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Combining Ability Estimation for Grain Yield of Maize Exotic Germplasm Using Testers from Three Heterotic Groups

文献类型： 外文期刊

作者： Fan, Xing-Ming 1 ; Yin, Xing-Fu 1 ; Zhang, Yu-Dong 1 ; Bi, Ya-Qi 1 ; Liu, Li 1 ; Chen, Hong-Mei 1 ; Kang, Manjit S. 2 ;

作者机构： 1.Yunnan Acad Agr Sci, Inst Food Crops, 2238 Beijing Rd, Kunming 650200, Yunnan Province, Peoples R China

2.Kansas State Univ, Dept Plant Pathol, Throckmorton Hall, Manhattan, KS 66506 USA

期刊名称：CROP SCIENCE （ 影响因子：2.319； 五年影响因子：2.631 ）

ISSN： 0011-183X

年卷期： 2016 年 56 卷 5 期

页码：

收录情况： SCI

摘要： Combining ability estimates of lines to be used in breeding are useful for maize (Zea mays L.) breeders. The objectives of this study were to (i) evaluate combining ability of 25 improved exotic germplasm using different numbers of testers (1 to 3) from Suwan1, Reid, and non-Reid heterotic groups; (ii) study differences in combining ability estimates obtained with different number of testers from the same vs. different heterotic groups; and (iii) determine the appropriate segregating ('S') generation in which line selection should be done to obtain stable general combining ability (GCA) estimates of lines. The results showed that three testers (one from each of the three heterotic groups) were economically best for estimating GCA effects of lines, and if a tester from one of the three heterotic groups was missed, GCA estimates for some lines were biased when compared with GCA estimates with testers from all three heterotic groups. Second, the specific combining ability (SCA) effects of test-crosses were quite similar regardless of whether one or two testers were used from each of the three heterotic groups. Thus, to obtain reliable SCA estimates, at least one tester would need to be used from each of the heterotic groups. Third, the SCA effects were different among crosses between different lines and testers, and to obtain stable estimates of GCA effects for a line, S4 or S5 generation should be the earliest generation in which to begin selection. However, to select lines with diverse genetic backgrounds, S3 should be the key generation for selection.

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