首页|期刊导航|佛山科学技术学院学报(自然科学版)|基于拉曼光谱鉴别三种冰片的特征图谱

基于拉曼光谱鉴别三种冰片的特征图谱OA

Characteristic spectra for the identification of three types of Borneol based on Raman spectroscopy

中文摘要英文摘要

目的 三种冰片(天然冰片、合成冰片、艾片)的相似度极高,使用拉曼光谱建立快速鉴别三种冰片的特征图谱,丰富冰片化学成分研究资料,为冰片的质量控制提供依据.方法 采用性状鉴别、薄层鉴别、旋光度测定、气相色谱法及拉曼光谱对三种冰片进行鉴别.结果 天然冰片、合成冰片和艾片药材性状相似,形状、大小、色泽有细微差别;薄层色谱相似度高,旋光度差异大;气相色谱可据图谱计算组分含量鉴别三者,拉曼光谱法可见有独特"指纹"图谱.结论 拉曼光谱可快速无损鉴别天然冰片、合成冰片和艾片,与其他方法检验结果一致,可为冰片质量控制及合理应用提供参考依据.

Objective Due to the extremely high similarity among the three types of borneol(Borneolum,Borneolum syntheticum,and l-Borneolum),Raman spectroscopy is used to establish the characteristic spectra for the rapid analysis of these three types of borneol,enriching the research data on the chemical components of borneol and providing a basis for the quality control of borneol.Methods Macroscopic identification,thin-layer chromatography(TLC)identification,specific rotation measurement,gas chromatography(GC),and Raman spectroscopy were used to identify the three types of borneol.Results The macroscopic characteristics of Borneolum,Borneolum syntheticum,and l-Borneolum are similar,with slight differences in shape,size,and color;their thin-layer chromatography shows high similarity,while significant differences were observed in in optical rotation;gas chromatography can identify the three based on the calculation of component contents from the chromatograms,and each has a unique Raman spectral"fingerprint"pattern.Conclusion Raman spectroscopy can quickly and non-destructively identify Borneolum,Borneolum syntheticum,and l-Borneolum,which is consistent with the test results of other methods.This method can provide a reference basis for their quality control and rational application.

谢倩;练卓;朱成义;刘明香;桂怡玲;马荣

佛山大学 医学部,广东 佛山 528225佛山大学 医学部,广东 佛山 528225佛山大学 医学部,广东 佛山 528225佛山大学 医学部,广东 佛山 528225佛山大学 医学部,广东 佛山 528225佛山大学 医学部,广东 佛山 528225

医药卫生

天然冰片合成冰片艾片拉曼光谱性状鉴别

BorneolumBorneolum syntheticuml-BorneolumRaman spectroscopymorphological identification

《佛山科学技术学院学报(自然科学版)》 2026 (3)

65-70,6

广东省基础与应用基础研究基金项目-粤佛联合基金(2023A1515110768)广东省高校科研项目(2024KQNCX147)佛山市科学技术局项目(2320001007331)

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