利用近红外光谱技术快速检测配方烟丝掺配均匀性

Study on rapid determination of tobacco blending uniformity by Near Infrared Spectroscopy

采用主成分分析构建反映主要化学成分含量及衍生指标值的统计量F得分,以F得分作为表征烟丝组分掺配均匀性的特性值。采集不同组分比例烟丝样品的近红外光谱数据,采用MSC结合一阶导数和S-G平滑处理将光谱信息进行预处理,提高信噪比,选择光谱范围为4281.2~4485.6,5542.4~6024.5,6043.8~7135.3cm-1,采用PLS法建立统计量F得分的近红外光谱模型,模型的决定系数(R2)为0.996,RMSECV为0.269,模型预测性能好,预测精度高。说明利用近红外技术可快速预测配方烟丝样品的统计量F得分,实现卷烟加工过程中烟丝掺配均匀性的快速检测。

Based on the principal component analysis, we established F score statistics to reflect comprehensive information about main chemical composition and their ratio and used F score as the characteristic value to characterize the homogeneity of formula tobacco.We detected the near-infrared spectral of tobacco samples with different formula tobacco and founded the near-infrared spectral model of F score by using the partial least square method based on the range of 4 281.2~4 485.6,5 542.4~ 6 024.5 ,6 043.8~7 135.3 cm -1 spectroscopy pretreated by multiplicative signal correction and first-order derivative and Savitzkyt-Golay smoothing.The determinant coefficient of F score model was 0.996 , and RMSECV was 0.269.The model was found to have good prediction performance and high prediction accuracy.The F statistics score of tobacco samples could be predicted quickly by NIR, and this provided a rapid and efficient monitoring method of tobacco blending uniformity and a technical guidance to the regulation and control of cigarette homogenization production.