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Evaluating maize phenotypic variance, heritability, and yield relationships at multiple biological scales across agronomically relevant environments.
Plant, Cell & Environment ( IF 7.3 ) Pub Date : 2020-02-05 , DOI: 10.1111/pce.13681
Sarah L Tucker 1 , Frank G Dohleman 1 , Dmitry Grapov 1 , Lex Flagel 1 , Sean Yang 1 , Kimberly M Wegener 1 , Kevin Kosola 1 , Shilpa Swarup 1 , Ryan A Rapp 2 , Mohamed Bedair 1 , Steven C Halls 1 , Kevin C Glenn 1 , Michael A Hall 1 , Edwards Allen 1 , Elena A Rice 1
Affiliation  

A challenge to improve an integrative phenotype, like yield, is the interaction between the broad range of possible molecular and physiological traits that contribute to yield and the multitude of potential environmental conditions in which they are expressed. This study collected data on 31 phenotypic traits, 83 annotated metabolites, and nearly 22,000 transcripts from a set of 57 diverse, commercially relevant maize hybrids across three years in central U.S. Corn Belt environments. Although variability in characteristics created a complex picture of how traits interact produce yield, phenotypic traits and gene expression were more consistent across environments, while metabolite levels showed low repeatability. Phenology traits, such as green leaf number and grain moisture and whole plant nitrogen content showed the most consistent correlation with yield. A machine learning predictive analysis of phenotypic traits revealed that ear traits, phenology, and root traits were most important to predicting yield. Analysis suggested little correlation between biomass traits and yield, suggesting there is more of a sink limitation to yield under the conditions studied here. This work suggests that continued improvement of maize yields requires a strong understanding of baseline variation of plant characteristics across commercially-relevant germplasm to drive strategies for consistently improving yield.

中文翻译:

在农业相关环境中的多个生物学规模上评估玉米表型变异,遗传力和产量关系。

改善整体表型(如产量)的挑战是,可能影响产量的各种可能的分子和生理性状与表达这些潜在环境的众多因素之间的相互作用。这项研究在美国中部玉米带环境中,收集了来自57种与商业相关的玉米杂交品种的31种表型性状,83种带注释的代谢物和近22,000个转录本的数据,历时3年。尽管特征的可变性产生了有关性状相互作用如何产生产量的复杂图景,但表型性状和基因表达在整个环境中更加一致,而代谢物水平显示出低的可重复性。物候特征 绿叶数,谷粒水分和全株氮含量等与产量的相关性最强。对表型性状的机器学习预测分析表明,耳部性状,物候和根系性状对于预测产量最重要。分析表明,生物量性状与产量之间几乎没有相关性,这表明在这里研究的条件下,产量更多地受到汇的限制。这项工作表明,要继续提高玉米产量,就需要对与商业相关的种质的植物特征的基线变化有深刻的了解,以推动持续提高产量的策略。分析表明,生物量性状与产量之间几乎没有相关性,这表明在这里研究的条件下,产量更多地受到汇的限制。这项工作表明,要继续提高玉米产量,就需要对与商业相关的种质的植物特征的基线变化有深刻的了解,以推动持续提高产量的策略。分析表明,生物量性状与产量之间几乎没有相关性,这表明在这里研究的条件下,产量更多地受到汇的限制。这项工作表明,要继续提高玉米产量,就需要对与商业相关的种质的植物特征的基线变化有深刻的了解,以推动持续提高产量的策略。
更新日期:2020-02-05
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