烟草科技2025，Vol.58Issue(4)：1-10,10.DOI:10.16135/j.issn1002-0861.2024.0881
近红外光谱法预测烟叶原料烟气常规化学成分释放量
Prediction on releases of routine cigarette smoke chemical components from near-infrared spectroscopy of tobacco leaves
摘要
Abstract
For rapid determination of tar,nicotine and CO in mainstream smoke released from tobacco leaves stored in warehouses of different tobacco enterprises,near-infrared(NIR)spectra of 889 tobacco strip samples were collected and the Kennard-Stone(K-S)algorithm was used to select 150 representative tobacco strip samples for Partial Least Squares(PLS)regression modeling.The spectra were pre-processed using Multivariate Scatter Correction(MSC),Savitzky-Golay(SG)smoothing and first order derivatives.By selecting the characteristic spectral segments and the optimal number of principal components,the prediction models for the releases of tar,nicotine and CO in cigarette smoke based on the NIR spectroscopy of tobacco leaves were established.The results showed that:1)There were no significant differences between the results of the prediction models and the standard methods at 0.05 level of significance.2)All the coefficients of determination(R2)of the best PLS prediction models for tar,nicotine and CO releases were higher than 0.80.3)The root mean square errors of calibration(RMSEC)for tar,nicotine and CO were 1.13,0.13 and 0.97,respectively.The ratios of the root mean square error of prediction(RMSEP)to the RMSEC for tar,nicotine and CO were 1.03,1.00 and 0.95,respectively.4)The results of the leaf blending overlay experiment showed that the predicted results of each tobacco raw material linearly added according to the formula ratios,which closely matched the actual determined result of the leaf blending with a relative deviation of less than 10％.The established near-infrared prediction models for the releases of tar,nicotine and CO were therefore considered to be accurate,reliable and suitable for rapid quantitative prediction of the releases of routine cigarette smoke components from tobacco leaves.关键词
近红外(NIR)光谱/烟叶/烟气常规化学成分/释放量/焦油/烟碱/CO/偏最小二乘法Key words
Near-infrared(NIR)spectroscopy/Tobacco leaf/Routine cigarette smoke chemical component/Release/Tar/Nicotine/CO/Partial least squares(PLS)分类
轻工业引用本文复制引用
王志才,李嘉,李山,秦国鑫,王聪,王洪波,赵乐,张建栋,杨松,朱先约,谭涛,王泽理,张志军,王祯,黄伟..近红外光谱法预测烟叶原料烟气常规化学成分释放量[J].烟草科技,2025,58(4):1-10,10.基金项目
甘肃省重点研发计划-工业类项目"基于近红外光谱的卷烟产品数字化设计与维护技术研究"(22YF7GA052) （22YF7GA052）
中国烟草实业发展中心科技项目"'兰州'品牌叶组配方模块化替代技术研究"(ZYSYQ-2024-08) （ZYSYQ-2024-08）
甘肃烟草工业有限责任公司科技项目"'兰州'品牌卷烟烟气常规成分释放量近红外预测技术研究"(KJXM-2022-02). （KJXM-2022-02）
