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Principal coordinate analysis of genotype × environment interaction for grain yield of bread wheat in the semi-arid regions

机译：半干旱地区面包小麦籽粒产量的基因型×环境互作的主坐标分析

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Multi-environmental trials have significant main effects and significant multiplicative genotype × environment (GE) interaction effect. Principal coordinate analysis (PCOA) offers a more appropriate statistical analysis to deal with such situations, compared to traditional statistical methods. Eighteen bread wheat genotypes were grown in four semi-arid regions over three year seasons to study the GE interaction and yield stability and obtained data on grain yield were analyzed using PCOA. Combined analysis of variance indicated that all of the studied effects including the main effects of genotype and environments as well as the GE interaction were highly significant. According to grand means and total mean yield, test environments were grouped to two main groups as high mean yield (H) and low mean yield (L). There were five H test environments and six L test environments which analyzed in the sequential cycles. For each cycle, both scatter point diagram and minimum spanning tree plot were drawn. The identified most stable genotypes with dynamic stability concept and based on the minimum spanning tree plots and centroid distances were G1 (3310.2 kg ha-1) and G5 (3065.6 kg ha-1), and therefore could be recommended for unfavorable or poor conditions. Also, genotypes G7 (3047.2 kg ha-1) and G16 (3132.3 kg ha-1) were located several times in the vertex positions of high cycles according to the principal coordinates analysis. The principal coordinates analysis provided useful and interesting ways of investigating GE interaction of barley genotypes. Finally, the results of principal coordinates analysis in general confirmed the breeding value of the genotypes, obtained on the basis of the yield stability evaluation.
机译：多环境试验具有重要的主要作用和显着的倍增基因型×环境（GE）相互作用作用。与传统的统计方法相比，主坐标分析（PCOA）提供了更合适的统计分析来处理这种情况。在三年的四个季节中，在四个半干旱地区种植了18种面包小麦基因型，以研究GE相互作用和产量稳定性，并使用PCOA分析获得的籽粒产量数据。组合方差分析表明，所有研究的影响，包括基因型和环境的主要影响，以及GE相互作用，都具有很高的意义。根据总体均值和总平均产量，将测试环境分为两个主要组：高平均产量（H）和低平均产量（L）。按顺序分析了五个H测试环境和六个L测试环境。对于每个循环，均绘制了散点图和最小生成树图。根据动态生成概念并根据最小生成树图和质心距离确定的最稳定的基因型为G1（3310.2 kg ha-1）和G5（3065.6 kg ha-1），因此建议在不利或恶劣条件下使用。此外，根据主坐标分析，基因型G7（3047.2 kg ha-1）和G16（3132.3 kg ha-1）多次位于高循环的顶点位置。主坐标分析提供了研究大麦基因型GE相互作用的有用和有趣的方式。最后，主坐标分析的结果总体上证实了基于产量稳定性评价而获得的基因型的育种价值。

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