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Predicting N Status in Maize with Clip Sensors: Choosing Sensor Leaf Sampling Point and Timing

机译:使用削波传感器预测玉米中的N状态:选择传感器叶片采样点和定时

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摘要

Nitrogen (N) losses from agricultural systems increase air and water pollution, and these losses are highly correlated with the excessive fertilization. An adjusted N fertilization is then a key factor in increasing the N fertilizer efficiency, and leaf clip sensors can help to improve it. This study (combining five different field experiments in Central Spain) tried to identify the ability of the clip sensors in maize N status identification and yield prediction, comparing two different devices (SPAD-502® and Dualex®) and identifying the best protocol for maize leaf sampling. As a result, the study demonstrated that different leaf clip chlorophyll sensors presented similar results, although some differences appeared at larger N concentrations. Complementary polyphenol information (as flavonol) can improve the maize N deficiency prediction. Moreover, valuable information for a proper sampling protocol was obtained with this study. It proved that the sampling position (in the leaf and in the plant) and sampling time were crucial for a better estimation of the maize N status. Proper fertilization recommendations could be achieved based on clip chlorophyll sensor measurements.
机译:农业系统中的氮损失增加了空气和水的污染,这些损失与过度施肥高度相关。调整后的氮肥利用率是提高氮肥利用率的关键因素,叶夹传感器可以帮助改善氮肥利用率。这项研究(结合西班牙中部的五个不同的田间试验)试图通过比较两个不同的设备(SPAD-502 ®和Dualex ®),并确定玉米叶片采样的最佳方案。结果,该研究表明不同的叶夹叶绿素传感器表现出相似的结果,尽管在较大的氮浓度下会出现一些差异。补充多酚信息(如黄酮醇)可以改善玉米氮素缺乏的预测。此外,这项研究还为正确的采样方案提供了有价值的信息。事实证明,采样位置(在叶片和植物中)和采样时间对于更好地估算玉米氮素状况至关重要。根据夹子叶绿素传感器的测量结果,可以实现适当的施肥建议。

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