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近红外光谱技术快速测定夏枯草中水溶性浸出物的含量
引用本文:卢慧娟,贾灿潮,曹庆玺,姬生国.近红外光谱技术快速测定夏枯草中水溶性浸出物的含量[J].中国实验方剂学杂志,2016,22(2):43-46.
作者姓名:卢慧娟  贾灿潮  曹庆玺  姬生国
作者单位:广东药学院中药学院, 广州 510006,广东药学院中药学院, 广州 510006,广东药学院中药学院, 广州 510006,广东药学院中药学院, 广州 510006
基金项目:广东省科技计划项目(2009B030801044)
摘    要:目的:建立夏枯草中水溶性浸出物含量的近红外光谱定量分析模型。方法:采用热浸法测定180批夏枯草中浸出物的含量;采集样品的近红外光谱数据,利用TQ8.0软件建立浸出物的定量分析模型。结果:所建立的近红外光谱定量分析模型的校正集内部交叉验证相关系数(R~2),校正均方差(RMSEC)和预测均方差(RMSEP)分别为0.981 4,0.347,0.378,验证集NIR预测值与热浸法参考值的t检验值为0.653,双侧P=0.5170.05,说明差异无统计学意义。结论:建立的近红外光谱法测定夏枯草中浸出物的含量测定方法准确、可靠,可用于夏枯草中浸出物的含量测定。

关 键 词:夏枯草  水溶性浸出物  近红外光谱法
收稿时间:2015/3/23 0:00:00

Content Determination of Water-soluble Extract in Prunellae Spica by Near-infrared Spectroscopy
LU Hui-juan,JIA Can-chao,CAO Qing-xi and JI Sheng-guo.Content Determination of Water-soluble Extract in Prunellae Spica by Near-infrared Spectroscopy[J].China Journal of Experimental Traditional Medical Formulae,2016,22(2):43-46.
Authors:LU Hui-juan  JIA Can-chao  CAO Qing-xi and JI Sheng-guo
Institution:School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou 510006, China,School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou 510006, China,School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou 510006, China and School of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou 510006, China
Abstract:Objective:To develop near-infrared spectroscopy (NIR) quantitative analysis model for water-soluble extract in Prunellae Spica. Method:The extract content of Prunellae Spica in 180 batches was determined by hot dipping method. NIRS spectrograms were measured, and the quantitative analysis model for extract was established by TQ8.0 software. Result:The correlation cross-validation coefficients (R2), root-mean-square error of calibration (RMSEC) and root-mean-square error of prediction (RMSEP) of the quantitative calibration model for water extract were 0.9814, 0.347 and 0.378 respectively, and the test value of NIR prediction values and the reference values of the validation set was 0.653, bilateral P=0.517>0.05, implying the difference was not significant. Conclusion:The method is steady, accurate and reliable to predict the water extracts content of Prunellae Spica by NIR.
Keywords:Prunellae Spica  water extracts  NIR spectroscopy
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