Spectroscopy and Spectral Analysis, Volume. 37, Issue 4, 1114(2017)

Research on Optimization of Wheat Seed Germination Rate NIR Model Based on Si-cPLS

WU Jing-zhu1,2、*, DONG Wen-fei1, DONG Jing-jing1, CHEN Yan1, MAO Wen-hua3, and LIU Cui-ling1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    To improve the detecting accuracy and robustness of wheat seed germination rate with near infrared spectroscopy technique, single PLS model and consensus PLS model(cPLS) developed on the full-spectral were compared and analyzed, thus, the Si-cPLS model which developed on the characteristic spectral regions was put forward. There were 84 samples partitioned into 66 training samples and 18 prediction samples using SPXY method. By randomly selecting 50 samples from training set as calibration set, a series of sub PLS models were build. 100 PLS sub models satisfying predefined criterion were selected and combined one cPLS model by averaging all predicted results. With this basis Si-cPLS model were developed on characteristic spectral regions selected with synergy interval method. Statistics on 50 repeat prediction of wheat seed germination by full-spectral PLS model, full-spectral cPLS model, and Si-cPLS model showed that, the mean correlation coefficient(R) were 0.901, 0.922 and 0.936 respectively, the mean RMSEP were 13.735%, 12.533% and 10.273% respectively with standard deviation of RMSEP of 1.144%, 0.096% and 0.080% respectively. Results showed that cPLS model was more stable and reliable than single PLS model, While Si-cPLS could further increase the stability and prediction accuracy of cPLS model.

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    WU Jing-zhu, DONG Wen-fei, DONG Jing-jing, CHEN Yan, MAO Wen-hua, LIU Cui-ling. Research on Optimization of Wheat Seed Germination Rate NIR Model Based on Si-cPLS[J]. Spectroscopy and Spectral Analysis, 2017, 37(4): 1114

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    Paper Information

    Received: Nov. 6, 2015

    Accepted: --

    Published Online: Jun. 20, 2017

    The Author Email: Jing-zhu WU (pubwu@163.com)

    DOI:10.3964/j.issn.1000-0593(2017)04-1114-04

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