Quantify Wheat Canopy Leaf Angle Distribution Using Terrestrial Laser Scanning Data

Leaf angle distribution (LAD) is an important structural attribute of crop canopies as it influences photosynthesis and radiation transport. Terrestrial laser scanning (TLS) has shown promise as a tool for quantifying LAD. However, the current TLS-derived crop canopy LAD estimation lacks automatic segmentation for the special curved leaves of the crop. Furthermore, mutual shading between plants results in an uneven distribution of leaf point density in the crop canopy. We developed a novel voxel segmentation normal vector (VSNV) method for automatically segmenting and spatially normalizing curved leaves to address those concerns. In this methodology, the wheat canopy is divided into voxels, and LAD is derived by averaging the angles from the planes associated with each point within every voxel. The ray-tracing 3-D radiative transfer model (LESS) was used to validate the effectiveness of the VSNV method, which produced better LAD results than the normal vector (NV) method. In addition, the mean leaf tilt angle (MTA) of wheat estimated by TLS using the VSNV approach correlated well with the measured value from LAI-2200C, especially at the booting stage ( R-2 = 0.76 and RMSE = 1.40(degrees)). The result shows that the improved VSNV method can trace LAD characteristics among cultivars, nitrogen levels, growth stages, and canopy heights. Quantifying the variability of LAD could provide strong technical support for high-throughput phenotyping.