A calculation method of phenotypic traits based on three-dimensional reconstruction of tomato canopy

Abstract

Accurate and rapid acquisition of tomato canopies’ phenotypic traits was significant for variety breeding, cultivation, and scientific management. Manual measurements were time-consuming, laborious, and error-prone. The large devices in the field were lack of mobility, while the single perspective was limited by the environment’s obstruction, making it challenging to achieve high-throughput detection of tomato plants’ phenotypes. Therefore, a method for high-throughput detection of tomato canopy’s phenotypic traits was proposed based on three-dimensional (3D) structure reconstruction with multi-views. First, the tomato variety named Dongnong 708 was set as an experimental object. The acquisition platform was constructed using three Kinect 2.0 sensors to acquire a full range point cloud of tomato canopy at crucial growth stages, including the initial flowering stage, florescence, and primary fruit stage. Second, the background and interference noises were removed by Conditional filtering and Statistical Outlier Removal (SOR) filtering. Then, its structural characteristic points were extracted, and spatial position was registered by combining with Intrinsic Shape Signatures (ISS) and Iterative Closest Point (ICP) algorithms. In addition, the 3D-Normal Distributions Transform (NDT) algorithm was used to realize accurate registration of three perspectives’ point clouds. Compared with NDT and ICP algorithms, the average error of the proposed methods here was 0.027, reduced by 0.02 and 0.04, respectively. Finally, the contour of tomato canopy was extracted using the AlphaShape algorithm. Based on the reconstructed result, plant height, canopy width, and leafstalk angle, were calculated. The results showed that the correlation coefficients were 0.9615, 0.809 and 0.9014 between the calculated values and measured values. The average errors were 1.38 cm, 5.1° and 1.92 cm, respectively. The methods proposed in the paper could be used as a rapid detection method for quantitative indexes of the phenotypic traits for the tomato canopy and provide technical support for breeding, scientific cultivation, and environmental regulation.