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