| Literature DB >> 30228391 |
Abul Kasem Mohammad Mydul Islam1, Su-Myeong Hong1, Hyo-Sub Lee1, Byeong-Chul Moon1, Danbi Kim1, Hyeyoung Kwon1.
Abstract
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.Entities:
Keywords: Flavonoids; GC–MS; LC–ESI–MS/MS; Matrix components; Pigments; UPLC-DAD
Year: 2018 PMID: 30228391 PMCID: PMC6133855 DOI: 10.1007/s13197-018-3318-4
Source DB: PubMed Journal: J Food Sci Technol ISSN: 0022-1155 Impact factor: 2.701