Identification of Radix Bupleuri From Different Geographic Origins Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry and Support Vector Machine Algorithm

支持向量机 规范化(社会学) 主成分分析 计算机科学 人工智能 欧几里德距离 模式识别(心理学) 质谱法 鉴定(生物学) 数据挖掘 算法 色谱法 化学 生物 人类学 植物 社会学
作者
Zhengyong Zhang,Yaju Zhao,Feiyue Guo,Haiyan Wang
出处
期刊:Journal of AOAC International [Oxford University Press]
卷期号:106 (6): 1682-1688 被引量:4
标识
DOI:10.1093/jaoacint/qsad060
摘要

Abstract Background The geographic origin of Radix bupleuri is an important factor affecting its efficacy, which needs to be effectively identified. Objective The goal is to enrich and develop the intelligent recognition technology applicable to the identification of the origin of traditional Chinese medicine. Method This article establishes an identification method of Radix bupleuri geographic origin based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and support vector machine (SVM) algorithm. The Euclidean distance method is used to measure the similarity between Radix bupleuri samples, and the quality control chart method is applied to quantitatively describe their quality fluctuation. Results It is found that the samples from the same origin are relatively similar and mainly fluctuate within the control limit, but the fluctuation range is large, and it is impossible to distinguish the samples from different origins. The SVM algorithm can effectively eliminate the impact of intensity fluctuations and huge data dimensions by combining the normalization of MALDI-TOF MS data and the dimensionality reduction of principal components, and finally achieve efficient identification of the origin of Radix bupleuri, with an average recognition rate of 98.5%. Conclusions This newly established approach for identification of the geographic origin of Radix bupleuri has been realized, and it has the advantages of objectivity and intelligence, which can be used as a reference for other medical and food-related research. Highlights A new intelligent recognition method of medicinal material origin based on MALDI-TOF MS and SVM has been established.
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
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
liyang发布了新的文献求助10
刚刚
talksilence完成签到,获得积分10
1秒前
2秒前
3秒前
4秒前
我不爱池鱼应助加菲丰丰采纳,获得10
4秒前
阔达故事完成签到,获得积分10
5秒前
烟花应助如山如河采纳,获得50
6秒前
淡然觅荷完成签到 ,获得积分10
7秒前
香蕉海之发布了新的文献求助10
7秒前
11完成签到,获得积分10
7秒前
8秒前
科研小白完成签到,获得积分20
9秒前
wallonce完成签到,获得积分10
10秒前
吃算不算超能力关注了科研通微信公众号
11秒前
11秒前
12秒前
zengliangke发布了新的文献求助50
12秒前
12秒前
13秒前
14秒前
虚幻的谷秋完成签到,获得积分20
15秒前
十字丝完成签到,获得积分10
15秒前
17秒前
17秒前
17秒前
桐桐应助zengwr采纳,获得10
17秒前
ZXD1989完成签到 ,获得积分10
18秒前
wjj完成签到,获得积分10
18秒前
比大家完成签到 ,获得积分10
19秒前
桐桐应助田1986采纳,获得10
19秒前
香蕉海之完成签到,获得积分10
19秒前
wallonce发布了新的文献求助10
19秒前
寻寻~发布了新的文献求助10
19秒前
冯藏花发布了新的文献求助10
20秒前
我是老大应助蓝梦一刀采纳,获得10
21秒前
21秒前
情怀应助miku1采纳,获得10
21秒前
田様应助霜之哀伤采纳,获得10
21秒前
期望应助WFFu采纳,获得30
23秒前
高分求助中
Licensing Deals in Pharmaceuticals 2019-2024 3000
Effect of reactor temperature on FCC yield 2000
Very-high-order BVD Schemes Using β-variable THINC Method 1020
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 800
Near Infrared Spectra of Origin-defined and Real-world Textiles (NIR-SORT): A spectroscopic and materials characterization dataset for known provenance and post-consumer fabrics 610
Mission to Mao: Us Intelligence and the Chinese Communists in World War II 600
MATLAB在传热学例题中的应用 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3304191
求助须知:如何正确求助?哪些是违规求助? 2938204
关于积分的说明 8487761
捐赠科研通 2612613
什么是DOI,文献DOI怎么找? 1426765
科研通“疑难数据库(出版商)”最低求助积分说明 662825
邀请新用户注册赠送积分活动 647344