菜豆青荚产量稳定性的AMMI分析埃塞俄比亚奥罗米亚州东舍瓦区基因型评价

T. Dinsa, Urgaya Balcha, Fisseha Tadesse
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引用次数: 0

摘要

该试验于2019年和2020年主要种植季在阿达米图鲁农业研究中心(ATARC)、卢姆区和杜格达区进行,旨在确定东舍瓦区和类似农业生态的适应性和高产小豆基因型。选用10个豆荚基因型作为种植材料。试验采用随机完全区组设计(RCBD), 3个重复。AMMI模型显示,环境占总变异的40.93%,GXE占31.79%,基因型占12.70%。环境因子所占比例较高,说明影响豆角产量的主要因素是环境因子。前2种ipca是最准确的预测基因型稳定性的模型,可以用GEI的IPCA-I(53.10%)和IPCA-II(21.1%)解释。结果表明,由于GEI的存在,在不同的测试环境下,豆角基因型的产量表现存在差异。根据稳定性参数(ASV和GGE双图)和平均产量结果显示,G-24和G-12基因型是各试验点最稳定的基因型。因此,建议G-24和G-12作为可能释放的候选基因型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AMMI Analysis for Green Pod Yield Stability of Snap Bean (Phaseolus vulgaris L.) Genotypes Evaluated in East Shewa Zone, Oromia, Ethiopia
The experiment was conducted at Adami Tulu Agricultural Research Center (ATARC), Lume and Dugda Districts during the 2019 and 2020 main cropping seasons to identify adaptable and high yielder snap bean genotypes for East Shewa Zone and similar agro ecologies. Ten snap bean genotypes were used as planting material. The experiment was laid down in Randomized Complete Block Design (RCBD) with three replications. The AMMI model shows that the environment accounted for 40.93%, GXE 31.79%, and genotype 12.70% of the total variation. The high percentage of the environment indicates that the major factor influencing the yield performance of snap beans is the environment. The first two IPCAs are the most accurate model that could predict the genotype’s stability and explained by IPCA-I (53.10%) and IPCA-II (21.1%) of GEI. This result revealed that there were differential yield performances among snap bean genotypes across testing environments due to the presence of GEI. According to stability parameters (ASV, and GGE Biplot) and mean yield results revealed that G-24 and G-12 genotypes are the most stable genotypes across test locations. Therefore, G-24 and G-12 were proposed as candidate genotypes for possible release.
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