Qualitative research: The impact of root orientation on coarse roots detection using ground-penetrating radar (GPR)

The growth of coarse roots is complex, leading to intricate patterns of root systems in three dimensions. To detect and recognize coarse roots, ground-penetrating radar (GPR) was used. According to the GPR theory, a clear profile hyperbola is formed on the GPR radargrams when electromagnetic waves travel across two surfaces with different dielectric constants. First, the forward models (different root orientations) were built with simulation software (GprMax3.0) based on the finite-different time-domain method (FDTD). As the radar moved forward, the signal reflection curve was generated in different root orientations. An algorithm was proposed to obtain the coordinates of a single coarse root and analyze the influence of root direction on the hyperbola of coarse root through a symmetry curve and relative error (RE). Based on GPR datasets from the simulation experiment, the controlled experiment evaluated feasibility and effectiveness of the simulation experiment. To demonstrate the effect of the root orientation, the algorithm was applied to in situ recognition of the Summer Palace. The results showed that the localization of root orientation was relatively accurate. However, the proposed algorithm was unable to implement automatic detection, and the results still required human intervention. This research provides a solid basis for the biomass measurement, diameter estimation, and especially the three-dimensional reconstruction of ancient and famous trees.

Development of a model estimating root length density from root impacts on a soil profile in pearl millet (Pennisetum glaucum(L.) R. Br). Application to measure root system response to water stress in field conditions

Pearl millet, unlike other cereals, is able to withstand dry and hot conditions and plays an important role for food security in arid and semi-arid areas of Africa and India. However, low soil fertility and drought constrain pearl millet yield. One of the main targets to address these constraints through agricultural practices or breeding is root system architecture. In this study, in order to easily phenotype the root system in field conditions, we developed a model to predict root length density (RLD) of pearl millet plants from root intersection densities (RID) counted on a trench profile in field conditions. We identified root orientation as an important parameter to improve the relationship between RID and RLD. Root orientation was notably found to differ between thick roots (more anisotropic with depth) and fine roots (isotropic at all depths). We used our model to study pearl millet root system response to drought and showed that pearl millet reorients its root growth toward deeper soil layers that retain more water in these conditions. Overall, this model opens ways for the characterization of the impact of environmental factors and management practices on pearl millet root system development.