Abstract
Background and aims
Variations in the water and soil background in the signal path can cause variations in canopy spectral reflectance, which leads to uncertainty in estimating the canopy nitrogen (N) status. The primary objective of this study was to explore the optimum vegetation indices that were highly correlated with canopy leaf N concentration (LNC) but less influenced by the canopy leaf area index (LAI) and vegetation coverage (VC) in rice.
Methods
A systematic analysis of the quantitative relationships between various hyperspectral vegetation indices and LNC, VC and LAI was conducted based on 4-year rice field experiments using different rice varieties, N rates and planting densities. New spectral indices were derived to estimate LNC in rice under variable vegetation coverage.
Results
Although the newly developed simple green ratio indices, SR (R553, R537) and SR (R545, R538), and the three-band index (R605-R521-R682)/(R605+R521+R682) correlated well with the LNC. Only SR (R553, R537) was less influenced by VC/LAI and showed a stable performance in both the independent calibration and validation datasets. For the published indices tested in the present study, NDVIg-b and ND (R503, R483) showed a good predictive ability for the LNC. However, both of these indices and other published indices were found to be significantly dominated by the VC/LAI.
Conclusion
SR (R553, R537) was the best index to reliably estimate the LNC in rice under various cultivation conditions, and is recommended for this use. However, other spectral indices need to be examined to determine if they influenced by factors such as VC/LAI. Such studies will improve the applicability of these indices to different types of rice cultivars and production systems.
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Acknowledgments
This work was supported by grants from the National 863 High-tech Program (2013AA102301 and 2011AA100703), the National Natural Science Foundation of China (31371535), the Special Fund for Agro-scientific Research in the Public Interest (201303109), the Science and Technology Support Program of Jiangsu (BE2010395, BE2011351 and BE2012302), and a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), China.
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Tian, YC., Gu, KJ., Chu, X. et al. Comparison of different hyperspectral vegetation indices for canopy leaf nitrogen concentration estimation in rice. Plant Soil 376, 193–209 (2014). https://doi.org/10.1007/s11104-013-1937-0
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DOI: https://doi.org/10.1007/s11104-013-1937-0