卷烟的感官特征与其烟丝提取物GC/MS数据之间的关系

Relationship Between Sensory Characteristics of Cigarettes and GC/MS Data of Cut Filler Extracts

为了通过烟丝提取物的GC/MS数据预测卷烟烟气的感官特征,对48种市售烤烟型卷烟样品的烟丝进行了加速溶剂萃取,得到的提取物进行GC/MS分析,对这些卷烟样品的感官特征进行了评价,并采用主成分回归(PCR)和偏最小二乘法(PLS)对这些卷烟样品的感官特征评价值与其烟丝提取物的GC/MS数据进行处理,建立了定量模型。结果表明,PCR模型的预测效果优于PLS模型。对于超过75%的感官特征,PCR模型的预测结果与专家评价值之间的平均绝对误差(MAE)小于0.5。PCR模型预测结果可靠,可作为一种预测卷烟感官特征的方法。

In order to predict the sensory characteristics of cigarettes with the GC/MS data of cut filler extracts, the samples of 48 commercial cigarette brands were panel tested and their cut fillers were extracted with accelerated solvent extraction, and the resultant extracts were analyzed by GC/MS. The quantitative models were developed by processing the GC/MS data and panel test data with principal component regression （PCR） and partial least square （PLS）. The results showed that the PCR models offered better predictive effects than did the PLS models. The mean absolute errors between the predictive results of PCR models and the values of panel test were below 0.5 for more than 75% of sensory characteristics. It was concluded that PCR models were reliable and could be used as a method for predicting the sensory characteristics of cigarettes.