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In-season estimation of spring maize nitrogen status with GreenSeeker active canopy sensor

机译:绿塞克斯有源冠层传感器春季玉米氮现状的季节估计

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Precision nitrogen (N) management (PNM) is a promising strategy to improve N use efficiency and protect the environment while maintaining or increasing crop yield. In-season non-destructive diagnosis of crop N status is crucial for the success of this strategy. The objectives of this study were to (i) evaluate how well the GreenSeeker active canopy sensor can non-destructively estimate N status indicators of spring maize (Zea mays L.) in Northeast China and (ii) evaluate different N status diagnostic approaches based on N nutrition index (NNI) estimated via GreenSeeker sensor measurements. Two N rate field experiments involving 6 N rates (0, 60, 120,180, 240, and 300 kg N ha) were conducted in 2014 in Lishu County, Jilin Province in Northeast China. The results indicated that across sites and growth stages, GreenSeeker-based vegetation indices explained 89%-90% and 80%-86% of maize aboveground biomass and plant N uptake variability, respectively. The performance of GreenSeeker for estimating N status indicators from crop growth stage V7 to V10 was better than early growth stages (V5 and V6). The normalized difference vegetation index (NDVI) became saturated when aboveground biomass reached about 3.1 t ha or plant N uptake reached about 75 kg ha; whereas no obvious saturation effect was found with ratio vegetation index (RVI). Across growth stages, about 50% of variability in maize N concentration was explained, but the standard error of estimate (SEa) was not acceptable. The NNI values were significantly correlated with GreenSeeker-based vegetation indices, with R being 0.64-0.80 at a specific growth stage. It is concluded that the GreenSeeker sensor has good potential for in-season non-destructive diagnosis of spring maize N status at V7-V8, but more studies are needed to further evaluate and improve its performance for practical applications.
机译:精密氮气(N)管理(PNM)是一种有希望的策略,可提高N利用效率,并在保持或增加作物产量的同时保护环境。季节性非破坏性诊断作物N状况对于这一战略的成功至关重要。本研究的目标是(i)评估绿赛克人有源冠覆传感器如何在东北地区的春季玉米(Zea Mays L.)的N个状态指标。(ii)基于以下评估不同的N个地位诊断方法N营养指数(NNI)通过GreenSeeker传感器测量估计。 2014年吉林省吉林省吉林县的2014年,涉及6吨率(0,60,120,180,240,240和300kg N和300公斤HA)的两个N率现场实验。结果表明,跨越地点和生长阶段,基于格林赛克的植被指数分别解释了89%-90%和80%-86%的玉米地上生物量和植物N吸收变异。从作物生长阶段V7至V10估算N个状态指标的绿塞克的性能优于早期生长阶段(V5和V6)。当地上生物量达到约3.1 t ha或植物n摄取时,归一化差异植被指数(NDVI)变得饱和而达到约75千克HA;虽然没有明显的饱和度效应,但植被指数(RVI)。跨越生长阶段,解释了玉米N浓度的约50%变异,但估计(海)的标准误差是不可接受的。 NNI值与基于Greenseeker的植被指数显着相关,R为0.64-0.80在特定的生长期。得出结论是,格林赛克传感器在V7-V8时具有良好的春季无损诊断季节性诊断潜力,但需要更多的研究来进一步评估和改善其对实际应用的性能。

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