近红外光谱快速检测苏黄止咳胶囊中间体苏黄颗粒的水分含量  

Rapid detection of moisture content in intermediate Suhuang granules of Suhuang Zhike capsules by near infrared spectroscopy

作　　者：马盼盼 吴晨璐 张婉莹 张茳莹 王海霞 李正 赵静 MA Pan-pan;WU Chen-lu;ZHANG Wan-ying;ZHANG Jiang-ying;WANG Hai-xia;LI Zheng;ZHAO Jing(College of Pharmaceutical Enginerring of Traditional Chinese Medicine,Tianjin University of Traditional Chinese Medicine,Tianjin 301617;State Key Laboratory of Component Traditional Chinese Medicine,Tianjin 301617;Department of Geriatrics,the Fourth Affiliated Hospital of Tianjin University of Traditional Chinese Medicine,Tianjin 301617)

机构地区：[1]天津中医药大学中药制药工程学院,天津301617 [2]省部共建组分中药国家重点实验室,天津301617 [3]天津中医药大学第四附属医院老年病科,天津301617

出　　处：《中南药学》2024年第4期1042-1047,共6页Central South Pharmacy

基　　金：国家自然科学基金项目(No.81973699,No.82274361)。

摘　　要：目的 对苏黄颗粒进行水分含量检测。方法 取吸湿程度不同的苏黄颗粒,分别使用AntarisⅡ傅里叶变换近红外光谱仪、Avantes便携式近红外光谱仪采集两种近红外光谱,同时采用烘干法测定样品含水量作为参考值。光谱采用一阶求导(1^(st)D)、标准正态变量变换(SNV)、多元散射校正(MSC)的预处理方法,运用偏最小二乘回归(PLS)建立基于近红外光谱的苏黄颗粒水分定量分析模型,并采用Passing-Bablok回归比较两种近红外设备预测苏黄颗粒含水量的能力。结果 采用1^(st)D预处理后,所建综合模型的预测能力优异,FT-NIR模型与P-NIR模型的R^(2)(c)均大于0.9897,RMSEC均小于0.0019,R^(2)(p)均大于0.9716,RMSEP均小于0.0029。FT-NIR批次验证模型的R^(2)均高于0.997,P-NIR批次验证模型的R^(2)均大于0.935,表明两种仪器所建模型对未知批次样品具有优秀的预测能力。结论 P-NIR的模型效果虽不及FT-NIR,但同样具有较高的准确度和稳定性,可以准确、快速检测苏黄颗粒中水分含量,应用于生产实践与样品大批量检测。Objective To determine the moisture content of Suhuang granules.Methods The AntarisⅡfourier transform near infrared spectrometer and Avantes portable near infrared spectrometer were used to collect near infrared spectra of Suhuang granules with different moisture absorption degrees.Meantime,the oven drying was used to measure the moisture content of samples as the reference value.A quantitative analysis model of moisture content of Suhuang granules based on near-infrared spectrum was established with first derivation(1^(st)D),standard normal variate transformation,multiple scattering correction and partial least squares.Passing-Bablok regression was used to compare the ability of two near infrared devices to predict the moisture content of Suhuang granules.Results The prediction ability of the synthesized models was excellent after the pretreatment with 1^(st)D.R^(2)(c)of FT-NIR model and P-NIR model was both bigger than 0.9897,RMSEC was less than 0.0019,R^(2)(p)was bigger than 0.9716,and RMSEP was less than 0.0029.The R^(2) of the FT-NIR batch validation model was consistently higher than 0.997,so was the R^(2) of the P-NIR batch validation model at 0.935,indicating that the models for both instruments had excellent predictive capabilities for unknown batch samples.Conclusion Although the P-NIR method exhibits poorer accuracy than that of FT-NIR,it still demonstrates good stability and precision in detecting the moisture content of Suhuang granules.Both methods can be used in mass production and sample testing.

关 键 词：便携式近红外光谱 近红外光谱技术 苏黄颗粒 苏黄止咳胶囊 水分 

分 类 号：R284[医药卫生—中药学]