Wen Weiliang, Wang Jinglu, Zhao Yanxin, Wang Chuanyu, Liu Kai, Chen Bo, Wang Yuanqiao, Duan Minxiao, Guo Xinyu
Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China.
Beijing Key Lab of Digital Plant, National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China.
Plant Phenomics. 2024 Aug 6;6:0225. doi: 10.34133/plantphenomics.0225. eCollection 2024.
Marked variations in the 3-dimensional (3D) shape of corn leaves can be discerned as a function of various influences, including genetics, environmental factors, and the management of cultivation processes. However, the causes of these variations remain unclear, primarily due to the absence of quantitative methods to describe the 3D spatial morphology of leaves. To address this issue, this study acquired 3D digitized data of ear-position leaves from 478 corn inbred lines during the grain-filling stage. We propose quantitative calculation methods for 13 3D leaf shape features, such as the leaf length, 3D leaf area, leaf inclination angle, blade-included angle, blade self-twisting, blade planarity, and margin amplitude. Correlation analysis, cluster analysis, and heritability analysis were conducted among the 13 leaf traits. Leaf morphology differences among subpopulations of the inbred lines were also analyzed. The results revealed that the 3D leaf traits are capable of revealing the morphological differences among different leaf surfaces, and the genetic analysis revealed that 84.62% of the 3D phenotypic traits of ear-position leaves had a heritability greater than 0.3. However, the majority of 3D leaf shape traits were strongly affected by environmental conditions. Overall, this study quantitatively investigated 3D leaf shape in corn, providing a reliable basis for further research on the genetic regulation of corn leaf morphology and advancing the understanding of the complex interplay among crop genetics, phenotypes, and the environment.
玉米叶片的三维（3D）形状存在显著差异，这可被视为多种影响因素的函数，包括遗传、环境因素以及栽培过程的管理。然而，这些差异的原因仍不明确，主要是由于缺乏描述叶片3D空间形态的定量方法。为解决这一问题，本研究获取了478个玉米自交系在灌浆期穗位叶的3D数字化数据。我们提出了13种3D叶片形状特征的定量计算方法，如叶片长度、3D叶面积、叶片倾斜角、叶片夹角、叶片自扭转、叶片平面度和边缘幅度。对这13个叶片性状进行了相关性分析、聚类分析和遗传力分析。还分析了自交系亚群间的叶片形态差异。结果表明，3D叶片性状能够揭示不同叶表面之间的形态差异，遗传分析表明，穗位叶84.62%的3D表型性状遗传力大于0.3。然而，大多数3D叶片形状性状受环境条件影响较大。总体而言，本研究对玉米3D叶片形状进行了定量研究，为进一步研究玉米叶片形态的遗传调控以及增进对作物遗传、表型和环境之间复杂相互作用的理解提供了可靠依据。
