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Dryad

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

Cite this dataset

Tanger, Paul et al. (2017). Data from: Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice [Dataset]. Dryad. https://doi.org/10.5061/dryad.53bj8

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.

Usage notes

Location

Philippines