2 Works

Data from: 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
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...

Data from: Combining high-throughput phenotyping and genomic information to increase prediction and selection accuracy in wheat breeding

Jared Crain, Suchismita Mondal, Jessica Rutkoski, Ravi P. Singh & Jesse Poland
Genomics and phenomics have promised to revolutionize the field of plant breeding. The integration of these two fields has just begun and is being driven through big data by advances in next-generation sequencing and developments of field-based high-throughput phenotyping (HTP) platforms. Each year the International Maize and Wheat Improvement Center (CIMMYT) evaluates tens-of-thousands of advanced lines for grain yield across multiple environments. To evaluate how CIMMYT may utilize dynamic HTP data for genomic selection (GS),...

Registration Year

  • 2017
    2

Resource Types

  • Dataset
    2

Affiliations

  • International Rice Research Institute
    2
  • Kansas State University
    2
  • The University of Texas at Austin
    1
  • International Maize and Wheat Improvement Center
    1
  • Colorado State University
    1