Additive Main Effects and Multiplicative Interactions in Field Pea (Pisum sativum L.) Genotypes Across the Major Agro-climatic Zones in India

被引:7
作者
Biswas, Tufleuddin [1 ]
Mazumdar, Debasis [1 ]
Das, Arpita [2 ]
Kumar, P. Dinesh [1 ]
Maji, Anirban [2 ]
Parihar, A. K. [3 ]
Gupta, Sanjeev [3 ]
机构
[1] Bidhan Chandra Krishi Viswavidyalaya, Dept Agr Stat, Mohanpur 741252, W Bengal, India
[2] Bidhan Chandra Krishi Viswavidyalaya, Dept Genet & Plant Breeding, Mohanpur 741252, W Bengal, India
[3] Indian Inst Pulses Res, AICRP MULLaRP, Kanpur 208024, Uttar Pradesh, India
关键词
AMMI; Biplot; Eigen value; Field pea; Stability; STATISTICAL-ANALYSIS; BIPLOT ANALYSIS; AMMI ANALYSIS; ENVIRONMENT; STABILITY; YIELD; PERFORMANCE;
D O I
10.18805/LR-4166
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
In agricultural experimentation, a large number of genotypes are normally evaluated over a wide range of environments for delineating stable genotypes. In this study, fifteen dwarf field pea genotypes were evaluated at six diverse locations under three Agro-climatic zones viz., Central zone, North West peninsular zone and North east peninsular zone for the purpose of identifying stable genotypes through deploying the additive main effects and multiplicative interaction (AMMI) model. The uniqueness of AMMI biplot is to provide comprehensive solution regarding multi-environment evaluation of genotype. In addition to identification of stable genotypes, this approach facilitates effective selection of test environment and allows optimum resource allocation in future testing programme. In the present study from the AMMI biplot and the ASV AMMI stability value (ASV), it was detected that genotypes 6 (Pant-P-345), 12 (KPF-14-50) and 4 (KPMR-940) were the stable genotypes amid the tested genotypes. These identified genotypes with wide adaptation would be valuable treasure troves for the breeder for utilizing as a parent in field pea breeding programme of India.
引用
收藏
页码:894 / 899
页数:6
相关论文
共 33 条
  • [1] Combining ability and heterosis of elite drought-tolerant maize inbred lines evaluated in diverse environments of lowland tropics
    Adebayo, Moses A.
    Menkir, Abebe
    Blay, Essie
    Gracen, Vernon
    Danquah, Eric
    [J]. EUPHYTICA, 2017, 213 (02)
  • [2] [Anonymous], 2017, PROJECT C ORDINATORS
  • [3] Baker R.J., 1990, GENOTYPE BY ENV INTE
  • [4] Banik B.R., 2010, Acad. J. Plant Sci., V3, P134
  • [5] Bavandpori F., 2014, AGR COMMUN, V3, P8
  • [6] Biswas Ufleuddin, 2018, RASHI: Journal of the Society for Application of Statistics in Agriculture and Allied Sciences, V3, P39
  • [7] Bose LK, 2014, CHIL J AGR RES, V74, P3, DOI [10.4067/S0718-58392014000100001, 10.4067/s0718-58392014000100001]
  • [8] AMMI ADJUSTMENT FOR STATISTICAL-ANALYSIS OF AN INTERNATIONAL WHEAT YIELD TRIAL
    CROSSA, J
    FOX, PN
    PFEIFFER, WH
    RAJARAM, S
    GAUCH, HG
    [J]. THEORETICAL AND APPLIED GENETICS, 1991, 81 (01) : 27 - 37
  • [9] Deciphering Genotype-by-Environment Interaction for Targeting Test Environments and Rust Resistant Genotypes in Field Pea (Pisum sativum L.)
    Das, Arpita
    Parihar, Ashok K.
    Saxena, Deepa
    Singh, Deepak
    Singha, K. D.
    Kushwaha, K. P. S.
    Chand, Ramesh
    Bal, R. S.
    Chandra, Subhash
    Gupta, Sanjeev
    [J]. FRONTIERS IN PLANT SCIENCE, 2019, 10
  • [10] Additive main effect and multiplicative interaction analysis of national turfgrass performance trials: II. Cultivar recommendations
    Ebdon, JS
    Gauch, HG
    [J]. CROP SCIENCE, 2002, 42 (02) : 497 - 506