguez,
  • Ricky B. Nellas,
  • Hiyas A. Junio

摘要

Philippine single-origin coffee is gaining international recognition and local interest, yet domestic production is declining, and scientific research remains limited. This study applies untargeted metabolomics to uncover the chemical diversity of Philippine Coffea sp. beans. Molecular profiles of green and roasted Coffea arabica, C. canephora, and C. liberica var. liberica beans collected across the Philippines were generated using UHPLC-QToF-MS. Key metabolite classes – alkaloids, hydroxycinnamic acids, triglycerides, diterpene esters, and carboxylic acid-5-hydroxytryptamides – were putatively identified through molecular networking. Multivariate analyses (PCA and PLS-DA) revealed species and location associated trends primarily driven by caffeine, trigonelline, and triglycerides. Notably, kahweol palmitate, caffeoyl tryptophan, and methylliberine emerged as potential species-specific markers for Arabica, Robusta, and Liberica, respectively. As the first LC-MS-based untargeted metabolomics study on Philippine coffee beans, this work establishes a molecular baseline to support future efforts toward improving the value and origin traceability of local coffee.