Automated phenotyping for early vigour of field pea seedlings in controlled environment by colour imaging technology

PLoS One. 2018 Nov 19;13(11):e0207788. doi: 10.1371/journal.pone.0207788. eCollection 2018.

Abstract

Early vigour of seedlings is a beneficial trait of field pea (Pisum sativum L.) that contributes to weed control, water use efficiency and is likely to contribute to yield under certain environments. Although breeding is considered the most effective approach to improve early vigour of field pea, the absence of a robust and high-throughput phenotyping tool to dissect this complex trait is currently a major obstacle of genetic improvement programs to address this issue. To develop this tool, separate trials on 44 genetically diverse field pea genotypes were conducted in the automated plant phenotyping platform of Plant Phenomics Victoria, Horsham and in the field, respectively. High correlation between estimated plant parameters derived from the automated phenotyping platform and important early vigour traits such as shoot biomass, leaf area and plant height indicated that the derived plant parameters can be used to predict vigour traits in field pea seedlings. Plant growth analysis demonstrated that the "broken-stick" model fitted well with the growth pattern of all field pea genotypes and can be used to determine the linear growth phase. Further analysis suggested that the estimated plant parameters collected at the linear growth phase can effectively differentiate early vigour across field pea genotypes. High correlation between normalised difference vegetation indices captured from the field trial and estimated shoot biomass and top-view area confirmed the consistent performance of early vigour field pea genotypes under controlled and field environments. Overall, our results demonstrated that this robust screening tool is highly applicable and will enable breeding programs to rapidly identify early vigour traits and utilise germplasm to contribute to the genetic improvement of field peas.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Automation
  • Environment, Controlled*
  • Genotype
  • Image Processing, Computer-Assisted*
  • Phenotype*
  • Pisum sativum / genetics
  • Pisum sativum / growth & development*
  • Seedlings / genetics
  • Seedlings / growth & development*

Grants and funding

This research was funded by the Grain Research and Development Corporation (https://grdc.com.au). Grant number GRDC 9176106 to S.L.N. S.L.N. conceived, designed and supervised the experiments; analysed the data and edited the paper.