Integrated root phenotypes for improved rice performance under low nitrogen availability

• Published in: Plant, cell and environment Vol. 45; no. 3; pp. 805 - 822
• Main Authors: Ajmera, Ishan, Henry, Amelia, Radanielson, Ando M., Klein, Stephanie P., Ianevski, Aleksandr, Bennett, Malcolm J., Band, Leah R., Lynch, Jonathan P.
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.03.2022; John Wiley and Sons Inc
• Subjects: Agricultural ecosystems; agroecosystems; Availability; biomass; crop models; Crop production; Crop yield; Cultivars; direct seeding; energy; Energy costs; environment; functional–structural plant modelling; grain yield; ideotypes; IR64; Nitrogen; nitrogen acquisition; nodal roots; OpenSimRoot; Original; Oryza - genetics; ORYZA_V3; phene synergism; Phenotype; Phenotypes; Plant breeding; Plant growth; Plant Roots; Rice; root system architecture; soil; Soil - chemistry; Structural models; Structure-function relationships; Synergism; Weather; ORYZA_V3; OpenSimRoot; functional-structural plant modelling; phene synergism; IR64; nitrogen acquisition; root system architecture; nodal roots
• DOI: 10.1111/pce.14284
• ISSN: 0140-7791; 1365-3040

Greater nitrogen efficiency would substantially reduce the economic, energy and environmental costs of rice production. We hypothesized that synergistic balancing of the costs and benefits for soil exploration among root architectural phenes is beneficial under suboptimal nitrogen availability. An enhanced implementation of the functional–structural model OpenSimRoot for rice integrated with the ORYZA_v3 crop model was used to evaluate the utility of combinations of root architectural phenes, namely nodal root angle, the proportion of smaller diameter nodal roots, nodal root number; and L‐type and S‐type lateral branching densities, for plant growth under low nitrogen. Multiple integrated root phenotypes were identified with greater shoot biomass under low nitrogen than the reference cultivar IR64. The superiority of these phenotypes was due to synergism among root phenes rather than the expected additive effects of phene states. Representative optimal phenotypes were predicted to have up to 80% greater grain yield with low N supply in the rainfed dry direct‐seeded agroecosystem over future weather conditions, compared to IR64. These phenotypes merit consideration as root ideotypes for breeding rice cultivars with improved yield under rainfed dry direct‐seeded conditions with limited nitrogen availability. The importance of phene synergism for the performance of integrated phenotypes has implications for crop breeding. Summary Statement Multiscale mechanistic modelling identified several integrated root phenotypes in rice with superior yield under low N availability. Synergism among root phenes was an important component of phenotypic performance.