ArticleG3 (Bethesda, Md.)2019
Optimizing Genomic Selection for a Sorghum Breeding Program in Haiti: A Simulation Study.
Article in G3 (Bethesda, Md.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed.
- Bridging tradition and innovation: a review of computer simulations in plant breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- Optimizing progeny size and number of crosses under genomic selection: insights into additive and epistatic contributions to long-term genetic gain.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Performance of multi-trait and single-trait genomic selection for grain Fe and Zn concentrations in sorghum under different breeding constraints.Scientific reports · 2025Article
- 110 years of rice breeding at LSU: realized genetic gains and future optimization.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Advancing Climate-Resilient Sorghum: the Synergistic Role of Plant Biotechnology and Microbial Interactions.Rice (New York, N.Y.) · 2025Review
- Optimal implementation of genomic selection in clone breeding programs exemplified in potato: II. Effect of selection strategy and cross-selection method on long-term genetic gain.The plant genome · 2025Article
- Optimizing training sets to identify superior genotypes in hybrid populations.Frontiers in plant science · 2025Article
- Optimizing the selection of quantitative traits in plant breeding using simulation.Frontiers in plant science · 2025Review
- Genomic resources, opportunities, and prospects for accelerated improvement of millets.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Review
- Use of simulation to optimize a sweet corn breeding program: implementing genomic selection and doubled haploid technology.G3 (Bethesda, Md.) · 2024Article
- Genetic Gain and Inbreeding in Different Simulated Genomic Selection Schemes for Grain Yield and Oil Content in Safflower.Plants (Basel, Switzerland) · 2024Article
- Simulations of multiple breeding strategy scenarios in common bean for assessing genomic selection accuracy and model updating.The plant genome · 2024Article
- Realized Genetic Gain in Rice: Achievements from Breeding Programs.Rice (New York, N.Y.) · 2023Review
- Improving hybrid rice breeding programs via stochastic simulations: number of parents, number of hybrids, tester update, and genomic prediction of hybrid performance.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Genomics and phenomics enabled prebreeding improved early-season chilling tolerance in Sorghum.G3 (Bethesda, Md.) · 2023Article
- Optimal implementation of genomic selection in clone breeding programs-Exemplified in potato: I. Effect of selection strategy, implementation stage, and selection intensity on short-term genetic gain.The plant genome · 2023Article
- Characterization of grain carotenoids in global sorghum germplasm to guide genomics-assisted breeding strategies.BMC plant biology · 2023Article
- Genomic selection strategies to increase genetic gain in tea breeding programs.The plant genome · 2023Article
- Enviromic-based kernels may optimize resource allocation with multi-trait multi-environment genomic prediction for tropical Maize.BMC plant biology · 2023Article
- Simulation of sugar kelp (Saccharina latissima) breeding guided by practices to accelerate genetic gains.G3 (Bethesda, Md.) · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
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Abstract
Young breeding programs in developing countries, like the Chibas sorghum breeding program in Haiti, face the challenge of increasing genetic gain with limited resources. Implementing genomic selection (GS) could increase genetic gain, but optimization of GS is needed to account for these programs' unique challenges and advantages. Here, we used simulations to identify conditions under which genomic-assisted recurrent selection (GARS) would be more effective than phenotypic recurrent selection (PRS) in small new breeding programs. We compared genetic gain, cost per unit gain, genetic variance, and prediction accuracy of GARS (two or three cycles per year)
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