[目的]研究不同风格及产地的卷烟.[方法]样品原始近红外光谱分别经过最小-最大归一化、一阶导数、一阶导数+矢量归一化、一阶导数+最小-最大归一化、二阶导数和连续小波变换(CWT)等方法处理后进行了主成分分析(PCA),建立了以马氏距离为基础的卷烟识别模型.[结果]小波变换模型有更好的样品识别能力,模型校正集样品的识别率为96.9%,检验集样品识别率为100%.分类可视化结果表明样品对本类型卷烟风格特征的表达最突出,国内烤烟型卷烟的国外混合型特征最不明显,国外混合型卷烟的国内烤烟型特征最不明显,国外烤烟型卷烟的国外混合型特征最不明显.[结论]采用近红外光谱技术可对不同风格及产地的卷烟进行正确识别.%[ Objective ] The research aimed to study different style characteristics and producing areas of cigarettes. [ Method ] The original spectra of samples were processed by minimum-maximum normalization, first-order derivative, first-order derivative + vector normalization,first-order derivative + minimum-maximum normalization, second-order derivative and continuous wavelet transform(CWT) individually. The processed spectra were treated by principal component analysis and the recognition models based on Mahalanobis distancewere built. [ Result]The recognition capability of CWT model was higher. The recognition rate of calibration set of CWT model was 96.9％ and the recognition rates of validation set was 100％. The visualization results showed that all samples showed their own specific style characteristics best. It was also found that Chinese flue-cured cigarettes showed least characteristics of overseas blended cigarettes. Overseas blended cigarettes showed least characteristics of Chinese flue-cured cigarettes. Overseas flue-cured cigarettes showed least characteristics of overseas blended cigarettes.[ Conclusion ] It was proved that different style characteristics and producing areas of cigarettes could be correctly recognized by near infrared spectroscopy technology.
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