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根系表型分析:作物根系建模所需的重要信息及最低信息要求

Root phenotyping: important and minimum information required for root modeling in crop plants.

作者信息

Takahashi Hirokazu, Pradal Christophe

机构信息

Graduate School of Bioagricultural Sciences, Nagoya University, Furo-cho, Chikusa, Nagoya, Aichi 464-8601, Japan.

UMR AGAP, CIRAD, F-34398 Montpellier, France.

出版信息

Breed Sci. 2021 Feb;71(1):109-116. doi: 10.1270/jsbbs.20126. Epub 2021 Feb 10.

Abstract

As plants cannot relocate, they require effective root systems for water and nutrient uptake. Root development plasticity enables plants to adapt to different environmental conditions. Research on improvements in crop root systems is limited in comparison with that in shoots as the former are difficult to image. Breeding more effective root systems is proposed as the "second green revolution". There are several recent publications on root system architecture (RSA), but the methods used to analyze the RSA have not been standardized. Here, we introduce traditional and current root-imaging methods and discuss root structure phenotyping. Some important root structures have not been standardized as roots are easily affected by rhizosphere conditions and exhibit greater plasticity than shoots; moreover, root morphology significantly varies even in the same genotype. For these reasons, it is difficult to define the ideal root systems for breeding. In this review, we introduce several types of software to analyze roots and identify important root parameters by modeling to simplify the root system characterization. These parameters can be extracted from photographs captured in the field. This modeling approach is applicable to various legacy root data stored in old or unpublished formats. Standardization of RSA data could help estimate root ideotypes.

摘要

由于植物无法移动,它们需要有效的根系来吸收水分和养分。根系发育可塑性使植物能够适应不同的环境条件。与地上部分相比,对作物根系的研究较为有限,因为根系难以成像。培育更有效的根系被提议作为“第二次绿色革命”。近期有几篇关于根系结构(RSA)的出版物,但用于分析RSA的方法尚未标准化。在这里,我们介绍传统和当前的根系成像方法,并讨论根系结构表型分析。一些重要的根系结构尚未标准化,因为根系很容易受到根际条件的影响,并且比地上部分表现出更大的可塑性;此外,即使是同一基因型,根系形态也有显著差异。由于这些原因,很难定义用于育种的理想根系。在这篇综述中,我们介绍了几种分析根系的软件,并通过建模识别重要的根系参数,以简化根系特征描述。这些参数可以从田间拍摄的照片中提取。这种建模方法适用于以旧格式或未发表格式存储的各种传统根系数据。RSA数据的标准化有助于估计根系理想型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/395e/7973500/df2c414c9ebe/71_109-g001.jpg

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