• Spectroscopy and Spectral Analysis
  • Vol. 34, Issue 11, 2984 (2014)
JIA Shi-qiang1、2、*, GUO Ting-ting3, LIU Zhe1, YAN Yan-lu1, AN Dong1、4, GU Jian-cheng5, LI Shao-ming1, ZHANG Xiao-dong1, and ZHU De-hai1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
  • 5[in Chinese]
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    DOI: 10.3964/j.issn.1000-0593(2014)11-2984-05 Cite this Article
    JIA Shi-qiang, GUO Ting-ting, LIU Zhe, YAN Yan-lu, AN Dong, GU Jian-cheng, LI Shao-ming, ZHANG Xiao-dong, ZHU De-hai. Feasibility Study on an Approach for Identifying Corn Kernel Varieties with Seed Coating Agents via Near Infrared Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2014, 34(11): 2984 Copy Citation Text show less

    Abstract

    It is generally accepted that near infrared reflectance spectroscopy (NIRS) can be used to identify variety authenticity of bare maize seeds. In practical, maize seeds are covered with seed coating agents. Therefore it’s of huge significance to investigate the feasibility of identifying coated maize seeds by NIRS. This study employed NIRS to quickly determine the variety of coated maize seeds. Influence of seed coating agent on NIR spectra was discussed. The NIR spectra of coated maize seeds were obtained using an innovative method to avoid the impact of the seed coating agent. Coated seeds were cut open, and the sections were scanned by the spectrometer, so as to acquire the information of the seed itself. Then, support vector machine (SVM), soft independent modeling of class analogy (SIMCA), and biomimetic pattern recognition (BPR) was employed to establish the identification model for four maize varieties, and yield 93%, 95.8%, 98% average correct rate respectively. BPR model showed better performance than SVM and SIMCA models. The robustness of identification model was tested by seeds harvested from four regions and model showed good performance.
    JIA Shi-qiang, GUO Ting-ting, LIU Zhe, YAN Yan-lu, AN Dong, GU Jian-cheng, LI Shao-ming, ZHANG Xiao-dong, ZHU De-hai. Feasibility Study on an Approach for Identifying Corn Kernel Varieties with Seed Coating Agents via Near Infrared Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2014, 34(11): 2984
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