土壤含水量对反射光谱法预测红壤土壤有机质的影响研究

研究土壤含水量对有机质预测的影响,可为野外红壤有机质快速测定提供理论依据。本文在实验室条件下测量了不同含水量红壤的可见光-近红外光谱反射率,运用偏最小二乘回归(PLSR)建立不同含水量的土壤有机质预测模型。结果显示,随土壤含水量的增加,有机质与一阶微分光谱的相关性先增加后下降,含水量为100～150 g/kg时相关系数最大。分380～2 400、380～1 300、1 300～2 400 nm三个波段建立不同含水量的有机质预测模型,模型预测精度均随土壤含水量增加而呈现先增加后下降的趋势。利用1 300～2 400 nm建立有机质预测模型可以有效避开氧化铁影响,建立的模型预测精度最高。本研究认为,当土壤含水量小于200 g/kg时,可以利用在室内控制条件下测定的土壤反射率,建立1 300～2 400 nm波段的PLSR模型,进行红壤土壤有机质含量预测。

Effects of soil moisture on determining red soil organic matter using VIS-NIR diffuse reflectance spectroscopy

The effect of soil moisture on the determination of red soil organic matter (SOM) is a theoretical basis for the rapid predication of SOM in the flied. Spectral measurements (350-2 500 nm) of soil samples under different moistures were conducted in a controlled laboratory environment and partial least-squares regression (PLSR) was used to establish SOM prediction model. The results showed that the correlation of SOM and first order derivative reflectance firstly were increased, and then decreased as soil moisture increased, the highest correlation occurred when soil moisture was at 100-150 g/kg. Spectral regions of 380-2 400 nm, 380-1 300 nm and 1 300-2 400 nm were selected to establish SOM prediction models under different soil moistures. The accuracy of prediction model were increased firstly and then decreased with the increase of soil moisture. Using 1 300-2 400 nm to build SOM prediction model could avoid the influence of iron oxide and get highest prediction accuracy. The results demonstrated that when soil moisture was less than 200 g/kg, SOM of red soil could be predicted by PLSR using first order derivative reflectance in 1 300-2 400 nm under a controlled environment.