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Three-Dimensional Wheat Modelling Based on Leaf Morphological Features and Mesh Deformation

文献类型： 外文期刊

作者： Zheng, Chenxi 1 ; Wen, Weiliang 2 ; Lu, Xianju 2 ; Chang, Wushuai 2 ; Chen, Bo 2 ; Wu, Qiang 4 ; Xiang, Zhiwei 2 ; Guo, Xinyu 2 ; Zhao, Chunjiang 1 ;

作者机构： 1.Northwest A&F Univ, Coll Informat Engn, Xianyang 712100, Peoples R China

2.Natl Engn Res Ctr Informat Technol Agr, Beijing Key Lab Digital Plant, Beijing 100097, Peoples R China

3.Beijing Acad Agr & Forestry Sci, Informat Technol Res Ctr, Beijing 100097, Peoples R China

4.Inner Mongolia Agr Univ, Coll Agron, Hohhot 010019, Peoples R China

关键词： three-dimensional modelling; mesh deformation; wheat; morphological leaf features; 3D digitization

期刊名称：AGRONOMY-BASEL （ 影响因子：3.949； 五年影响因子：4.117 ）

ISSN：

年卷期： 2022 年 12 卷 2 期

页码：

收录情况： SCI

摘要： The three-dimensional (3D) morphological structure of wheat directly reflects the interrelationship among genetics, environments, and cropping systems. However, the morphological complexity of wheat limits its rapid and accurate 3D modelling. We have developed a 3D wheat modelling method that is based on the progression from skeletons to mesh models. Firstly, we identified five morphological parameters that describe the 3D leaf features of wheat from amounts of 3D leaf digitizing data at the grain filling stage. The template samples were selected based on the similarity between the input leaf skeleton and leaf templates in the constructed wheat leaf database. The leaf modelling was then performed using the as-rigid-as-possible (ARAP) mesh deformation method. We found that 3D wheat modelling at the individual leaf level, leaf group, and individual plant scales can be achieved. Compared with directly acquiring 3D digitizing data for 3D modelling, it saves 79.9% of the time. The minimum correlation R-2 of the extracted morphological leaf parameters between using the measured data and 3D model by this method was 0.91 and the maximum RMSE was 0.03, implying that this method preserves the morphological leaf features. The proposed method provides a strong foundation for further morphological phenotype extraction, functional-structural analysis, and virtual reality applications in wheat plants. Overall, we provide a new 3D modelling method for complex plants.

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