| 近红外漫反射光谱法非破坏分析颠茄粉末药品质量 |
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| 引用本文： | 李岩梅,国警月,陈庆先,孙立丽,李光和,王友兵,任玉林.近红外漫反射光谱法非破坏分析颠茄粉末药品质量[J].福建农林大学学报(哲学社会科学版),2009(2). |
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| 作者姓名： | 李岩梅 国警月 陈庆先 孙立丽 李光和 王友兵 任玉林 |
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| 作者单位： | 吉林省大安市食品药品监督局稽察分局;吉林大学化学学院;吉林省白城市食品药品检验所;吉林省白城医学高等专科学校; |
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| 基金项目： | 吉林省科技厅项目基金(批准号:2005123) |
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| 摘 要： | 本文应用偏最小二乘法(PLS)同近红外漫反射光谱法结合,对颠茄粉末药品进行无损非破坏定量分析,建立了最佳的数学校正模型。讨论了光谱的预处理方法和主成分数对PLS定量预测能力的影响,并对预测集样品含量进行预测,得到了较为满意的结果。
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| 关 键 词： | 长波近红外光谱法 偏最小二乘法（PLS） 非破坏定量分析 颠茄粉末药品 |
Non-destructive Analysis of Belladonna Powder Lsamples by Use of PLS and Long-wavelength NIR Spectroscopy |
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| Yanmei Li,Jingyue Guo,Qingxian Chen,Lili Sun,Guanghe Li,Youbing Wang,Yulin Ren .Branch Bureau of Examination & Leechdom Hyhiene Supervision , Administration Bureau in Jilin Province Da'an City,Daan,..College of Chemistry,Jilin University,Changchun,..Baicheng Food , Leechdom Inspection Office..Non-destructive Analysis of Belladonna Powder Lsamples by Use of PLS and Long-wavelength NIR Spectroscopy[J].Journal of Fujian Agriculture and Forestry University,2009(2). |
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| Authors: | Yanmei Li Jingyue Guo Qingxian Chen Lili Sun Guanghe Li Youbing Wang Yulin Ren Branch Bureau of Examination & Leechdom Hyhiene Supervision Administration Bureau in Jilin Province Da'an City Daan College of Chemistry Jilin University Changchun Baicheng Food Leechdom Inspection Office |
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| Institution: | Yanmei Li1,Jingyue Guo2,Qingxian Chen3,Lili Sun3,Guanghe Li3,Youbing Wang4,Yulin Ren2 1.Branch Bureau of Examination & Leechdom Hyhiene Supervision , Administration Bureau in Jilin Province Da'an City,Daan,130061.2.College of Chemistry,Jilin University,Changchun,130023.3.Baicheng Food , Leechdom Inspection Office.4.The Medical College of Beicheng City,Jinlin Province |
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| Abstract: | In this article, PLS combined with near-infrared spectroscopy method was used for non-destructive quantitative analysis of Belladonna powder samples, and the best mathematic calibration models were built simultaneously.Furthermore, the PLS models that established with different pretreated spectra were designed and compared, and the affection on the prediction ability of PLS model that caused by the numbers of principal component were discussed.In this model, the prediction set was predicted, and the results... |
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