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A snapshot of the root phenotyping landscape in 2021

bioRxiv · 31 Jan 2022 · 10.1101/2022.01.28.478001

Abstract

Root phenotyping describes methods for measuring root properties, or traits. While root phenotyping can be challenging, it is advancing quickly. In order for the field to move forward, it is essential to understand the current state and challenges of root phenotyping, as well as the pressing needs of the root biology community. In this letter, we present and discuss the results of a survey that was created and disseminated by members of the Graduate Student and Postdoc Ambassador Program at the 11th symposium of the International Society of Root Research. This survey aimed to (1) provide an overview of the objectives, biological models and methodological approaches used in root phenotyping studies, and (2) identify the main limitations currently faced by plant scientists with regard to root phenotyping. Our survey highlighted that (1) monocotyledonous crops dominate the root phenotyping landscape, (2) root phenotyping is mainly used to quantify morphological and architectural root traits, (3) 2D root scanning/imaging is the most widely used root phenotyping technique, (4) time-consuming tasks are an important barrier to root phenotyping, (5) there is a need for standardised, high-throughput methods to sample and phenotype roots, particularly under field conditions, and to improve our understanding of trait-function relationships.

Plant phenotyping relevance

根系フェノタイピングの手法、利用状況、限界、標準化ニーズを調査・整理したレビュー的研究であり、フェノタイピング方法論が中心です。

abstractRoot phenotyping describes methods for measuring root properties, or traits.
abstractThis survey aimed to (1) provide an overview of the objectives, biological models and methodological approaches used in root phenotyping studies, and (2) identify the main limitations currently faced by plant scientists with regard to root phenotyping.
abstractthere is a need for standardised, high-throughput methods to sample and phenotype roots

Code and data availability

The paper's Data availability statement explicitly deposits the survey raw data and R analysis code on Zenodo (DOI 10.5281/zenodo.5901959), a public, paper-specific, actionable asset. The Nottingham Hidden Half maize image URL is only a credited Figure 1 image source, not a paper-specific dataset, and is not listed asa

Codepublic

Raw data and R code are available on Zenodo at https://doi.org/10.5281/zenodo.5901959.

Open resource ↗Zenodo · 10.5281/zenodo.5901959 · pdf-page:10 lines:1-39

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