High‐fidelity detection of crop biomass quantitative trait loci from low‐cost imaging in the field
Abstract
Abstract Field‐based, rapid, and nondestructive techniques for assessing plant productivity are needed to accelerate the discovery of genotype‐to‐phenotype relationships in next‐generation biomass grass crops. The use of hemispherical imaging and light attenuation modeling was evaluated against destructive harvest measures with respect to their ability to accurately capture phenotypic and genotypic relationships in a field‐grown grass crop. Plant area index ( PAI ) estimated from below‐canopy hemispherical images, as well as a suite of thirteen traits assessed by manual destructive harvests, were measured in a Setaria recombinant inbred line mapping population segregating for aboveground productivity and architecture. A significant correlation was observed between PAI and biomass production across the population at maturity ( r 2 = .60), as well as for select diverse genotypes sampled repeatedly over the growing season ( r 2 = .79). Twenty‐seven quantitative trait loci ( QTL ) were detected for manually collected traits associated with biomass production. Of these, twenty‐one were found in four clusters of colocalized QTL . Analysis of image‐based estimates of PAI successfully identified all four QTL hot spots for biomass production. QTL for PAI had greater overlap with those detected for traits associated with biomass production than with those for plant architecture and biomassmore »
- Authors:
-
- University of Illinois at Urbana‐Champaign Urbana IL USA
- Donald Danforth Plant Science Center St. Louis MO USA
- USDA‐ARS Donald Danforth Plant Science Center St. Louis MO USA
- Publication Date:
- Research Org.:
- Donald Danforth Plant Science Center, St. Louis, MO (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1423165
- Alternate Identifier(s):
- OSTI ID: 1423169; OSTI ID: 1530865
- Grant/Contract Number:
- DE‐SC0008769; SC0018277; SC0008769
- Resource Type:
- Published Article
- Journal Name:
- Plant Direct
- Additional Journal Information:
- Journal Name: Plant Direct Journal Volume: 2 Journal Issue: 2; Journal ID: ISSN 2475-4455
- Publisher:
- Wiley Blackwell (John Wiley & Sons)
- Country of Publication:
- United Kingdom
- Language:
- English
- Subject:
- 09 BIOMASS FUELS; crop production; hemispherical photographs; high-throughput phenotyping; Leaf Area Index; setaria
Citation Formats
Banan, Darshi, Paul, Rachel E., Feldman, Max J., Holmes, Mark W., Schlake, Hannah, Baxter, Ivan, Jiang, Hui, and Leakey, Andrew D. B. High‐fidelity detection of crop biomass quantitative trait loci from low‐cost imaging in the field. United Kingdom: N. p., 2018.
Web. doi:10.1002/pld3.41.
Banan, Darshi, Paul, Rachel E., Feldman, Max J., Holmes, Mark W., Schlake, Hannah, Baxter, Ivan, Jiang, Hui, & Leakey, Andrew D. B. High‐fidelity detection of crop biomass quantitative trait loci from low‐cost imaging in the field. United Kingdom. https://doi.org/10.1002/pld3.41
Banan, Darshi, Paul, Rachel E., Feldman, Max J., Holmes, Mark W., Schlake, Hannah, Baxter, Ivan, Jiang, Hui, and Leakey, Andrew D. B. Thu .
"High‐fidelity detection of crop biomass quantitative trait loci from low‐cost imaging in the field". United Kingdom. https://doi.org/10.1002/pld3.41.
@article{osti_1423165,
title = {High‐fidelity detection of crop biomass quantitative trait loci from low‐cost imaging in the field},
author = {Banan, Darshi and Paul, Rachel E. and Feldman, Max J. and Holmes, Mark W. and Schlake, Hannah and Baxter, Ivan and Jiang, Hui and Leakey, Andrew D. B.},
abstractNote = {Abstract Field‐based, rapid, and nondestructive techniques for assessing plant productivity are needed to accelerate the discovery of genotype‐to‐phenotype relationships in next‐generation biomass grass crops. The use of hemispherical imaging and light attenuation modeling was evaluated against destructive harvest measures with respect to their ability to accurately capture phenotypic and genotypic relationships in a field‐grown grass crop. Plant area index ( PAI ) estimated from below‐canopy hemispherical images, as well as a suite of thirteen traits assessed by manual destructive harvests, were measured in a Setaria recombinant inbred line mapping population segregating for aboveground productivity and architecture. A significant correlation was observed between PAI and biomass production across the population at maturity ( r 2 = .60), as well as for select diverse genotypes sampled repeatedly over the growing season ( r 2 = .79). Twenty‐seven quantitative trait loci ( QTL ) were detected for manually collected traits associated with biomass production. Of these, twenty‐one were found in four clusters of colocalized QTL . Analysis of image‐based estimates of PAI successfully identified all four QTL hot spots for biomass production. QTL for PAI had greater overlap with those detected for traits associated with biomass production than with those for plant architecture and biomass partitioning. Hemispherical imaging is an affordable and scalable method, which demonstrates how high‐throughput phenotyping can identify QTL related to biomass production of field trials in place of destructive harvests that are labor, time, and material intensive.},
doi = {10.1002/pld3.41},
journal = {Plant Direct},
number = 2,
volume = 2,
place = {United Kingdom},
year = {2018},
month = {2}
}
https://doi.org/10.1002/pld3.41
Web of Science
Figures / Tables:

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Figures / Tables found in this record: