Application of Slope/Bias and Direct Standardization Algorithms to Correct the Effect of Soil Moisture for the Prediction of Soil Organic Matter Content Based on the Near Infrared Spectroscopy

文献类型： 外文期刊

第一作者： Wang Shi-fang

作者： Wang Shi-fang;Han Ping;Liang Gang;Wang Shi-fang;Song Hai-yan;Cheng Xu;Wang Shi-fang;Han Ping;Liang Gang

作者机构：

关键词： Slope/bias algorithm; Direct standardization algorithm; Soil moisture; Soil organic matter; Near infrared spectroscopy

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 影响因子：0.589； 五年影响因子：0.504 ）

ISSN： 1000-0593

年卷期： 2019 年 39 卷 6 期

页码：

收录情况： SCI

摘要： Soil moisture has strong absorption in near infrared spectroscopy (NIRS) and causes interference in the prediction of the soil organic matter (SOM) content. In this paper, 41 dry soil samples were used to establish the SOM calibration model by PLSR, and 9 samples were used as the prediction set. All soil samples were rewetted to four different moisture contents (5%, 10%, 15% and 17%). The slope/bias (S/B) and direct standardization (DS) algorithms were used to correct SOM prediction results and whole-spectra obtained by different moisture content, eliminating the differences caused by soil moisture. The results showed that the bias reduced and prediction performances of the model were improved, with R-p higher than 0.89 and RMSEP lower than 0.885%. The study indicated that S/B and DS algorithm corrections could effectively remove the influence of soil moisture in NIRS and improve the accuracy of SOM predictions.

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