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Calibration and Algorithm Development for Estimation of Nitrogen in Wheat Crop Using Tractor Mounted N-Sensor

机译:拖拉机安装N传感器的小麦作物氮素校准和算法开发

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摘要

The experiment was planned to investigate the tractor mounted N-sensor (Make Yara International) to predict nitrogen (N) for wheat crop under different nitrogen levels. It was observed that, for tractor mounted N-sensor, spectrometers can scan about 32% of total area of crop under consideration. An algorithm was developed using a linear relationship between sensor sufficiency index (SIsensor) and SISPAD to calculate the Napp as a function of SISPAD. There was a strong correlation among sensor attributes (sensor value, sensor biomass, and sensor NDVI) and different N-levels. It was concluded that tillering stage is most prominent stage to predict crop yield as compared to the other stages by using sensor attributes. The algorithms developed for tillering and booting stages are useful for the prediction of N-application rates for wheat crop. N-application rates predicted by algorithm developed and sensor value were almost the same for plots with different levels of N applied.
机译:计划进行该实验以研究安装在拖拉机上的N传感器(Make Yara International)在不同氮水平下预测小麦作物的氮(N)。据观察,对于安装在拖拉机上的N传感器,光谱仪可以扫描正在考虑的农作物总面积的约32%。利用传感器充足指数(SIsensor)和SISPAD之间的线性关系开发了一种算法,以计算Napp作为SISPAD的函数。传感器属性(传感器值,传感器生物量和传感器NDVI)与不同的N水平之间存在很强的相关性。结论是,与其他阶段相比,分sensor期是通过使用传感器属性来预测作物产量的最重要阶段。为分er和孕穗期开发的算法可用于预测小麦的氮肥施用量。通过开发的算法预测的氮肥施用率和传感器值在氮肥水平不同的情况下几乎相同。

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