DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays)

Liu, Suxing; Barrow, Carlos Sherard; Hanlon, Meredith; Lynch, Jonathan P.; Bucksch, Alexander

doi:10.1093/plphys/kiab311

DIRT/3D: 3D root phenotyping for field-grown maize (Zea mays)

Journal Article · Thu Jul 08 00:00:00 EDT 2021 · Plant Physiology (Bethesda)

DOI:https://doi.org/10.1093/plphys/kiab311· OSTI ID:1979584

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University of Georgia, Athens, GA (United States); OSTI
University of Georgia, Athens, GA (United States)
Pennsylvania State University, State College, PA (United States)
Department of Plant Biology, University of Georgia, Athens, Georgia 30602, USA; Warnell School of Forestry and Natural Resources, University of Georgia, Athens, Georgia 30602, USA; Institute of Bioinformatics, University of Georgia, Athens, Georgia 30602, USA

The development of crops with deeper roots holds substantial promise to mitigate the consequences of climate change. Deeper roots are an essential factor to improve water uptake as a way to enhance crop resilience to drought, to increase nitrogen capture, to reduce fertilizer inputs, and to increase carbon sequestration from the atmosphere to improve soil organic fertility. A major bottleneck to achieving these improvements is high-throughput phenotyping to quantify root phenotypes of field-grown roots. We address this bottleneck with Digital Imaging of Root Traits (DIRT)/3D, an image-based 3D root phenotyping platform, which measures 18 architecture traits from mature field-grown maize (Zea mays) root crowns (RCs) excavated with the Shovelomics technique. DIRT/3D reliably computed all 18 traits, including distance between whorls and the number, angles, and diameters of nodal roots, on a test panel of 12 contrasting maize genotypes. The computed results were validated through comparison with manual measurements. Overall, we observed a coefficient of determination of r² > 0.84 and a high broad-sense heritability of H$$_{mean}^{2}$$ < 0.6 for all but one trait. The average values of the 18 traits and a developed descriptor to characterize complete root architecture distinguished all genotypes. DIRT/3D is a step toward automated quantification of highly occluded maize RCs. Therefore, DIRT/3D supports breeders and root biologists in improving carbon sequestration and food security in the face of the adverse effects of climate change.

View Accepted Manuscript (DOE)

Research Organization:: Pennsylvania State University, University Park, PA (United States)

Sponsoring Organization:: National Science Foundation (NSF); USDOE Advanced Research Projects Agency - Energy (ARPA-E)

Grant/Contract Number:: AR0000821

OSTI ID:: 1979584

Journal Information:: Plant Physiology (Bethesda), Journal Name: Plant Physiology (Bethesda) Journal Issue: 2 Vol. 187; ISSN 0032-0889

Publisher:: American Society of Plant BiologistsCopyright Statement

Country of Publication:: United States

Language:: English

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