Quantitative relationships of leaf nitrogen status to canopy spectral reflectance in rice
Yan Zhu A , Dongqin Zhou A , Xia Yao A , Yongchao Tian A and Weixing Cao A BA Hi-Tech Key Laboratory of Information Agriculture of Jiangsu Province, Key Laboratory of Crop Growth Regulation of Ministry of Agriculture, Nanjing Agricultural University, Nanjing,
Jiangsu 210095, P. R. China.
B Corresponding author. Email: caow@njau.edu.cn
Australian Journal of Agricultural Research 58(11) 1077-1085 https://doi.org/10.1071/AR06413
Submitted: 21 December 2006 Accepted: 3 September 2007 Published: 26 November 2007
Abstract
Non-destructive and quick methods for assessing leaf nitrogen (N) status are helpful for precision N management in field crops. The present study was conducted to determine the quantitative relationships of leaf N concentration on a leaf dry weight basis (LNC) and leaf N accumulation per unit soil area (LNA) to ground-based canopy spectral reflectance in rice (Oryza sativa L.). Time-course measurements were taken on canopy spectral reflectance, LNC, and leaf dry weights, with 4 field experiments under different N application rates and rice cultivars across 4 growing seasons. All possible ratio vegetation indices (RVI), difference vegetation indices (DVI), and normalised difference vegetation indices (NDVI) of key wavebands from the MSR16 radiometer were calculated. The results showed that LNC, LNA, and canopy reflectance spectra all markedly varied with N rates, with consistent change patterns among different rice cultivars and experiment years. There were highly significant linear correlations between LNC and canopy reflectance in the visible region from 560 to 710 nm (|r| > 0.85), between LNA and canopy reflectance from 760 to 1100 nm (|r| > 0.79), and from 460 to 710 nm wavelengths (|r| > 0.70). Among all possible RVI, DVI, and NDVI of key wavebands from the MSR16 radiometer, NDVI of 1220 and 710 nm was most highly correlated to LNC, and RVI of 950 and 660 nm and RVI of 950 and 680 nm were the best spectral indices for quantitative monitoring of LNA in rice. The average relative root mean square errors (RRMSE) between the predicted LNC and LNA and the observed values with independent data were no more than 11% and 25%, respectively. These results indicated that the canopy spectral reflectance can be potentially used for non-destructive and real-time monitoring of leaf N status in rice.
Additional keywords: leaf nitrogen accumulation, leaf nitrogen concentration, nitrogen monitoring, Oryza sativa L., remote sensing, spectral index.
Acknowledgments
We acknowledge the financial support of the National Natural Science Foundation of China (30571092), State Hi-tech R&D Plan of China (2006AA10A303, 2006AA10Z202), Natural Science Foundation (BK2005212), and Hi-tech Research Plan (BG2006340) of Jiangsu Province for this research.
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