Preliminary construction of integral analysis for characteristic components in complex matrices by in-house fabricated solid-phase microextraction fibers combined with gas chromatography-mass spectrometry
Preliminary construction of integral analysis for characteristic components in complex matrices by in-house fabricated solid-phase microextraction fibers combined with gas chromatography-mass spectrometry
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DOI：
10.1016/j.chroma.2016.07.047
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发表时间：
2016-08-26
影响因子：
4.1
通讯作者：
Duan, Yixiang
中科院分区：
文献类型：
--
作者：
Tang, Zhentao;Hou, Wenqian;Duan, Yixiang
Integral analysis plays an important role in study and quality control of substances with complex matrices in our daily life. As the preliminary construction of integral analysis of substances with complex matrices, developing a relatively comprehensive and sensitive methodology might offer more informative and reliable characteristic components. Flavoring mixtures belonging to the representatives of substances with complex matrices have now been widely used in various fields. To better study and control the quality of flavoring mixtures as additives in food industry, an in-house fabricated solid-phase microextraction (SPME) fiber was prepared based on sol-gel technology in this work. The active organic component of the fiber coating was multi-walled carbon nanotubes (MWCNTs) functionalized with hydroxyl-terminated polydimethyldiphenylsiloxane, which integrate the non-polar and polar chains of both materials. In this way, more sensitive extraction capability for a wider range of compounds can be obtained in comparison with commercial SPME fibers. Preliminarily integral analysis of three similar types of samples were realized by the optimized SPME-GC-MS method. With the obtained GC-MS data, a valid and well-fit model was established by partial least square discriminant analysis (PLS-DA) for classification of these samples (R2X =0.661, R2Y = 0.996, Q2 = 0.986). The validity of the model (R2 = 0.266, Q2 = -0.465) has also approved the potential to predict the "belongingness" of new samples. With the PLS-DA and SPSS method, further screening out the markers among three similar batches of samples may be helpful for monitoring and controlling the quality of the flavoring mixtures as additives in food industry. Conversely, the reliability and effectiveness of the GC-MS data has verified the comprehensive and efficient extraction performance of the in-house fabricated fiber. (c) 2016 Elsevier B.V. All rights reserved.
