Zhang Xijie, Li Minzan, Zhang Yan′e, Zhao Peng, Zhang Jianping. Estimating nitrogen content of cucumber leaf based on solar irradiance spectral reflectance in greenhouse[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2004, 20(6): 11-14.
    Citation: Zhang Xijie, Li Minzan, Zhang Yan′e, Zhao Peng, Zhang Jianping. Estimating nitrogen content of cucumber leaf based on solar irradiance spectral reflectance in greenhouse[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2004, 20(6): 11-14.

    Estimating nitrogen content of cucumber leaf based on solar irradiance spectral reflectance in greenhouse

    • Spectral reflectance of cucumber leaves in growing status was measured using the ASD FieldSpec Pro VNIR spectrometer with natural illumination in greenhouse, and the first derivative of the spectral reflectance was also calculated. The results from both spectral reflectance and the first derivative show that higher correlation coefficients were obtained within wavelength range of 505~664 nm, and 685~722 nm. Four wavelengths of 568 nm, 596 nm, 640 nm and 664 nm were obtained when using spectral reflectance data. Partial least square regression(PLSR) and the single linear regression(SLR) of the normal difference color index(NDCI) of 527 nm and 762 nm were executed to spectral reflectance to avoid the harms from multicollinearity. The PLSR results show that square of the correlation coefficients were 0.819 and 0.727, respectively for calibration and validation. The SLR results of the NDCI show that squares of the correlation coefficients were 0.815 and 0.740, respectively for calibration and validation. But a linear model with single wavelength(520nm) was better when using the first derivative data. Squares of the correlation coefficients for calibration and validation were 0.880 and 0.787, respectively. These show that both spectral reflectance and the first derivative can be used to estimate cucumber leaf N-content in greenhouse, and both models will provide a basis for developing potable instrument to diagnose crop growth potential.
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