中文摘要：

野外进行土壤有机质的光谱快速预测时需考虑土壤含水量的影响。在室内设计人工加湿实验分别获取9个土壤含水量梯度（0—32％，间隔4％）的土壤光谱数据，分析土壤含水量变化对光谱的影响，再利用外部参数正交化法（external parameter orthogonalization，EPO）进行湿土光谱校正，并结合偏最小二乘回归和支持向量机回归分别建立土壤有机质预测模型。结果表明，土壤光谱反射率随着土壤含水量的增加呈非线性降低趋势，偏最小二乘回归模型的预测偏差比为1．16，模型不可用；经EPO算法校正后，各土壤含水量梯度之间的光谱差异性降低，能实现土壤有机质在不同土壤含水量梯度的有效估算，偏最小二乘回归和支持向量机回归模型的预测偏差比分别提高至1．76和2．15。研究结果可为田间快速预测土壤有机质提供必要参考。

英文摘要：

[Objective] Soil organic matter is an important index of soil properties, because it is vital to crop growth and soil quality. The technology of hyperspectral analysis is a rapid, convenient, low- cost and alternative method and exhibits an increasingly remarkable development potential in estimation of soil organic matter. However, when hyperspectral reflectance is used in the field, there are several external environmental factors, including soil moisture content, temperature, and surface of the soil that may affect soil spectra. Especially soil moisture content, a major limit to field hyperspectral survey, might mask the absorption features of soil organic matter, and hence dramatically lower accuracy of the prediction of soil organic matter. Therefore, it is essential to find a method capable of removing the impact of soil moisture content on spectral reflectance, so as to improve the accuracy of quantitative prediction of soil organic matter. In this paper, the EPO （external parameter orthogonalization ） algorithm was introduced for that purpose. [Method] A total of 217 soil samples were collected from the 0- 20 cm soil layer in the Jianghan Plain. In the laboratory, the soil samples were air-dried and ground to pass a sieve with mesh 〈 2 mm. Then the soil samples were analyzed separately for soil organic matter content with the potassium dichromate external heating method.The total of 217 soil samples were further divided into three non-overlapping subsets： a model calibration set （ SO ） , consisting of 122 samples and dedicated to development of a multivariate model for soil organic matter; an EPO development subset （ S1 ） consisting of 60 samples for EPO development; and a validation subset （ S2 ） consisting of 35 samples for independentEPO validation. Then, the samples in S1 and S2 were rewetted in line with the following procedure： from each soil sample 150 g oven-dried soil was weighed out, put in a black cylindrical box and rewetted along the gradient of soil moisture content inc