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Untargeted GC-MS and FT-NIR study of the effect of 14 processing methods on the volatile components of Polygonatum kingianum

文献类型: 外文期刊

作者: Xu, Yulin 1 ; Yang, Meiquan 1 ; Yang, Tianmei 1 ; Yang, Weize 1 ; Wang, Yuanzhong 1 ; Zhang, Jinyu 1 ;

作者机构: 1.Yunnan Acad Agr Sci, Med Plants Res Inst, Kunming, Peoples R China

2.Yunnan Univ, Sch Agr, Kunming, Peoples R China

关键词: Polygonatum kingianum; processing methods; untargeted GC-MS; FT-NIR; volatile components

期刊名称:FRONTIERS IN PLANT SCIENCE ( 影响因子:5.6; 五年影响因子:6.8 )

ISSN: 1664-462X

年卷期: 2023 年 14 卷

页码:

收录情况: SCI

摘要: IntroductionPolygonatum kingianum is a traditional medicinal plant, and processing has significantly impacts its quality. MethodsTherefore, untargeted gas chromatography-mass spectrometry (GC-MS) and Fourier transform-near-infrared spectroscopy (FT-NIR) were used to analyze the 14 processing methods commonly used in the Chinese market.It is dedicated to analyzing the causes of major volatile metabolite changes and identifying signature volatile components for each processing method. ResultsThe untargeted GC-MS technique identified a total of 333 metabolites. The relative content accounted for sugars (43%), acids (20%), amino acids (18%), nucleotides (6%), and esters (3%). The multiple steaming and roasting samples contained more sugars, nucleotides, esters and flavonoids but fewer amino acids. The sugars are predominantly monosaccharides or small molecular sugars, mainly due to polysaccharides depolymerization. The heat treatment reduces the amino acid content significantly, and the multiple steaming and roasting methods are not conducive to accumulating amino acids. The multiple steaming and roasting samples showed significant differences, as seen from principal component analysis (PCA) and hierarchical cluster analysis (HCA) based on GC-MS and FT-NIR. The partial least squares discriminant analysis (PLS-DA) based on FT-NIR can achieve 96.43% identification rate for the processed samples. DiscussionThis study can provide some references and options for consumers, producers, and researchers.

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