Estimation of Vegetative Growth in Strawberry Plants Using Mobile LiDAR Laser Scanner

Abstract

Monitoring 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.

Volume Determination Challenges in Waste Sorting Facilities: Observations and Strategies

“…Other cutting-edge technologies, such as LIDAR ("Light Detecting and Ranging") and 3D Laser scanners, are currently under development by various companies. For example, LIDAR scanners have been employed to monitor the vegetative growth in strawberry plants, including volume estimates from 3D point clouds [20]. These technologies may be applied to accurately determine the volume of different materials within industrial bunkers and conveyor belts.…”

“…Incorporating more accurate level measurements within the bunker by diversifying the sensor suite, albeit potentially higher in cost, could deliver more precise information about current material quantities. The ultrasonic sensors referenced in this study focused on the highest point, while other models may provide more comprehensive data on the 3D surface [20]. Another idea to overcome the challenge of measuring uneven surfaces may involve the installation of sensors before waste entry, above each bunker's input conveyor belt.…”

Design and experiments with a SLAM system for low-density canopy environments in greenhouses based on an improved Cartographer framework

“…In recent years, with the development of computer technology and edge computing equipment, the sensors used for greenhouse operating environment perception and localization have included ultrasonic technology (Palleja and Landers, 2017;Chen et al, 2018;Lao et al, 2021), ultra-wideband (UWB) technology (Hou et al, 2020;Yao et al, 2021), LiDAR technology (Chen et al, 2019;Zhang et al, 2020;Saha et al, 2022;Sun et al, 2022), and machine vision technology (Nissimov et al, 2015;Wang et al, 2022a;Wang et al, 2022b). Huang et al (2021) designed a robot localization system based on spread spectrum sounds for a greenhouse containing a strawberry ridge and achieved centimeter-level localization accuracy in a small greenhouse.…”

Precision Management of Fruit Trees

“…The results suggested that cultivar differences in response to light quality may be relevant for understanding adaptation to dense orchards and identifying cultivars best suited to them. Saha et al [4] found that monitoring 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, threedimensional (3D) data from strawberry plants.…”