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• W3035337555 abstract "Canopy nitrogen content in wheat is a key indicator of wheat grain yield and quality. When using remote sensing technology to predict wheat canopy nitrogen content, a hyperspectral mode with high adaptability and high accuracy is needed to improve the inversion efficiency. We developed a new three-band spectral vegetation index (NEW-NDRE) by combining a two-band spectral index NDRE and the spectral reflectance at 550 nm based on field data collected from different sites, years, with different varieties and nitrogen levels and at multiple growth stages. The NEW-NDRE was compared with 11 traditional spectral vegetation indices in terms of wheat canopy nitrogen content inversion. NEW-NDRE and three traditional indices (NDRE, NDDA and RI-1dB) all closely correlated with wheat canopy nitrogen content. NEW-NDRE displayed the highest correlation with wheat canopy nitrogen content at early grain filling stage, with a coefficient (R2) of 0.9 and a root mean squared error (RMSE) of 0.4. The inversion model developed with the NEW-NDRE was validated with an independent dataset. The relative error (RE) of the model was 9.3%, which was significantly lower than that of NDRE, NDDA and RI-1dB. Generally, NEW-NDRE is a more robust index for wheat canopy nitrogen content inversion than traditional indices through eliminating environmental limitation, and it could be used as a new tool for precise fertilizer application.冬小麦冠层叶片氮含量是反映其产量与品质的重要指标,构建高普适性、高精准性冬小麦冠层叶片氮含量高光谱反演模型对提高其监测效率具有重要意义。以不同地点、品种、年份、施氮水平、生育期的大田试验数据为基础,基于两波段光谱植被指数NDRE和550 nm光谱反射率组合构建一个三波段植被指数NEW-NDRE,并与11个传统冬小麦冠层叶片氮素光谱指数进行比较。结果表明: NEW-NDRE及传统植被指数中NDRE、NDDA、RI-1dB与冬小麦冠层叶片氮含量的相关性较好;其中,灌浆初期NEW-NDRE与冬小麦冠层叶片氮含量相关性最好,决定系数R2为0.9,均方根误差(RMSE)为0.4;经独立数据检验,以NEW-NDRE为变量建立的冬小麦冠层叶片氮含量反演模型的平均相对误差(RE)为9.3%,明显低于以NDRE、NDDA、RI-1dB为变量的模型RE。总体上,新构建的NEW-NDRE对冬小麦冠层叶片氮含量的模拟能力显著优于传统指数,减弱了试验条件的限制性,可为精准施肥提供新的技术支撑。." @default.
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• W3035337555 date "2020-05-01" @default.
• W3035337555 modified "2023-10-18" @default.
• W3035337555 title "[Nitrogen content inversion of wheat canopy leaf based on ground spectral reflectance data]." @default.
• W3035337555 doi "https://doi.org/10.13287/j.1001-9332.202005.022" @default.
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