Using high-throughput phenotyping platform MVS-Pheno to decipher the genetic architecture of plant spatial geometric 3D phenotypes for maize

文献类型： 外文期刊

第一作者： Wu, Sheng

作者： Wu, Sheng;Zhang, Ying;Wen, Weiliang;Wang, Chuanyu;Lu, Xianju;Guo, Minkun;Guo, Xinyu;Zhao, Jiuran;Zhao, Chunjiang;Wu, Sheng;Zhang, Ying;Wen, Weiliang;Wang, Chuanyu;Lu, Xianju;Guo, Minkun;Guo, Xinyu;Zhao, Chunjiang;Zhao, Yanxin;Zhao, Jiuran

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关键词： Maize; Plant architecture; 3D phenotypes; Genome-wide association study

期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：7.7； 五年影响因子：8.4 ）

ISSN： 0168-1699

年卷期： 2024 年 225 卷

页码：

收录情况： SCI

摘要： Maize (Zea mays) is one of the world's most important crops, and its abundant and stable yield is crucial for ensuring global food security. Optimizing maize plant architecture can effectively enhance canopy structure, and ensure an ample supply of assimilates, thereby constituting a crucial strategy for achieving high yields in highdensity planting systems. In this study, we used the phenotyping platform MVS-Pheno to synchronously collect multi-view image data of plant architecture, and the 3D phenotype analysis algorithm was developed to batch and automatically extract traits of spatial geometric structure. Using this phenotypic acquisition and analysis platform, 44 traits of maize plant architecture were defined and extracted, including 6 categories: basic phenotype, projection area related phenotype, leaf related phenotype, plant architecture dispersion related phenotype, volume related phenotype, and color related phenotype. Based on abundant phenotypic traits of plant architecture, we analyzed the phenotypic variations among a group of 495 inbred lines and further conducted GWAS to reveal the genetic components of the plant architecture. In summary, our work demonstrates valuable advances in high-throughput identification of qualitative traits for plant architecture, which could have major implications for improving high-density tolerant maize breeding and production.

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