Cargando…

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

INTRODUCTION: Polygonatum kingianum is a traditional medicinal plant, and processing has significantly impacts its quality. METHODS: Therefore, untargeted gas chromatography-mass spectrometry (GC-MS) and Fourier transform-near-infrared spectroscopy (FT-NIR) were used to analyze the 14 processing met...

Descripción completa

Detalles Bibliográficos
Autores principales: Xu, Yulin, Yang, Meiquan, Yang, Tianmei, Yang, Weize, Wang, Yuanzhong, Zhang, Jinyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10200983/
https://www.ncbi.nlm.nih.gov/pubmed/37223798
http://dx.doi.org/10.3389/fpls.2023.1140691
Descripción
Sumario:INTRODUCTION: Polygonatum kingianum is a traditional medicinal plant, and processing has significantly impacts its quality. METHODS: Therefore, 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. RESULTS: The 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. DISCUSSION: This study can provide some references and options for consumers, producers, and researchers.