化学
代谢组学
碎片(计算)
质谱法
极地的
仿形(计算机编程)
色谱法
代谢物分析
计算机科学
操作系统
天文
物理
作者
Marcos Valério Vieira Lyrio,Danieli Grancieri Debona,Amanda Eiriz Feu,Nayara A. dos Santos,Arlan da Silva Gonçalves,Ricardo Machado Kuster,Eustáquio Vinícius Ribeiro de Castro,Wanderson Romão
标识
DOI:10.1021/jasms.4c00418
摘要
High Resolution Image Download MS PowerPoint Slide Coffee is characterized by a complex chemical matrix that significantly influences its organoleptic properties and market value. This complexity is driven by factors such as botanical species, geographical origin, cultivation conditions, and post-harvest processing methods. Metabolomic studies aim to elucidate how these factors impact the biosynthesis of metabolites that contribute to the sensory qualities of high-quality coffee. Among various analytical techniques, liquid chromatography-mass spectrometry (LC-MS) is particularly effective for separating, identifying, and quantifying these compounds. Most metabolomic studies employ high-resolution mass spectrometry (HRMS) for its superior mass accuracy (<1 ppm), whereas the interpretation of low-resolution data requires additional effort, often relying on literature references and proposed fragmentation mechanisms. In this study, we applied LC-ESI(±)LTQ MS n to comprehensively profile coffee metabolites, identifying 60 compounds, including polar compounds and their isomers such as chlorogenic acids, carbohydrates, amino acids, alkaloids, glycosylated diterpenes, and flavonoids. Fragmentation mechanisms were proposed and discussed. The results demonstrate the effectiveness of LC-ESI(±)LTQ MS n in a detailed metabolomic analysis, providing a robust platform for future research in coffee metabolomics.
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