Multilocational evaluation of white yam genotypes using gge bi-plot methodology.

Emmanuel C Nwachukwu
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Abstract

Yams are Cultivated in diverse agroecologies and there is evidence of strong genotype and environment interaction. This has necessitated the evaluation of new yam genotypes in multi-locational trials. Five new white yam genotypes were evaluated in different locations of major yam producing areas; Umudike, Nsukka, Ubiaja, Abuja and Katsina-Ala, to test the performance and stability of these genotypes across the environments using GGE bi-plot software. The GGE bi-plot generated several graphic bi-plots which showed Umudike, Nsukka, Ubiaja and Katsina-Ala belonging to one mega- environment while Abuja and Ubiaja belong to another. The GGE bi-plot also showed the discriminating and non-discriminating environments. Katsina-Ala was the most discriminating environment while Nsukka was the least. A test environment that lacks discriminating ability lacks the capacity to provide information about the genotype being used. Such environment lacks usefulness and should be discarded as a test environment Katsina-Ala, with the longest vector is the most discriminating. This is followed by Ubiaja, Umudike and Abuja in that order. Nsukka is the least discriminating.
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利用gge双图方法对白山药基因型进行多位点评价。
山药种植在不同的农业生态中,有证据表明基因型和环境相互作用很强。这就需要在多地点试验中评估新的山药基因型。在山药主产区的不同地点对5种新的白山药基因型进行了评价;Umudike、Nsukka、Ubiaja、Abuja和Katsina-Ala,利用GGE双图软件测试这些基因型在不同环境中的表现和稳定性。GGE双图生成了几个图形双图,显示乌穆代克、恩苏卡、乌比亚加和卡齐纳-阿拉属于一个大型环境,而阿布贾和乌比亚加属于另一个大型环境。GGE双图也显示了歧视和非歧视环境。Katsina-Ala是最具歧视性的环境,而Nsukka是最不具歧视性的环境。缺乏鉴别能力的测试环境无法提供所使用基因型的信息。这种环境缺乏有用性,应该放弃作为Katsina-Ala测试环境,最长的向量是最具鉴别性的。其后依次是乌比亚贾、乌穆代克和阿布贾。恩苏卡是最没有辨别力的。
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