ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2023
Models to estimate genetic gain of soybean seed yield from annual multi-environment field trials.
Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Photosynthesis-informed breeding to enhance Soybean (Glycine max) yield potential: a framework integrating high-throughput phenomics, genomic prediction and G×E×M.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- Efficiency under epistasis of haplotype-based genomic selection for pure line breeding.Heredity · 2026Article
- Global Genetic Gain and Changes for Seed Yield, Agronomic, and Compositional Attributes in Soybean (Plants (Basel, Switzerland) · 2026Review
- Breeding Climate-Resilient Soybeans for 2050 and Beyond: Leveraging Novel Technologies to Mitigate Yield Stagnation and Climate Change Impacts.Plants (Basel, Switzerland) · 2026Review
- Transformer model to determine spatio-temporal relationships of variables, and interpretability for soybean seed yield, oil, and protein prediction.Frontiers in artificial intelligence · 2026Article
- 110 years of rice breeding at LSU: realized genetic gains and future optimization.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Phenotypic plasticity of flowering time and plant height related traits in wheat.BMC plant biology · 2025Article
- Genomic and phenomic prediction for soybean seed yield, protein, and oil.The plant genome · 2025Article
- Robust soybean seed yield estimation using high-throughput ground robot videos.Frontiers in plant science · 2025Article
- A framework for simulating genotype-by-environment interaction using multiplicative models.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Q&A: Methods for estimating genetic gain in sub-Saharan Africa and achieving improved gains.The plant genome · 2024Article
- ProbBreed: a novel tool for calculating the risk of cultivar recommendation in multienvironment trials.G3 (Bethesda, Md.) · 2024Article
- Understanding the Molecular Regulatory Networks of Seed Size in Soybean.International journal of molecular sciences · 2024Review
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5 authors.
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Abstract
key messageSimulations demonstrated that estimates of realized genetic gain from linear mixed models using regional trials are biased to some degree. Thus, we recommend multiple selected models to obtain a range of reasonable estimates. Genetic improvements of discrete characteristics are obvious and easy to demonstrate, while quantitative traits require reliable and accurate methods to disentangle the confounding genetic and non-genetic components. Stochastic simulations of soybean [Glycine max (L.) Merr.] breeding programs were performed to evaluate linear mixed models to estimate the realized genetic gain (RGG) from annual multi-environment trials (MET). True breeding values were simulated under an infinitesimal model to represent the genetic contributions to soybean seed yield under various MET conditions. Estimators were evaluated using objective criteria of bias and linearity. Covariance modeling and direct versus indirect estimation-based models resulted in a substantial range of estimated values, all of which were biased to some degree. Although no models produced unbiased estimates, the three best-performing models resulted in an average bias of [Formula: see text] kg/ha[Formula: see text]/yr[Formula: see text] ([Formula: see text] bu/ac[Formula: see text]/yr[Formula: see text]). Rather than relying on a single model to estimate RGG, we recommend the application of several models with minimal and directional bias. Further, based on the parameters used in the simulations, we do not think it is appropriate to use any single model to compare breeding programs or quantify the efficiency of proposed new breeding strategies. Lastly, for public soybean programs breeding for maturity groups II and III in North America, the estimated RGG values ranged from 18.16 to 39.68 kg/ha[Formula: see text]/yr[Formula: see text] (0.27-0.59 bu/ac[Formula: see text]/yr[Formula: see text]) from 1989 to 2019. These results provide strong evidence that public breeders have significantly improved soybean germplasm for seed yield in the primary production areas of North America.
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