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| DOI：10.13522/j.cnki.ggps.2019292 |
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| Estimating Nitrogen Content in Cotton Canopy Using Hyperspectral Imaging |
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MA Yanchuan, LIU Hao, CHEN Zhifang, ZHANG Kai, WANG Jinglei, SUN Jingsheng
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Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Water Use and Regulation, Ministry of Agriculture, Xinxiang 453002, China
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| Abstract: |
| 【Objective】Timely monitoring the change in nitrogen content in plant canopy can improve fertilization, and in this paper we investigated the feasibility of using hyperspectral imagining to estimate nitrogen in carbon canopy under different irrigation and fertilization gradients.【Method】The irrigation and nitrogen application gradients were established in a field. During the growth period of the cotton, we measured spectral reflectance, canopy nitrogen content and canopy equivalent water thickness (CEWT) concurrently. The impacts of nitrogen content and the equivalent water thickness on the spectral index were quantitatively analyzed to determine the optimal spectral index that can be used to estimate the nitrogen content in the cotton canopy. 【Result】The spectra that were most sensitive to the canopy nitrogen content were the wave between the visible and near-infrared bands, and the maximum correlation coefficient between them was 0.53 at the band of 718 nm. The NDSI (800,770) gave the best results with R2=0.76 without considering the influence of CEWT, but it was less accurate for estimating canopy nitrogen content at the flower-boll stage. Considering the influence of CEWT, we chose NDSI (570, 500) as the optimal spectral index which can reduce errors caused by water content (RRMSE=0.18). 【Conclusion】The NDSI(570, 500), a moisture-insensitive spectral index established in this paper, can effectively improve estimation of nitrogen content in cotton canopy, providing a quick way to estimate nitrogen content in plant canopy of cotton at large scales. |
| Key words: hyperspectral; cotton; different water gradients; canopy nitrogen content |
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