Unverified paper record
Model-based plant phenomics on morphological traits using morphometric descriptors.
Ikushugaku zasshi · 1 Jan 2022 · 10.1270/jsbbs.21078
Abstract
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.
Plant phenotyping relevance
植物形態形質のフェノタイピングに用いる形態記述子、幾何学的形態計測、トポロジカルデータ解析、モデルベース測定を中心に論じる方法論レビューである。
abstractIn this review, we introduce morphological descriptors that can be used for phenotyping plant morphological traits.
abstractThese morphological descriptors provide us with the advantages of model-based plant phenotyping, including robust quantification of limited datasets.
Code and data availability
This is an invited review introducing morphometric descriptors for plant phenotyping; it reports no original phenotype/trait datasets, plant images, sensor/3D inputs, or author analysis code with public availability statements. The cited figshare item (Noshita 2021a, 'Form, Shape') is a conceptual illustration reused (
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