作物/植物建模支持植物育种:II。性状发现的功能植物表型指南。

IF 7.6 1区 农林科学 Q1 AGRONOMY
Plant Phenomics Pub Date : 2023-09-28 eCollection Date: 2023-01-01 DOI:10.34133/plantphenomics.0091
Pengpeng Zhang, Jingyao Huang, Yuntao Ma, Xiujuan Wang, Mengzhen Kang, Youhong Song
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引用次数: 0

摘要

可观察的形态性状被广泛用于育种用的植物表型,通常是由植物的一系列功能作用驱动的外部表型。识别和表型分析内在功能性状,以提高作物产量或适应恶劣环境,仍然是一项重大挑战。功能结构植物模型(FSPM)中的整个植物性能预测是由基于器官尺度的植物生长算法驱动的,该算法包裹着微观环境。特别是,这些模型可以灵活地通过器官连接处的特定功能进行缩小或放大,从而可以预测从基因组到田地的作物系统行为。因此,通过FSPM,可以系统地描述从分子到整个植物水平确定器官发生、发育、生物量生产、分配和形态发生的模型参数,并使其易于用于表型分析。FSPM除了形态特征外,还可以提供丰富的功能特征,代表动态系统中不同尺度的生物调控机制,如Rubisco羧化速率、叶肉电导、比叶氮、辐射利用效率和源库比。还讨论了这些性状的高通量表型,这为进化FSPM提供了前所未有的机会。这将加速FSPM和植物表型的共同进化,从而提高育种效率。为了扩大FSPM在作物科学中的巨大前景,FSPM仍然需要在多尺度、机制、生殖器官和根系建模方面付出更多努力。总之,本研究表明,FSPM是指导各种规模的功能性状表型的宝贵工具,因此可以为作物改良表型提供丰富的功能靶标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery.

Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery.

Crop/Plant Modeling Supports Plant Breeding: II. Guidance of Functional Plant Phenotyping for Trait Discovery.

Observable morphological traits are widely employed in plant phenotyping for breeding use, which are often the external phenotypes driven by a chain of functional actions in plants. Identifying and phenotyping inherently functional traits for crop improvement toward high yields or adaptation to harsh environments remains a major challenge. Prediction of whole-plant performance in functional-structural plant models (FSPMs) is driven by plant growth algorithms based on organ scale wrapped up with micro-environments. In particular, the models are flexible for scaling down or up through specific functions at the organ nexus, allowing the prediction of crop system behaviors from the genome to the field. As such, by virtue of FSPMs, model parameters that determine organogenesis, development, biomass production, allocation, and morphogenesis from a molecular to the whole plant level can be profiled systematically and made readily available for phenotyping. FSPMs can provide rich functional traits representing biological regulatory mechanisms at various scales in a dynamic system, e.g., Rubisco carboxylation rate, mesophyll conductance, specific leaf nitrogen, radiation use efficiency, and source-sink ratio apart from morphological traits. High-throughput phenotyping such traits is also discussed, which provides an unprecedented opportunity to evolve FSPMs. This will accelerate the co-evolution of FSPMs and plant phenomics, and thus improving breeding efficiency. To expand the great promise of FSPMs in crop science, FSPMs still need more effort in multiscale, mechanistic, reproductive organ, and root system modeling. In summary, this study demonstrates that FSPMs are invaluable tools in guiding functional trait phenotyping at various scales and can thus provide abundant functional targets for phenotyping toward crop improvement.

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来源期刊
Plant Phenomics
Plant Phenomics Multiple-
CiteScore
8.60
自引率
9.20%
发文量
26
审稿时长
14 weeks
期刊介绍: Plant Phenomics is an Open Access journal published in affiliation with the State Key Laboratory of Crop Genetics & Germplasm Enhancement, Nanjing Agricultural University (NAU) and published by the American Association for the Advancement of Science (AAAS). Like all partners participating in the Science Partner Journal program, Plant Phenomics is editorially independent from the Science family of journals. The mission of Plant Phenomics is to publish novel research that will advance all aspects of plant phenotyping from the cell to the plant population levels using innovative combinations of sensor systems and data analytics. Plant Phenomics aims also to connect phenomics to other science domains, such as genomics, genetics, physiology, molecular biology, bioinformatics, statistics, mathematics, and computer sciences. Plant Phenomics should thus contribute to advance plant sciences and agriculture/forestry/horticulture by addressing key scientific challenges in the area of plant phenomics. The scope of the journal covers the latest technologies in plant phenotyping for data acquisition, data management, data interpretation, modeling, and their practical applications for crop cultivation, plant breeding, forestry, horticulture, ecology, and other plant-related domains.
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