The two most important activities in maize breeding are the development of inbred lines with high values of general combining ability (GCA) and specific combining ability (SCA), and the identification of hybrids with high yield potentials. Genomic selection (GS) is a promising genomic tool to perform selection on the untested breeding material based on the genomic estimated breeding values estimated from the genomic prediction (GP). In this study, GP analyses were carried out to estimate the performance of hybrids, GCA, and SCA for grain yield (GY) in three maize line-by-tester trials, where all the material was phenotyped in 10 to 11 multiple-location trials and genotyped with a mid-density molecular marker platform. Results showed that the prediction abilities for the performance of hybrids ranged from 0.59 to 0.81 across all trials in the model including the additive effect of lines and testers. In the model including both additive and non-additive effects, the prediction abilities for the performance of hybrids were improved and ranged from 0.64 to 0.86 across all trials. The prediction abilities of the GCA for GY were low, ranging between ? 0.14 and 0.13 across all trials in the model including only inbred lines;the pre-diction abilities of the GCA for GY were improved and ranged from 0.49 to 0.55 across all trials in the model including both inbred lines and testers, while the prediction abilities of the SCA for GY were neg-ative across all trials. The prediction abilities for GY between testers varied from ? 0.66 to 0.82;the per-formance of hybrids between testers is difficult to predict. GS offers the opportunity to predict the performance of new hybrids and the GCA of new inbred lines based on the molecular marker information, the total breeding cost could be reduced dramatically by phenotyping fewer multiple-location trials.

Ao Zhang;Paulino Pérez-Rodríguez;Felix San Vicente;Natalia Palacios-Rojas;Thanda Dhliwayo;Yubo Liu;Zhenhai Cui;Yuan Guan;Hui Wang;Hongjian Zheng;Michael Olsen;Boddupalli M.Prasanna;Yanye Ruan;Jose Crossa;Xuecai Zhang

College of Biological Science and Technology,Shenyang Agricultural University,Shenyang 110866,Liaoning,China;International Maize and Wheat Improvement Center(CIMMYT),El Batan,Texcoco 56237,Mexico;CIMMYT-China Specialty Maize Research Center,Shanghai Academy of Agricultural Sciences,Shanghai 200063,China;Colegio de Postgraduados,Estado De México,Mexico;Crop Breeding and Cultivation Research Institute,Shanghai Academy of Agricultural Sciences,Shanghai 200063,China;International Maize and Wheat Improvement Center(CIMMYT),P.O.Box 1041,Village Market,Nairobi 00621,Kenya

作物学报（英文版）

[1]Ao Zhang;Paulino Pérez-Rodríguez;Felix San Vicente;Natalia Palacios-Rojas;Thanda Dhliwayo;Yubo Liu;Zhenhai Cui;Yuan Guan;Hui Wang;Hongjian Zheng;Michael Olsen;Boddupalli M.Prasanna;Yanye Ruan;Jose Crossa;Xuecai Zhang-.Genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize)[J].作物学报（英文版）,2022(01):109-116

phenotyped,testers

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