文献类型：期刊文献

英文题名：Characterization of Radix Angelicae sinensis by Fluorescence and Near-Infrared Spectroscopies

作者：Wang, Zihan[1,2];Li, Boyan[1,2];Hu, Yun[3];Zhang, Jin[1,2];Zhang, Junhan[4];Pan, Xinbo[4];Wang, Yali[4]

第一作者：Wang, Zihan

通信作者：Li, BY[1];Li, BY[2]

机构：[1]Guizhou Med Univ, Sch Publ Hlth, Key Lab Endem & Ethn Dis, Minist Educ, Guiyang, Peoples R China;[2]Guizhou Med Univ, Key Lab Med Mol Biol Guizhou Prov, Guiyang, Peoples R China;[3]Guizhou Ind Co Ltd, Technol Ctr China Tobacco, Guiyang, Peoples R China;[4]Gansu Univ Chinese Med, Sch Pharm, Lanzhou, Peoples R China

第一机构：Guizhou Med Univ, Sch Publ Hlth, Key Lab Endem & Ethn Dis, Minist Educ, Guiyang, Peoples R China

通信机构：[1]corresponding author), Guizhou Med Univ, Sch Publ Hlth, Key Lab Endem & Ethn Dis, Minist Educ, Guiyang, Peoples R China;[2]corresponding author), Guizhou Med Univ, Key Lab Med Mol Biol Guizhou Prov, Guiyang, Peoples R China.

年份：2024

卷号：57

期号：10

起止页码：1563

外文期刊名：ANALYTICAL LETTERS

收录：;Scopus(收录号：2-s2.0-85171591306);WOS:【SCI-EXPANDED(收录号:WOS:001070478500001)】；

基金：This work was supported by the National Natural Science Foundation of China (Grants 21864008, 82060712 and 22004022), the Guizhou Provincial Science and Technology Projects (Grants [2018]1130 and ZK[2021]045), and the Key R&D Program of Science and Technology Department of Gansu Province, China (Grant 20YF8NA067)

语种：英文

外文关键词：Radix Angelicae sinensis; compositional fingerprint; fluorescence; multiplicative; scatter correction; multivariate statistical; analysis; near-infrared (NIR); spectroscopy; principal; discriminant variate

摘要：Angelica sinensis (Oliv.) diels is a perennial herbaceous plant. Its dried root, referred to as radix Angelicae sinensis (RAS), has been used for edible and medicinal purposes. This study is dedicated to spectroscopic characterization and quality detection of RAS powder material or aqueous solution using fluorescence excitation-emission matrix and near-infrared (NIR) spectroscopies. It is the first time that the fluorescence combined with net analyte signal-classical least-squares was able to accurately determine two active substances in 131 RAS batches from five geographical origins in Gansu, China. The concentrations of Z-ligustilide and L-tryptophan were 1.17 +/- 0.43 mg g(-1) and 0.59 +/- 0.19 mg g(-1), respectively. A satisfactory NIR-principal discriminant variate model was achieved, enabling the RAS batches to be discriminated by the location. The correct discrimination rates reached 100% for calibration and 87.50% for validation. The work provides an alternative and holistic strategy for reliable fingerprint authentication of RAS materials and helps promote its utility.