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    烟丝提取物紫外—可见光谱预测烟气烟碱含量

    Prediction of Nicotine Content in Cigarette Smoke by UV-VIS Spectroscopy of Cut Tobacco Extraction

    • 摘要: 用80%乙醇为溶剂,获得烟叶乙醇提取物紫外—可见光谱,化学分析获取卷烟烟气烟碱含量,利用紫外—可见光谱和烟气烟碱化学测定值建立卷烟烟气烟碱含量预测模型。结果表明,模型预测准确率为98.68%。模型外部验证后,通过t 检验,发现预测值和测定值间在统计学意义上无显著性差异,说明本方法具有较高的准确度,能快速、准确预测烟气烟碱含量,为叶组研发带来便利。

       

      Abstract: In this study, ethanol extraction of cut tobacco, its UV-VIS spectrum and nicotine content of smoke were acquired in order to establish UV-VIS spectroscopy model for predicting nicotine content in cigarettes smoke. By using outer validation and t-test, the results showed that the forecasted value and measured value had no significant difference. This prediction method has advantages of high precision and can be applied to rapid determination of nicotine content in cigarettes smoke, which is very helpful in cigarette blending formulation.

       

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