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Dependency Measures for Assessing the Covariation of Spectrally Active and Inactive Soil Properties in Diffuse Reflectance Spectroscopy

机译:评估弥漫性反射光谱中光谱活性和无活性土壤性质的协变的依赖性措施

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摘要

Diffuse reflectance spectroscopy (DRS) is a rapid and noninvasive assessment technique for several spectrally active soil properties (chromophores) such as sand, clay, organic C, and Fe contents. The approach is also used for estimating many spectrally inactive constituents (non-chromophores) based on the assumption of covariation between non-chromophores and chromophores. The linkage between covariation and the ability of DRS to estimate a non-chromophore has not been reported in the literature. In this study, we evaluated the covariation assumption using three dependency measures (Pearson correlation coefficient, r; biweight midcorrelation, bicor; and mutual information based adjacency, AMI), five chromophores (organic C, Fe, clay, and sand contents, and geometric mean diameter), and seven non-chromophores (pH, electrical conductivity, P, K, B, Zn, and Al contents) measured in 247 Alfisol and 249 Vertisol samples. An average dependency index (ADI) was developed for each of the three measures (ADIr, ADIbicor, and ADIAMI). The first derivative of the reflectance in conjunction with partial least squares regression was used for data modeling. Model accuracy was evaluated using residual prediction deviation (RPD). The relationships between RPD values of non-chromophores and the ADI values were examined for different chromophore groups (physical, chemical, and combined). The performance of ADIAMI was found to be superior to ADIr and ADIbicor. The ADIAMI computed using chemical chromophores gave strong linear relationships (R2 = 0.93) between ADIAMI and the RPD of chemical non-chromophores, suggesting that the AMI may be used as a robust dependency measure to assess the covariation of non-chromophores with chromophores in DRS.
机译:弥漫反射光谱(DRS)是一种快速和非侵入性评估技术,用于几种光谱活性土壤(发色团),如砂,粘土,有机C和Fe含量。该方法还用于基于非发色团和发色团之间的共变量的假设估计许多光谱活性成分(非发色团)。在文献中尚未报告协变性与DRS估计非发色团的能力之间的联系。在这项研究中,我们使用三个依赖措施(Pearson相关系数,R; Biweight Medcorrelation,Bicor;和相互信息基于邻接,AMI),五种发色团(有机C,Fe,Clay和砂内容物,以及几何的调节假设在247羟乙醇和249个转胶样品中测量的平均直径)和七种非发色体(pH,电导率,P,K,B,Zn和Al含量)。为三项措施(Adir,Adibicor和Adiami)中的每一个开发了平均依赖指数(ADI)。结合偏最小二乘回归的反射率的第一导数用于数据建模。使用剩余预测偏差(RPD)评估模型精度。检查非发色团的RPD值与ADI值之间的关系,用于不同的发色团(物理,化学和合并)。发现Adiami的表现优于阿迪尔和替代者。使用化学色团计算的Adiami在Adiami和化学非发色团的RPD之间进行了强烈的线性关系(R2 = 0.93),表明AMI可以用作稳健的依赖措施,以评估非发色团在DRS中的发色团进行共变量。

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