摘要
为实现硫熏牛膝中SO_(2)含量的快速无损检测,该研究首先制备不同硫磺熏蒸程度的硫熏牛膝样品,硫磺使用量分别为牛膝饮片质量的0、2.5%和5%。采用《中国药典》2020年版方法测定不同批次硫熏牛膝的SO_(2)含量,然后利用高光谱成像技术采集硫熏牛膝在可见-近红外波段(435~1 042 nm)和短波红外波段(898~1 751 nm)范围内的高光谱信息。应用一阶导数、AUTO、多元散射矫正、SG平滑及标准正态变量变换方法对原始高光谱数据进行预处理,对预处理后的光谱信息进行竞争性自适应重加权(CARS)特征波长提取和偏最小二乘回归分析,建立硫熏牛膝中SO_(2)含量的定量检测模型,发现采用可见-近红外光谱对牛膝SO_(2)残留量进行定量建模的准确率较高,在可见-近红外光谱SO_(2)模型中预测集相关系数(R_(p)^(2))为0.900 1。该研究所建立的牛膝SO_(2)残留量定量检测模型可以实现不同硫熏程度牛膝中SO_(2)残留量的快速、无损检测,可以作为药典检测方法的一种有效补充。
In order to realize the rapid and non-destructive detection of SO_(2)content in sulphur-fumigated Achyranthis Bidentatae Radix, this paper first prepared the sulphur-fumigated Achyranthis Bidentatae Radix samples with the usage amount of sulphur being 0, 2.5%, and 5% of the mass of Achyranthis Bidentatae Radix pieces. The SO_(2)content in different batches of sulphur-fumigated Achyranthis Bidentatae Radix was determined using the method in Chinese Pharmacopoeia, followed by the acquisition of their hyperspectral data within both visible-near infrared(435-1 042 nm) and short-wave infrared(898-1 751 nm) regions by hyperspectral imaging. Meanwhile, the first derivative, AUTO, multiplicative scatter correction, Savitzky-Golay(SG) smoothing, and standard normal variable transformation algorithms were used to pre-process the original hyperspectral data, which were then subjected to characteristic band extraction based on competitive adaptive reweighted sampling(CARS) and the partial least square regression analysis for building a quantitative model of SO_(2)content in sulphur-fumigated Achyranthis Bidentatae Radix. It was found that the accuracy of the quantitative model built depending on the visible-near infrared spectra was high, with the determination coefficient of prediction set(R_(p)^(2)) reaching 0.900 1. The established quantitative model has enabled the rapid and non-destructive detection of SO_(2)content in sulphur-fumigated Achyranthis Bidentatae Radix, which can serve as an effective supplement to the method described in Chinese Pharmacopeia.
作者
江恩赐
陈林
颜继忠
陶益
JIANG En-ci;CHEN Lin;YAN Ji-zhong;TAO Yi(Colley of Phdrnuicculical Science,Zhejiang University of Technology,Hangzhou 310014,China)
出处
《中国中药杂志》
CAS
CSCD
北大核心
2022年第7期1864-1870,共7页
China Journal of Chinese Materia Medica
基金
国家自然科学基金项目(81703701)
浙江工业大学“课程思政”改革试点课程建设项目(PX-52203112)。
关键词
高光谱成像技术
牛膝
SO_(2)
竞争性自适应重加权
定量模型
hyperspectral imaging
Achyranthis Bidentatae Radix
SO_(2)
competitive adaptive reweighted sampling(CARS)
quantitative model