Monitoring leaf nitrogen in rice using canopy reflectance spectra

被引:0
|
作者
Tian, Yongchao [1 ]
Zhou, Dongqin [1 ]
Yao, Xia [1 ]
Cao, Weixing [1 ]
Zhu, Yan [1 ]
机构
[1] Nanjing Agr Univ, Hi Tech Key Lab Informat Agr Jiangsu Province, Jiangsu 210095, Peoples R China
关键词
leaf nitrogen accumulation; leaf nitrogen concentration; nitrogen monitoring; Oryza sativa L; remote sensing; spectral index;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Non-destructive monitoring of leaf nitrogen (N) status can assist in growth diagnosis, N management and productivity forecast in field crops. The primary objective of this study was 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 reflectance spectra in rice (Oryza sativa L.). Four field experiments were conducted with different N application rates and rice cultivars across four growing seasons, and time-course measurements were taken on canopy spectral reflectance, LNC and leaf dry weights under the various treatments. In these studies, 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 560nm to 710nm (vertical bar r vertical bar > 0.85), and an integrated regression equation of LNC to normalized difference vegetation index (NDVI) of 1220nm and 710nm described the dynamic change pattern in LNC in rice. Canopy reflectance in the range from 760nm to] 100nm (vertical bar r vertical bar > 0.79), and from 460nm to 710nm wavelengths (vertical bar r vertical bar > 0.70) was highly linear related to LNA. The ratio vegetation index (RVI) of 950nm and 660nm and RVI of 950nm and 680nm were the best spectral indices for quantitative estimation of LNA in rice. The average relative root mean square error (RRMSE) values for the predicted LNC and LNA relative to the observed values with independent data were no more than 11% and 25%, respectively, indicating a good fit. Our relationships of LNC and LNA to spectral indices of canopy reflectance can be potentially used for non-destructive and real-time monitoring of leaf N status in rice.
引用
收藏
页码:639 / 649
页数:11
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