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

机译:使用拖拉机安装N传感器对小麦作物中氮估计的校准和算法开发

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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) andSISPADto calculate theNappas a function ofSISPAD. 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:计划进行实验,以研究拖拉机安装的N-传感器(使Yara International)以预测不同氮水平下的小麦作物的氮(n)。观察到,对于拖拉机安装的N-传感器,光谱仪可以扫描所考虑的作物总面积的约32%。使用传感器充足索引(Sisensor)和SisPad之间的线性关系来开发一种算法,计算该函数的SISPAD。传感器属性(传感器值,传感器生物质和传感器NDVI)和不同的N级存在强烈的相关性。得出结论是,通过使用传感器属性,分蘖期是预测作物产量的最突出阶段。为分蘖和引导阶段开发的算法对于预测小麦作物的N申请率是有用的。由算法预测的N申请率和传感器值对于具有不同级别的N级别的曲线几乎相同。

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