Application of AMMI Model to Assess Spring Maize Genotypes under Multi-Environment Trials in Hebei Province
文献类型： 外文期刊
作者： Ye, Meijin 1 ; Wei, Jianwei 2 ; Bu, Junzhou 2 ; Gu, Zenghui 3 ; Wang, Yanbing 4 ; Chen, Shuping 2 ; Peng, Haicheng 2 ; Yu 1 ;
作者机构： 1.Chengdu Normal Univ, Coll Chem & Life Sci, Chengdu, Sichuan, Peoples R China
2.Hebei Acad Agr & Forestry Sci, Dryland Farming Inst, Hebei Prov Key Lab Crops Drought Resistance Res, Hengshui, Peoples R China
3.Agr Technol Extens Ctr Shijiazhuang, Shijiazhuang, Hebei, Peoples R China
4.Hebei Acad Agr & Forestry Sci, Inst Grain & Oil Crops, Shijiazhuang, Hebei, Peoples R China
关键词： Adaptability; Grain yield; Stability parameters; Zea mays L.
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 21 卷 4 期
页码：
收录情况： SCI
摘要： The genotype (G) by environment (E) interaction (GEI) determines the stability of maize grain yield in multi-environment trials (METs). This study evaluated the high-yielding and promising maize genotypes over years and locations by the additive main effects and multiplicative interaction (AMMI) model. The grain yield of 13 spring maize genotypes was evaluated for two consecutive years (2012-2013) when planted in six and eight ecological environments, respectively, using a randomized complete block design (RCBD) with three replications. The AMMI model explained 77.49 and 75.57% of total observed genotypic variation, respectively. A comprehensive analysis of variances showed a highly significant impact of environment, genotype and genotype x environment (GE) interaction on grain yield (P < 0.01). The AMMI model analysis of variance showed that the environment contributed the most to variations in grain yield (55.58 and 72.50% of the total variation, respectively), followed by GE interaction (24.61 and 10.71% of the total variation, respectively) and genotype (3.01 and 3.01% of the total variation, respectively). Among the interaction effects, first interaction principal component axis (IPCA1), IPCA2 and IPCA3 explained the vast majority of genetic and environmental interaction information. Two years of experimental data showed that the genotype with high yield and stability was G4 (Zhongdi175) while G3 (C807) and G8 (LY10) of poor yield and unstable. The check genotype G6 (Nongda108) had good stability and general high-yielding. The best and worst discriminative environments for each of the locations in 2012-2013 were XT (Xingtai) and LH (Longhua), WA (Wuan) and PQ (Pingquan), respectively. (C) 2019 Friends Science Publishers
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