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Canopy Nitrogen Concentration Monitoring Techniques of Summer Corn Based on Canopy Spectral Information

机译:基于冠层光谱信息的夏玉米冠层氮浓度监测技术

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摘要

Crop nitrogen monitoring techniques, particularly choosing sensitive monitoring bands and suitable monitoring models, have great significance both in theory and in practice for achieving non-destructive monitoring of nitrogen concentration and accurate management of water and fertilizer in large-scale areas. In this study, a lysimeter experiment was carried out to examine the characteristics of canopy spectral reflectance variation of summer corn under different fertilization levels. The relationship between canopy spectral reflectance and nitrogen concentration was investigated, based on which sensitive bands for the corn canopy nitrogen monitoring were selected and a suitable spectral index model was determined. The results suggest that under different fertilization levels, the canopy spectral reflectance of summer corn decreases with the increase of the canopy nitrogen concentration in the visible light band, but varies in the opposite direction in the near-infrared band, with a premium put on a higher correlation between the spectral reflectance of the characteristic bands and their first derivatives and the canopy nitrogen concentration. The most sensitive bands for monitoring the canopy nitrogen concentration using spectral reflectance and its first derivative are found to be 762 nm and 726 nm and the correlation coefficients are 0.550 and 0.795, respectively. The optimal band combination, generated by multivariate stepwise regression analysis, is composed of 762 nm, 944 nm and 957 nm bands. From the 55 reported spectral index models of crop nitrogen concentration monitoring, the most suitable index model, NDRE, is chosen such that this index model has the highest correlation with the canopy nitrogen concentration in summer corn. This model has a significant positive correlation with the canopy nitrogen concentration at each growth period, and the correlation coefficient is up to 0.738 during the whole growth period. Spectral monitoring models of canopy nitrogen concentration are constructed using sensitive bands, and a combination of bands and the spectral index, suggesting that these models perform well in monitoring. The models arranged in descending order of simulation accuracy are as follows: the suitable spectral index model, the optimal band combination model, the sensitive band reflectance first derivative model, the sensitive band reflectance model. The determination coefficients are 0.754, 0.711, 0.639 and 0.306, respectively.
机译:作物氮素监测技术,特别是选择敏感的监测带和合适的监测模型,在理论上和实践中对于实现大范围氮素浓度的无损监测和水肥的精确管理都具有重要意义。在这项研究中,进行了溶渗仪实验,研究了不同施肥水平下夏玉米冠层光谱反射率变化的特征。研究了冠层光谱反射率与氮素浓度之间的关系,在此基础上选择了玉米冠层氮素监测的敏感带,确定了合适的光谱指数模型。结果表明,在不同施肥水平下,夏玉米冠层光谱反射率随可见光波段冠层氮浓度的增加而降低,但在近红外波段却相反。特征谱带及其一阶导数的光谱反射率与冠层氮浓度之间的相关性更高。使用光谱反射率及其一阶导数监测冠层氮浓度的最灵敏带为762 nm和726 nm,相关系数分别为0.550和0.795。通过多元逐步回归分析生成的最佳波段组合由762 nm,944 nm和957 nm波段组成。从报告的55种作物氮浓度监测光谱指数模型中,选择最合适的指数模型NDRE,以使该指数模型与夏季玉米冠层氮浓度具有最高的相关性。该模型在每个生育期与冠层氮浓度呈显着的正相关,在整个生育期相关系数高达0.738。冠层氮浓度的光谱监测模型是使用敏感谱带以及谱带和光谱指数的组合构建的,表明这些模型在监测中表现良好。这些模型按仿真精度的降序排列如下:合适的光谱指数模型,最佳波段组合模型,敏感波段反射率一阶导数模型,敏感波段反射率模型。判定系数分别为0.754、0.711、0.639和0.306。

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