Xu Yulin, Yang Meiquan, Yang Tianmei, Yang Weize, Wang Yuanzhong, Zhang Jinyu
Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, China.
School of Agriculture, Yunnan University, Kunming, China.
Front Plant Sci. 2023 May 8;14:1140691. doi: 10.3389/fpls.2023.1140691. eCollection 2023.
is a traditional medicinal plant, and processing has significantly impacts its quality.
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.
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.
This study can provide some references and options for consumers, producers, and researchers.
是一种传统药用植物，加工过程对其质量有显著影响。
因此，采用非靶向气相色谱-质谱联用（GC-MS）和傅里叶变换近红外光谱（FT-NIR）对中国市场常用的14种加工方法进行分析。致力于分析主要挥发性代谢物变化的原因，并识别每种加工方法的标志性挥发性成分。
非靶向GC-MS技术共鉴定出333种代谢物。相对含量占糖类（43%）、酸类（20%）、氨基酸类（18%）、核苷酸类（6%）和酯类（3%）。多次蒸制和烘焙的样品含有较多的糖类、核苷酸、酯类和黄酮类，但氨基酸较少。糖类主要是单糖或小分子糖，主要是由于多糖解聚。热处理显著降低了氨基酸含量，多次蒸制和烘焙方法不利于氨基酸的积累。基于GC-MS和FT-NIR的主成分分析（PCA）和层次聚类分析（HCA）表明，多次蒸制和烘焙的样品存在显著差异。基于FT-NIR的偏最小二乘判别分析（PLS-DA）对加工样品的识别率可达96.43%。
本研究可为消费者、生产者和研究人员提供一些参考和选择。
