Genotype by Environment Interaction Analysis in Summer Maize Hybrids for Grain Yield under Multi-Environment Trials in Huang-Huai-Hai Area, China
文献类型： 外文期刊
作者： Wang, Shaoqiang 1 ; Jiang, Xuwen 2 ; Wang, Shudong 1 ; Bu, Junzhou 2 ; Wei, Jianwei 2 ; Chen, Shuping 2 ; Peng, Haiche 1 ;
作者机构： 1.China Univ Petr, Coll Comp & Commun Engn, Qingdao 266580, Shandong, Peoples R China
2.Qingdao Agr Univ, Coll Agron, Qingdao 266109, Shandong, Peoples R China
3.Hebei Acad Agr & Forestry Sci, Dryland Farming Inst, Hengshui 053000, Peoples R China
4.Hebei Prov Key Lab Crops Drought Resistance Res, Hengshui 053000, Peoples R China
5.Hebei Acad Agr & Forestry Sci, Shijiazhuang 050031, Hebei, Peoples R China
关键词： AMMI model; Zea mays L.; Stability; Interaction principal component axes; Biplot
期刊名称：INTERNATIONAL JOURNAL OF AGRICULTURE AND BIOLOGY （ 影响因子：0.822； 五年影响因子：0.906 ）
ISSN： 1560-8530
年卷期： 2019 年 22 卷 6 期
页码：
收录情况： SCI
摘要： Maize is one of the most important cereal crops supporting millions of people in China. The main purpose of this research was to assess the genotype by environment interaction (GEI) and yield performance of 20 maize genotypes in 16 different environments of Huang-Huai-Hai area, China. In this research, the additive main effects and multiplicative interactions (AMMI) model was applied to analyze the GEI effect and to evaluate the suitability and yield stability of 20 different maize genotypes. The AMMI model analysis indicated that genotype (G), environment (E) and GEI had significant effects on grain yield and the contribution to the total sum of squares difference was 3.10%, 35.05% and 42.25%, respectively, suggesting that GEI was the primary factor affecting grain yield. The AMMI model analysis partitioned sum of squares of GEI into fourteen interaction principal components axes (IPCA), of which all the IPCA were significant (P < 0.01) and the first five IPCA (IPCA1, IPCA2, IPCA3, IPCA4 and IPCA5) explained 77.7% of variation. The AMMI model analysis using IPCA1 scores and G main effect indicated that two genotypes Hengyul47 and Hengyu321 had relatively stable performance across the environments. Among the locations, Quwo was the most productive site in distinguishing genotypes and the most representative environment. In conclusion, this study suggested that genotype and environment interactions were the major source of variation in maize yield, and use of AMMI model seemed useful for screening and identifying the response of summer maize genotypes in different environments. (C) 2019 Friends Science Publishers
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