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首页> 外文期刊>African Journal of Plant Science >GGE biplot analysis of genotypes by environment interaction on Sorghum bicolor L. (Moench) in Zimbabwe
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GGE biplot analysis of genotypes by environment interaction on Sorghum bicolor L. (Moench) in Zimbabwe

机译:津巴布韦高粱双子醇L.(Moench)对基因型的GGE双型分析

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The genotype by environment interaction (GEI) reduces the success of genotype selection and recommendations by breeders, thus slowing down the progress of plant breeding. The understanding of genotype by environment interaction (GEI) multi-locational yield trials (MLYT) enables researchers to identify locations which are efficient in distinguishing tested genotypes, which are ideal across the test-locations as well as environments which are good representatives of the target regions of interest. The main objective of the study was to assess the genotype by environment interaction on grain yield stability of promising sorghum genotypes across five diverse environments of Zimbabwe. Sorghum yield data of twenty-seven cultivars was obtained from the replicated trials. After performing a pooled analysis of variance for grain yield across five diverse environments during the 2013/14 rainy season, the GxE interaction was significant (P<0.001), and this justified need for testing for GEI components using the GGE biplot analysis to enhance the understanding the effects of components. The results revealed that three mega-environments were identifiable which are Matopos, Save-Valley and Kadoma falling in one mega-environment, then Makoholi was identified as a second mega-environment and then Gwebi was identified as the third mega-environment. Gwebi had the most discriminating ability and good representativeness whereby Save Valley had a poor discriminating ability as well as least representativeness.
机译:环境相互作用(GEI)的基因型降低了种族型选择和育种者建议的成功,从而减缓了植物育种的进展。通过环境相互作用(GEI)多场屈服试验(MLYT)对基因型的理解使研究人员能够识别在区分测试基因型中的有效的位置,这是对测试位置的理想,以及目标是目标的好代表的环境感兴趣的地区。该研究的主要目的是评估环境相互作用对Zimbabwe五种不同环境的有前高粱基因型的粮食产量稳定性的基因型。二十七种品种的高粱产量数据从复制的试验中获得。在2013/14雨季在五种不同环境中进行汇总分析的谷物产量方差,GXE相互作用很大(P <0.001),并且这种合理的需要使用GGE双批分析来测试GEI组件以增强了解组件的影响。结果表明,三个兆瓦环境是识别的,其是Matopos,拯救谷和喀代码落在一个兆瓦环境中,然后Makoholi被鉴定为第二兆环境,然后将Gwebi被确定为第三兆环境。 GWEBI具有最具歧视的能力和良好的代表性,拯救谷具有差的歧视能力以及最小的代表性。

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