Abstract:
Nitrogen nitrates play a significant role in the soil\'s nutrient cycle, and near-infrared spectroscopy can efficiently and accurately detect the content of nitrate-nitrogen in the soil. Accordingly, it can provide a scientific basis for soil improvement and agricultural productivity by deeply examining the cycle and transformation pattern of nutrients in the soil. To investigate the impact of drying temperature on NIR soil nitrogen detection, soil samples with different N concentrations were dried at temperatures of 50 °C, 65 °C, 80 °C, and 95 °C, respectively. Additionally, soil samples naturally air-dried at room temperature (25 °C) were used as a control group. Different drying times were modified based on the drying temperature to completely eliminate the impact of moisture. Following data collection with an NIR spectrometer, the best preprocessing method was chosen to handle the raw data. Based on the feature bands chosen by the RFFS, CARS, and SPA methods, two linear models, PLSR and SVM, and a nonlinear ANN model were then established for analysis and comparison. It was found that the drying temperature had a great effect on the detection of soil nitrogen by near-infrared spectroscopy. In the meantime, the SPA-ANN model simultaneously yielded the best and most stable accuracy, with Rc2 = 0.998, Rp2 = 0.989, RMSEC = 0.178 g/kg, and RMSEP = 0.257 g/kg. The results showed that NIR spectroscopy had the least effect and the highest accuracy in detecting nitrogen at 80 °C soil drying temperature. This work provides a theoretical foundation for agricultural production in the future.
摘要:
硝酸氮在土壤养分循环中起着重要作用,近红外光谱技术可以高效、准确地检测土壤中的硝态氮含量。因此,通过深入研究土壤养分的循环和转化模式,可以为土壤改良和农业生产力提供科学依据。为探讨干燥温度对近红外土壤氮素检测的影响,将具有不同氮浓度的土壤样品在50°C的温度下干燥,65°C,80°C,和95°C,分别。此外,在室温(25°C)下自然风干的土壤样品用作对照组。根据干燥温度修改不同的干燥时间以完全消除水分的影响。用近红外光谱仪收集数据后,选择最佳的预处理方法来处理原始数据。根据RFFS选择的特征带,汽车,和SPA方法,两个线性模型,PLSR和SVM,然后建立非线性神经网络模型进行分析比较。研究发现,干燥温度对近红外光谱检测土壤氮素有很大影响。同时,SPA-ANN模型同时产生了最佳和最稳定的准确性,Rc2=0.998,Rp2=0.989,RMSEC=0.178g/kg,RMSEP=0.257g/kg。结果表明,近红外光谱在80℃土壤干燥温度下检测氮的效果最小,准确度最高。为今后的农业生产提供了理论基础。