TopoRoot+: Computing Whorl and Soil Line Traits of Maize Roots from CT Imaging

Abstract Background: The use of 3D imaging techniques, such as X-ray CT, in root phenotyping has become more widespread in recent years. However, due to the complexity of root structure, analyzing the resulting 3D volumes to obtain detailed architectural traits of the root system remains a challenging computational problem. Two types of root features that are notably missing from existing computational image-based phenotyping methods are the whorls of a nodal root system and soil line in an excavated root crown. Knowledge of these features would give biologists deeper insights into the structure of nodal roots and the below- and above-ground root properties. Results: We developed TopoRoot+, a computational pipeline that computes architectural traits from 3D X-ray CT volumes of excavated maize root crowns. TopoRoot+ builds upon the TopoRoot software [1], which computes a skeleton representation of the root system and produces a suite of fine-grained traits including the number, geometry, connectivity, and hierarchy level of individual roots. TopoRoot+ adds new algorithms on top of TopoRoot to detect whorls, their associated nodal roots, and the soil line location. These algorithms offer a new set of traits related to whorls and soil lines, such as internode distances, root traits at every hierarchy level associated with a whorl, and aggregate root traits above or below the ground. TopoRoot+ is validated on a diverse collection of field-grown maize root crowns consisting of nine genotypes and spanning across three years, and it exhibits reasonable accuracy against manual measurements for both whorl and soil line detection. TopoRoot+ runs in minutes for a typical downsampled volume size of 4003 on a desktop workstation. Our software and test dataset are freely distributed on Github. Conclusions: TopoRoot+ advances the state-of-the-art in image-based root phenotyping by offering more detailed architectural traits related to whorls and soil lines. The efficiency of TopoRoot+ makes it well-suited for high-throughput image-based root phenotyping.