The whole script that was used to compute the root hydraulic atlas from the root anatomical measurement is presented as a Rmarkdown script stored in a GitHub repository ( https://github.com/granar/B73_HydraulicMap doi: https://doi.org/10.5281/zenodo.4320861 ). All input and output data of this study are stored in the same repository.
Open resource ↗granar/B73_HydraulicMap · 10.5281/zenodo.4320861 · lines:267-339Unverified paper record
Combining cross-section images and modeling tools to create high-resolution root system hydraulic atlases in Zea mays .
Plant direct · 16 Jul 2021 · 10.1002/pld3.334
Abstract
Root hydraulic properties play a central role in the global water cycle, in agricultural systems productivity, and in ecosystem survival as they impact the canopy water supply. However, the existing experimental methods to quantify root hydraulic conductivities, such as the root pressure probing, are particularly challenging, and their applicability to thin roots and small root segments is limited. Therefore, there is a gap in methods enabling easy estimations of root hydraulic conductivities in diverse root types. Here, we present a new pipeline to quickly estimate root hydraulic conductivities across different root types, at high resolution along root axes. Shortly, free-hand root cross-sections were used to extract a selected number of key anatomical traits. We used these traits to parametrize the Generator of Root Anatomy in R (GRANAR) model to simulate root anatomical networks. Finally, we used these generated anatomical networks within the Model of Explicit Cross-section Hydraulic Anatomy (MECHA) to compute an estimation of the root axial and radial hydraulic conductivities ( k x and k r , respectively). Using this combination of anatomical data and computational models, we were able to create a root hydraulic conductivity atlas at the root system level, for 14-day-old pot-grown Zea mays (maize) plants of the var. B73 . The altas highlights the significant functional variations along and between different root types. For instance, predicted variations of radial conductivity along the root axis were strongly dependent on the maturation stage of hydrophobic barriers. The same was also true for the maturation rates of the metaxylem vessels. Differences in anatomical traits along and across root types generated substantial variations in radial and axial conductivities estimated with our novel approach. Our methodological pipeline combines anatomical data and computational models to turn root cross-section images into a detailed hydraulic atlas. It is an inexpensive, fast, and easily applicable investigation tool for root hydraulics that complements existing complex experimental methods. It opens the way to high-throughput studies on the functional importance of root types in plant hydraulics, especially if combined with novel phenotyping techniques such as laser ablation tomography.
Plant phenotyping relevance
根の断面画像と計算モデルを組み合わせ、根の解剖形質から油圧伝導性を推定する新規パイプラインを開発しており、植物表現型の取得・推定手法が研究の中心である。
abstractHere, we present a new pipeline to quickly estimate root hydraulic conductivities across different root types, at high resolution along root axes.
abstractOur methodological pipeline combines anatomical data and computational models to turn root cross-section images into a detailed hydraulic atlas.
Code and data availability
The paper provides two paper-specific public assets: the GRANAR–MECHA coupling workflow (Jupyter notebook via Binder, GitHub repo HeymansAdrien/GranarMecha, Zenodo DOI 10.5281/zenodo.4316762) and the Rmarkdown script plus all input/output data used to compute the B73 root hydraulic atlas (GitHub repo granar/B73_Hydraul
The whole script that was used to compute the root hydraulic atlas from the root anatomical measurement is presented as a Rmarkdown script stored in a GitHub repository ( https://github.com/granar/B73_HydraulicMap doi: https://doi.org/10.5281/zenodo.4320861 ). All input and output data of this study are stored in the same repository.
Open resource ↗granar/B73_HydraulicMap · 10.5281/zenodo.4320861 · lines:267-339This is an automatically classified, unverified record. Curator approval is required before any resource enters the Catalog.