为卷烟配方替代和产品质量稳定性评价奠定基础,利用近红外光谱结合模式识别方法,建立了卷烟烟丝配方比例的识别模型。在某牌号卷烟成品烟丝中添加5种不同比例的A模块烟丝,采集其近红外光谱信息,采用求导法(一阶求导、二阶求导)和平滑法(Savitzky-Golay平滑、Norris平滑)对样品近红外光谱进行预处理,结合主成分分析-马氏距离(PCA-MD)、偏最小二乘法-判别分析(PLS-DA)和正交偏最小二乘法-判别分析(OPLS-DA)建立上述5种成品烟丝的识别模型。结果显示,最佳光谱预处理方式为一阶求导+Savitzky-Golay平滑,最佳模式识别方法为OPLS-DA。当主成分数为4时,最佳识别模型的光谱变量累计解释能力为0.995,分类变量累计解释能力为0.953,特征值为0.196,累计交叉有效性为0.912,模型外部验证的整体识别率为99%。置换验证结果表明该模型稳定可靠,未出现过拟合现象。对5种成品烟丝进行感官评吸,该模型对不同卷烟烟丝配方比例的识别效果更好。

In order to lay a foundation for cigarette formula substitution and product quality stability evaluation, the recognition model of cigarette tobacco formula proportion was established based on near infrared spectroscopy with pattern recognition method. 5 different proportions of A module tobacco were added into a brand cigarette finished tobacco, and its near infrared spectral information were collected. Near infrared spectra of the samples were pretreated by derivation method (first-order derivative and second-order derivative) and smoothing method (Savitzky-Golay smoothing and Norris smoothing). Combined with principal components analysis-mahalanophil distance (PCA-MD), partial least square method-discriminant analysis (PLS-DA) and orthogonal partial least square method-discriminant analysis (OPLS-DA), the recognition models of the above 5 kinds of finished tobacco were established. It was shown that the best spectral pretreatment method was first-order derivative + Savitzky-Golay smoothing, and the best pattern recognition method was OPLS-DA. When the number of principal components was 4, the cumulative interpretation ability of spectral variables for the optimal recognition model was 0.995, with the cumulative interpretation ability of classified variables of 0.953, the eigenvalue of 0.196, the cumulative crossover validity of 0.192, and the overall recognition rate of external validation for the model was 99%. The results of substitution verification showed that the model was stable and reliable without overfitting phenomenon. The sensory evaluation of 5 finished tobacco was carried out, and the recognition effect of different proportions of cigarette tobacco formula was better by near infrared spectroscopy combined with pattern recognition method.