Maximizing yield is very important when developing new cultivars. However, yield must usually be improved jointly with other key traits, which can prove challenging when they are unfavorably correlated. Genomic predictions can facilitate the selection of promising lines among the progeny of crosses, but it may also help in selecting crosses that are more likely to produce improved lines by predicting progeny performance for the various key traits considered jointly. To assess whether genomic predictions of cross performance could help breeders simultaneously improve multiple traits, yield and maturity were predicted for 60,000 soybean [Glycine max (L.) Merr.] crosses. These predictions were then compared with the persistence of 101 biparental crosses throughout the selection process measured as the success in advancing progeny lines through to registration and commercialization. All but 2 of the 22 superior crosses retained by breeders had been predicted to display above-average mean yield within different maturity windows. At the opposite end of the spectrum, 96.2% of all crosses predicted to produce progeny with a below-average mean yield within a specific maturity window were eliminated during selection. Our results therefore suggest that by making crosses predicted to produce progeny meeting target requirements for multiple key traits, breeders could either achieve the same genetic gains with fewer resources or invest the same resources on a more promising set of crosses and thereby achieve greater gains.

中文翻译：

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通过优良杂交的基因组预测改善大豆关键农艺性状

在开发新品种时，最大限度地提高产量非常重要。然而，产量通常必须与其他关键性状共同提高，当它们不利相关时，这可能具有挑战性。基因组预测可以促进在杂交后代中选择有希望的品系，但它也可以通过预测联合考虑的各种关键性状的后代性能，帮助选择更有可能产生改良品系的杂交。为了评估杂交性能的基因组预测是否可以帮助育种者同时改善多个性状，预测了 60,000 颗大豆的产量和成熟度 [ Glycine max(L.) Merr.] 交叉。然后将这些预测与整个选择过程中 101 个双亲杂交的持久性进行比较，以将后代系成功推进到注册和商业化。育种者保留的 22 个优良杂交种中，除 2 个外，所有品种均预计在不同的成熟期窗口内显示高于平均水平的产量。在光谱的另一端，在选择过程中，96.2% 的杂交被预测为在特定成熟窗口内产生低于平均产量的后代。因此，我们的结果表明，通过预测杂交产生满足多个关键性状目标要求的后代，