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New Approach to Measure Soil Particulate Organic Matter in Intact Samples using X-Ray Computed Microtomography

机译:X射线计算机断层摄影术测量完整样品中土壤颗粒有机物的新方法

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摘要

Particulate soil organic matter (POM) is the biologically and chemically active fraction of soil organic matter that plays an important role in soil C processes. Measuring POM in soil samples with intact structure is crucial for a better understanding the role of the soil structure in providing physical protection to soil C. However, so far a lack of tools for POM identification has hindered progress. The objective of this study was to develop a procedure for identification and quantitative characterization of POM within intact soil samples using X-ray computed microtomography (mu-CT) images and to test performance of the proposed procedure. We used 16 4- to 6-mm soil aggregates collected at the 0- to 15-cm depth from a Typic Hapludalf soil and scanned at 6.3-mm resolution. The developed procedure combined image preprocessing steps with discriminant analysis classification. Image preprocessing was used for preliminary POM identification based on the range of gray-scale values (GVs), shape, and size of POM pieces. Final POM identification was achieved with discriminant analysis conducted using statistical and geostatistical characteristics. The POM identified in the intact individual aggregates using the proposed procedure was in a good agreement with POM measured using a conventional laboratory method (R-2 = 0.73). Of particular importance for accurate identification of POM in the images was the information on spatial characteristics of POM's GVs. To illustrate new possibilities that the use of X-ray m-CT opens in analyzing POM within intact soil samples, we also explored and reported GVs and size-volume distributions of POM particles in the studied aggregates.
机译:颗粒状土壤有机质(POM)是土壤有机质的生物和化学活性成分,在土壤C过程中起着重要作用。测量具有完整结构的土壤样品中的POM对于更好地了解土壤结构在为土壤C提供物理保护方面的作用至关重要。但是,到目前为止,缺乏用于POM识别的工具阻碍了其发展。这项研究的目的是开发使用X射线计算机显微断层扫描(mu-CT)图像对完整土壤样品中的POM进行鉴定和定量表征的程序,并测试所提出程序的性能。我们使用了从Typic Hapludalf土壤中0至15厘米深度处收集的16种4至6毫米土壤聚集体,并以6.3毫米分辨率进行了扫描。开发的程序将图像预处理步骤与判别分析分类相结合。图像预处理用于基于灰度值(GV)的范围,形状和大小的POM进行初步的POM识别。通过使用统计和地统计特征进行的判别分析,最终实现了POM识别。使用建议的方法在完整的单个聚集体中鉴定出的POM与使用常规实验室方法测得的POM高度吻合(R-2 = 0.73)。对于准确识别图像中的POM而言,特别重要的是有关POM GV空间特征的信息。为了说明使用X射线m-CT开辟分析完整土壤样品中POM的新可能性的方法,我们还探索并报告了所研究聚集体内POM颗粒的GV和粒径-体积分布。

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