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蔡剑华 ,王先春,胡惟文,基于形态小波的烟草尼古丁含量近红外光谱检测, 农业工程学报, 2012,28(15):281-286

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Cai Jianhua. Near-infrared spectrum detection of tobacco nicotine content based on morphological wavelet,

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liu2004m: 金币+10, 谢谢支持 2013-02-06 11:44:11
liu2004m: 博学EPI+1, 谢谢支持! 2013-02-06 11:44:20
Accession number:  20124415630982

  Title:  Near-infrared spectrum detection of tobacco nicotine content based on morphological wavelet
  Authors:  Cai, Jianhua1 ; Wang, Xianchun1; Hu, Weiwen1  
  Author affiliation:  1 Information Institute, Hunan University of Arts and Science, Changde 415000, China  
  Corresponding author:  Cai, J. (cjh1021cjh@163.com)  
  Source title:  Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
  Abbreviated source title:  Nongye Gongcheng Xuebao
  Volume:  28
  Issue:  15
  Issue date:  August 1, 2012
  Publication year:  2012
  Pages:  281-286
  Language:  Chinese
  ISSN:  10026819  
  CODEN:  NGOXEO  
  Document type:  Journal article (JA)
  Publisher:  Chinese Society of Agricultural Engineering, Agricultural Exhibition Road South, Beijing, 100026, China
  Abstract:  In order to improve the accuracy of non-destructive detection of nicotine content of tobacco, a novel method was proposed to get the pretreatment of near-infrared (NIR) spectrum based on morphological wavelet de-noising. The principle and steps of the method were given. The first derivative NIR spectrum of tobacco was served as the target to evaluate the application effect of this method. Then the tobacco nicotine content was calculated based on the de-noised spectrum, and it was compared with the result from wavelet method. Experimental results show that as a kind of nonlinear wavelet, morphological wavelet has both the morphological characteristic of mathematical morphology and the multi-resolution feature of wavelet. It had good performance in keeping details of spectrum and resisting noises. Compared to wavelet threshold method, it had more ideal effects that the correlation ratio (r2) of the prediction set was improved from 0.9877 to 0.9931, and the RMSEP reduced from 0.0539 to 0.0492. The method can be a reference for improving the accuracy of the detection of nicotine content of tobacco and the robustness of model by using near infrared spectroscopy.
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