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首页> 外文期刊>Journal of Experimental Botany >Dynamic quantification of canopy structure to characterize early plant vigour in wheat genotypes
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Dynamic quantification of canopy structure to characterize early plant vigour in wheat genotypes

机译：动态定量冠层结构表征小麦基因型早期植物活力

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An efficient workflow based on photos to monitor early growth and development of isolated wheat plants dynamically is described.Early vigour is an important physiological trait to improve establishment, water-use efficiency, and grain yield for wheat. Phenotyping large numbers of lines is challenging due to the fast growth and development of wheat seedlings. Here we developed a new photo-based workflow to monitor dynamically the growth and development of the wheat canopy of two wheat lines with a contrasting early vigour trait. Multiview images were taken using a 'vegetation stress' camera at 2 d intervals from emergence to the sixth leaf stage. Point clouds were extracted using the Multi-View Stereo and Structure From Motion (MVS-SFM) algorithm, and segmented into individual organs using the Octree method, with leaf midribs fitted using local polynomial function. Finally, phenotypic parameters were calculated from the reconstructed point cloud including: tiller and leaf number, plant height, Haun index, phyllochron, leaf length, angle, and leaf elongation rate. There was good agreement between the observed and estimated leaf length (RMSE=8.6mm,R (2)=0.98,n=322) across both lines. Significant contrasts of phenotyping parameters were observed between the two lines and were consistent with manual observations. The early vigour line had fewer tillers (2.4 +/- 0.6) and larger leaves (308.0 +/- 38.4mm and 17.1 +/- 2.7mm for leaf length and width, respectively). While the phyllochron of both lines was quite similar, the non-vigorous line had a greater Haun index (more leaves on the main stem) on any date, as the vigorous line had slower development of its first two leaves. The workflow presented in this study provides an efficient method to phenotype individual plants using a low-cost camera (an RGB camera is also suitable) and could be applied in phenotyping for applications in both simulation modelling and breeding. The rapidity and accuracy of this novel method can characterize the results of specific selection criteria (e.g. width of leaf three, number of tillers, rate of leaf appearance) that have been or can now be utilized to breed for early leaf growth and tillering in wheat.
机译：描述了一种有效的基于照片的工作流程，可以动态地监测孤立的小麦植物的早期生长和发育。早期活力是提高小麦植株，水分利用效率和谷物产量的重要生理特征。由于小麦幼苗的快速生长和发育，对大量株系进行表型分型具有挑战性。在这里，我们开发了一种基于照片的新工作流程，以动态监视具有鲜明的早期活力特征的两个小麦品系的小麦冠层的生长和发育。从出苗到第六叶片阶段，以2 d的间隔使用“植被应力”相机拍摄多视图图像。使用多视图立体和运动结构（MVS-SFM）算法提取点云，并使用Octree方法将其分割为单个器官，并使用局部多项式函数拟合叶中脉。最后，从重建的点云计算表型参数，包括：分till和叶片数，植株高度，Haun指数，叶序，叶片长度，角度和叶片伸长率。两条线之间的观察叶长和估计叶长之间有很好的一致性（RMSE = 8.6mm，R（2）= 0.98，n = 322）。在两条线之间观察到表型参数的显着对比，并且与手工观察一致。早期活力线的分till数较少（2.4 +/- 0.6），叶片较大（叶长和宽分别为308.0 +/- 38.4mm和17.1 +/- 2.7mm）。尽管两株系的叶系时间非常相似，但非活力系在任何日期的Haun指数都较高（主茎上的叶片较多），因为活力系的前两片叶片发育较慢。本研究中介绍的工作流程提供了一种使用低成本相机（也可以使用RGB相机）对单个植物进行表型化的有效方法，并且可以应用于在表型分析中用于模拟建模和育种。这种新方法的快速性和准确性可以表征已经或现在可以用于小麦早期叶片生长和分till的育种的特定选择标准（例如，三叶的宽度，分ers数，叶出现率）的结果。 。

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