| 基于近红外光谱的淫羊藿定性鉴别及定量检测 |
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| 引用本文： | 范茹军,秦晓晔,宋岩,陶贵斌.基于近红外光谱的淫羊藿定性鉴别及定量检测[J].中国实验方剂学杂志,2010,16(13):85-89. |
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| 作者姓名： | 范茹军 秦晓晔 宋岩 陶贵斌 |
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| 作者单位： | 1. 吉林大学白求恩制药厂,长春,130012
2. 长春中医药大学中医药与生物工程研发中心,长春,130021 |
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| 摘 要： | 目的: 对淫羊藿进行产地的定性鉴别和主成分的定量检测。 方法: 对9个不同产地的样品分别对其采用矢量归一化、一阶导数、一阶导数加上矢量归一化的预处理方法进行定性检测;通过高效液相色谱法得到淫羊藿主成分的含量,并将其与对应的近红外漫反射光谱相对应,利用多元散射校正方法进行处理,建立偏最小二乘定量校正模型。 结果: 采用矢量归一化的预处理方法所得的定性模型效果最好,聚类结果令人满意,误分率为0,可将不同产地淫羊藿样品进行定性鉴别;偏最小二乘法所得到的预测集样本的标准偏差为0.020 6,建立的模型预测精度非常高,预测效果良好。 结论: 所建立的方法操作简单,测定速度快,费用低,无需进行复杂的前处理,可直接对大量未知样品进行测定,为近红外光谱技术应用于药物检测与分析提供了有效的方法和依据。
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| 关 键 词： | 淫羊藿 近红外光谱 化学计量学 偏最小二乘 定性鉴别 定量检测 |
| 收稿时间： | 2010/6/22 0:00:00 |
Qualitative Identification and Quantitative Detection of Epimedy Based on Near Infrared Spectroscopy |
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| FAN Ru-jun,QIN Xiao-ye,SONG Yan and TAO Gui-bin.Qualitative Identification and Quantitative Detection of Epimedy Based on Near Infrared Spectroscopy[J].China Journal of Experimental Traditional Medical Formulae,2010,16(13):85-89. |
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| Authors: | FAN Ru-jun QIN Xiao-ye SONG Yan and TAO Gui-bin |
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| Affiliation: | Pharmaceutical Factory, Normal Bethune University of Medical Science, Changchun 130012, China;Development Center for Chinese Medicine and Bioengineering, Changchun University of Traditional Chinese Medicine, Changchun 130021, China;Development Center for Chinese Medicine and Bioengineering, Changchun University of Traditional Chinese Medicine, Changchun 130021, China;Development Center for Chinese Medicine and Bioengineering, Changchun University of Traditional Chinese Medicine, Changchun 130021, China |
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| Abstract: | Objective: Near infrared (NIR) spectroscopy and chemometrics were used to identify the origins of Aceranthus sagittatus samples and to quantitatively analyze their active ingredients. Method: Nine different samples collected from different areas were analyzed, using vector normalization and/or first-order derivative processing methods. The active ingredients of these Aceranthus sagittatus samples were determined using HPLC method, and then they were used as the training data to generate the NIR quantitative analysis model using partial least square (PLS) method. Result: The results suggest that the vector normalization data processing gave us better qualitative identification model, the cluster analysis gave us satisfactory results. The classification error rate was 0. It can effectively identify the different origins of the samples thus this resulted qualitative analysis model can be used to quickly identify the origin of unknown samples. The PLS method indicated that the standard deviation of the prediction was 0.020 6, which means that it has very good accuracy of prediction. Conclusion: This analysis method is fast, simple and low-cost, which provides us a novel way for the qualitative identification of herbal medicine. |
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| Keywords: | epimedy near infrared spectroscopy chemometrics partial least square qualitative identification quantitative detection |
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