Miniaturized sample preparation techniques and ambient mass spectrometry as approaches for food residue analysis

被引:34
|
作者
Martins, Rafael Oliveira [1 ]
de Araujo, Giovanna Lopes [1 ]
de Freitas, Carla Santos [1 ]
Silva, Allyster Rodrigues [1 ]
Simas, Rosineide Costa [1 ]
Vaz, Boniek Gontijo [1 ]
Chaves, Andrea Rodrigues [1 ]
机构
[1] Univ Fed Goias, Inst Quim, BR-74690900 Goiania, Go, Brazil
关键词
Miniaturized sample preparation; Ambient mass spectrometry; Food residues analysis; PERFORMANCE LIQUID-CHROMATOGRAPHY; BAR SORPTIVE EXTRACTION; PHASE MICROEXTRACTION; HOLLOW-FIBER;
D O I
10.1016/j.chroma.2021.461949
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Analytical methods such as liquid chromatography (LC) and mass spectrometry (MS) are widely used techniques for the analyses of different classes of compounds. This is due to their highlighted capacity for separating and identifying components in complex matrices such food samples. However, in most cases, effective analysis of the target analyte becomes challenging due to the complexity of the sample, especially for quantification of trace concentrations. In this case, miniaturized sample preparation methods have been used as a strategy for analysis of complex matrices. This involves removing the interferents and concentrating the analytes in a sample. These methods combine simplicity and effectiveness and given their miniaturized scale, they are in accordance with green chemistry precepts. Besides, ambient mass spectrometry represents a new trend in fast and rapid analyses, especially for qualitative and screening analysis. However, for complex matrix analyses, sample preparation is still a difficult step and the miniaturized sample preparation techniques show great potential for an improved and widespread use of ambient mass spectrometry techniques. . This review aims to contribute as an overview of current miniaturized sample preparation techniques and ambient mass spectrometry methods as different approaches for selective and sensitive analysis of residues in food samples. (C) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页数:17
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