Root phenotypic plasticity: agronomic, breeding and modelling implications

Abstract

Abstract CONTEXT. Phenotypic plasticity is one of four strategies for coping with environmental heterogeneity, and can be valuable for crop adaptation. OBJECTIVE. With a perspective of phenotypic plasticity, we focus on root traits associated to water uptake and yield formation in field-grown sorghum aiming to study: (1) How do genetic (G), environmental (E) and management (M) factors and their interactions, affect functional root traits? (2) How does plasticity in root traits affect crop yield and yield stability?; and (3) How can plasticity in root traits be introduced in functional crop models? METHODS. A new high-throughput functional root phenotyping approach, that uses time-lapsed electromagnetic induction (EMI) surveys, was used in field G´E´M trials to quantify maximum rooting depth – RD, and a root activity index– RA. Phenotypic plasticity was determined using a reaction norm method. RESULTS. The root phenotyping approach captured G´E´M effects on RA and RD. There was a hierarchy of plasticities for above and below ground traits, i.e., grain number traits > root traits > grain weight traits. The plasticity of root traits was associated to the stability in grain yield traits. Hybrids with high plasticity in root traits tended to stabilise grain numbers and grain weights. Useful diversity in the mean value and plasticity of root traits amongst commercial sorghum hybrids was found here, that could be used to match root phenotypes to target production environments. CONCLUSIONS. The developed high-throughput root phenotyping approach can be a useful tool in breeding and agronomy to increase crop adaptation to drought stress.

Plant phenotyping relevance

時系列電磁誘導調査を用いた高スループット根系フェノタイピング手法を開発・適用し、根深度と根活性を定量化しているため、フェノタイピング手法が中心である。

Code and data availability

The paper describes field root phenotyping (EMI surveys, drone/satellite imagery) of six sorghum hybrids and APSIM modelling, but the supplied blocks contain no public deposit of the phenotype datasets, EMI/drone imagery, analysis code, or modified APSIM model. The only URLs mentioned (SILO climate data, APSoil) are un

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