Article CC BY 4.0
refereed
published

Phenomic Selection for Hybrid Rapeseed Breeding

ORCID
0009-0006-7540-4888
Affiliation
Department of Plant Breeding, Justus Liebig University, Giessen, Germany
Roscher-Ehrig, Lennard;
Affiliation
Department of Plant Breeding, Justus Liebig University, Giessen, Germany
Weber, Sven E.;
GND
123198879
Affiliation
NPZ Innovation GmbH, Holtsee, Germany
Abbadi, Amine;
Affiliation
NPZ Innovation GmbH, Holtsee, Germany
Malenica, Milka;
Affiliation
Limagrain GmbH, Peine-Rosenthal, Germany
Abel, Stefan;
Affiliation
Limagrain GmbH, Peine-Rosenthal, Germany
Hemker, Reinhard;
GND
118147064
Affiliation
Department of Plant Breeding, Justus Liebig University, Giessen, Germany
Snowdon, Rod J.;
GND
1032147660
Affiliation
Department of Plant Breeding, Justus Liebig University, Giessen, Germany
Wittkop, Benjamin;
GND
1222562243
Affiliation
Julius Kühn Institute (JKI), Institute for Resistance Research and Stress Tolerance, Germany
Stahl, Andreas

Phenomic selection is a recent approach suggested as a low-cost, high-throughput alternative to genomic selection. Instead of using genetic markers, it employs spectral data to predict complex traits using equivalent statistical models. Phenomic selection has been shown to outperform genomic selection when using spectral data that was obtained within the same generation as the traits that were predicted. However, for hybrid breeding, the key question is whether spectral data from parental genotypes can be used to effectively predict traits in the hybrid generation. Here, we aimed to evaluate the potential of phenomic selection for hybrid rapeseed breeding. We performed predictions for various traits in a structured population of 410 test hybrids, grown in multiple environments, using near-infrared spectroscopy data obtained from harvested seeds of both the hybrids and their parental lines with different linear and nonlinear models. We found that phenomic selection within the hybrid generation outperformed genomic selection for seed yield and plant height, even when spectral data was collected at single locations, while being less affected by population structure. Furthermore, we demonstrate that phenomic prediction across generations is feasible, and selecting hybrids based on spectral data obtained from parental genotypes is competitive with genomic selection. We conclude that phenomic selection is a promising approach for rapeseed breeding that can be easily implemented without any additional costs or efforts as near-infrared spectroscopy is routinely assessed in rapeseed breeding.

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License Holder: 2024 Lennard Roscher-Ehrig et al.

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