文献类型：期刊文献

英文题名：Comparative Study on Morphological Features and Chemical Components of Wild and Cultivated Angelica sinensis Based on Bionic Technologies and Chemometrics

作者：Chen, Yiyang[1];Zhang, Jialing[1];Liu, Juanjuan[1];Hu, Huifang[1];Wang, Liangcai[1];Jin, Ling[1]

第一作者：陈云逸

通信作者：Jin, L[1]

机构：[1]Gansu Univ Chinese Med, Coll Pharm, Lanzhou 730000, Gansu, Peoples R China

第一机构：甘肃中医药大学药学院（西北中藏药协同创新中心办公室）

通信机构：[1]corresponding author), Gansu Univ Chinese Med, Coll Pharm, Lanzhou 730000, Gansu, Peoples R China.|[1073501e14fb35863569f]甘肃中医药大学药学院（西北中藏药协同创新中心办公室）;[10735]甘肃中医药大学;

年份：2024

卷号：9

期号：40

起止页码：41408

外文期刊名：ACS OMEGA

收录：;WOS:【SCI-EXPANDED(收录号:WOS:001324308600001)】；

基金：This study was supported by the Gansu Provincial Science and Technology Major Project (23ZDFA013-1), Strategic Research and Consulting Project of the Chinese Academy of Engineering (GS2021ZDA06-2), Gansu Provincial Department of Education "Double First-Class" Key Scientific Research Project (GSSYLXM-05), Gansu Provincial University Youth Doctoral Fund funded project (2023QB-094), and Gansu Provincial Science and Technology Project (20JR5RA182).

语种：英文

摘要：As a traditional Chinese medicine, Angelica sinensis is primarily sourced from cultivated plants due to the significant decline in wild resources. This shift raises concerns about potential differences in efficacy resulting from variations in morphological features and chemical composition between wild (WA) and cultivated (CA) A. sinensis. In this study, a suite of advanced analytical techniques including electronic nose, electronic tongue, and electronic eye, alongside headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry and high-performance liquid chromatography, was applied to compare the morphological features and chemical components of WA and CA. Furthermore, principal component analysis and partial least-squares discriminant were employed for data analysis. The morphological features and chemical components of WA and CA were compared and analyzed. The results showed that three bionic technologies can distinguish WA from CA well and that fusion signals can distinguish better. There were differences between WA and CA in odor, taste, color, and content of the indicator components. There were correlations between the morphological features and the content of indicator components.