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Real-time soil sensing based on fiber optics and spectroscopy

机译:基于光纤和光谱的实时土壤感应

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Using NIR spectroscopic techniques, correlation analysis and regression analysis for soil parameter estimation was conducted with raw soil samples collected in a cornfield and a forage field. Soil parameters analyzed were soil moisture, soil organic matter, nitrate nitrogen, soil electrical conductivity and pH. Results showed that all soil parameters could be evaluated by NIR spectral reflectance. For soil moisture, a linear regression model was available at low moisture contents below 30 % db, while an exponential model can be used in a wide range of moisture content up to 100 % db. Nitrate nitrogen estimation required a multi-spectral exponential model and electrical conductivity could be evaluated by a single spectral regression. According to the result above mentioned, a real time soil sensor system based on fiber optics and spectroscopy was developed. The sensor system was composed of a soil subsoiler with four optical fiber probes, a spectrometer, and a control unit. Two optical fiber probes were used for illumination and the other two optical fiber probes for collecting soil reflectance from visible to NIR wavebands at depths around 30 cm. The spectrometer was used to obtain the spectra of reflected lights. The control unit consisted of a data logging device, a personal computer, and a pulse generator. The experiment showed that clear photo-spectral reflectance was obtained from the underground soil. The soil reflectance was equal to that obtained by the desktop spectrophotometer in laboratory tests. Using the spectral reflectance, the soil parameters, such as soil moisture, pH, EC and SOM, were evaluated.
机译:利用NIR光谱技术,用玉米田和牧场收集的原料土样品进行了土壤参数估计的相关分析和回归分析。分析土壤参数是土壤水分,土壤有机物,硝酸盐氮,土壤导电性和pH。结果表明,所有土壤参数都可以通过NIR光谱反射来评估。对于土壤水分,在低于30%dB的低水分含量下提供线性回归模型,而指数模型可用于宽范围的水分含量,高达100%DB。硝酸盐氮估计需要多光谱指数模型,并且可以通过单一光谱回归来评估电导率。根据上述结果,开发了一种基于光纤和光谱的实时土壤传感器系统。传感器系统由具有四种光纤探针,光谱仪和控制单元的土壤底线组成。两种光纤探针用于照明,另外两个光纤探针用于在约30厘米约为30厘米的深度下从可见的土壤反射率。光谱仪用于获得反射光的光谱。控制单元由数据记录设备,个人计算机和脉冲发生器组成。实验表明,从地下土壤中获得清晰的光谱反射率。土壤反射率等于通过桌面分光光度计在实验室测试中获得的。使用光谱反射率,评估土壤参数,如土壤水分,pH,EC和SOM。

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