Measurement method of maize morphological parameters based on point cloud image conversion

Abstract

The plant height (PH), stem thickness long axis (STLA), and stem thickness short axis (STSA) in maize morphological parameters can effectively reflect the growth, lodging resistance and yield information of maize plants. Terrestrial laser scanning (TLS) can achieve rapid measurement of crop phenotypic parameters. To address the problems of low automation and leaf interference in the existing measurement methods, TLS was used as the measurement sensor, and a morphological measurement method for PH, STLA and STSA of field maize based on point cloud image conversion was proposed. First, in the V3, V6, V9, and V12 stages, three-dimensional (3D) point cloud data of two maize varieties (Jingnongke 728 and Nongda 84) were obtained by TLS. Second, the point cloud processing software was used to match the collected maize point cloud data, obtain the registered multi-site cloud data, remove the background point cloud data, extract the maize row data, and carry out down-sampling. Programming was used to realize data format conversion and individual plant segmentation. Third, several methods, including plane segmentation, statistical filtering, pass filtering, maximum and minimum traversal, and Euclidean clustering were used to remove ground point clouds, judge whether there was maize plant, and extract area maize point clouds. A method of point cloud image conversion was proposed to realize the segmentation of maize stem and leaf. Finally, the height of the plant was measured by calculating the vertical distance from the highest point of the plant to its base. The point cloud of the stem at a specific location was identified, and the ellipse fitting method was used to measure the thickness of the long axis and the short axis of the stem. Compared with the measured value of artificial point cloud, the PH, STLA and STSA of maize in 4 growth stages were measured using automatic program. The root mean square error (RMSE) of the PH, STLA and STSA of Jingnongke 728 were 0.61 cm, 3.16 mm and 2.53 mm respectively, and the mean absolute percentage error (MAPE) were 0.52%, 7.90% and 9.70% respectively. The RMSE of Nongda 84 were 0.66 cm, 2.63 mm and 2.42 mm respectively, and the MAPE were 0.75%, 7.07% and 9.76% respectively. The results show that the point cloud image conversion method for measuring PH, STLA and STSA proposed in this article is suitable for maize of different growth periods and different maize varieties. It is highly consistent with the artificial point cloud measurement values and can replace manual measurement. It can provide breeders with a fast, automatic and accurate measurement program for the PH, STLA and STSA of maize.