Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems.

Abstract

Root phenotyping provides trait information for plant breeding. A shortcoming of high-throughput root phenotyping is the limitation to seedling plants and failure to make inferences on mature root systems. We suggest root system architecture (RSA) models to predict mature root traits and overcome the inference problem. Sixteen pea genotypes were phenotyped in (i) seedling (Petri dishes) and (ii) mature (sand-filled columns) root phenotyping platforms. The RSA model RootBox was parameterized with seedling traits to simulate the fully developed root systems. Measured and modelled root length, first-order lateral number, and root distribution were compared to determine key traits for model-based prediction. No direct relationship in root traits (tap, lateral length, interbranch distance) was evident between phenotyping systems. RootBox significantly improved the inference over phenotyping platforms. Seedling plant tap and lateral root elongation rates and interbranch distance were sufficient model parameters to predict genotype ranking in total root length with an RSpearman of 0.83. Parameterization including uneven lateral spacing via a scaling function substantially improved the prediction of architectures underlying the differently sized root systems. We conclude that RSA models can solve the inference problem of seedling root phenotyping. RSA models should be included in the phenotyping pipeline to provide reliable information on mature root systems to breeding research.

Plant phenotyping relevance

幼植物の根表現型から成熟根系形質を推定するRSAモデルを開発・評価し、根表現型ワークフローへの組込みを検証しており、方法が研究の中心です。

Code and data availability

The supplied blocks describe pea seedling and mature root phenotyping and RootBox simulations, but contain no public dataset, image, code, or model deposit with an authors' URL. The only URLs present are Creative Commons license links. A supplementary protocol is referenced but without a public URL or deposit language.

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