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Research on the Optimum Water Content of Detecting Soil Nitrogen Using Near Infrared Sensor

机译:近红外传感器检测土壤氮气最佳含水量的研究

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摘要

Nitrogen is one of the important indexes to evaluate the physiological and biochemical properties of soil. The level of soil nitrogen content influences the nutrient levels of crops directly. The near infrared sensor can be used to detect the soil nitrogen content rapidly, nondestructively, and conveniently. In order to investigate the effect of the different soil water content on soil nitrogen detection by near infrared sensor, the soil samples were dealt with different drying times and the corresponding water content was measured. The drying time was set from 1 h to 8 h, and every 1 h 90 samples (each nitrogen concentration of 10 samples) were detected. The spectral information of samples was obtained by near infrared sensor, meanwhile, the soil water content was calculated every 1 h. The prediction model of soil nitrogen content was established by two linear modeling methods, including partial least squares (PLS) and uninformative variable elimination (UVE). The experiment shows that the soil has the highest detection accuracy when the drying time is 3 h and the corresponding soil water content is 1.03%. The correlation coefficients of the calibration set are 0.9721 and 0.9656, and the correlation coefficients of the prediction set are 0.9712 and 0.9682, respectively. The prediction accuracy of both models is high, while the prediction effect of PLS model is better and more stable. The results indicate that the soil water content at 1.03% has the minimum influence on the detection of soil nitrogen content using a near infrared sensor while the detection accuracy is the highest and the time cost is the lowest, which is of great significance to develop a portable apparatus detecting nitrogen in the field accurately and rapidly.
机译:氮是评价土壤的生理生化特性的重要指标之一。土壤氮含量的高低直接影响农作物的营养水平。近红外检测器可以用于检测土壤氮含量迅速,非破坏性地,方便。为了研究由近红外传感器对土壤氮素检测不同土壤水分含量的效果,土壤样品进行了处理不同的干燥时间,并测量相应的水含量。干燥时间为1个小时至8小时,并检测每1个小时90个样品(10个样品每个氮浓度)。通过近红外传感器获得的样本的光谱信息,同时,土壤水分含量计算每1个小时。的土壤氮含量的预测模型是由两个线性建模方法,包括偏最小二乘法(PLS)和无信息变量消除(UVE)建立的。实验结果表明,在土壤具有最高的检测精度时,干燥时间为3小时,对应的土壤水分含量是1.03%。校准组的相关系数是0.9721和0.9656,以及预测套组的相关系数分别为0.9712和0.9682。两个模型的预测精度高,而PLS模型的预测效果更好,更稳定。结果表明,在1.03%的土壤含水量已经使用近红外线传感器,而检测精度最高,时间成本是最低的,这是发展具有重要的意义在检测土壤氮含量的影响最小便携式设备在现场准确和快速检测氮。

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