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Multiple-trait breeding values for parental selection in self-pollinating crops

机译:自花授粉作物父母选择的多性状育种价值

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摘要

Using breeding values in parental selection of self-pollinating crops seems to be superior to conventional selection strategies, where selection is often based on several traits which are correlated among each other. However, analysing each trait separately can bias estimates of breeding values. This study examined responses to selection for total merit indices based on breeding values resulting from single- and multiple-trait best linear unbiased prediction (BLUP). We generated data for a multi-environment trial of a “virtual” parental population in which the phenotypic value of inbred lines was influenced by additive, additive-by-additive epistatic, year, location, block and genotype-by-environment interaction effects. Two traits with heritabilities of 0.7 and 0.3 and nine different correlation scenarios between traits (estimated phenotypic correlation ranging from −0.39 to +0.36) were simulated. Gain in selection response was greater for multiple-trait than for single-trait breeding values, especially if traits were negatively correlated. For all correlation scenarios, the overall standard errors of difference of multiple-trait predictors were lower than those of single-trait analysis.
机译:在自花授粉作物的亲本选择中使用育种值似乎优于常规选择策略,在传统选择策略中,选择通常基于相互关联的几个性状。但是,单独分析每个性状可能会使育种值的估计产生偏差。这项研究基于单性和多性最佳线性无偏预测(BLUP)产生的育种值,检验了对总绩效指标选择的反应。我们为“虚拟”父母群体的多环境试验生成了数据,其中近交系的表型价值受累加,累加上位的上位性,年份,位置,基因型和环境相互作用的影响。遗传性状分别为0.7和0.3的两个性状,以及性状之间的九个不同相关情景(估计表型相关性介于-0.39至+0.36之间)。多性状的选择响应收益大于单性状的育种值,特别是如果性状呈负相关。对于所有相关情景,多特征预测变量差异的总体标准误均低于单特征分析。

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