电子鼻技术结合化学计量学用于卷烟包装纸VOCs残留量的表征

Electronic nose combined with chemometrics for characterizing VOCs'residues in cigarette packing paper

摘要: 为建立更加简便快速、环保和低成本的卷烟包装纸品质判别方法，结合卷烟包装纸挥发性有机化合物（VOCs）的质量分数和电子鼻检测结果，用判别因子分析（DFA）、主成分分析（PCA）和簇类独立软模型分析（SIMCA）3种方法分别构建苯残留量判别模型和15种VOCs总量判别模型，并对比了3种方法的建模结果。结果表明：采用DFA构建苯残留量判别模型，以及采用DFA或SIMCA构建15种VOCs总量判别模型，均可较好地实现卷烟包装纸品质的快速判别。

Abstract: For a simple, fast, environment-friendly and cost-effective means to differentiate the quality of cigarette packing paper, a method was developed by analyzing the contents of volatile organic compounds (VOCs) emitted from cigarette packing paper using an electronic nose system. In addition, three discriminant models for benzene contents and the total contents of 15 VOCs were developed with discriminant factor analysis (DFA), principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA) algorithms, separately. The modeling outputs from the three methods were compared, and the results showed that both the model for benzene contents based on DFA and that for the total contents of 15 VOCs based on DFA or SIMCA could be applied for the fast differentiation of quality of cigarette packing paper.