Abstract：
For many plant and animal species, commercial products are hybrids between individuals from different genetic groups. For allogamous plant species such as maize, the breeding objective is to produce single-cross hybrid varieties from two inbred lines each selected in complementary groups. Efficient hybrid breeding requires methods that (1) quickly generate homozygous and homogeneous parental lines with high combining abilities, (2) efficiently choose among the large number of available parental lines the most promising ones, and (3) predict the performances of sets of non-phenotyped single-cross hybrids, or hybrids phenotyped in a limited number of environments, based on their relationship with another set of hybrids with known performances. The maize breeding community has been developing model-based prediction of hybrid performances well before the genomic era. This chapter (1) provides a reminder of the maize breeding scheme before the genomic era; (2) describes how genomic data were incorporated in the prediction models involved in different steps of genomic-based single-cross maize hybrid breeding; and (3) reviews factors affecting the accuracy of genomic prediction, approaches for optimizing GP-based single-cross maize hybrid breeding schemes, and ensuring the long-term sustainability of genomic selection.
摘要：
对于许多植物和动物物种来说，商业产品是来自不同遗传群体的个体之间的混合体。对于同类植物物种，如玉米，育种目标是从两个自交系中产生单杂交杂交品种，每个自交系在互补组中选择。高效的杂种育种需要（1）快速产生具有高结合能力的纯合和均质亲本系的方法，（2）有效地在大量可用的父系中选择最有前途的父系，(3)预测非表型单交杂种的表现，或在有限数量的环境中表型的杂种，基于它们与另一组具有已知性能的杂种的关系。早在基因组时代之前，玉米育种社区就一直在开发基于模型的杂种性能预测。本章（1）提醒了基因组时代之前的玉米育种方案；（2）描述了如何将基因组数据纳入基于基因组的单杂交玉米杂交育种的不同步骤所涉及的预测模型中；（3）回顾了影响基因组预测准确性的因素，基于GP的单交玉米杂交育种方案的优化方法，并确保基因组选择的长期可持续性。
