Joint modeling of additive and non-additive (genetic line) effects in multi-environment trials

被引：63

作者：

Oakey, Helena

Verbyla, Arunas P.

Cullis, Brian R.

Wei, Xianming

Pitchford, Wayne S.

机构：

[1] Univ Adelaide, Sch Agr Food & Wine, Glen Osmond, SA 5064, Australia

[2] NSW Dept Primary Ind, Wagga Wagga Agr Inst, PMB, Wagga Wagga, NSW 2650, Australia

[3] BSES Ltd, Mackay Cent Sugar Expt Stn, Mackay, Qld 4741, Australia

[4] Univ Adelaide, Sch Agr Food & Wine, Roseworthy, SA 5371, Australia

来源：

THEORETICAL AND APPLIED GENETICS | 2007年 / 114卷 / 08期

关键词：

D O I：

10.1007/s00122-007-0515-3

中图分类号：

S3 [农学（农艺学）];

学科分类号：

0901 ;

摘要：

A statistical approach for the analysis of multi-environment trials (METs) is presented, in which selection of best performing lines, best parents, and best combination of parents can be determined. The genetic effect of a line is partitioned into additive, dominance and residual non-additive effects. The dominance effects are estimated through the incorporation of the dominance relationship matrix, which is presented under varying levels of inbreeding. A computationally efficient way of fitting dominance effects is presented which partitions dominance effects into between family dominance and within family dominance line effects. The overall approach is applicable to inbred lines, hybrid lines and other general population structures where pedigree information is available.

引用

页码：1319 / 1332

页数：14

共 49 条

[1] NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION [J].

AKAIKE, H .

IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1974, AC19 (06) :716-723

[2]

Bernardo R, 1996, CROP SCI, V36, P50, DOI [10.2135/cropsci1996.0011183X003600010009x, 10.2135/cropsci1996.0011183X003600040007x, 10.2135/cropsci1996.0011183X003600040009x]

[3] PREDICTION OF MAIZE SINGLE-CROSS PERFORMANCE USING RFLPS AND INFORMATION FROM RELATED HYBRIDS [J].