基于近红外光谱法建立的模型预测维生素B_(6)的含量  

Predicition of Vitamin B_(6) with Models Based on Near Infrared Spectrometry

作　　者：陈梓云[1] 彭梦侠[1] CHEN Ziyun;PENG Mengxia(School of Chemistry and Environment,Jiaying University,Meizhou 514015,China)

机构地区：[1]嘉应学院化学与环境学院,梅州514015

出　　处：《理化检验（化学分册）》2022年第1期13-18,共6页Physical Testing and Chemical Analysis(Part B:Chemical Analysis)

摘　　要：采用近红外光谱法结合偏最小二乘法(PLS),分别建立了药物复合维生素B片和保健品B族维生素片中维生素B_(6)的定量分析模型。取药物复合维生素B片或保健品B族维生素片6~12片,研磨,以转速4000r·min^(-1)振荡1min,将样品粉末分别装入3个样品杯中,采用积分球漫反射分析模块采集其近红外谱图,每个样品采集5次,得到15张近红外光谱图。以高效液相色谱法为参比方法,以不同类型维生素B片为建模的训练集样品,每个样品中,任取12张光谱图作为训练集样本,余下3张光谱图作为内部验证集样本,采用TQ Analyst 9.0软件中的PLS,用一阶导数光谱数据形式,选择3个波段(药物复合维生素B片4700.46~5125.86cm^(-1),5444.60~5708.26cm^(-1),5754.69~6159.52cm^(-1);保健品B族维生素B片4133.67~5512.28cm^(-1),5944.17~6495.08cm^(-1),8105.85~9005.94cm^(-1))同时进行建模,使用诺里斯导数滤噪,节段长度为5,段间间隙为5(药物复合维生素B片)或6(保健品B族维生素B片)。结果显示:药物复合维生素B片定量分析模型(模型2)的校正均值方差(RMSEC)为0.0030,校正相关系数(R_(c))为0.9947,预测均值方差(RMSEP)为0.0029,预测相关系数(R_(p))为0.9954,交叉验证均值方差(RMSECV)为0.0052,交叉验证相关系数(R_(cv))为0.9941,性能指数为92.8;保健品B族维生素B片定量分析模型(模型3)的RMSEC为0.0314,R_(c)为0.9987,RMSEP为0.0358,R_(p)为0.9987,RMSECV为0.0388,R_(cv)为0.9981,性能指数为93.5。利用模型2预测药物复合维生素B片中维生素B_(6)的含量,预测值的绝对误差为-0.0044%~0.0080%,相对误差为-1.7%~3.3%;利用模型3预测保健品B族维生素片中维生素B_(6)的含量,预测值的绝对误差为-0.0071%~0.0497%,相对误差为-1.9%~5.0%。The models for quantitative analysis of vitamin B_(6)in compound vitamin B tablets for drug and vitamin B complex tablets for health products was established respectively by near infrared spectrometry combined with partial least square(PLS)method.6-12tablets of compound vitamin B tablets or vitamin B complex tablets were ground and oscillated at 4000r·min^(-1) for 1min,and the sample powder was respectively put into 3sample cups.The near infrared spectra were collected by integrating sphere diffuse reflection analysis module.Each sample was collected 5times,and 15near infrared spectra were obtained.High performance liquid chromatography was used as the reference method,and different types of vitamin B tablets were used as modeling samples of the training set.In each sample,12spectra were used as the training set samples,and the remaining 3spectra were used as the internal verification set samples.PLS method in TQ Analyst 9.0was adopted,and the spectral data of the first derivative was used.3band ranges were selected for modeling(ranges of compound vitamin B tablets of 4700.46-5125.86cm^(-1),5444.60-5708.26cm^(-1),5754.69-6159.52cm_(-1);ranges of vitamin B complex tablets of 4133.67-5512.28cm^(-1),5944.17-6495.08cm^(-1),8105.85-9005.94cm^(-1)).Norris derivative noise filter was used.The length of the segment was 5,and the interval between segments was 5(compound vitamin B tablets)or 6(vitamin B complex tablets).As shown by the results,quantitative analysis model of compound vitamin B tablets(model 2)of the corrected mean variance(RMSEC)was 0.0030,with the corrected correlation coefficient(R_(c))of 0.9947,the predicted mean variance(RMSEP)of 0.0029,the predicted correlation coefficient(R_(p))of 0.9954,the cross validation mean variance(RMSECV)of 0.0052,the cross validation correlation coefficient(R_(cv))of 0.9941 and the performance index of 92.8.Quantitative analysis model of vitamin B complex tablets(model 3)of RMSEC was 0.0314,with R_(c) of 0.9987,RMSEP of 0.0358,R_(p) of 0.9987,RMSECV of 0.0388,R_(cv) of 0.998

关 键 词：近红外光谱法 偏最小二乘法 维生素B_(6) 复合维生素B片 B族维生素片 预测 

分 类 号：O657.33[理学—分析化学]