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首页> 外文期刊>Agronomy Journal >Aerial Color Infrared Photography to Optimize In-Season Nitrogen Fertilizer Recommendations in Winter Wheat
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Aerial Color Infrared Photography to Optimize In-Season Nitrogen Fertilizer Recommendations in Winter Wheat

机译:航拍彩色红外摄影可优化冬小麦的季节性氮肥建议

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摘要

Remote sensing in the form of aerial color infrared (CIR) photography has been shown to be a useful tool for in-season N management in winter wheat (Triticum aestivum L.). The objectives of this study were (i) to develop a methodology for predicting in-season optimum fertilizer N rates for winter wheat at growth stage (GS) 30 directly from aerial CIR photography and (ii) to quantify how the relationships between these optimum N rates and spectral indices respond to different levels of biomass of the wheat crop. Field studies were conducted for three winter wheat growing seasons (2002-2004) over a wide range of soil conditions across North Carolina using a split-split plot randomized complete block design. Different planting date-seeding rate (PDSR) combinations were applied to create a range of biomass levels at GS 30. Different levels of N were applied at GS 25 (N25) to create a range of N supply and winter wheat radiance, and at GS 30 (N30) to measure grain yield response to N30. Aerial CIR photographs were obtained at each site at GS 30 before N applications. Significant biomass response to PDSR and yield response to N25 and N30 were observed. Optimum N30 ranged from 0 to 124 kg ha-1 with a mean of 55 kg ha-1. Better prediction of optimum N30 rates were obtained with spectral indices calculated relative to high-N reference strips compared to absolute bands or spectral indices. Biomass measured at GS 30 influenced the strength of the relationship between optimum N30 and spectral indices. When the GS-30 biomass was >1000 kg ha-1, the best predictor of optimum N30 (R2 = 0.85) was a quadratic model based on measured winter wheat radiance relative to mean radiance in the G band for the high N reference strip (Rel GS).
机译:航空彩色红外(CIR)摄影形式的遥感已被证明是用于冬小麦(Triticum aestivum L.)氮素管理的有用工具。这项研究的目的是(i)直接通过空中CIR摄影开发一种方法来预测生长阶段(GS)30的冬小麦季节内最佳肥料氮含量;以及(ii)量化这些最佳氮之间的关系。速率和光谱指数响应于小麦作物生物量的不同水平。在北卡罗来纳州的多个土壤条件下,使用分割图随机完整区组设计对三个冬小麦生长季节(2002-2004)进行了田间研究。应用了不同的播种播种量(PDSR)组合,以在GS 30处产生一定的生物量水平。在GS 25(N25)处应用了不同水平的氮,以产生一定范围的氮素供应和冬小麦辐射度,以及在GS 30(N30)以测量对N30的谷物产量响应。在进行N次施用之前,已在GS 30的每个站点获得了航空CIR照片。观察到对PDSR的显着生物量响应以及对N25和N30的产量响应。最佳N30在0到124 kg ha-1之间,平均55 kg ha-1。与绝对谱带或光谱指数相比,通过相对于高N参考条计算的光谱指数,可以更好地预测最佳N30速率。在GS 30处测得的生物量影响了最佳N30与光谱指数之间关系的强度。当GS-30生物量> 1000 kg ha-1时,最佳N30的最佳预测因子(R2 = 0.85)是一个二次模型,该模型基于测得的冬小麦辐射度相对于高氮参考条带G波段平均辐射度( Rel GS)。

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