烟叶最佳化学组成与烟气成分预测模型的建立

Establishment of the Optimal Model on Chemical Content in Flue-Cured Tobacco and Smoke Composition

摘要:

为选择最佳的烟叶化学组成与烟气成分的预测模型,运用不同的回归分析统计方法,对烟叶化学组成和烟气成分进行了回归分析。结果表明:全模型、双重筛选逐步回归以及仅含相关变量的逐步回归,方程均通过检验,但是不同方法得到的模型预测精度不同,且预测变量回归系数未全部通过检验;剔除不显著变量后,重新拟合回归预测模型,得到的焦油、烟气烟碱、烟气一氧化碳的回归模型,焦油回归方程为Y焦油=11.7+1.857X烟碱,烟气烟碱回归方程为Y烟气烟碱=0.679X烟碱,烟气一氧化碳回归模型为YCO=1.428 6X烟碱+0.121 7X还原糖+2.822 5X总氯+8.488 9,且回归方程检验均达到显著水平(P<0.01),方程回归系数均通过显著性检验(P<0.01)。这些结果为提高烟叶安全性和设计低焦油卷烟配方提供了科学依据。

Abstract:

Regression analysis and statistical methods were used to establish the optimal model of the chemical content and smoke composition.The results show that:1) equations were examined in full model,double screening stepwise regression,and stepwise regression only containing relevant variable.However,the prediction accuracy of the model was different in these methods,and not all the regression coefficient of the predictor variables was examined.2) when the indistinctive variable removed,the higher prediction accuracy and regression diagnostics models about Tar,nicotinamide and CO were obtainted.Tar regression equation was Ytar=11.7+1.857Xnicotine,Nicotine regression equation was Ynicotion=0.679Xnicotion,CO regression equation was YCO=1.428 6Xnicotion+0.121 7Xreducing sugar+2.822 5Xtotal chlorine+8.488 9,and all the regression equation test were significant(P<0.01).