Modelling strategies for assessing and increasing the effectiveness of new phenotyping techniques in plant breeding

Fred A. van Eeuwijk*, Daniela Bustos-Korts, Emilie J. Millet, Martin P. Boer, Willem Kruijer, Addie Thompson, Marcos Malosetti, Hiroyoshi Iwata, Roberto Quiroz, Christian Kuppe, Onno Muller, Konstantinos N. Blazakis, Kang Yu, Francois Tardieu, Scott C. Chapman

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

16 Citations (Scopus)

Abstract

New types of phenotyping tools generate large amounts of data on many aspects of plant physiology and morphology with high spatial and temporal resolution. These new phenotyping data are potentially useful to improve understanding and prediction of complex traits, like yield, that are characterized by strong environmental context dependencies, i.e., genotype by environment interactions. For an evaluation of the utility of new phenotyping information, we will look at how this information can be incorporated in different classes of genotype-to-phenotype (G2P) models. G2P models predict phenotypic traits as functions of genotypic and environmental inputs. In the last decade, access to high-density single nucleotide polymorphism markers (SNPs) and sequence information has boosted the development of a class of G2P models called genomic prediction models that predict phenotypes from genome wide marker profiles. The challenge now is to build G2P models that incorporate simultaneously extensive genomic information alongside with new phenotypic information. Beyond the modification of existing G2P models, new G2P paradigms are required. We present candidate G2P models for the integration of genomic and new phenotyping information and illustrate their use in examples. Special attention will be given to the modelling of genotype by environment interactions. The G2P models provide a framework for model based phenotyping and the evaluation of the utility of phenotyping information in the context of breeding programs.

Original languageEnglish
Pages (from-to)23-39
JournalPlant Science
Volume282
Early online date30 Jun 2018
DOIs
Publication statusPublished - May 2019

Fingerprint

plant breeding
Genotype
phenotype
Single Nucleotide Polymorphism
Plant Physiological Phenomena
Phenotype
Breeding
methodology
Genome
genomics
genotype
Plant Breeding
plant morphology
prediction
plant physiology
single nucleotide polymorphism
genome
breeding

Keywords

  • Crop growth model
  • Genomic prediction
  • Genotype-by-environment-interaction
  • Genotype-to-phenotype model
  • Mixed model
  • Multi-environment model
  • Multi-trait model
  • Phenotyping
  • Phenotyping platform
  • Physiology
  • Plant breeding
  • Prediction
  • Reaction norm
  • Response surface
  • Statistical genetics

Cite this

van Eeuwijk, Fred A. ; Bustos-Korts, Daniela ; Millet, Emilie J. ; Boer, Martin P. ; Kruijer, Willem ; Thompson, Addie ; Malosetti, Marcos ; Iwata, Hiroyoshi ; Quiroz, Roberto ; Kuppe, Christian ; Muller, Onno ; Blazakis, Konstantinos N. ; Yu, Kang ; Tardieu, Francois ; Chapman, Scott C. / Modelling strategies for assessing and increasing the effectiveness of new phenotyping techniques in plant breeding. In: Plant Science. 2019 ; Vol. 282. pp. 23-39.
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abstract = "New types of phenotyping tools generate large amounts of data on many aspects of plant physiology and morphology with high spatial and temporal resolution. These new phenotyping data are potentially useful to improve understanding and prediction of complex traits, like yield, that are characterized by strong environmental context dependencies, i.e., genotype by environment interactions. For an evaluation of the utility of new phenotyping information, we will look at how this information can be incorporated in different classes of genotype-to-phenotype (G2P) models. G2P models predict phenotypic traits as functions of genotypic and environmental inputs. In the last decade, access to high-density single nucleotide polymorphism markers (SNPs) and sequence information has boosted the development of a class of G2P models called genomic prediction models that predict phenotypes from genome wide marker profiles. The challenge now is to build G2P models that incorporate simultaneously extensive genomic information alongside with new phenotypic information. Beyond the modification of existing G2P models, new G2P paradigms are required. We present candidate G2P models for the integration of genomic and new phenotyping information and illustrate their use in examples. Special attention will be given to the modelling of genotype by environment interactions. The G2P models provide a framework for model based phenotyping and the evaluation of the utility of phenotyping information in the context of breeding programs.",
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author = "{van Eeuwijk}, {Fred A.} and Daniela Bustos-Korts and Millet, {Emilie J.} and Boer, {Martin P.} and Willem Kruijer and Addie Thompson and Marcos Malosetti and Hiroyoshi Iwata and Roberto Quiroz and Christian Kuppe and Onno Muller and Blazakis, {Konstantinos N.} and Kang Yu and Francois Tardieu and Chapman, {Scott C.}",
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Modelling strategies for assessing and increasing the effectiveness of new phenotyping techniques in plant breeding. / van Eeuwijk, Fred A.; Bustos-Korts, Daniela; Millet, Emilie J.; Boer, Martin P.; Kruijer, Willem; Thompson, Addie; Malosetti, Marcos; Iwata, Hiroyoshi; Quiroz, Roberto; Kuppe, Christian; Muller, Onno; Blazakis, Konstantinos N.; Yu, Kang; Tardieu, Francois; Chapman, Scott C.

In: Plant Science, Vol. 282, 05.2019, p. 23-39.

Research output: Contribution to journalArticleAcademicpeer-review

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AU - van Eeuwijk, Fred A.

AU - Bustos-Korts, Daniela

AU - Millet, Emilie J.

AU - Boer, Martin P.

AU - Kruijer, Willem

AU - Thompson, Addie

AU - Malosetti, Marcos

AU - Iwata, Hiroyoshi

AU - Quiroz, Roberto

AU - Kuppe, Christian

AU - Muller, Onno

AU - Blazakis, Konstantinos N.

AU - Yu, Kang

AU - Tardieu, Francois

AU - Chapman, Scott C.

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KW - Phenotyping platform

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KW - Plant breeding

KW - Prediction

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