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Multi-spectral imaging of rhizobox systems: New perspectives for the observation and discrimination of rhizosphere components

机译:根箱系统的多光谱成像:观察和辨别根际成分的新观点

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摘要

In this issue of Plant and Soil Nakaji et al. (Plant Soil, this volume, 2008) report a novel approach for automatically identifying roots and other rhizosphere components in rhizosphere images acquired using a multi-spectral (visible—VIS- and near-infrared—NIR-) imaging system. The images are acquired through a root-window observation device and the study highlights the perspectives offered by this imaging system. An outstanding outcome of this research is that the new approach can be applied to effectively separate soil litter from the purely mineral phase and distinguish root tissues that differ in physiological status, i.e. live (different age classes), senescent and dead. If achievable routinely, such a detailed classification of rhizosphere components could greatly improve our appraisal of root turnover and associated organic matter input to the soil, information of paramount importance for an improved understanding of many essential processes such as global geochemical cycles. Minirhizotrons (MR) systems have been increasingly used in global change studies because they are a convenient way to frequently and nondestructively quantify root length production and mortality (Norby and Jackson, New Phytol, 147:3–12, 2000; Hendrick and Pregitzer, Ecology, 73:1094–1104, 1992). However, the MR technique still has many limitations, including the lack of a standard, accurate and rapid procedure to extract and classify rhizosphere components from the MR images obtained. The recent work by Nakaji et al. (Plant Soil, this volume, 2008) provides convincing evidence that the inclusion of a VIS-NIR multi-spectral capability into conventional MR systems could substantially improve this method, and extend its adoption by the wider plant scientist community as a standard research tool.
机译:在《植物与土壤》中,Nakaji等人。 (Plant Soil,本册,2008年)报告了一种新颖的方法,该方法可自动识别使用多光谱(可见光-VIS和近红外-NIR)成像系统采集的根际图像中的根和其他根际成分。这些图像是通过根窗口观察设备获取的,研究重点介绍了该成像系统提供的视角。这项研究的杰出成果是,该新方法可用于有效地将土壤凋落物与纯矿物相分离,并区分生理状态不同的根组织,即活体(不同年龄段),衰老和死亡。如果能按常规实现,对根际成分的这种详细分类可以极大地改善我们对根周转率和向土壤中输入的相关有机物质的评估,这对于增进对许多基本过程(例如全球地球化学循环)的理解至关重要。 Minirhizotrons(MR)系统已越来越广泛地用于全球变化研究中,因为它们是一种频繁且无损地量化根长产生和死亡的便捷方法(Norby和Jackson,New Phytol,147:3-12,2000; Hendrick和Pregitzer,生态学) ,73:1094–1104,1992)。但是,MR技术仍然有很多局限性,包括缺乏从获得的MR图像中提取和分类根际成分的标准,准确和快速的程序。 Nakaji等人的最新著作。 (Plant Soil,本册,2008年)提供了令人信服的证据,表明将VIS-NIR多光谱功能包含在常规MR系统中可以大大改善该方法,并扩大其作为标准研究工具的广泛应用范围。

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