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.