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Multi-trait multi-environment diallel analyses for maize breeding
Euphytica ( IF 1.6 ) Pub Date : 2020-08-24 , DOI: 10.1007/s10681-020-02677-9
Igor Ferreira Coelho , Rodrigo Silva Alves , João Romero do Amaral Santos de Car Rocha , Marco Antônio Peixoto , Larissa Pereira Ribeiro Teodoro , Paulo Eduardo Teodoro , Jefferson Fernando Naves Pinto , Edésio Fialho dos Reis , Leonardo Lopes Bhering

Genetic study in maize (Zea mays) germplasm development is an important step to understand the genetic variability and complementarity between heterotic groups, as well as additive and dominance genetic effects. Thus, diallel analyses have been widely adopted with the aim of identifying the best parental lines and the best crosses. In addition, different environmental conditions make genetic selection difficult. Thus, the objectives of this study were to compare individual and joint analyses of a diallel design through a mixed model methodology for maize breeding, and to evaluate and interpret the genetic effects and their interaction with the environmental effect. Thirteen F2 hybrids were crossed in an incomplete diallel scheme. Seventy-eight inter-population hybrids, and thirteen self-pollinated parents were evaluated. Eleven traits were evaluated, and emphasis was given to the Grain Yield (GY) trait. The significance of the GY trait, specifically, varied across environments. Joint analysis, in particular, presented significance for dominance and additive by environment interaction effects. Joint analysis had the highest selective accuracies for six traits. The correlation coefficients showed similar results, with values from 0.15 to 0.50 between pairs of environments. Gains with selection, considering each environment, ranged from 9.17 to 20.66%, when five hybrids were selected. When direct gains were compared with indirect gains, combined analysis confirmed the high efficiency of selection. For selection of parents, combined analysis achieves the same results as direct selection when two parents were selected.

中文翻译:

玉米育种的多性状多环境双列分析

玉米(Zea mays)种质发育的遗传研究是了解杂种优势群体之间的遗传变异性和互补性,以及加性和显性遗传效应的重要一步。因此,双列分析已被广泛采用,目的是确定最佳亲本系和最佳杂交。此外,不同的环境条件使遗传选择变得困难。因此,本研究的目的是通过玉米育种的混合模型方法比较双列设计的个体和联合分析,并评估和解释遗传效应及其与环境效应的相互作用。13 个 F2 杂种以不完整的双列方案杂交。评估了 78 个种群间杂种和 13 个自花授粉的亲本。评估了 11 个性状,重点是粮食产量 (GY) 性状。特别是 GY 特征的重要性因环境而异。联合分析尤其表明了环境相互作用效应对优势和可加性的重要性。联合分析对六个性状的选择准确度最高。相关系数显示出类似的结果,环境对之间的值从 0.15 到 0.50。考虑每个环境的选择,在选择五个混合动力车时,选择的选择,从9.17%到20.66%。当直接收益与间接收益进行比较时,综合分析证实了选择的高效率。对于父母的选择,组合分析可以在选择两个父母时实现与直接选择相同的结果。重点放在谷物产量 (GY) 特性上。特别是 GY 特征的重要性因环境而异。特别是联合分析显示了环境相互作用效应对优势和加性的重要性。联合分析对六个性状的选择准确度最高。相关系数显示出类似的结果,环境对之间的值从 0.15 到 0.50。考虑每个环境的选择,在选择五个混合动力车时,选择的选择,从9.17%到20.66%。当直接收益与间接收益进行比较时,综合分析证实了选择的高效率。对于父母的选择,组合分析可以在选择两个父母时实现与直接选择相同的结果。重点放在谷物产量 (GY) 特性上。特别是 GY 特征的重要性因环境而异。特别是联合分析显示了环境相互作用效应对优势和加性的重要性。联合分析对六个性状的选择准确度最高。相关系数显示出类似的结果,环境对之间的值从 0.15 到 0.50。考虑每个环境的选择,在选择五个混合动力车时,选择的选择,从9.17%到20.66%。当直接收益与间接收益进行比较时,综合分析证实了选择的高效率。对于父母的选择,组合分析可以在选择两个父母时实现与直接选择相同的结果。特别是联合分析显示了环境相互作用效应对优势和加性的重要性。联合分析对六个性状的选择准确度最高。相关系数显示出类似的结果,环境对之间的值从 0.15 到 0.50。考虑每个环境的选择,在选择五个混合动力车时,选择的选择,从9.17%到20.66%。当直接收益与间接收益进行比较时,综合分析证实了选择的高效率。对于父母的选择,组合分析可以在选择两个父母时实现与直接选择相同的结果。特别是联合分析显示了环境相互作用效应对优势和加性的重要性。联合分析对六个性状的选择准确度最高。相关系数显示出类似的结果,环境对之间的值从 0.15 到 0.50。考虑每个环境的选择,在选择五个混合动力车时,选择的选择,从9.17%到20.66%。当直接收益与间接收益进行比较时,综合分析证实了选择的高效率。对于父母的选择,组合分析可以在选择两个父母时实现与直接选择相同的结果。相关系数显示出类似的结果,环境对之间的值从 0.15 到 0.50。考虑每个环境的选择,在选择五个混合动力车时,选择的选择,从9.17%到20.66%。当直接收益与间接收益进行比较时,综合分析证实了选择的高效率。对于父母的选择,组合分析可以在选择两个父母时实现与直接选择相同的结果。相关系数显示出类似的结果,环境对之间的值从 0.15 到 0.50。考虑每个环境的选择,在选择五个混合动力车时,选择的选择,从9.17%到20.66%。当直接收益与间接收益进行比较时,综合分析证实了选择的高效率。对于父母的选择,组合分析可以在选择两个父母时实现与直接选择相同的结果。
更新日期:2020-08-24
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