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A Comparative Analysis of Quantitative Metrics of Root Architecture.

Plant phenomics (Washington, D.C.) · 24 Feb 2021 · 10.34133/2021/6953197

Abstract

High throughput phenotyping is important to bridge the gap between genotype and phenotype. The methods used to describe the phenotype therefore should be robust to measurement errors, relatively stable over time, and most importantly, provide a reliable estimate of elementary phenotypic components. In this study, we use functional-structural modeling to evaluate quantitative phenotypic metrics used to describe root architecture to determine how they fit these criteria. Our results show that phenes such as root number, root diameter, and lateral root branching density are stable, reliable measures and are not affected by imaging method or plane. Metrics aggregating multiple phenes such as total length , total volume , convex hull volume , and bushiness index estimate different subsets of the constituent phenes; they however do not provide any information regarding the underlying phene states. Estimates of phene aggregates are not unique representations of underlying constituent phenes: multiple phenotypes having phenes in different states could have similar aggregate metrics. Root growth angle is an important phene which is susceptible to measurement errors when 2D projection methods are used. Metrics that aggregate phenes which are complex functions of root growth angle and other phenes are also subject to measurement errors when 2D projection methods are used. These results support the hypothesis that estimates of phenes are more useful than metrics aggregating multiple phenes for phenotyping root architecture. We propose that these concepts are broadly applicable in phenotyping and phenomics.

Plant phenotyping relevance

根系アーキテクチャの定量的表現型指標を機能構造モデルで評価し、測定誤差、安定性、信頼性を比較しており、表現型測定法の技術的検証が中心です。

abstractIn this study, we use functional-structural modeling to evaluate quantitative phenotypic metrics used to describe root architecture to determine how they fit these criteria.
abstractThese results support the hypothesis that estimates of phenes are more useful than metrics aggregating multiple phenes for phenotyping root architecture.

Code and data availability

The paper's Data Availability statement explicitly deposits the executable SimRoot code used in this study, the parameters used to generate the simulated root phenotypes, and the raw simulated root data on a public figshare link, which is an allowed URL.

Codepublic

The executable code of the version of SimRoot employed in this study, parameters used to generate these data, and the raw data are all available at https://figshare.com/s/58c7599752bcb75fbd76 .

Open resource ↗figshare · lines:450-462

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