基于 NanoSIMS 数据自动识别土壤功能成分

IF 5.8 2区 环境科学与生态学 Q1 ECOLOGY
Yahan Hu , Johann Maximilian Zollner , Carmen Höschen , Martin Werner , Steffen A. Schweizer
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引用次数: 0

摘要

NanoSIMS 技术可以在材料科学、宇宙化学和生物地球化学等多个科学领域研究复杂结构中的微观空间组织。在土壤生物地球化学应用中,基于 NanoSIMS 的方法旨在揭示异质土壤微观结构中有机物(OM)和矿物相的相互作用。要了解这些成分如何相互作用并促进土壤系统中的生物地球化学过程,就必须对不同有机物和矿物功能成分的空间排列进行调查。在 NanoSIMS 测量中识别土壤功能成分需要先进高效的数据处理工具,这些工具必须能够实现无障碍和自动化。我们开发了一种预处理工具,以简化 NanoSIMS 数据的准备和处理。该工具以开源软件工具箱(NanoT)的形式提供。此外,我们还开发了一种两步无监督分割方法,用于根据 NanoSIMS 分析结果识别土壤功能成分。为了说明该分割方法,我们在此介绍其在两个 NanoSIMS 测量示例中的应用。这种方法可以区分以矿物和 OM 为主的区域,以及不同的矿物相。为了改进铁氧化物和铝硅酸盐的检测,我们对 56Fe16O- 通道进行了单独处理。所介绍的基于 NanoSIMS 的处理工作流程有助于区分土壤中具有生物地球化学多样性的微观结构中的功能成分,并可进一步应用于各种复杂的环境样本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Automated identification of soil functional components based on NanoSIMS data

Automated identification of soil functional components based on NanoSIMS data
NanoSIMS technique allows to investigate the micro-spatial organization in complex structures in multiple scientific fields such as material science, cosmochemistry, and biogeochemistry. In soil biogeochemistry applications, NanoSIMS-based approaches aim to disentangle the interactions of organic matter (OM) and mineral phases in the heterogeneous soil microstructure. Investigating the spatial arrangement of distinct organic and mineral functional components is necessary to understand how these components interact and contribute to biogeochemical processes in soil systems. Identifying soil functional components within NanoSIMS measurements necessitates advanced and efficient data processing tools capable of accessibility and automation. We have developed a pre-processing tool to streamline NanoSIMS data preparation and handling. The tool is provided as an open-source software toolbox (NanoT). In addition, a two-step unsupervised segmentation method was developed to identify soil functional components based on NanoSIMS analyses. To illustrate the segmentation method, here we describe its application to two exemplary NanoSIMS measurements. This allows to distinguish mineral- and OM-dominated regions, as well as different mineral phases. To improve the detection of iron oxides and aluminosilicates, the 56Fe16O channel was separately processed. The presented NanoSIMS-based processing workflow helps to disentangle functional components within a biogeochemically-diverse microstructure in soils and further warrants applications to a wide range of complex environmental samples.
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来源期刊
Ecological Informatics
Ecological Informatics 环境科学-生态学
CiteScore
8.30
自引率
11.80%
发文量
346
审稿时长
46 days
期刊介绍: The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change. The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.
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