GiA Roots: software for the high throughput analysis of plant root system architecture
By Taras Galkovskyi, Yuriy Mileyko, Alexander Bucksch, Brad T. Moore, O. Symonova, C. Price, C. Topp, A. Iyer‐Pascuzzi, Paul R. Zurek, Suqin Fang and 3 more. BMC Plant Biology, 2012
354 citations recorded by the source corpus.
Characterizing root system architecture (RSA) is essential to understanding the development and function of vascular plants. Identifying RSA-associated genes also represents an underexplored opportunity for crop improvement. Software tools are needed to accelerate the pace at which quantitative traits of RSA are estimated from images of root networks. We have developed GiA Roots (General Image Analysis of Roots), a semi-automated software tool designed specifically for the high-throughput analysis of root system images. GiA Roots includes user-assisted algorithms to distinguish root from background and a fully automated pipeline that extracts dozens of root system phenotypes. Quantitative information on each phenotype, along with intermediate steps for full reproducibility, is returned to the end-user for downstream analysis. GiA Roots has a GUI front end and a command-line interface for interweaving the software into large-scale workflows. GiA Roots can also be extended to estimate novel phenotypes specified by the end-user. We demonstrate the use of GiA Roots on a set of 2393 images of rice roots representing 12 genotypes from the species Oryza sativa. We validate trait measurements against prior analyses of this image set that demonstrated that RSA traits are likely heritable and associated with genotypic differences. Moreover, we demonstrate that GiA Roots is extensible and an end-user can add functionality so that GiA Roots can estimate novel RSA traits. In summary, we show that the software can function as an efficient tool as part of a workflow to move from large numbers of root images to downstream analysis.
Subfields: Plant Science
View Paper: https://www.semanticscholar.org/paper/645baac3ff233db648826be434a4ab438d57b174
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In Plant Science
Citations in the corpus
- Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype–phenotype relationships and its relevance to crop improvement (2013, methodology): “A notable example is GiaRoots, a software program that allows users to incorporate their own processing and algorithms into the automated analysis routines as a way of overcoming the limitations imposed by more integrated approaches (Galkovskyi et al. 2012).”
- Growth Responses and Root Characteristics of Lettuce Grown in Aeroponics, Hydroponics, and Substrate Culture (2018, background): “The measured root characteristics included average root diameter (width), root length (network length), root area (network surface area), root volume (network volume), maximum number of roots, median number of roots, and network perimeter[27].”
- Crop Phenomics and High-throughput Phenotyping: Past Decades, Current Challenges and Future Perspectives. (2020, neutral): “Other 3D image reconstruction and image analysis pipelines include GiARoots (Galkovskyi et al., 2012) and RootReader3D (Clark et al., 2011).”