Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.; Lovell, John T.; Moyers, Brook T.; Baraoidan, Marietta; Naredo, Maria Elizabeth B.; McNally, Kenneth L.; Poland, Jesse; Bush, Daniel R.; Leung, Hei; Leach, Jan E.; McKay, John K.

doi:10.1038/srep42839

Title: Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

Journal Article · 21 February 2017 · Scientific Reports

DOI: https://doi.org/10.1038/srep42839 · OSTI ID:1366463

Tanger, Paul ^[1]; Klassen, Stephen ^[2]; Mojica, Julius P. ^[3]; Lovell, John T. ^[4]; Moyers, Brook T. ^[1]; Baraoidan, Marietta ^[2]; Naredo, Maria Elizabeth B. ^[2]; McNally, Kenneth L. ^[2]; Poland, Jesse ^[5]; Bush, Daniel R. ^[6]; Leung, Hei ^[2]; Leach, Jan E. ^[1]; McKay, John K. ^[1]

Colorado State Univ., Fort Collins, CO (United States). Bioagricultural Sciences and Pest Management
International Rice Research Inst. (IRRI), Los Banos (Phillippines)
Colorado State Univ., Fort Collins, CO (United States). Bioagricultural Sciences and Pest Management; Duke Univ., Durham, NC (United States). Dept. of Biology
Univ. of Texas, Austin, TX (United States). Dept. of Integrative Biology
Kansas State Univ., Manhattan, KS (United States). Dept. of Plant Pathology
Colorado State Univ., Fort Collins, CO (United States). Dept. of Biology

In order to ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. We demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor- intensive measures of flowering time, height, biomass, grain yield, and harvest index. Furthermore, genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.

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Research Organization:: Colorado State Univ., Fort Collins, CO (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: FG02-08ER64629

OSTI ID:: 1366463

Journal Information:: Scientific Reports, Vol. 7; ISSN 2045-2322

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 55 works

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