• Spectroscopy and Spectral Analysis
  • Vol. 41, Issue 2, 473 (2021)
Yun-fei SHA1、1、*, Wen HUANG1、1, Liang WANG1、1, Tai-ang LIU1、1, Bao-hua YUE1、1, Min-jie LI1、1, Jing-lin YOU1、1, Jiong GE1、1, and Wen-yan XIE1、1
Author Affiliations
  • 1[in Chinese]
  • 11. Technology Center of Shanghai Tobacco Group Co., Ltd., Shanghai 200082, China
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    DOI: 10.3964/j.issn.1000-0593(2021)02-0473-05 Cite this Article
    Yun-fei SHA, Wen HUANG, Liang WANG, Tai-ang LIU, Bao-hua YUE, Min-jie LI, Jing-lin YOU, Jiong GE, Wen-yan XIE. Merging MIR and NIR Spectral Data for Flavor Style Determination[J]. Spectroscopy and Spectral Analysis, 2021, 41(2): 473 Copy Citation Text show less
    MIRs (a) and NIRs (b) of tobacco samples
    Fig. 1. MIRs (a) and NIRs (b) of tobacco samples
    (a)The first derivative MIR spectra and (b)The first derivative NIR spectra
    Fig. 2. (a)The first derivative MIR spectra and (b)The first derivative NIR spectra
    (a) PCA projection plot based on MIR; (b) PCA projection plot based on NIR and (c) PCA projection plot based on MIR and NIR
    Fig. 3. (a) PCA projection plot based on MIR; (b) PCA projection plot based on NIR and (c) PCA projection plot based on MIR and NIR
    (a) PCA projection plot based on 34 varieties; (b) PCA projection plot based on 24 varieties and (c) PCA projection plot based on 19 varieties
    Fig. 4. (a) PCA projection plot based on 34 varieties; (b) PCA projection plot based on 24 varieties and (c) PCA projection plot based on 19 varieties
    建模结果留一法结果预报结果
    清香型中间香型浓香型准确率/%清香型中间香型浓香型准确率/%清香型中间香型浓香型准确率/%
    清香型603193.75584290.63152088.24
    中间香型235192.11433186.8416085.71
    浓香型224591.84244387.76111285.71
    整体准确率/%92.7288.7486.84
    Table 1. The accuracies of the SVC
    Yun-fei SHA, Wen HUANG, Liang WANG, Tai-ang LIU, Bao-hua YUE, Min-jie LI, Jing-lin YOU, Jiong GE, Wen-yan XIE. Merging MIR and NIR Spectral Data for Flavor Style Determination[J]. Spectroscopy and Spectral Analysis, 2021, 41(2): 473
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