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

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

Research output: Contribution to journalArticlepeer-review

75 Scopus citations

Abstract

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. 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.
Original languageEnglish (US)
JournalScientific Reports
Volume7
DOIs
StatePublished - Feb 21 2017
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2022-09-13

ASJC Scopus subject areas

  • General

Fingerprint

Dive into the research topics of 'Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice'. Together they form a unique fingerprint.

Cite this