Saha, Kowshik KumarTsoulias, NikosWeltzien, CorneliaZude-Sasse, Manuela2022-02-142022-02-142022-01-19https://depositonce.tu-berlin.de/handle/11303/16360http://dx.doi.org/10.14279/depositonce-15136Monitoring of plant vegetative growth can provide the basis for precise crop management. In this study, a 2D light detection and ranging (LiDAR) laser scanner, mounted on a linear conveyor, was used to acquire multi-temporal three-dimensional (3D) data from strawberry plants (‘Honeoye’ and ‘Malling Centenary’) 14–77 days after planting (DAP). Canopy geometrical variables, i.e., points per plant, height, ground projected area, and canopy volume profile, were extracted from 3D point cloud. The manually measured leaf area exhibited a linear relationship with LiDAR-derived parameters (R2 = 0.98, 0.90, 0.93, and 0.96 with number of points per plant, volume, height, and projected canopy area, respectively). However, the measuring uncertainty was high in the dense canopies. Particularly, the canopy volume estimation was adapted to the plant habitus to remove gaps and empty spaces in the canopy point cloud. The parametric values for maximum point to point distance (Dmax) = 0.15 cm and slice height (S) = 0.10 cm resulted in R² = 0.80 and RMSPE = 26.93% for strawberry plant volume estimation considering actual volume measured by water displacement. The vertical volume profiling provided growth data for cultivars ‘Honeoye’ and ‘Malling Centenary’ being 51.36 cm³ at 77 DAP and 42.18 cm3 at 70 DAP, respectively. The results contribute an approach for estimating plant geometrical features and particularly strawberry canopy volume profile based on LiDAR point cloud for tracking plant growth.en630 Landwirtschaft und verwandte Bereichecanopy volumenon-destructivepoint cloudvolume profileFragaria × ananassaArticle2022-02-082311-7524