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

dc.citationTanger, P., Klassen, S., Mojica, J. P., Lovell, J. T., Moyers, B. T., Baraoidan, M., . . . McKay, J. K. (2017). Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice. Scientific Reports, 7, 8. https//doi.org/10.1038/srep42839
dc.citation.doi10.1038/srep42839
dc.citation.epage8
dc.citation.issn2045-2322
dc.citation.issue1
dc.citation.jtitleScientific Reports
dc.citation.spage1
dc.citation.volume7
dc.contributor.authorTanger, P.
dc.contributor.authorKlassen, S.
dc.contributor.authorMojica, J. P.
dc.contributor.authorLovell, J. T.
dc.contributor.authorMoyers, B. T.
dc.contributor.authorBaraoidan, M.
dc.contributor.authorNaredo, M. E. B.
dc.contributor.authorMcNally, K. L.
dc.contributor.authorPoland, Jesse A.
dc.contributor.authorBush, D. R.
dc.contributor.authorLeung, H.
dc.contributor.authorLeach, J. E.
dc.contributor.authorMcKay, J. K.
dc.contributor.authoreidjpoland
dc.contributor.kstatePoland, Jesse A.
dc.date.accessioned2017-11-30T21:53:39Z
dc.date.available2017-11-30T21:53:39Z
dc.date.issued2017-02-21
dc.date.published2017
dc.descriptionCitation: Tanger, P., Klassen, S., Mojica, J. P., Lovell, J. T., Moyers, B. T., Baraoidan, M., . . . McKay, J. K. (2017). Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice. Scientific Reports, 7, 8. doi:10.1038/srep42839
dc.description.abstractTo 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. Here 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. 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.
dc.description.versionArticle: Version of Record
dc.identifier.urihttp://hdl.handle.net/2097/38402
dc.relation.urihttps://doi.org/10.1038/srep42839
dc.rights© The Author(s) 2017. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectQuantitative Trait Loci
dc.subjectGreen-Revolution
dc.subjectCrosses
dc.subjectScience & Technology - Other Topics
dc.titleField-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice
dc.typeArticle

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