Accurate hybrid prediction and knowledge about the relative contribution of general (GCA) and specific combining ability (SCA) are of utmost importance for efficient hybrid breeding. We therefore evaluated 91 triticale single‐cross hybrids in field trials at seven environments for plant height, heading time, fresh biomass, dry matter content and dry biomass. Fresh and dry biomass showed the highest proportion (23%) of variance due to SCA. Prediction accuracies based on GCA were slightly higher than based on mid‐parent values. Utilizing parental kinship information yielded the highest prediction accuracies when both parental lines have been tested in other hybrid combinations, but still moderate‐to‐low prediction accuracies for two untested parents. Thus, hybrid prediction for biomass traits in triticale is currently promising based on mid‐parent values as emphasized by our simulation study, but can be expected to shift to GCA‐based prediction with an increasing importance of GCA due to selection in hybrid breeding. Moreover, the performance of potential hybrids between newly developed lines can be predicted with moderate accuracy using genomic relationship information.

中文翻译：

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冬季黑小麦生物量产量的杂交育种：II。结合能力与混合预测

准确的杂交预测以及有关一般（GCA）和特定结合能力（SCA）的相对贡献的知识对于有效的杂交育种至关重要。因此，我们在七个环境下的田间试验中评估了91个小黑麦单交杂种的株高，抽穗时间，新鲜生物量，干物质含量和干燥生物量。由于SCA，新鲜和干燥的生物量显示出最大的比例变化（23％）。基于GCA的预测准确性略高于基于中父母的预测准确性。当在两个杂种组合中对两个亲本系进行了测试时，利用父母亲属信息可获得最高的预测准确度，但对于两个未经测试的亲本仍然具有中等至较低的预测准确度。从而，正如我们的模拟研究所强调的那样，目前基于中亲本值的小黑麦生物量性状的杂种预测很有希望，但是由于在杂种育种中的选择，随着GCA重要性的提高，可以预期将其转变为基于GCA的预测。此外，可以使用基因组关系信息以中等准确度预测新开发品系之间潜在杂种的表现。