Variation in root system architecture (RSA) can have profoundly different effects on plant health and productivity in different environments ( Fitter, 1987 Lynch, 1995). This approach connects individual and system-wide scales of root growth dynamics, which could eventually be used to predict genetic variation for complex RSAs and their functions.
The 3D imaging of mature field-grown root crowns showed that several genetic differences in seedling architectures could persist throughout development and across environments. Genetically driven differences in root branching zone size and lateral branching densities along a single root, combined with differences in peak growth rate and the relative allocation of carbon resources to new versus existing roots, manifest as sharply distinct global RSAs over time. We used time-lapse 3D imaging and mathematical modeling to assess root system architectures (RSAs) of two maize ( Zea mays) inbred genotypes and their hybrid as they grew in complexity from a few to many roots.
A critical gap in our knowledge is how root systems build in complexity from a single primary root to a network of thousands of roots that collectively compete for ephemeral, heterogeneous soil resources. Root systems are one of the most important but poorly understood aspects of plants, largely due to the three-dimensional (3D), dynamic, and multiscale phenotyping challenge they pose. Understanding how an organism’s phenotypic traits are conditioned by genetic and environmental variation is a central goal of biology.
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