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| Hauptseite > Publikationsdatenbank > 3D Reconstruction of Cassava Roots Using COLMAP |
| Hauptseite > Publikationsdatenbank > 3D Reconstruction of Cassava Roots Using COLMAP |
| Internal Report | FZJ-2025-04413 |
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2025
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Please use a persistent id in citations: doi:10.34734/FZJ-2025-04413
Abstract: Cassava (Manihot esculenta) is an important crop for food security in tropical and subtropical regions, with roots containing up to 85% starch on a dry weight basis [25]. Understanding root system architecture is essential for breeding programs aimed at improving yield and stress tolerance [1]. Traditional 2D imaging methods for root phenotyping have limitations in capturing threedimensional root structures, leading to incomplete trait measurements [28, 8]. While advanced 3D methods like DIRT/3D 2.0 exist [14], they require specialized equipment that may not be accessible to all research facilities. This laboratory work implemented a cost-effective 3D reconstruction pipeline using standard DSLR cameras and open-source software (REMBG, COLMAP) to extract morphological traits from cassava roots. The pipeline combined deep learning-based segmentation with structure from motion techniques to analyze 1039 cassava root system acquisitions from plants aged 5-10 weeks collected at the Rayong Field Crops Research Center in Thailand, achieving 62% reconstruction success (644 successfully reconstructed roots).
Keyword(s): Instrument and Method Development (2nd)
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