Rapid Authentication of Medicinal Plants: Exploring the Applicability of Mass Spectrometry Imaging for Species Discrimination

化学 质谱成像 植物化学 质谱法 认证(法律) 再现性 分析化学(期刊) 色谱法 考古 地理 生物化学
作者
Lieyan Huang,Lixing Nie,Xianrui Wang,Yanpei Wu,Jing Dong,Shuai Kang,Feng Wei,Shuang‐Cheng Ma
出处
期刊:Journal of the American Society for Mass Spectrometry [American Chemical Society]
卷期号:35 (9): 2187-2196 被引量:4
标识
DOI:10.1021/jasms.4c00214
摘要

In the past few years, mass spectrometry imaging (MSI) has brought many new inspirations to plant research. However, current MSI experiments usually include only a single batch of samples, casting doubts on the reproducibility of phytochemical distribution across different batches. Consequently, MSI has seldom been applied to conduct species discrimination. In this experiment, MSI was employed to discriminate between two taxonomically similar plants, Scutellaria baicalensis Georgi and Scutellaria rehderiana Diels. A new concept termed a "spatial marker" was proposed in this article, which referred to the phytochemical marker that presented both intraspecies similarity and interspecies dissimilarity. Multiple batches of S. baicalensis and S. rehderiana were analyzed using MSI, proving that the authentication protocol using spatial markers was reliable and reproducible. The observed spatial markers were further identified using on-tissue tandem mass spectrometry and liquid chromatography coupled with mass spectrometry. Additionally, the spectral data collected from MSI were utilized to set up algorithm models for species discrimination. External validation confirmed that the established random forest model was extrapolated well to unknown samples. Overall, this investigation successfully explored the analytical applicability of MSI, facilitating rapid authentication of medicinal plants.
最长约 10秒,即可获得该文献文件

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
NexusExplorer的应助被科研通管家采纳,获得10
刚刚
刚刚
Criminology34的应助被科研通管家采纳,获得10
刚刚
852的应助被科研通管家采纳,获得10
刚刚
bkagyin的应助被科研通管家采纳,获得10
1秒前
SciGPT的应助被科研通管家采纳,获得10
1秒前
今后的应助被科研通管家采纳,获得10
1秒前
领导范儿的应助被科研通管家采纳,获得10
1秒前
汉堡包的应助被科研通管家采纳,获得10
1秒前
1秒前
1秒前
Lucas的应助被科研通管家采纳,获得10
1秒前
沉静依风发布了新的文献求助10
1秒前
在水一方的应助被科研通管家采纳,获得10
2秒前
领导范儿的应助被科研通管家采纳,获得10
2秒前
呼呼夫人发布了新的文献求助10
2秒前
5秒前
8秒前
情怀的应助被呆萌的源智采纳,获得10
8秒前
9秒前
无私的梦柏完成签到 ,获得积分10
9秒前
路人发布了新的文献求助10
9秒前
老的火龙果的应助被yyyyyy采纳,获得10
10秒前
每天每天完成签到,获得积分20
11秒前
SciGPT的应助被耍酷慕梅采纳,获得10
12秒前
嘻嘻嘻完成签到 ,获得积分10
14秒前
14秒前
15秒前
DW的应助被陈仲采纳,获得10
17秒前
biochen完成签到,获得积分10
18秒前
18秒前
18秒前
呼呼夫人发布了新的文献求助10
20秒前
完美世界的应助被每天每天采纳,获得10
22秒前
22秒前
彭于晏的应助被liugm采纳,获得10
23秒前
卢乃旋发布了新的文献求助10
25秒前
无花果的应助被深情的不斜采纳,获得30
25秒前
无敌阿东发布了新的文献求助10
25秒前
滴歪歪完成签到,获得积分10
26秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Rosenblum, Global Change Biology 800
自動車の空力技術 800
Organizational Behavior 510
Management and the Arts 510
Issues in Task-Based Language Teaching 500
Wafer Surface Defect 420
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7784662
求助须知:如何正确求助?哪些是违规求助? 9323973
关于积分的说明 20396272
捐赠科研通 7373384
什么是DOI,文献DOI怎么找? 3321113
关于科研通互助平台的介绍 2469029
邀请新用户注册赠送积分活动 2337386