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Voxel carving‐based 3D reconstruction of sorghum identifies genetic determinants of light interception efficiency

机译:高粱的基于体素雕刻的3D重建识别光拦截效率的遗传决定因素

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摘要

Changes in canopy architecture traits have been shown to contribute to yield increases. Optimizing both light interception and light interception efficiency of agricultural crop canopies will be essential to meeting the growing food needs. Canopy architecture is inherently three‐dimensional (3D), but many approaches to measuring canopy architecture component traits treat the canopy as a two‐dimensional (2D) structure to make large scale measurement, selective breeding, and gene identification logistically feasible. We develop a high throughput voxel carving strategy to reconstruct 3D representations of sorghum from a small number of RGB photos. Our approach builds on the voxel carving algorithm to allow for fully automatic reconstruction of hundreds of plants. It was employed to generate 3D reconstructions of individual plants within a sorghum association population at the late vegetative stage of development. Light interception parameters estimated from these reconstructions enabled the identification of known and previously unreported loci controlling light interception efficiency in sorghum. The approach is generalizable and scalable, and it enables 3D reconstructions from existing plant high throughput phenotyping datasets. We also propose a set of best practices to increase 3D reconstructions’ accuracy.
机译:已经显示了树冠架构特征的变化有助于产量增加。优化农业作物的光线拦截和轻拦截效率,对满足日益增长的食物需求至关重要。天底架构本质上是三维(3D),但是测量冠层架构组件的方法是将冠层视为二维(2D)结构,以制作大规模测量,选择性育种和基因识别逻辑上可行的。我们开发出高吞吐量的体素雕刻策略,从少数RGB照片重建高粱的3D表示。我们的方法在体素雕刻算法上建立了允许全自动重建数百家植物。在晚期营养阶段的发展中,它用于在高粱会群中产生单个植物的三维重建。从这些重建估计的光拦截参数使得能够识别高粱中的已知和先前未报告的基因座控制光拦截效率。该方法是概括和可扩展的,并且它能够从现有的植物高吞吐量表型数据集中实现3D重建。我们还提出了一系列最佳实践来提高3D重建的准确性。

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