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基于近红外光谱技术的电子烟油烟碱含量快速检测研究
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作者单位
杨双艳,周瑾,沈彦文,杨紫刚,费宇,张四伟 1.云南巴菰生物科技有限公司2.云南财经大学统计与数学学院3.云南省烟草公司文山州公司 
基金项目:国家自然科学基金资助项目(11971421)
中文摘要:烟碱是电子烟烟油中的主要成分,其含量决定了电子烟油的风味口感及产品的安全性。为了提高电子烟油烟碱含量的测量效率,该文采用近红外光谱技术和极限学习机回归(ELMR)建立了电子烟油烟碱含量的定量预测模型。实验结果表明:相比于传统的主成分回归(PCR)和偏最小二乘回归(PLSR)模型,所建立的ELMR预测模型的决定系数R2为0.926 2,远高于PCR预测模型的0.859 0和PLSR预测模型的0.860 4;同时,使用ELMR模型的预测均方根误差(RMSEP)为0.026 8,小于PCR预测模型的0.043 1和PLSR预测模型的0.040 9。以上结果说明该文所建立的近红外光谱定量模型能够应用于烟碱含量的快速准确测量,为实现电子烟油烟碱含量的实时在线监测和其它质量参数的快速测量奠定了良好的基础。
中文关键词:电子烟油  烟碱含量  近红外光谱  极限学习机  快速检测
 
Rapid Determination of Nicotine Content of E cigarette Liquid Based on Near infrared Spectroscopy Technology
Abstract:Nicotine is the most important component in E cigarette liquid,whose content determines the flavor and the safety of the product.In order to improve the detecting efficiency of the nicotine content,a novel near infrared spectroscopy(NIR) combined with extreme learning machine regression(ELMR) algorithm was adopted to establish an NIR-ELMR prediction model for nicotine content in E cigarette liquid.The experimental results showed that,compared with traditional partial least squares regression(PLSR) model and principal component regression(PCR) model,the NIR-ELMR model was much better with a determination coefficient(R2) of 0.926 2,which was higher than 0.859 0 for PCR prediction model and 0.860 4 for PLSR prediction model.Besides,the root mean square error of prediction(RMSEP) for NIR-ELMR model was 0.026 8,which was smaller than 0.043 1 for PCR model and 0.040 9 for PLSR model.The above results indicated the established model could be applied to the rapid and accurate determination of the nicotine content of E cigarette liquid,which lay a foundation for the online analysis of nicotine content and the rapid determination of other quality parameters.
Key Words:E-cigarette liquid  nicotine content  near infrared spectroscopy (NIR)  extreme learning machine (ELM)  rapid determination
引用本文:杨双艳,周瑾,沈彦文,杨紫刚,费宇,张四伟.基于近红外光谱技术的电子烟油烟碱含量快速检测研究[J].分析测试学报,2020,39(11):1411-1415.
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