Development of a Ground-Based Peanut Canopy Phenotyping System. Issue 17 (2018)

• Record Type: Journal Article
• Authors: Yuan, Hongbo; Wang, Ning; Bennett, Rebecca; Burditt, Dakota; Cannon, Alec; Chamberlin, Kelly
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 17(2018)
• Page Start: 162
• Page End: 165
• Publication Date: 2018
• Subjects: Phenotyping -- Image processing and analysis -- Laser scanner; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.08.081
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Phenotypic information of peanut canopy, including height, width, shape, and density are important in the selection of the best cultivars of peanuts. However, current methods to acquire these data are mainly by manual measurements or qualitative scorings. These methods are laborious, time-consuming, and subjective. In this study, a ground-based peanut canopy phenotypic system was developed to improve the efficiency and accuracy of the data collection on peanut canopy architecture. The system was on a ground-based, remote controlled cart with a sensor suite of two RGB cameras, a thermal camera, a laser scanner and an RTK GPS. Software programs was developed to control the system and collect, store, and analyze the data. This system was tested in the peanut growth season of 2017. The result showed that the system was able to complete the data collection at least four times faster than previous manual collection. The data collected were with a much higher resolution, thus could be used to acquire detailed features of peanut canopy.