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Acta Agron Sin ›› 2009, Vol. 35 ›› Issue (9): 1681-1690.doi: 10.3724/SP.J.1006.2009.01681


Quantitative Relationship between Hyper-spectral Red Edge Position and Canopy Leaf NitrogenConcentration in Rice

TIAN Yong-Chao,YANG Jie,YAO Xia,ZHU Yan,CAO Wei-Xing*   

  1. Jiangsu Key Laboratory for Information Agriculture / Nanjing Agricultural University, Nanjing 210095, China
  • Received:2008-12-11 Revised:2009-04-17 Online:2009-09-12 Published:2009-07-04
  • Contact: CAO Wei-Xing,E-mail: caow@njau.edu.cn


Real-time and non-destructive monitoring of crop nitrogen status is needed for precision management and dynamic regulation in rice fertilization. This research made a systematic analysis on the characteristics of the first-derivative reflectance spectra in red edge area, and the quantitative relationships between red edge position (REP) with different algorithms and canopy leaf nitrogen concentrations in the conditions of different nitrogen rates and rice varieties in different seasons of field-grown rice. The results showed that spectrum in red edge area was significantly affected by nitrogen levels and varietal types, and “three-peak” feature could be observed with the first derivative spectrum in this area. Traditional REP (the maximum value of the fist derivative spectra in 670–780 nm range) was not sensitive to canopy leaf nitrogen concentration because of the three-peak feature, but the REPs based on inverted Gaussian fitting, linear four-point interpolation, linear extrapolation and adjusted linear extrapolation generated continuous REP data, and could be used to estimate canopy leaf nitrogen concentration. Besides, REP from a three-point Lagrangian interpolation with three first-derivatives bands (695, 700 and 705 nm) also had a good relationship with canopy leaf nitrogen concentration. Comparison of these REPs based on different approaches indicated that the adjusted linear extrapolation method (755FD730+675FD700) / (FD730+FD700) gave the best prediction of canopy leaf nitrogen concentration, with relative simple algorithm, and thus is a good REP parameter for monitoring canopy leaf nitrogen concentration in rice.

Key words: Rice, Red edge position, Adjusted linear extrapolation, Leaf nitrogen concentration, Monitoring model

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