Neutron computed laminography yields 3D root system architecture and complements investigations of spatiotemporal rhizosphere patterns

Abstract

Abstract Purpose Root growth, respiration, water uptake as well as root exudation induce biogeochemical patterns in the rhizosphere that can change dynamically over time. Our aim is to develop a method that provides complementary information on 3D root system architecture and biogeochemical gradients around the roots needed for the quantitative description of rhizosphere processes. Methods We captured for the first time the root system architecture of maize plants grown in rectangular rhizotrons in 3D using neutron computed laminography (NCL). Simultaneously, we measured pH and oxygen concentration using fluorescent optodes and the 2D soil water distribution by means of neutron radiography. We co-registered the 3D laminography data with the 2D oxygen and pH maps to analyze the sensor signal as a function of the distance between the roots and the optode. Results The 3D root system architecture was successfully segmented from the laminographic data. We found that exudation of roots in up to 2 mm distance to the pH optode induced patterns of local acidification or alkalization. Over time, oxygen gradients in the rhizosphere emerged for roots up to a distance of 7.5 mm. Conclusion Neutron computed laminography allows for a three-dimensional investigation of root systems grown in laterally extended rhizotrons as the ones designed for 2D optode imaging studies. The 3D information on root position within the rhizotrons derived by NCL explained measured 2D oxygen and pH distribution. The presented new combination of 3D and 2D imaging methods facilitates systematical investigations of a wide range of dynamic processes in the rhizosphere.

Plant phenotyping relevance

NCLを用いた3D根系構造の取得・セグメンテーションが研究の中心であり、根系アーキテクチャという植物表現型を抽出する新しい画像計測法を開発・適用している。

Code and data availability

The paper's Data availability statement deposits the raw and reconstructed 3D neutron computed laminography dataset of one maize root sample in the datacite repository at Helmholtz-Zentrum Berlin (DOI 10.5442/ND000004), a public, paper-specific phenotyping asset. No author analysis code or trained models are disclosed;