ArticleScientific reports2021
Deterministic and stochastic modelling of impacts from genomic selection and phenomics on genetic gain for perennial ryegrass dry matter yield.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Genomic selection shows improved expected genetic gain over phenotypic selection of agronomic traits in allotetraploid white clover.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- The value of early root development traits in breeding programs for biomass yield in perennial ryegrass (Lolium perenne L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Machine learning solutions for integrating partially overlapping genetic datasets and modelling host-endophyte effects in ryegrass (Frontiers in plant science · 2025Article
- Estimation of ryegrass (Frontiers in plant science · 2025Article
- Quantitative genetic analysis reveals potential to breed for improved white clover growth in symbiosis with nitrogen-fixingFrontiers in plant science · 2022Article
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Authors and funding
17 authors.
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Abstract
Increasing the efficiency of current forage breeding programs through adoption of new technologies, such as genomic selection (GS) and phenomics (Ph), is challenging without proof of concept demonstrating cost effective genetic gain (∆G). This paper uses decision support software DeltaGen (tactical tool) and QU-GENE (strategic tool), to model and assess relative efficiency of five breeding methods. The effect on ∆G and cost ($) of integrating GS and Ph into an among half-sib (HS) family phenotypic selection breeding strategy was investigated. Deterministic and stochastic modelling were conducted using mock data sets of 200 and 1000 perennial ryegrass HS families using year-by-season-by-location dry matter (DM) yield data and in silico generated data, respectively. Results demonstrated short (deterministic)- and long-term (stochastic) impacts of breeding strategy and integration of key technologies, GS and Ph, on ∆G. These technologies offer substantial improvements in the rate of ∆G, and in some cases improved cost-efficiency. Applying 1% within HS family GS, predicted a 6.35 and 8.10% ∆G per cycle for DM yield from the 200 HS and 1000 HS, respectively. The application of GS in both among and within HS selection provided a significant boost to total annual ∆G, even at low GS accuracy r
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