Study on the Model of Six Components in Tobacco Using OSC-PCR
WU Li-jun1, TIAN Kuang-da1, LI Qian-qian1, LI Zu-hong2, QIU Kai-xian1, MIN Shun-geng1*
1. Department of Applied Chemistry, College of Science, China Agricultural University, Beijing 100193, China 2. Yunnan Qujing Tobacco Company, Qujing 655000, China
Abstract：In the present paper, the authors used NIR to determine routine chemical components, namely total sugar, reducing sugar, nicotine, total nitrogen, starch and volatile alkali. Orthogonal signal correction (OSC) was employed as spectral pretreatment and the principal component regression (PCR) models for 6 chemical components were established with Monte Carlo cross-validation modeling strategy. RPD value for each model was calculated to evaluate the methods. The orientation of PCR projection is the largest variance direction and has no relationship with the concentration. OSC can not only get rid of uninformative concentration but also solve the problem of noise, baseline drift and stray light. Compared with conventional PCR, OSC-PCR sustains the accuracy of the predicting model and improves the stability of the model significantly. It proves that NIR coupled with OSC-PCR method can be applied to the determination of routine chemical components, which is of great significance in evaluation of tobacco quality and analysis of tobacco aroma components.
Key words：Tobacco;OSC;PCR;NIR spectroscopy;Routine chemical component
吴丽君1，田旷达1，李倩倩1，李祖红2，邱凯贤1，闵顺耕1* . 烟叶中六种成分OSC-PCR定量模型的研究 [J]. 光谱学与光谱分析, 2013, 33(06): 1517-1520.
WU Li-jun1, TIAN Kuang-da1, LI Qian-qian1, LI Zu-hong2, QIU Kai-xian1, MIN Shun-geng1* . Study on the Model of Six Components in Tobacco Using OSC-PCR . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2013, 33(06): 1517-1520.
[1] JING Yan-qiu, GONG Chang-rong, ZHANG Yue-hua，et al(景延秋，宫长荣，张月华，等). Chinese Tobacco Science(中国烟草科学), 2005, (2): 44. [2] ZHOU Ji-heng, ZHU Xiao-ping, WANG Yan-ting, et al(周冀衡, 朱晓平, 王彦亭, 等). Physiology and Biochemistry of Tobacco(烟草生理与生物化学). Hefei: China Science Technology University Press(合肥：中国科学技术大学出版社), 1996. 415. [3] Wu Y P, Deng J H, Wen D R, et al. Tobacco Chemistry, 2010, 9: 40. [4] BAI Chang-min, ZHONG Ke-jun, HUANG Jian-guo, et al(白长敏, 钟科军, 黄建国, 等). Chinese Journal of Analytical Chemistry(分析化学), 2006, 34(11): 1619. [5] Lü Hai-tao, SUN Hai-feng, QU Bao-han, et al(吕海涛, 孙海峰, 曲宝涵, 等). Chinese Journal of Analytical Chemistry(分析化学), 2007, 35(10): 1425. [6] YAN Yan-lu, ZHAO Long-lian, HAN Dong-hai, et al(严衍禄，赵龙莲，韩东海，等). Basis and Application of Near Infrared Spectral Analysis(近红外光谱分析基础与应用). Beijing: China Light Industry Press(北京: 中国轻工业出版社), 2005. 12. [7] TANG Shou-peng, YAO Xin-feng, YAO Xia, et al(汤守鹏, 姚鑫锋, 姚 霞，等). Chinese Journal of Analytical Chemistry(分析化学), 2009, 37(10): 1445. [8] Kim H C, Kim D J, Bang S Y. Recognition Letters, 2003, 24: 1385. [9] Zhang R, Wang W J, Chen Y. Expert Systems with Applications, 2010, 37: 6531. [10] Popescu M C, Froidevaux J, Navi P, et al. Journal of Molecular Structure, 2013, 1033: 176. [11] Svante W, Henrik A, Fredrik L, et al. Chemometrics and Intelligent Laboratory Systems, 1998, 44: 175. [12] Wu Y Q, Noda I, Meersman F, et al. Journal of Molecular Structure, 2006, 799: 121. [13] Yu H L, John F. Gregor M. Chemometrics and Intelligent Laboratory Systems 2004, 73: 199. [14] Xu Q S, Liang Y Z. Chemometrics and Intelligent Laboratory Systems, 2004, 56: 1.
