Comparison of Ammi, Parametric and Non-Parametric Models in Identifying High-Yielding and Stable Oilseed Rape Genotypes

Year 2022, Volume: 27 Issue: 2, 224 - 234, 23.12.2022

Hassan Amiri Oghan Behnam Bakhshi , Valiollah Rameeh Abolfazl Faraji Abdolhossein Askari Hamid Reza Fanaei

https://doi.org/10.17557/tjfc.1055496

Cited By: 3

Abstract

One of the complex issue in the way of releasing new high-yielding and stable oilseed rape ‎cultivars is genotype by environment interaction (GEI) which reduce selection efficiency. In ‎the current study, parametric and non-parametric statistics as well as the AMMI model have ‎been compared to identify the best stability models to clarify GEI complexity. The ‎experiment has been conducted in the warm regions of Iran including; Gorgan, Sari, Zabol, ‎and Hajiabad during two cropping seasons (2016-2017 and 2017-2018) for 16 genotypes in a ‎randomized complete block design with three replications. The AMMI analysis of variance on ‎grain yield showed the significant effects of genotype, environment, and the interaction ‎effects of GEI on yield. Based on the AMMI ANOVA, the major contribution of GEI was ‎captured by the first and second interaction principal component axes (IPCA1 and IPCA2) ‎which explained 34.29% and 29.81% of GEI sum of the square, respectively. Additionally, ‎Different parametric and non-parametric stability methods including; bi, S2di, CVi, W2i, σ2i, Pi, ‎Si(1), Si(2), Si(3), Si(6), Npi(1), Npi(2), Npi(3), Npi(4), KR and TOP have also investigated. Based on ‎AMMI, parametric, and non-parametric stability statistics, genotypes G2 (SRL-95-7) and G9 ‎‎(SRL-95-16)‎‏ ‏were selected as the stable and high-yielding genotypes. Likewise, Principal ‎component analysis based on rank correlation matrix enabled us to distinguish high-yielding ‎genotypes to stable (high-yielding genotypes in various environments) and unstable (high-‎yielding genotypes in low-yielding environments) ones. Furthermore, a significant Spearman ‎correlation was observed between yield mean and GSI, Pi, Si(3), Si(6), Npi(3), Npi(4), and KR. ‎Therefore, different efficient strategies were identified in this study‏ ‏and since we looked up ‎high-yielding and stable genotypes, G2 (SRL-95-7) and G9 (SRL-95-16)‎‏ ‏were finally ‎selected.‎

Keywords

AMMI, Brassica napus, Genotype by environment interaction (GEI), Parametric and non-‎parametric stability statistics, Principal component analysis

Supporting Institution

Seed and Plant Improvement Institute, Agricultural Research, Education and Extension ‎Organization (AREEO‎)

Project Number

‎0-03-03-327-961673‎

Thanks

We would like to thank the Seed and Plant Improvement Institute of Iran for supporting us in ‎conducting the research with grant number 0-03-03-327-961673.‎

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