基于近红外光谱相似的烟叶替代与卷烟配方维护

为辅助卷烟配方设计与维护,改善传统配方维护模式完全依赖人的问题,以近红外光谱信息为基础,通过一种局部校正的光谱预处理方法及集成的光谱相似度算法,排除了光谱中的基线、散射等干扰因素,形成基于光谱相似表征烟叶相似的技术,实现辅助卷烟配方的维护。结果表明:通过光谱相似筛选出的相似片烟与目标片烟在产地、部位的符合度分别为82.0%、75.7%,总糖、烟碱等主要化学成分的平均差异小于5%。采用片烟相似+片烟组合相似的方式,模拟计算出的替代配方在化学成分、感官指标等方面与原配方无显著差异。

Tobacco substitution and cigarette blend maintenance based on near infrared spectral similarity

Near infrared spectroscopic spectral similarity was investigated and applied to tobacco substitution and cigarette blend maintenance. By means of a local spectral pre-processing and an ensemble spectral similarity algorithm,any interference on baseline and scattering in the spectrum was eliminated and the technique was used for characterizing tobacco leaf based on spectral similarity to aid cigarette blending. The results showed that the matching rates according to the spectral similarity with target strips were 82.0% and 75.7% viewed from the producing area and stalk position respectively. The average differences on main chemical components,such as total sugar and nicotine,were less than 5%. There was no significant difference in chemical components and sensory indexes between the original blend and a simulated blend obtained through combining strip similarity with strip combination similarity.