Coffee is one of the most important agricultural commodities and has the unique organoleptic characteristics such as strong but not bitter taste,fragrant,oily,and fruity.In this study,an untargeted metabolomics approa...Coffee is one of the most important agricultural commodities and has the unique organoleptic characteristics such as strong but not bitter taste,fragrant,oily,and fruity.In this study,an untargeted metabolomics approach based on UHPLC-QE-MS was used to investigate the differences in terms of components of precursor metabolites in coffee beans from 18 producing regions worldwide.Fingerprint analysis,principal component analysis and hierarchical clustering analysis revealed a neat separation among coffee beans.Compounds with high relevance to variance in the projection values in supervised multivariate analysis were selected as important metabolites for the discrimination of coffee samples.In total,10 different families of compounds were considered as potential markers of the coffee beans:3-hydroxycoumarin,4,5-di-O-caffeoylquinic,cryptochlorogenic acid,palmitic amide,linoleamide,arachidic acid,petroselinic acid,trehalose,L-glutamic acid,L-malic acid.The findings presented herein serve as a suitable framework for the design of novel discrimination strategies in food origin tracing.展开更多
基金This work was supported by Risk assessment of agricultural product quality and safety-Building a coffee quality index system[grant number 125D0202].
文摘Coffee is one of the most important agricultural commodities and has the unique organoleptic characteristics such as strong but not bitter taste,fragrant,oily,and fruity.In this study,an untargeted metabolomics approach based on UHPLC-QE-MS was used to investigate the differences in terms of components of precursor metabolites in coffee beans from 18 producing regions worldwide.Fingerprint analysis,principal component analysis and hierarchical clustering analysis revealed a neat separation among coffee beans.Compounds with high relevance to variance in the projection values in supervised multivariate analysis were selected as important metabolites for the discrimination of coffee samples.In total,10 different families of compounds were considered as potential markers of the coffee beans:3-hydroxycoumarin,4,5-di-O-caffeoylquinic,cryptochlorogenic acid,palmitic amide,linoleamide,arachidic acid,petroselinic acid,trehalose,L-glutamic acid,L-malic acid.The findings presented herein serve as a suitable framework for the design of novel discrimination strategies in food origin tracing.
