Abstract:
Root crown phenotyping measures the top portion of crop root systems and can be used for marker-assisted breeding, genetic mapping, and understanding how roots influence soil resource acquisition. Several imaging protocols and image analysis programs exist, but they are not optimized for high-throughput, repeatable, and robust root crown phenotyping. The RhizoVision Crown platform integrates an imaging unit, image capture software, and image analysis software that are optimized for reliable extraction of measurements from large numbers of root crowns. The hardware platform utilizes a back light and a monochrome machine vision camera to capture root crown silhouettes. RhizoVision Imager and RhizoVision Analyzer are free, open-source software that streamline image acquisition and image analysis with intuitive graphical user interfaces. RhizoVision Analyzer was physically calibrated using copper wire and extensively validated with 10,464 ground-truth simulated images of dicot and monocot root systems. The entire platform was further validated by phenotyping 6,256 root crowns from field-grown wheat and soybean populations, and linear discriminant analysis accurately classified the root crowns using the multivariate measurements. Overall, the integrated RhizoVision Crown platform facilitates state-of-the-art phenotyping of crop root crowns, and sets a standard for which open plant phenotyping platforms broadly can be benchmarked.
Links:
Citation:
A. Seethepalli, H. Guo, X. Liu, M. Griffiths, H. Almtarfi, Z. Li, S. Liu, A. Zare, F. Fritschi, E. Blancaflor, X. Ma, and L. York, “RhizoVision Crown: An Integrated Hardware and Software Platform for Root Crown Phenotyping,” in Plant Phenomics, vol. 2020, Article ID 3074916, 15 pages, https://doi.org/10.34133/2020/3074916, 2020.
@Article{Seethepalli2019RhizoVision,
Title = {RhizoVision Crown: An Integrated Hardware and Software Platform for Root Crown Phenotyping },
Author = {Seethepalli, Anand and Guo, Haichao and Liu, Xiuwei and Griffiths, Marcus and Almtarfi, Hussien and Li, Zenglu and Liu, Shuyu and Zare, Alina and Fritschi, Felix and Blancaflor, Elison and Ma, Xuefeng and York, Larry},
Journal = {Plant Phenomics},
Volume = {2020},
Article ID = {3074916},
DOI = {https://doi.org/10.34133/2020/3074916},
Year = {2020},
}