ArticlePloS one2018
Genetic insights into elephantgrass persistence for bioenergy purpose.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Modeling temporal genetic variability using mixed models improves yield stability and selection efficiency inFrontiers in plant science · 2026Article
- Assessing genotype adaptability and stability in perennial forage breeding trials using random regression models for longitudinal dry matter yield data.G3 (Bethesda, Md.) · 2025Article
- Integrating environmental gradients into breeding: application of genomic reactions norms in a perennial species.Heredity · 2024Article
- Leveraging spatiotemporal genomic breeding value estimates of dry matter yield and herbage quality in ryegrass via random regression models.The plant genome · 2022Article
- Multiple-trait, random regression, and compound symmetry models for analyzing multi-environment trials in maize breeding.PloS one · 2020Article
- Article
- Random regression for modeling yield genetic trajectories in Jatropha curcas breeding.PloS one · 2020Article
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Authors and funding
6 authors.
Funding
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Abstract
Persistence may be defined as high sustained yield over multi-harvest. Genetic insights about persistence are essential to ensure the success of breeding programs and any biomass-based project. This paper focuses on assessing the biomass yield persistence for bioenergy purpose of 100 elephantgrass clones measured in six growth seasons in Brazil. To assess the clones' persistence, an index based on random regression models and genotype-ideotype distance was proposed. Results suggested the existence of wide genetic variability between elephantgrass clones, and that the yield trajectories along the harvests generate genetic insights into elephantgrass clones' persistence and G x E interaction. A gene pool that acts over the biomass yield (regardless of the harvest) was detected, as well as other gene pools, which show differences on genes expression (these genes are the major responsible for clones' persistence). The lower and higher clones' persistence was discussed based on genome dosage effect and natural biological nitrogen fixation ability applied to bioenergy industry. The huge potential of energy crops necessarily is associated with genetic insights into persistence, so just this way, breeding programs could breed a new cultivar that fulfills the bioenergy industries.
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