Polyphenolic profiling of coffee beverages by Liquid Chromatography-High-Resolution mass Spectrometry for classification and characterization

被引:0
|
作者
Nunez, Nerea [1 ]
Saurina, Javier [1 ,2 ]
Nunez, Oscar [1 ,3 ]
机构
[1] Univ Barcelona, Dept Chem Engn & Analyt Chem, Marti & Franques 1-11, E-08028 Barcelona, Spain
[2] Univ Barcelona, Res Inst Food Nutr & Food Safety, Av Prat Riba 171,Edif Recerca Gaudi, E-08921 Santa Coloma De Gramenet, Spain
[3] Generalitat Catalunya, Serra Hunter Fellow Programme, Via Laietana 2, E-08003 Barcelona, Spain
关键词
Liquid Chromatography-High-Resolution Mass; Spectrometry (LC-HRMS); Polyphenolic Profiling; Coffee Classification and Characterization; Principal Component Analysis (PCA); Partial least squares (PLS) regression; Partial least squares-discriminant analysis (PLS-DA); HPLC; QUANTIFICATION; EXTRACTION; SAMPLES; ACIDS;
D O I
10.1016/j.microc.2024.111770
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The importance of monitoring the presence of bioactive compounds as food attributes for sample classification and characterization is increasing. In this study, targeted Liquid Chromatography coupled with High-Resolution Mass Spectrometry (LC-HRMS) was employed to analyze the chemical profile of polyphenolic compounds as the source of information for the characterization and classification of 306 commercial coffee samples. Coffee holds a distinguished position as one of the most widely popular beverages globally but also one of the most easily adulterated. Regrettably, in recent times, instances of coffee adulteration have been on the rise. Consequently, implementing rigorous quality control measures for coffee becomes imperative to guarantee its quality. The results obtained in this work confirm that the proposed chemical profiles serve as excellent descriptors for sample characterization and classification through the implementation of principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), achieving classification rates higher than 83.3% in PLS-DA validation. Moreover, the proposed LC-HRMS polyphenolic approach was employed to identify and measure adulteration levels in coffee samples using partial least squares (PLS) regression with prediction errors below 7.8%.
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页数:10
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