Particle Swarm Optimization Algorithm Establish the Model of Tobacco Ingredients in Near Infrared Spectroscopy Quantitative Analysis

  • Bibo Ma
  • Haiyan Ji
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 393)


57 tobacco samples were chosen, the near-infrared diffuse reflectance spectra at five different parts of tobacco leafs were averaged as the original spectra, the range of 4000-9000 wavenumber of spectral information was selected after wavelength selection, first-order differential was used to eliminate the impact of offset, PCA was used to reduce the dimensions and select the most representative of the principal components of the sample information. After these, use PSO and the data of chemical composition of nicotine and total nitrogen, to establish the models of near-infrared spectra of the main ingredient in tobacco quantitative analysis. In which, nicotine and total nitrogen quantitative analysis of modeling set correlation coefficients were 0.8886,0.9290; the prediction set correlation coefficients were 0.8786,0.8487. RMSEC values were 0.4737,0.2215; RMSEP values were 0.6417,0.2677. The results show that: PSO can be used to establish the model of nicotine and total nitrogen by near infrared spectroscopy quantitative analysis in tobacco.


Tobacco Particle Swarm Optimization (PSO) Principal Component Analysis (PCA) Near infrared spectroscopy 


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Copyright information

© IFIP International Federation for Information Processing 2013

Authors and Affiliations

  • Bibo Ma
    • 1
    • 2
  • Haiyan Ji
    • 1
    • 2
  1. 1.College of Information and Electrical EngineeringChina Agricultural UniversityBeijingChina
  2. 2.Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of EducationChina Agricultural UniversityBeijingChina

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