High-throughput phenotyping with deep learning gives insight into the genetic architecture of flowering time in wheat.

Journal: GigaScience
Published Date: Nov 1, 2019

Abstract

BACKGROUND: Measurement of plant traits with precision and speed on large populations has emerged as a critical bottleneck in connecting genotype to phenotype in genetics and breeding. This bottleneck limits advancements in understanding plant genomes and the development of improved, high-yielding crop varieties.

Authors

  • Xu Wang
    Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907.
  • Hong Xuan
    Department of Computer Science, George Washington University, 4000 Science and Engineering Hall, 800 22nd Street NW, Washington, DC 20052, USA.
  • Byron Evers
    Department of Plant Pathology, Kansas State University, 4024 Throckmorton PSC, 1712 Claflin Road, Manhattan, KS 66506, USA.
  • Sandesh Shrestha
    Department of Plant Pathology, Kansas State University, 4024 Throckmorton PSC, 1712 Claflin Road, Manhattan, KS 66506, USA.
  • Robert Pless
    Department of Computer Science, George Washington University, 4000 Science and Engineering Hall, 800 22nd Street NW, Washington, DC 20052, USA.
  • Jesse Poland
    Department of Plant Pathology, Kansas State University, 4024 Throckmorton PSC, 1712 Claflin Road, Manhattan, KS 66506, USA.

Keywords

External Resources

Popular Topics
Recent Journals