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

Yulin Xu; Meiquan Yang; Tianmei Yang; Weize Yang; Yuanzhong Wang; Jinyu Zhang

doi:10.3389/fpls.2023.1140691

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

Front Plant Sci. 2023 May 8:14:1140691. doi: 10.3389/fpls.2023.1140691. eCollection 2023.

Authors

Yulin Xu^{1

2}, Meiquan Yang¹, Tianmei Yang¹, Weize Yang¹, Yuanzhong Wang¹, Jinyu Zhang¹

Affiliations

¹ Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, China.
² School of Agriculture, Yunnan University, Kunming, China.

Abstract

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.

Keywords: FT-NIR; Polygonatum kingianum; processing methods; untargeted GC-MS; volatile components.

Grants and funding

This work was supported by Medical Services and Security Capacity Enhancement Subsidy Funds-Chinese Medicine Business Heritage and Development Part, (grant number 10000015Z155080000004); Yunnan Provincial Department of Science and Technology Rural Revitalisation Industry Key Technology Integration Demonstration Project, Lushui "Orange-Medicine" Eco-efficient Production Technology Research and Demonstration (grant number 202204BP090024); Yunnan Provincial Department of Science and Technology Rural Revitalisation Science and Technology Special Project, Yunnan Province Fugong County Grass and Fruit Industry Science and Technology Special Mission (grant number 202104BI090011).