4.7 Article

Development of sequential online extraction electrospray ionization mass spectrometry for accurate authentication of highly-similar Atractylodis Macrocephalae

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FOOD RESEARCH INTERNATIONAL
卷 175, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.foodres.2023.113681

关键词

Food authentication; Highly-similar Atractylodis macrocephalae; Sequential online ionization mass spectrometry; Multivariate statistical analysis; MS fingerprints

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In this study, a novel online extraction electrospray ionization mass spectrometry method was developed to comprehensively characterize complex foods. Meanwhile, a characteristic marker screening method and chemometrics modeling were used for the accurate authentication of highly-similar foods. This research has significant implications for ensuring food quality and safety.
The accurate and rapid authentication techniques and strategies for highly-similar foods are still lacking. Herein, a novel sequential online extraction electrospray ionization mass spectrometry (S-oEESI-MS) was developed to achieve spatio-temporally resolved ionization and comprehensive characterization of complex foods with multicomponents (high, medium, and low polarity substances). Meanwhile, a characteristic marker screening method and an integrated research strategy based on MS fingerprinting, characteristic marker and chemometrics modeling were established, which are especially suitable for the accurate and rapid authentication of highlysimilar foods that are difficult to be authenticated by traditional techniques (e.g., LC-MS). Thirty-two batches of highly-similar Atractylodis macrocephalae rhizome from four different origins were used as model samples. As a result, S-oEESI-MS enabled a more comprehensive MS characterization of substance profiles in complex plant samples in 1.0 min. Further, 22 characteristic markers of Atractylodis macrocephalae were ingeniously screened out and combined with multivariate statistical analysis model, the accurate authentication of highly-similar Atractylodis macrocephalae was realized. This study presents a comprehensive strategy for accurate authentication and origin analysis of highly-similar foods, which has potentially significant applications for ensuring food quality and safety.

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