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Linking soil N dynamics and plant N uptake by means of sensor support
European Journal of Agronomy ( IF 4.5 ) Pub Date : 2022-02-01 , DOI: 10.1016/j.eja.2022.126462
F. Argento 1, 2, 3 , F. Liebisch 2, 3 , M. Simmler 1 , C. Ringger 3 , M. Hatt 1 , A. Walter 2 , T. Anken 1
Affiliation  

Monitoring the spatial and temporal plant availability of nitrogen (N) in agroecosystems is a key step to improve the synchronization between N fertilizer application and crop N demand, consequently reducing the risk of N emissions to the environment. Using a winter wheat N fertilization dataset from six site-years, we linked dynamic nitrate data measured in the soil solution to standard soil and crop analyses data and multispectral imagery acquired by an unmanned aerial vehicle. Wheat N uptake was determined as remotely estimated N uptake (REN) from the spectral data with a power regression model (mean absolute error = 17 kg N ha−1). The nitrate-N in the soil solution (NSS), extracted by means of suction cups, was measured with an ion-selective electrode. The REN proved to be suitable for monitoring the accumulation of N in the plants along the season. The NSS was characterized by low values and found of limited use as a direct indicator for potentially plant-available N. The N balances resulted in N surplus in the range of 43–100 kg N ha−1 over the six site-years. The most important contribution to the N balances was the soil N supply (67–143 kg N ha−1; mineralization and atmospheric input). Including this factor in the fertilization strategy was investigated post-season by calculating the ‘adjusted N fertilization norm’, reflecting the current best fertilization practice in Switzerland. The approach suggested lower N fertilization rates in the fields with higher N surplus. However, such static empirical strategies do not allow to react to in-season changes. Sensor-based monitoring could help to overcome this shortcoming.



中文翻译:

通过传感器支持将土壤 N 动态与植物 N 吸收联系起来

监测农业生态系统中氮 (N) 的时空植物可用性是提高氮肥施用和作物氮需求之间同步的关键步骤,从而降低氮排放到环境中的风险。使用来自六个地点年的冬小麦氮肥数据集,我们将土壤溶液中测量的动态硝酸盐数据与标准土壤和作物分析数据以及无人机获取的多光谱图像联系起来。小麦 N 吸收确定为使用功率回归模型从光谱数据中远程估计的 N 吸收 (REN)(平均绝对误差 = 17 kg N ha -1)。通过吸盘提取的土壤溶液 (NSS) 中的硝酸盐-N 用离子选择电极测量。事实证明,REN 适用于监测植物中 N 在整个季节的积累。NSS 的特点是低值,发现作为潜在植物可利用 N 的直接指标的用途有限。N 平衡导致在六个地点年的 N 盈余在 43-100 kg N ha -1范围内。对 N 平衡最重要的贡献是土壤 N 供应(67–143 kg N ha -1; 矿化和大气输入)。通过计算“调整后的 N 施肥标准”,对在施肥策略中包含这一因素进行了调查,反映了瑞士目前的最佳施肥实践。该方法表明在氮过剩较高的田地中氮施肥率较低。然而,这种静态的经验策略不允许对季节变化做出反应。基于传感器的监测可以帮助克服这一缺点。

更新日期:2022-02-01
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