The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-2/W13
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 357–361, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-357-2019
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 357–361, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-357-2019

  04 Jun 2019

04 Jun 2019

HIGH THROUGHPUT PHENOTYPING OF PHYSIOLOGICAL GROWTH DYNAMICS FROM UAS-BASED 3D MODELING IN SOYBEAN

M. Herrero-Huerta and K. M. Rainey M. Herrero-Huerta and K. M. Rainey
  • Department of Agronomy, Purdue University, IN 47906, USA

Keywords: Unmanned Aerial System (UAS), Photogrammetry, High-Throughput Phenotyping, 3D model, Soybean, Physiological growth, Structure from Motion (SfM)

Abstract. Nowadays, an essential tool to improve the efficiency of crop genetics is automated, precise and cost-effective phenotyping of the plants. The aim of this study is to generate a methodology for high throughput phenotyping the physiological growth dynamics of soybeans by UAS-based 3D modelling. During the 2018 growing season, a soybean experiment was performed at the Agronomy Center for Research and Education (ACRE) in West-Lafayette (Indiana, USA). Periodic images were acquired by G9X Canon compact digital camera on board senseFly eBee. The study area is reconstructed in 3D by Image-based modelling. Algorithms and techniques were combined to analyse growth dynamics of the crop via height variations and to quantify biomass. Results provide practical information for the selection of phenotypes for breeding.