近红外光谱法预测烟气总粒相物中的烟碱含量

采用近红外(NIR)光谱技术直接扫描烟叶粉末,建立了预测烟气总粒相物中烟碱含量的数学模型。该模型的内部验证决定系数(R2)为86.57,均方差(RMSECV)为0.385;外部验证的决定系数(R2)为81.32,均方差(RMSEP)为0.398,近红外预测值与标准测定值的平均相对偏差为8.89%。通过配对t-检验,该方法与标准方法测定的效果无显著性差异。该方法精密度高,可用于烟气总粒相物中烟碱含量的快速预测。

Prediction of nicotine in total particulate matter by near infrared spectroscopy

A mathematical model of nicotine in total particulate matter was established by scanning tobacco powder with FT-NIR spectrometry. The determination coefficient(R2) was 86.57, and the Root Mean Square Error of Cross Validation(RMSECV) was 0.385 in cross validation. The determination coefficient(R2) was 81.32,and the Root Mean Square Error of Prediction (RMSEP) was 0.398 in test set validation. It has been validated that the average relative error between NIR-predicted results and the standard-determinated results was 8.89%.By statistical significance test,the results of prediction were compared with those of standard methods with no significant difference at 0.05 level. NIR analysis has advantages of rapidity and precision, and can be applied for rapid determination of nicotine in total particulate matter.