In common bean breeding programs, experiments are conducted in different environments to select plants with high potential for inbred lines extraction and/or recombination. The occurrence of genetic and/or statistical unbalance is common in these experiments. Moreover, there may be (co)variance between genetic and non-genetic effects when treatments are assessed in different environments. Our aim was to (1) test different (co)variance structures between seasons for genetic and non-genetic effects; (2) choose the model with the highest predictive capacity of the genotypic value; and (3) select the superior progenies to mitigate the effects of genotype-by-environment interactions. To this end, two experiments were conducted in the 2015 drought and winter seasons. The grain yield and grain aspect were assessed. Model 4, with an unstructured (co)variance for genetic effects, homogeneous block variance, and heterogeneous residual diagonal variance, was the model that best fit the data. The heritability estimates and their accuracy differed between the different adjusted models, with the most accurate estimates observed in model 4. The genetic correlation between the drought and winter seasons was of low magnitude (− 0.04) for grain yield, which corroborates the strong genotype by environment interaction. The average gain predicted with the recombination of the selected progenies in model 4 was 2.97% for grain yield. The modeling of different (co)variance structures for genetic and non-genetic effects could be applicable for analyses involving statistical unbalance and the assessment of progenies in different environments, with the aim of selecting those with high potential for recombination.

中文翻译：

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对常见豆子后代选择中遗传和非遗传效应的（共）方差结构建模

在常见的豆类育种计划中，在不同环境中进行实验以选择具有高潜力进行自交系提取和/或重组的植物。遗传和/或统计不平衡的发生在这些实验中很常见。此外，当在不同环境中评估治疗时，遗传和非遗传效应之间可能存在（共）变异。我们的目标是（1）测试不同季节之间的遗传和非遗传效应的（协）方差结构；(2)选择基因型值预测能力最高的模型；(3) 选择优良后代以减轻基因型与环境相互作用的影响。为此，在2015年旱季和冬季进行了两次试验。评估了谷物产量和谷物方面。型号 4, 具有遗传效应的非结构化（协）方差、同质块方差和异质残差对角线方差，是最适合数据的模型。不同调整模型之间的遗传力估计及其准确性不同，模型 4 中观察到的估计最准确。干旱和冬季之间的遗传相关性在粮食产量方面较低（- 0.04），这证实了强基因型环境互动。模型 4 中所选后代的重组预测的平均增益为 2.97% 的谷物产量。遗传和非遗传效应的不同（共）方差结构的建模可适用于涉及统计不平衡的分析和不同环境中后代的评估，