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Evaluation of maize grain yield and yield stability by AMMI analysis

机译:利用AMMI分析评价玉米籽粒产量和产量稳定性。

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Significant genotype x environment interaction for quantitative traits, such is grain yield, reduces the usefulness of genotype means, over all environments, for selecting superior genotypes. AMMI model is a valuable statistical tool in identifying systemic variation contained in the interaction effect. Obtained data could be applied in maximizing yield potential in every environment based on both narrow and wide genotype adaptability, without the necessity of developing breeding programs for smaller targeted environments. Precise assortment of superior genotypes, with the assistance of AMMI model, leads to the better recommendation of newly bred hybrids, and thus increasing maize grain yield in a targeted environment. In this research genotype x environment interaction and yield stability of 36 maize hybrids of FAO 300-700 maturity group was investigating. The trial was set according to Randomized Complete Block Design (RCBD). Data were processed in order to obtain average estimates of grain yield, and yield stability was assessed by the method of AMMI analysis. The highest average grain yield was achieved in 2011 (11.62 t/ha), and the lowest in the most stressful and dry 2012 (6.90 t/ha). In the region Loznica L2 the highest average yield was noticed (13.81 t/ha), while at L7 (Sremska Mitrovica) average grain yield was the lowest (6.97 t/ha). Results of AMMI analysis gave precise recommendation for production of maize hybrids in certain environments, by determining winning areas of hybrids H20, H11 and H36. Medium early maturing and high yielding hybrids (H11 and H20) are therefore considered more favorable for production in environments with lower precipitation, while high yielding and more stable hybrids H21 and H35 are suitable for a wider range of environments. Hybrid H36 (FAO 700) showed its full potential at L2, and L3 which did not suffer from a lack of moisture. This hybrid also expressed its best potential in environments with favorable conditions.
机译:对于数量性状(例如谷物产量)而言,显着的基因型x环境交互作用会降低基因型手段在所有环境中用于选择优良基因型的有用性。 AMMI模型是识别相互作用效应中包含的系统变异的有价值的统计工具。可以根据狭窄和广泛的基因型适应性,将获得的数据用于最大化每个环境中的产量潜力,而无需针对较小的目标环境制定育种计划。在AMMI模型的帮助下,优良基因型的精确分类可以更好地推荐新品种,从而在目标环境中提高玉米的单产。在这项研究中,研究了粮农组织300-700成熟度组的36个玉米杂交种的基因型x环境相互作用和产量稳定性。该试验是根据随机完整区组设计(RCBD)进行的。对数据进行处理以获得谷物单产的平均估计值,并通过AMMI分析方法评估单产稳定性。 2011年平均单产最高(11.62吨/公顷),而在最干旱的2012年则最低(6.90吨/公顷)。在Loznica L2地区,平均单产最高(13.81 t / ha),而在L7(Sremska Mitrovica),平均谷物单产最低(6.97 t / ha)。 AMMI分析的结果通过确定杂交体H20,H11和H36的获胜区域,为在某些环境下生产玉米杂交体提供了精确的建议。因此,中等早熟和高产杂种(H11和H20)被认为更适合在降水量较低的环境中生产,而高产和更稳定的杂种H21和H35适用于更广泛的环境。杂种H36(FAO 700)在L2和L3处都发挥了全部潜力,而L3却没有缺水。这种混合动力汽车在条件良好的环境中也表现出了最大的潜力。

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