中国农业科学 ›› 2018, Vol. 51 ›› Issue (6): 1034-1044.doi: 10.3864/j.issn.0578-1752.2018.06.003

• 耕作栽培·生理生化·农业信息技术 • 上一篇    下一篇

基于三维数字化的玉米株型参数提取方法研究

温维亮1,2,3,郭新宇1,2,赵春江1,2,3,肖伯祥1,2,王勇健1,2

 
  

  1. 1北京农业信息技术研究中心,北京 100097;2数字植物北京市重点实验室,北京 100097;3北京工业大学计算机学院,北京 100124
  • 收稿日期:2017-05-17 出版日期:2018-03-16 发布日期:2018-03-16
  • 通讯作者: 郭新宇,Tel:010-51503422;E-mail:guoxy@nercita.org.cn
  • 作者简介:温维亮,Tel:010-51503362;Email:wenwl@nercita.org.cn
  • 基金资助:
    “863”计划(2013AA102404-02)、国家自然科学基金(31601215)、北京市农林科学院青年科研基金(QNJJ201625)、北京市农林科学院数字植物科技创新团队(JNKYT201604)

Research on Maize Plant Type Parameter Extraction by Using Three Dimensional Digitizing Data

WEN WeiLiang1,2,3, GUO XinYu1,2, ZHAO ChunJiang1,2,3, XIAO BoXiang1,2, WANG YongJian1,2   

  1. 1Beijing Research Center for Information Technology in Agriculture, Beijing 100097; 2Beijing Key Laboratory of Digital Plant, Beijing 100097; 3College of Computer Science, Beijing University of Technology, Beijing 100124
  • Received:2017-05-17 Online:2018-03-16 Published:2018-03-16

摘要: 【目的】玉米株型参数获取是玉米精确化育种和栽培研究的重要环节,研究解决玉米株型参数获取中存在的测量标准不一致、测量精度低、数据难以可视化、算法提取参数精度低等问题具有重要意义。【方法】本文利用三维数字化仪获取玉米植株骨架结构,提出玉米茎、叶、雄穗和雌穗器官三维数字化获取标准规程。通过将植株三维数字化数据旋转至与Z轴正方向平行并平移至坐标系原点进行数据标准化,进一步根据三维数字化数据位置关系,结合各株型参数的定义实现了株高、叶片着生高度、叶片最高点高度、叶长、叶宽、叶展、叶倾角及叶方位角等主要株型参数的提取,同时提出一种新的玉米植株方位平面计算方法,通过构建植株方位平面与各叶方位角角度差绝对值之和作为目标优化函数,进一步对该L1优化问题进行迭代求解得到植株方位平面,当叶数量是偶数时,方法可以给出精确的方位平面区间,在此基础上,引入dev值作为评价植株叶相对植株方位平面偏离度的指标。【结果】利用6个品种吐丝期玉米植株三维数字化数据和人工测量参数数据进行株型参数提取方法验证。结果表明,方法提取的叶长、叶倾角、方位角误差较小,RMSE分别为3.44 cm、3.41°和8.23°,叶长和叶倾角的MAPE分别为4.06%和4.72%,叶宽因叶片在叶脉垂直平面上的曲线形态不一致导致误差相对较大,RMSE和MAPE分别为0.80 cm和7.21%。与传统负方向能量均值法相比,所提出新的玉米植株方位平面计算方法给出了玉米植株方位平面更确切的定量化描述,对于玉米株型的定量评价具有一定价值。【结论】基于三维数字化的玉米株型参数提取方法为玉米株型参数的提取与分析提供了一种精确、便捷、可视的技术手段,对于玉米株型表型组学、玉米功能结构模型及玉米株型优化研究具有重要作用。

关键词: 玉米, 株型参数, 三维数字化, 植株方位平面

Abstract: 【Objective】Morphological parameters acquisition of maize plant is an important part for maize breeding research. Now, the mainly acquisition method of plant type parameter is manual measurement, which has the problems of non-uniform standard, low accuracy and difficult to visualize, etc. Plant type parameter extraction from image or three dimensional (3D) point cloud depends on the algorithms of skeleton extraction, and it has a low accuracy of recent methods.【Method】In this paper, we proposed a maize plant type parameter extraction method by using 3D digitizing data. The maize plant skeleton data was obtained by using 3D digitizer, and an acquisition standard for maize stalk, leaf, tassel and ear was proposed to promise uniform morphological data. The 3D digitized data was regularized by moving to the origin of the space coordinate system and rotating parallel to the Z axis. Morphological parameters, including plant height, leaf insertion height, blade peak height, leaf length, leaf width, blade span length, leaf insertion inclination, and leaf azimuthal angle, were extracted according to the relationship of 3D digitizing point and the definition of each parameter. Exact formulas were given of each morphological parameter. Meanwhile, a novel method for calculating plant azimuth plane was proposed by iteratively for solving an L1 optimization problem, which is described by the minimum sum of every azimuth angle to the azimuthal plane. The algorithm could calculate the exact plant azimuthal range when the leaf number was even. An index called dev value was introduced to evaluate the deviation of maize leaves from the azimuthal plane. 【Result】 3D digital data and manual measured parameters of 6 different cultivars of maize plant, with the abbreviations of JK665, JK968, MC812, ND108, XY335 and ZD958, were obtained to verify the extraction method. Experimental results showed that the error of leaf length, leaf insertion inclination and leaf azimuth were very small, the corresponding RMSE (root mean square error) were 3.44 cm, 3.41°, and 8.23°, respectively. The MAPE (mean absolute percent error) of leaf length and leaf insertion inclination were 4.06% and 4.72%, respectively. The error of leaf width with RMSE = 0.8 cm and MAPE = 7.21%, was a little larger than other parameters, because the curve shape vertical to the midrib on the leaf was different. The novel azimuthal plane estimation method gave a quantitative description and derived better results than the averaged azimuth angle approach. The dev value could be used for estimating the spatial expansion of maize plants. In theory, larger dev value cultivar maize plants could intercept more photosynthetically active radiation. 【Conclusion】 The research provided an accurate, convenient and visual way for extracting and analyzing maize plant type parameters and had an important role in the optimization of maize plant type, functional-structural plant modeling, and plant phenotyping research.

Key words: maize, plant type parameter, 3D digitizing, plant azimuthal plane