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

Authors

LI Ruili, School of Tobacco Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan 450001, China
LIU Yuye, Anyang Cigarette Factory, China Tobacco Henan Industry Co., Ltd., Anyang, Henan 455000, China
LI Wenwei, Anyang Cigarette Factory, China Tobacco Henan Industry Co., Ltd., Anyang, Henan 455000, China
LI Tiancheng, School of Tobacco Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan 450001, China
WANG Jianmin, School of Tobacco Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan 450001, China

Abstract

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.

Publication Date

5-28-2019

First Page

83

Last Page

87

DOI

10.13652/j.issn.1003-5788.2019.05.015

Recommended Citation

Ruili, LI; Yuye, LIU; Wenwei, LI; Tiancheng, LI; and Jianmin, WANG (2019) "Study on rapid determination of tobacco blending uniformity by Near Infrared Spectroscopy," Food and Machinery: Vol. 35: Iss. 5, Article 15.
DOI: 10.13652/j.issn.1003-5788.2019.05.015
Available at: https://www.ifoodmm.cn/journal/vol35/iss5/15

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