The use of an AMMI model and its parameters to analyse yield stability in multi-environment trials

被引:82
|
作者
Sabaghnia, N. [1 ]
Sabaghpour, S. H. [2 ]
Dehghani, H. [1 ]
机构
[1] Tarbiat Modares Univ, Fac Agr, Dept Plant Breeding, Tehran, Iran
[2] Dry Land Agr Res Inst, Kermanshah, Iran
来源
关键词
D O I
10.1017/S0021859608007831
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Genotype by environment (G x E) interaction effects are of special interest for breeding programmes to identify adaptation targets and test locations. Their assessment by additive main effect and multiplicative interaction (AMMI) model analysis is currently defined for this situation. A combined analysis of two former parametric measures and seven AMMI stability statistics was undertaken to assess G x E interactions and stability analysis to identify stable genotypes of 11 lentil genotypes across 20 environments. G x E interaction introduces inconsistency in the relative rating of genotypes across environments and plays a key role in formulating strategies for crop improvement. The combined analysis of variance for environments (E), genotypes (G) and G x E interaction was highly significant (P<0.01). suggesting differential responses of the genotypes and the need for stability analysis. The parametric stability measures of environmental variance showed that genotype ILL 6037 was the most stable genotype, whereas the priority index measure indicated genotype FLIP 82-1L to be the most stable genotype. The first seven principal component (PC) axes (PC1-PC7) were significant (P<0.01), but the first two PC axes Cumulatively accounted for 71% of the total G x E interaction. In contrast, the AMMI stability statistics suggested different genotypes to be the most stable. Most of the AMMI stability statistics showed biological stability, but the SIPCF statistics of AMMI model had agronomical concept stability. The AMMI stability value (ASV) identified genotype FLIP 92-12L as a more stable genotype, which also had high mean performance. Such an outcome could be regularly employed in the future to delineate predictive, more rigorous recommendation strategies as well as to help define stability concepts for recommendations for lentil and other crops in the Middle East and other areas of the world.
引用
收藏
页码:571 / 581
页数:11
相关论文
共 50 条
  • [21] One compound approach combining factor-analytic model with AMMI and GGE biplot to improve multi-environment trials analysis
    Zhang, Weihua
    Hu, Jianlin
    Yang, Yuanmu
    Lin, Yuanzhen
    JOURNAL OF FORESTRY RESEARCH, 2020, 31 (01) : 123 - 130
  • [22] A mixed model analysis of variance for multi-environment variety trials
    T. Caliński
    S. Czajka
    Z. Kaczmarek
    P. Krajewski
    W. Pilarczyk
    Statistical Papers, 2009, 50 : 735 - 759
  • [23] A mixed model analysis of variance for multi-environment variety trials
    Calinski, T.
    Czajka, S.
    Kaczmarek, Z.
    Krajewski, P.
    Pilarczyk, W.
    STATISTICAL PAPERS, 2009, 50 (04) : 735 - 759
  • [24] Genotype x environment interaction analysis of multi-environment wheat trials in India using AMMI and GGE biplot models
    Singh, Charan
    Gupta, Arun
    Gupta, Vikas
    Kumar, Pradeep
    Sendhil, R.
    Tyagi, B. S.
    Singh, Gyanendra
    Chatrath, Ravish
    Singh, G. P.
    CROP BREEDING AND APPLIED BIOTECHNOLOGY, 2019, 19 (03): : 309 - 318
  • [25] Genotype × Environment Interactions and Simultaneous Selection for High Seed Yield and Stability in Winter Rapeseed (Brassica napus) Multi-Environment Trials
    Bahram Alizadeh
    Abbas Rezaizad
    Mohammad Yazdandoost Hamedani
    Gholamhossein Shiresmaeili
    Farshad Nasserghadimi
    Hamid Reza Khademhamzeh
    Amir Gholizadeh
    Agricultural Research, 2022, 11 : 185 - 196
  • [26] GGE-Biplot analysis of multi-environment yield trials in bread wheat
    Bahri Daǧdaş International Agricultural Research Institute, P.O. Box 125, Konya, Turkey
    Turk. J. Agric. For., 2006, 5 (325-337):
  • [27] AMMI, GGE biplots and regression analysis to comprehend the G x E interaction in multi-environment barley trials
    Kumar, Vishnu
    Kharub, A. S.
    Verma, R. P. S.
    Verma, Ajay
    INDIAN JOURNAL OF GENETICS AND PLANT BREEDING, 2016, 76 (02) : 202 - 204
  • [28] Evaluation of productivity and stability of elite summer soybean cultivars in multi-environment trials
    Jun Qin
    Ran Xu
    Haichao Li
    Chunyan Yang
    Duan Liu
    Zhangxiong liu
    Lifeng Zhang
    Weiguo Lu
    Terrence Frett
    Pengyin Chen
    Mengchen Zhang
    Lijuan Qiu
    Euphytica, 2015, 206 : 759 - 773
  • [29] Genotype x Environment Interactions and Simultaneous Selection for High Seed Yield and Stability in Winter Rapeseed (Brassica napus) Multi-Environment Trials
    Alizadeh, Bahram
    Rezaizad, Abbas
    Hamedani, Mohammad Yazdandoost
    Shiresmaeili, Gholamhossein
    Nasserghadimi, Farshad
    Khademhamzeh, Hamid Reza
    Gholizadeh, Amir
    AGRICULTURAL RESEARCH, 2022, 11 (02) : 185 - 196
  • [30] Evaluation of productivity and stability of elite summer soybean cultivars in multi-environment trials
    Qin, Jun
    Xu, Ran
    Li, Haichao
    Yang, Chunyan
    Liu, Duan
    Liu, Zhangxiong
    Zhang, Lifeng
    Lu, Weiguo
    Frett, Terrence
    Chen, Pengyin
    Zhang, Mengchen
    Qiu, Lijuan
    EUPHYTICA, 2015, 206 (03) : 759 - 773