ArticleFrontiers in genetics2023
Enhancing genetic gain through the application of genomic selection in developing irrigated rice for the favorable ecosystem in Bangladesh.
Article in Frontiers in genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Integrating molecular genetics with plant breeding to deliver impact.Plant physiology · 2025Review
- 110 years of rice breeding at LSU: realized genetic gains and future optimization.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Environment ensemble models for genomic prediction in common bean (Phaseolus vulgaris L.).The plant genome · 2025Article
- Article
- Genetic Gain and Inbreeding in Different Simulated Genomic Selection Schemes for Grain Yield and Oil Content in Safflower.Plants (Basel, Switzerland) · 2024Article
- Genetic progress in cowpea [Vigna unguiculata (L.) Walp.] stemming from breeding modernization efforts at the International Institute of Tropical Agriculture.The plant genome · 2024Article
- Validation of sorghum quality control (QC) markers across African breeding lines.The plant genome · 2024Article
- Stochastic simulation to optimize rice breeding at IRRI.Frontiers in plant science · 2024Article
- Realized Genetic Gain in Rice: Achievements from Breeding Programs.Rice (New York, N.Y.) · 2023Review
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11 authors.
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Abstract
Increasing selection differential and decreasing cycle time, the rate of genetic improvement can be accelerated. Creating and capturing higher genetic with higher accuracy within the shortest possible time is the prerequisite for enhancing genetic gain for any trait. Comprehensive yield testing at multi-locations at early generations together with the shortest line fixation time can expedite the rapid recycling of parents in the breeding program through recurrent selection. Genomic selection is efficient in capturing high breeding value individuals taking additive genetic effects of all genes into account with and without extensive field testing, thus reducing breeding cycle time enhances genetic gain. In the Bangladesh Rice Research Institute, GS technology together with the trait-specific marker-assisted selection at the early generation of RGA-derived breeding lines showed a prediction accuracy of 0.454-0.701 with 0.989-2.623 relative efficiency over the four consecutive years of exercise. This study reports that the application of GS together with trait-specific MAS has expedited the yield improvement by 117 kg ha
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