摘要
以检测土壤有机质含量为例,探讨经验模态分解在土壤近红外光谱检测中的应用,提出了应用的原理和步骤。用处理后的光谱计算了土壤中的有机质含量,并与九点平滑和小波变换方法的处理结果进行了对比分析。结果表明:与传统的九点平滑处理结果相比,SNR从3 dB左右提高到10 dB左右,原始信号与消噪信号之间的标准差由2.972降到0.901;预测集的决定系数r2由0.941 0提高到0.980 3,预测均方根误差RMSEP由0.670 2降为0.301 1。证明了经验模态分解方法在光谱处理过程中的可靠性,提高了土壤有机质含量近红外光谱的定量分析精度。
Taking detection of soil organic matter content as an example,this paper discussed the application method of empirical mode decomposition（EMD） for processing soil near-infrared（NIR） differential spectrum using empirical mode decomposition.And the principles and steps of processing were proposed.Then the soil organic matter content was calculated based on the de-noised spectrum,and it was compared with the result from the nine-point smoothing method and wavelet method.Experimental results showed that the SNR was improved from 3 dB to 10 dB,and the root mean square error of between raw signal and de-noised signal were reduced to 0.901 from 2.972.The correlation ratio of the prediction set was improved to 0.980 3 from 0.941 0,and the RMSEP was reduced to 0.301 1 from 0.670 2.This improved that EMD is effective to get the pretreatment of NIR spectrum,and the EMD method improves the accuracy of near-infrared spectrum detection of soil organic matter content.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2010年第9期182-186,共5页
Transactions of the Chinese Society for Agricultural Machinery
基金
湖南省"十一五"重点建设学科基金资助项目
湖南文理学院优秀青年项目(YXQN0904)
关键词
土壤有机质
检测
经验模态分解
近红外光谱
信噪比
去噪
Soil organic matter
Detection
Empirical mode decomposition
Near-infrared spectrum
Signal-to-noise
De-noising
