TopoRoot: a method for computing hierarchy and fine-grained traits of maize roots from 3D imaging

Abstract

Background 3D imaging, such as X-ray CT and MRI, has been widely deployed to study plant root structures. Many computational tools exist to extract coarse-grained features from 3D root images, such as total volume, root number and total root length. However, methods that can accurately and efficiently compute fine-grained root traits, such as root number and geometry at each hierarchy level, are still lacking. These traits would allow biologists to gain deeper insights into the root system architecture. Results We present TopoRoot, a high-throughput computational method that computes fine-grained architectural traits from 3D images of maize root crowns or root systems. These traits include the number, length, thickness, angle, tortuosity, and number of children for the roots at each level of the hierarchy. TopoRoot combines state-of-the-art algorithms in computer graphics, such as topological simplification and geometric skeletonization, with customized heuristics for robustly obtaining the branching structure and hierarchical information. TopoRoot is validated on both CT scans of excavated field-grown root crowns and simulated images of root systems, and in both cases, it was shown to improve the accuracy of traits over existing methods. TopoRoot runs within a few minutes on a desktop workstation for images at the resolution range of 400^3, with minimal need for human intervention in the form of setting three intensity thresholds per image. Conclusions TopoRoot improves the state-of-the-art methods in obtaining more accurate and comprehensive fine-grained traits of maize roots from 3D imaging. The automation and efficiency make TopoRoot suitable for batch processing on large numbers of root images. Our method is thus useful for phenomic studies aimed at finding the genetic basis behind root system architecture and the subsequent development of more productive crops.

The topological shape of gene expression across the evolution of flowering plants

“…Topological data analysis has been applied to complex, high dimensionality biological datasets including gene expression profiles correlated with human cancers and other diseases (5,43,44). To our knowledge, TDA has not been used for plant science datasets outside of shape (45)(46)(47). Flowering plants have tremendous phylogenetic, developmental, phenotypic, and genomic scale diversity, creating additional layers of complexity compared to other lineages.…”

X‐ray CT reveals 4D root system development and lateral root responses to nitrate in soil

“…Root growth and development directly affects the volume of soil explored for both foraging and interception of water and nutrients. Phenotyping roots without disturbing the root system architecture is a technical challenge with approaches generally destructive or in vitro (Fang et al., 2009; Liu et al., 2021; Tracy et al., 2015; Zeng et al., 2021). Utilizing μCT for scanning of undisturbed roots in soil provides an unparalleled opportunity to characterize dynamic rhizosphere processes (Bao et al., 2014; Giri et al., 2018).…”

Root System Architecture and Environmental Flux Analysis in Mature Crops using 3D Root Mesocosms

“…This means that dense root crowns or areas of thick matted lateral roots are not resolvable. Thus, we are considering the potential to complement the photogrammetry derived point cloud with X-ray CT derived root crown reconstructions (Shao et al, 2021;Zeng et al, 2021).…”