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Root phenotyping: from component trait in the lab to breeding.

René C P Kuijken1, Fred A van Eeuwijk2, Leo F M Marcelis3

  • 1Wageningen UR, Greenhouse Horticulture, Wageningen, 6708 PB, The Netherlands Wageningen UR, Laboratory of Plant Physiology, Wageningen, 6708 PB, The Netherlands.

Journal of Experimental Botany
|June 14, 2015
PubMed
Summary

Advancements in automated plant phenotyping platforms accelerate genetic gain in breeding. Optimizing these platforms requires understanding root trait heritability and environmental interactions for improved crop performance.

Keywords:
Genomic selectionheritabilityphenotypingrhizosphereroot exudationroot system architecture (RSA).

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Area of Science:

  • Plant Science
  • Genetics
  • Agricultural Science

Background:

  • Genomic data has surged due to cheaper sequencing, making high-throughput genotyping standard in plant breeding.
  • Phenotypic data collection is now a bottleneck, especially for complex root traits and inaccessible rhizosphere environments.
  • Automated phenotyping platforms are developing rapidly to address these limitations.

Purpose of the Study:

  • To review recent developments in root phenotyping technologies.
  • To analyze factors influencing root phenotype and heritability.
  • To propose strategies for optimizing phenotyping platforms to maximize genetic gain.

Main Methods:

  • Review of current literature on automated root phenotyping platforms.
  • Analysis of environmental and genetic factors affecting root traits.
  • Description of a quantitative framework for evaluating phenotyping platform efficiency.

Main Results:

  • The efficiency of phenotyping platforms in increasing genetic gain is often overlooked.
  • Heritability of phenotyped traits and their correlation with breeding targets are crucial for efficiency.
  • Environmental and genetic factors significantly influence root phenotype and heritability.

Conclusions:

  • Phenotyping platforms can be maximized by increasing trait heritability and managing genotype-environment interactions.
  • Quantifying the genetic relationship between platform-based traits and breeding targets is essential.
  • Future breeding strategies should focus on optimizing root system functioning through advanced phenotyping.