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Phenomic Selection: A New and Efficient Alternative to Genomic Selection.

Pauline Robert1,2, Charlotte Brault3,4,5, Renaud Rincent1,2

  • 1INRAE-Université Clermont-Auvergne, UMR1095, GDEC, Clermont-Ferrand, France.

Methods in Molecular Biology (Clifton, N.J.)
|April 22, 2022
PubMed
Summary
This summary is machine-generated.

Phenomic selection (PS) uses near-infrared (NIR) spectra instead of molecular markers for predicting traits. This cost-effective approach shows promise for advancing plant breeding selection strategies.

Keywords:
Genomic selection (GS)Genomic-like omics-based (GLOB) selectionHyperspectral imagingNear-infrared spectroscopy (NIRS )Phenomic selection (PS)Plant breeding

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Area of Science:

  • Plant breeding
  • Genetics
  • Spectroscopy

Background:

  • Genomic selection (GS) traditionally uses molecular markers to infer relationships and predict breeding values.
  • Phenomic selection (PS) offers a cost-effective alternative by utilizing spectral data, such as near-infrared (NIR) spectra, analogous to GS.
  • While NIR spectroscopy (NIRS) is established for quality traits, its application in predicting diverse traits for selection is novel.

Purpose of the Study:

  • To review the concept and evolution of phenomic selection (PS) in plant breeding.
  • To classify and analyze existing literature on PS, focusing on technologies, data preprocessing, and statistical modeling.
  • To discuss factors influencing PS efficiency and compare its predictive ability with genomic selection (GS).

Main Methods:

  • Review and classification of selected publications on phenomics in plant breeding.
  • Analysis of technologies used (NIRS, hyperspectral imaging), spectral preprocessing techniques, and statistical prediction models.
  • Comparative analysis of predictive abilities between PS and GS.

Main Results:

  • PS utilizes low-cost phenomic information, primarily NIR spectra, for predicting traits.
  • Various spectral acquisition technologies and statistical models are employed in PS.
  • Factors affecting PS efficiency are identified, with comparisons to GS predictive ability.

Conclusions:

  • Phenomic selection (PS) presents a promising, cost-effective strategy for plant breeding, complementing or potentially replacing traditional genomic selection (GS).
  • Further research and application of PS are encouraged to optimize its use in breeding programs.
  • NIRS and hyperspectral imaging are key technologies enabling PS for a broader range of traits.