Identification and characterization of matrix components in spinach during QuEChERS sample preparation for pesticide residue analysis by LC–ESI–MS/MS, GC–MS and UPLC-DAD

Autor: Su-Myeong Hong, Hyeyoung Kwon, Hyo-Sub Lee, Danbi Kim, Abul Kasem Mohammad Mydul Islam, Byeong-Chul Moon
Rok vydání: 2018
Předmět:
Zdroj: Journal of Food Science and Technology. 55:3930-3938
ISSN: 0975-8402
0022-1155
DOI: 10.1007/s13197-018-3318-4
Popis: In this article matrix components in spinach were investigated in detail. The samples were prepared using two QuEChERS (quick, easy, cheap, effective, rugged and safe) methods, AOAC and CEN. Liquid chromatography–electrospray ionization–tandem mass spectrometry (LC–ESI–MS/MS), gas chromatography–mass spectrometry (GC–MS) and ultra performance liquid chromatography-diode array detector (UPLC-DAD), were applied for component identification. The strategies of identification by LC–ESI–MS/MS include accurate mass spectra of the parent ion, comparison with previous literature data and investigation of the mass spectral decomposition pattern. Overall, fourteen components were identified by LC–ESI–MS/MS in each methods of AOAC and CEN, which were phytosteroids, flavonoids, fatty acids and fatty acid amides. Fifty components using AOAC method and fifty-seven components using CEN method were identified in GC–MS by comparing mass data with the National Institute of Standards and Technology (NIST, U.S.) database. The results indicate that the major components of the matrix are terpenoids, fatty acids and fatty acid esters. Moreover, three pigments (neoxanthin, violaxanthin and lutein) in the AOAC method and eight pigments (neoxanthin, violaxanthin, zeaxanthin, lutein, chlorophyll a, chlorophyll b, pheophytin a and beta-carotene) in the CEN method that gave a characteristics peak at 440 nm were identified by the UPLC-DAD. According to the sample preparation condition using different amounts of graphitized carbon black (GCB) in this study, the AOAC method had higher matrix component removal efficiency than the CEN method. A better understanding of matrix components would increase the current knowledge for improvement of existing QuEChERS methodology, as well as contribute to new method developments. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13197-018-3318-4) contains supplementary material, which is available to authorized users.
Databáze: OpenAIRE
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