Untargeted metabolomics coupled with chemometric analysis deducing robust markers for discrimination of processing procedures: Wine‐processed Angelica sinensis as a case study

当归 代谢组学 化学计量学 色谱法 化学 葡萄酒 食品科学 中医药 医学 病理 替代医学
作者
Haoran Yin,Hui Ni,Linlin Zhang,Wenyong Wu,Xingdong Wu,Zijia Zhang,Huali Long,Min Lei,Jinjun Hou,Wanying Wu
出处
期刊:Journal of Separation Science [Wiley]
卷期号:44 (22): 4092-4110 被引量:9
标识
DOI:10.1002/jssc.202100566
摘要

Wine-processed Angelica Sinensis is a widely used Chinese medicinal decoction piece in China. However, there are hardly any robust markers indicating the processing procedure of wine-processed Angelica Sinensis, including the amount of rice wine and processing degree. A strategy integrating untargeted metabolomics and chemometric analysis for deducing robust markers was provided and applied to the discrimination of processing procedure. First, 86 compounds were tentatively identified in wine-processed Angelica Sinensis by ultra-high-performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry. Second, 93 potential chemical markers were selected using multivariate analysis, among which nine robust chemical markers were selected by verification with commercial samples. Finally, the effects of processing temperature, time, and amount of rice wine on the three selected chemical markers were investigated through a rapid analytical method. It was demonstrated that both m/z 258.1097 and 238.1189 were positively correlated with the amount of rice wine and processing degree. In summary, this study introduced two candidate processing markers as robust markers for discriminating the processing procedures of wine-processed Angelica sinensis. It also proposed a strategy to provide the reference for the research of other decoction pieces.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
周涨杰完成签到 ,获得积分10
刚刚
XY发布了新的文献求助10
1秒前
lily完成签到,获得积分10
1秒前
2秒前
3秒前
遇疯儿完成签到,获得积分10
3秒前
4秒前
不搭发布了新的文献求助10
4秒前
4秒前
4秒前
三万五发布了新的文献求助10
5秒前
月yue发布了新的文献求助10
5秒前
111发布了新的文献求助10
5秒前
5秒前
蒲勇兵完成签到 ,获得积分10
6秒前
6秒前
曾志伟发布了新的文献求助30
8秒前
未完发布了新的文献求助10
8秒前
9秒前
9秒前
蒲勇兵关注了科研通微信公众号
9秒前
9秒前
鸡鱼蚝发布了新的文献求助10
10秒前
思源应助辛勤凝蕊采纳,获得10
10秒前
彭于晏应助catherine采纳,获得10
10秒前
11秒前
12秒前
12秒前
石破茧完成签到,获得积分10
13秒前
当当发布了新的文献求助10
13秒前
平常乐安发布了新的文献求助10
13秒前
开心砖头发布了新的文献求助10
13秒前
NaudX发布了新的文献求助10
13秒前
酷炫忆秋完成签到,获得积分10
13秒前
hai完成签到,获得积分10
14秒前
lalll发布了新的文献求助30
14秒前
任性凡雁发布了新的文献求助10
14秒前
14秒前
hyhy完成签到,获得积分10
15秒前
打打应助掮客采纳,获得10
15秒前
高分求助中
Overcoming Stigma and Bias in Obesity Management 1200
Signals, Systems, and Signal Processing 610
Software that combines deep learning,3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging 500
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
Adhesion Science: Principles & Practice 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6492937
求助须知:如何正确求助?哪些是违规求助? 8290508
关于积分的说明 17691208
捐赠科研通 5585086
什么是DOI,文献DOI怎么找? 2915526
邀请新用户注册赠送积分活动 1892599
关于科研通互助平台的介绍 1750900