Abstract
Drought is a major source of yield loss in the production of rice (Oryza sativa L.), and cultivars that maintain yield under drought across environments and drought stress scenarios are urgently needed. Root phenotypes directly affect water interception and uptake, so plants with root systems optimized for water uptake under drought would likely exhibit reduced yield loss. Deeper nodal roots that have a low metabolic cost per length (i.e., cheaper roots) via smaller root diameter and/or more aerenchyma and that transport water efficiently through smaller diameter metaxylem vessels may be beneficial during drought. Subsets of the Rice Diversity Panel 1 and Azucena × IR64 recombinant inbred lines were grown in two greenhouse and two rainout shelter experiments under drought stress to assess their shoot, root anatomical, and root architectural phenotypes. Root traits and root trait plasticity in response to drought varied with genotype and environment. The best-performing groups in the rainout shelter experiments had less plasticity of living tissue area in nodal roots than the worst performing groups. Root traits under drought were partitioned into similar groups or clusters via the partitioning-around-medoids algorithm, and this revealed two favorable integrated root phenotypes common within and across environments. One favorable integrated phenotype exhibited many, deep nodal roots with larger root cross-sectional area and more aerenchyma, while the other favorable phenotype exhibited many, deep nodal roots with small root cross-sectional area and small metaxylem vessels. Deeper roots with high theoretical axial hydraulic conductance combined with reduced root metabolic cost contributed to greater shoot biomass under drought. These results reflect how some root anatomical and architectural phenes work in concert as integrated phenotypes to influence the performance of plant under drought stress. Multiple integrated root phenotypes are therefore recommended to be selected in breeding programs for improving rice yield across diverse environments and drought scenarios.
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