LiDAR Platform for Acquisition of 3D Plant Phenotyping Database

• Published in: Plants (Basel) Vol. 11; no. 17; p. 2199
• Main Authors: Forero, Manuel G, Murcia, Harold F, Méndez, Dehyro, Betancourt-Lozano, Juan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 25.08.2022; MDPI
• Subjects: 3D maize database; 3D reconstruction; Analysis; Cameras; Genotype & phenotype; Lasers; Lidar; LiDAR platform; Morphology; Optical radar; Phenotype; Phenotyping; plant phenotyping; Plants (botany); point clouds; Power supply; Seedlings; Sensors; Software; Three dimensional models; Time synchronization; Wide area networks; Colombia
• ISSN: 2223-7747; 2223-7747
• DOI: 10.3390/plants11172199

Currently, there are no free databases of 3D point clouds and images for seedling phenotyping. Therefore, this paper describes a platform for seedling scanning using 3D Lidar with which a database was acquired for use in plant phenotyping research. In total, 362 maize seedlings were recorded using an RGB camera and a SICK LMS4121R-13000 laser scanner with angular resolutions of 45° and 0.5° respectively. The scanned plants are diverse, with seedling captures ranging from less than 10 cm to 40 cm, and ranging from 7 to 24 days after planting in different light conditions in an indoor setting. The point clouds were processed to remove noise and imperfections with a mean absolute precision error of 0.03 cm, synchronized with the images, and time-stamped. The database includes the raw and processed data and manually assigned stem and leaf labels. As an example of a database application, a Random Forest classifier was employed to identify seedling parts based on morphological descriptors, with an accuracy of 89.41%.