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Estimation of nitrogen content based on fluorescence spectrum and principal component analysis in paddy rice

Author

Listed:
  • J. Yang

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, P.R. China)

  • W. Gong

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, P.R. China
    Collaborative Innovation Center of Geospatial Technology, Wuhan, P.R. China)

  • S. Shi

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, P.R. China
    Collaborative Innovation Center of Geospatial Technology, Wuhan, P.R. China
    School of Resource and Environmental Sciences, Wuhan University, Wuhan, P.R. China)

  • L. Du

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, P.R. China
    School of Physics and Technology, Wuhan University, Wuhan, P.R. China)

  • J. Sun

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, P.R. China)

  • S.-L. Song

    (Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan,)

Abstract

Paddy rice is one of the most important cereal crops in China. Nitrogen (N) is closely related to crops production by influencing the photosynthetic efficiency of paddy rice. In this study, laser-induced fluorescence (LIF) technology with the help of principal component analysis (PCA) and back-propagation neural network (BPNN) is proposed to monitor leaf N content (LNC) of paddy rice. The PCA is utilized to extract the characteristic variables of LIF spectra by analysing the major attributes. The results showed that the first three principal components (PCs) can explain 95.76% and 93.53% of the total variance contained in the fluorescence spectra for tillering stage and shooting stage, respectively. Then, BPNN was utilized to inverse the LNC on the basis of the first three PCs as input variables and can obtain the satisfactory inversion results (R2 of tillering stage and shooting stage are 0.952 and 0.931, respectively; residual main range from -0.2 to 0.2 mg/g). The experimental results demonstrated that LIF technique combined with multivariate analysis will be a useful method for monitoring the LNC of paddy rice, which can provide consultations for the decision-making of peasants in their N fertilization strategies.

Suggested Citation

  • J. Yang & W. Gong & S. Shi & L. Du & J. Sun & S.-L. Song, 2016. "Estimation of nitrogen content based on fluorescence spectrum and principal component analysis in paddy rice," Plant, Soil and Environment, Czech Academy of Agricultural Sciences, vol. 62(4), pages 178-183.
    • Handle: RePEc:caa:jnlpse:v:62:y:2016:i:4:id:802-2015-pse
    DOI: 10.17221/802/2015-PSE
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    References listed on IDEAS

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    1. J. Olszewski & M. Makowska & A. Pszczółkowska & A. Okorski & T. Bieniaszewski, 2014. "The effect of nitrogen fertilization on flag leaf and ear photosynthesis and grain yield of spring wheat," Plant, Soil and Environment, Czech Academy of Agricultural Sciences, vol. 60(12), pages 531-536.
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    Cited by:

    1. Honghui SANG & Xiyun JIAO & Shufang WANG & Weihua GUO & Mohamed Khaled SALAHOU & Kaihua LIU, 2018. "Effects of micro-nano bubble aerated irrigation and nitrogen fertilizer level on tillering, nitrogen uptake and utilization of early rice," Plant, Soil and Environment, Czech Academy of Agricultural Sciences, vol. 64(7), pages 297-302.

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