Noshita Koji, Murata Hidekazu, Kirie Shiryu
Department of Biology, Kyushu University, Fukuoka, Fukuoka 819-0395, Japan.
Plant Frontier Research Center, Kyushu University, Fukuoka, Fukuoka 819-0395, Japan.
Breed Sci. 2022 Mar;72(1):19-30. doi: 10.1270/jsbbs.21078. Epub 2022 Feb 17.
The morphological traits of plants contribute to many important functional features such as radiation interception, lodging tolerance, gas exchange efficiency, spatial competition between individuals and/or species, and disease resistance. Although the importance of plant phenotyping techniques is increasing with advances in molecular breeding strategies, there are barriers to its advancement, including the gap between measured data and phenotypic values, low quantitativity, and low throughput caused by the lack of models for representing morphological traits. In this review, we introduce morphological descriptors that can be used for phenotyping plant morphological traits. Geometric morphometric approaches pave the way to a general-purpose method applicable to single units. Hierarchical structures composed of an indefinite number of multiple elements, which is often observed in plants, can be quantified in terms of their multi-scale topological characteristics using topological data analysis. Theoretical morphological models capture specific anatomical structures, if recognized. These morphological descriptors provide us with the advantages of model-based plant phenotyping, including robust quantification of limited datasets. Moreover, we discuss the future possibilities that a system of model-based measurement and model refinement would solve the lack of morphological models and the difficulties in scaling out the phenotyping processes.
植物的形态特征有助于许多重要的功能特性,如辐射截获、抗倒伏性、气体交换效率、个体和/或物种之间的空间竞争以及抗病性。尽管随着分子育种策略的进步,植物表型分析技术的重要性日益增加,但其发展仍存在障碍,包括测量数据与表型值之间的差距、定量性低以及由于缺乏形态特征表示模型而导致的低通量。在本综述中,我们介绍了可用于植物形态特征表型分析的形态描述符。几何形态测量方法为适用于单个单元的通用方法铺平了道路。由不定数量的多个元素组成的层次结构,这在植物中经常观察到,可以使用拓扑数据分析根据其多尺度拓扑特征进行量化。理论形态模型如果被识别,可以捕捉特定的解剖结构。这些形态描述符为基于模型的植物表型分析提供了优势,包括对有限数据集的稳健量化。此外,我们讨论了基于模型的测量和模型改进系统将解决形态模型缺乏以及表型分析过程难以扩大规模的未来可能性。