摘要
目的建立快速评价不同产地何首乌的方法。方法运用化学计量预处理方法处理4个产地何首乌样品的红外光谱,分析各产地样本的平均光谱,建立主成分分析鉴别和SIMCA预测模型。结果 ①何首乌含有蒽醌类、二苯乙烯类、磷脂类、多糖和苷类等化学成分。②主成分分析模型能基本鉴别不同产地何首乌。③不同产地何首乌的差异主要体现在芳香族化合物、草酸钙、磷脂、糖蛋白、多糖和苷类共6种化学成分上。④SIMCA模型预测未知样品的准确率达到100%。结论 红外光谱结合化学计量学是一种快速、无损地评价何首乌的有效方法。
Objective To develop a rapid assessment method of Polygonum multiflorum based on different origins.Methods The infrared spectra of Polygonum multiflorum from four different region were preprocessed by chemometric preprocessing methods,and the average spectra were analyzed,then principal component analysis(PCA) model and SIMCA model were constructed to distinguish and predict samples.Results(1) The anthraquinones,stilbenes,phospholipids,polysaccharides and glycosides were contained in Polygonum multiflorum.(2) The PCA model was basically able to identify the Polygonum multiflorum samples from different origins.(3) The differences between Polygonum multiflorum samples mostly depended on the contents of aromatic compounds,calcium oxalate,phospholipids,glycoprotein,polysaccharides and glycosides.(4) According to the SIMCA model,the recognition rate of blind samples was up to 100%.Conclusion Combined with chemometrics,infrared spectroscopy provides an effective way to assess Polygonum multiflorum rapidly and undamagedly.
出处
《时珍国医国药》
CAS
CSCD
北大核心
2011年第8期1835-1837,共3页
Lishizhen Medicine and Materia Medica Research
基金
国家自然科学基金(No.31060128)
广西壮族自治区科学研究与技术开发计划项目(No.0992003A-20)
广西研究生教育创新项目(No.2010106020702M44)
关键词
红外光谱
何首乌
主成分分析
载荷因子分析
SIMCA
Infrared spectra
Polygonum multiflorum
Principal component analysis
Loading factor analysis
SIMCA