单糖
化学
指纹(计算)
多糖
主成分分析
色谱法
质量评定
分析化学(期刊)
人工智能
生物化学
评价方法
计算机科学
工程类
可靠性工程
作者
Chanyi Li,Hong‐Yuan Chen,Wuping Liu,Wen Rui
标识
DOI:10.1016/j.ijbiomac.2018.11.037
摘要
It is a challenge to ascertain the quality of polysaccharides due to their complex chemical structure; therefore, multi-fingerprint profiling was used to investigate the quality of Astragalus polysaccharides (APS) harvested from Inner Mongolia (NM) and Gansu (GS) with the help of chemometric analysis. Additionally, FT-IR and 1H NMR were applied to characterize the chemical structure of the harvested APS. The spectral fingerprinting results indicated that APS had reduced similarity when they were from different origins. Further, PCA showed that NM and GS could be distinguished and that the main differences from the loading plots were in the absorption intensity of carbonyls and H1 signals of Galp and β-glucose. Moreover, UPLC/Q-TOF-MS fingerprints were established based on the monosaccharide composition of the APS. The concentration of monosaccharides and results of cluster analysis indicated that GlcA might be an indicator that can be used to distinguish NM and GS. Overall, this multiple fingerprint method was stable, comprehensive and valid for monitoring APS quality.
科研通智能强力驱动
Strongly Powered by AbleSci AI