| 光谱学与光谱分析 |
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| Tobacco Quality Analysis of Producing Areas of Yunnan Tobacco Using Near-Infrared (NIR) Spectrum |
| WANG Yi1, MA Xiang1, WEN Ya-dong1, YU Chun-xia1, WANG Luo-ping1, ZHAO Long-lian2, LI Jun-hui2* |
1. Hongta Tobacco(Group)Co., Ltd., Yuxi 653100, China
2. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China |
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Abstract In the present study, tobacco quality analysis of different producing areas was carried out applying spectrum projection and correlation methods. The group of industrial classification data was near-infrared (NIR) spectrum in 2010 year of middle parts of tobacco plant from Hongta Tobacco(Group) Co., Ltd. Twelve hundred seventy six superior tobacco leaf samples were collected from four producing areas, in which three areas from Yuxi，Chuxiong and Zhaotong, in Yunnan province all belong to tobacco varieties of K326 and one area from Dali belongs to tobacco varieties of Hongda. The conclusion showed that when the samples were divided into two parts by the ratio of 2∶1 randomly as analysis and verification sets, the verification set corresponded with the analysis set applying spectrum projection because their correlation coefficients by the first and second dimensional projection were all above 0.99. At the same time, The study discussed a method to get the quantitative similarity values of different producing areas samples. The similarity values were instructive in tobacco plant planning, quality management, acquisition of raw materials of tobacco and tobacco leaf blending.
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Received: 2012-02-08
Accepted: 2012-09-20
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Corresponding Authors:
LI Jun-hui
E-mail: caunir@cau.edu.cn
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[1] ZHANG Tao(章 涛). Guidebook of Cigarette Formulation， Process Technology， Organoleptic evaluation and Quality Control(卷烟配方设计、生产工艺技术与感官鉴定及质量控制检验实务全书). Hong Kong：China Science， Technology and Culture Press(香港：中国科技文化出版社)， 2005.
[2] LU Yong-heng(陆永恒). Chinese Tobacco Science(中国烟草科学), 2007, 28(3): 43.
[3] LIU Guo-shun, FU Yun-peng, et al(刘国顺， 符云鹏， 等). Tillage and Cultivation(耕作与栽培), 1996, (1): 28.
[4] XIE Juan, LUO Jian-qun, YAO He-ming, et al(谢 娟， 罗建群， 姚鹤鸣， 等). Tobacco Science&Technology(烟草科技), 2008, (7): 42.
[5] WEN Ya-dong， WANG Yi， WANG Neng-ru， et al(温亚东， 王 毅， 王能如， 等). Acta Tabacaria Sinica(中国烟草学报)， 2009， 15(5)：6.
[6] YAN Yan-lu， ZHAO Long-lian， HAN Dong-hai ， et al(严衍禄， 赵龙莲， 韩东海， 等). Foundation and Application of NIR Spectra 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. 13.
[7] ZHANG Jian-ping, CHEN Jiang-hua, SHU Ru-xin， et al(张建平， 陈江华， 束茹欣， 等). Acta Tabacaria Sinica(中国烟草学报), 2007, 13(5): 1.
[8] ZHANG Yong, CONG Qian, XIE Yun-fei, et al(张 勇, 丛 茜, 谢云飞， 等). Chemical Research in Chinese Universities(高等学校化学学报), 2009, 30(4): 697.
[9] Ni Lijun， Zhang Liguo， Xie Juan， et al. Analytica Chimica Acta， 2009， 633(1)：43.
[10] Jing Ming, Cai Wensheng, Shao Xueguang. Analytical Letters, 2010, 43: 10.
[11] McClure W F，Hamid Abdul，Giesbrecht F G，et al. Applied Spectroscopy，1984，38(3)：322.
[12] WANG Guo-dong，SHU Ru-xin，ZHANG Jian-ping，et al(王国东，束茹欣，张建平). Tobacco Science & Technology(烟草科技)，2006，(5)：36.
[13] ZHANG Xiao-hui, LIU Jian-xue, et al(张晓慧，刘建学，等). Laser & Infrared(激光与红外), 2008，38(4)：342.
[14] WANG Jia-jun，LI Juan(王家俊，李 娟). Tobacco Science& Technology(烟草科技), 2008，(3)：5. |
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