NIRS Analysis of Ranitidine Hydrochloride Capsules
摘 要
应用化学计量学与近红外光谱方法相结合,分析了盐酸雷尼替丁胶囊。以交叉验证均方根误差(RMSECV)、预测均方根误差(RMSEP)和决定系数为评价指标,分别建立了上述药物的定性和定量分析的模型。在定性判别分析方面,当采用多元散射校正(MSC)和一阶导数法对NIRS谱图进行预处理,并确定样品判别模型的主成分数为6,波长范围在波数为9 090.92~4 008.81 cm-1之间时误判数为0;在定量分析方面,选定的建模条件为:光谱的预处理方法为一阶导数法,建模波段在9 090.92~4 008.81 cm-1波数之间,主因子数为5。对13批次样品进行验证,测定值与预测值的相对偏差在-4.20%~4.04%之间。
Abstract
NIRS with application of chemometric method was applied to the analysis of Ranitidine hydrochloride capsules. Taking data of root of mean square error of cross-validation (RMSECV), root of mean square error of prediction (RMSEP) and determination coefficient as evaluation targets, models for qualitative and quantitative analysis of Ranitide hydrochloride capsules were established. By applying the multi-scattering correction (MSC) and 1st order derivation to the pretreatment of NIR spectra of the drug capsules, taking the number of principal component as 6, and the range of wave number between 9 090.92 cm-1 and 4 008.81 cm-1, number of wrong judgement of zero was attained in qualitative classification. In respect to quantitative analysis, the model was established under the following conditions: ① 1st order derivation was used in pretreatment of NIR spectra; ② range of wavenumber between 9 090.92 cm-1 and 4 008.81 cm-1 was selected, and ③ number of principal component of 5 was taken. The model was verified by analysis of samples taken from 13 different batches. Values of relative deviation between the determined values and the predicted values were found in the range of -4.20%-4.04%.
中图分类号 O657.33 DOI 10.11973/lhjy-hx201604007
所属栏目 工作简报
基金项目 河南省科技发展计划(112102110034);郑州市科研 攻关项目(131PPTGG422-1)
收稿日期 2015/4/15
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备注李长滨(1983-),男,河南卫辉人,硕士研究生,主要 从事食品与药物分析研究。
引用该论文: LI Chang-bin,XIE Xin,LONG Jiao-yan,REN Cong,ZHUANG Jun-hui. NIRS Analysis of Ranitidine Hydrochloride Capsules[J]. Physical Testing and Chemical Analysis part B:Chemical Analysis, 2016, 52(4): 402~406
李长滨,谢 欣,龙娇妍,任 聪,庄军辉. 近红外光谱法分析盐酸雷尼替丁胶囊[J]. 理化检验-化学分册, 2016, 52(4): 402~406
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【3】朱自红,曹玉梅.复方雷尼替丁分散片中盐酸雷尼替丁含量测定研究[J].中国伤残医学, 2010,18(6):112-113.
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【7】褚小立,陆婉珍.近五年我国近红外光谱分析技术研究与应用进展[J].光谱学与光谱分析, 2014,34(10):2595-2605.
【8】姬玉梅.近红外光谱技术在小麦品质育种中的应用研究[J].湖北农业科学, 2012,51(10):2096-2097.
【9】ZHANG B, RONG Z Q, SHI Y, et al. Prediction of the amino acid composition in brown rice using different sample status by near-infrared reflectance spectroscopy[J]. Food Chemistry, 2011,127(1):275-281.
【10】CHOUDHARY R, MAHESH S, PALIWAL J, et al. Identification of wheat classes using wavelet features from near infrared hyperspectral images of bulk samples[J]. Biosystems Engineering, 2009,102(2):115-127.
【11】张锐,尹利辉,金少鸿.5种近红外光谱仪采集药品光谱的一致性检验[J].药物分析杂志, 2013,33(6):1067-1071.
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