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ClearDepth: a simple, robust, and low-cost method to assess root depth in soil.

The Plant journal : for cell and molecular biology · 8 Dec 2024 · 10.1111/tpj.17177

Abstract

Root depth is a major determinant of plant performance during drought and a key trait for strategies to improve soil carbon sequestration to mitigate climate change. While the model Arabidopsis thaliana offers numerous advantages for studies of root system architecture and root depth, its small and fragile roots severely limit the use of the methods and techniques currently available for such studies in soils. To overcome this, we have developed ClearDepth, a conceptually simple, non-destructive, sensitive, and low-cost method to estimate the root depth of Arabidopsis in relatively small pots that are amenable to mid- and large-scale studies. In our method, the root system develops naturally inside of the soil, without considerable space constraints. The ClearDepth parameter wall root shallowness (WRS) quantifies the shallowness of the root system by measuring the depth of roots that reach the transparent walls of clear pots. We show that WRS is a robust and sensitive parameter that distinguishes deep root systems from shallower ones while also capturing relatively smaller differences in root depth caused by the influence of an environmental factor. In addition, we leveraged ClearDepth to study the relation between lateral root angles measured in non-soil systems and root depth in soil. We found that Arabidopsis genotypes characterized by steep lateral roots in transparent growth media produce deeper root systems in the ClearDepth pots. Finally, we show that ClearDepth can also be used to study root depth in crop species like rice.

Plant phenotyping relevance

根系深度という植物形質を定量する低コスト・非破壊手法を開発し、その頑健性と感度を検証しているため、方法が研究の中心です。

abstractwe have developed ClearDepth, a conceptually simple, non-destructive, sensitive, and low-cost method to estimate the root depth of Arabidopsis
abstractThe ClearDepth parameter wall root shallowness (WRS) quantifies the shallowness of the root system
abstractWe show that WRS is a robust and sensitive parameter that distinguishes deep root systems from shallower ones

Code and data availability

The paper describes ClearDepth phenotyping and a UNet++ root segmentation pipeline, but no public deposit of the phenotype data, images, annotations, trained model, or analysis code is stated. All URLs in the text are generic tools/vendors or cited resources, not authors' asset repositories.

No evidence-backed public reproduction asset is currently recorded.

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