光谱学与光谱分析 |
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The Application of Near-Infrared Diffuse Reflection Spectra Based on the Principle of Linear Additive in Tobacco Redrying Formula |
ZHANG Ya-juan1,MA Xiang2,ZHANG Ye-hui1,MI Jin-rui3,XU Li1,WANG Yi2,WEN Ya-dong2,ZHAO Long-lian1,LI Jun-hui1*,ZHANG Lu-da3 |
1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China 2. Technology Center of Yuxi Hongta Group, Yuxi 653100, China 3. College of Science, China Agricultural University, Beijing 100193, China |
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Abstract In the process of analyzing and designing tobacco redrying formula using near infrared spectroscopy, a great deal of spectra for different ratio mixed samples are badly needed. However these sample spectra are very hard to obtain in the actual production process. Furthermore, for the samples of different grades it is difficult to achieve the goal of even mixing, in consequence of introducing inevitable errors. In order to solve the above problems, the present paper proposes to use “theory of even mixed spectrum” produced by linear additive near infrared spectroscopy in place of the spectra of actual mixed samples. This way can not only eliminate the errors caused by uneven mixture, but also leave out the course of mixing samples and measuring spectra and save time, effort, and material simultaneously. This article analyzes the comparison between linear additive spectra and the spectra of actual mixed samples from the following four aspects: original spectra, derivative spectra, principal components, and the data of PPF projection, accordingly verifing the feasibility and superiority of the linear additive spectra.
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Received: 2010-05-10
Accepted: 2010-08-20
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Corresponding Authors:
LI Jun-hui
E-mail: caunir@cau.edu.cn
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[1] 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. [2] ZHANG Ling-shuai,XING Jun,GU Yun-hong,et al(张灵帅,邢 军,谷运红,等). Acta Laser Biology Sinica(激光生物学报),2009,18(1):138. [3] Shao Yongni,He Yong,Wang Yanyan. Eur. Food Res. Technol., 2007, 224: 591. [4] Tan Chao,Qin Xin,Li Menglong. Vibrational Spectroscopy, 2009, 51: 276. [5] Zhang Yong, Cong Qian, Xie Yunfei, et al. Spectrochimica Acta Part A, 2008, 71: 1408. [6] JIANG Su,MA Xiang,CHEN Yong-fu,et al(江 苏,马 翔,陈永福,等). Chinese Journal of Spectroscopy Laboratory(光谱实验室), 2006,23(5):633. [7] QIU Jun, ZHANG Huai-bao, SONG Yan,et al(邱 军,张怀宝,宋 岩,等). Chinese Tobacco Science(中国烟草科学),2008,29(1):55. [8] Ni Lijun, Zhang Liguo, Xie Juan, et al. Analytica Chimica Acta, 2009, 633: 43. [9] XIA Xin-en(夏新恩). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报),2004,20(2):172. [10] 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. [11] YAN Yan-lu,ZHANG Lu-da,JING Mao,et al(严衍禄,张录达,景 茂,等). Acta Agriculture University Pekinensis(北京农业大学学报),1990,16(Suppl.):5. [12] JIANG Jian,YUE Bao-lin,DING Wen-xing,et al(姜 健,岳宝林,丁文兴,等). Measurement Technique(计量技术),2005,9:45. [13] LI Shen-an(李慎安),China Metrology(中国计量),2008,4:81.
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