您好，欢迎访问北京市农林科学院 机构知识库！
北京市农林科学院机构知识库

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

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

作者： Wang Shi-fang 1 ; Han Ping 1 ; Song Hai-yan 2 ; Liang Gang 1 ; Cheng Xu 2 ;

作者机构： 1.Beijing Res Ctr Agr Stand & Testing, Beijing 100097, Peoples R China

2.Shanxi Agr Univ, Coll Engn, Taigu 030801, Peoples R China

3.Beijing Municipal Key Lab Agr Environm Monitoring, Beijing 100097, Peoples R China

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.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：北京市农林科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台