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

Authors : Hassan AMİRİ OGHAN, Behnam BAKHSHİ, Valiollah RAMEEH, Abolfazl FARAJİ, Abdolhossein ASKARİ, Hamid Reza FANAEİ

Pages : 224-234

Doi:10.17557/tjfc.1055496

View : 50 | Download : 14

Publication Date : 2022-12-23

Article Type : Research Paper

Abstract :One of the complex issue in the way of releasing new high-yielding and stable oilseed rape ‎cultivars is genotype by environment interaction insert ignore into journalissuearticles values(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 insert ignore into journalissuearticles values(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 insert ignore into journalissuearticles values(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, ‎Siinsert ignore into journalissuearticles values(1);, Siinsert ignore into journalissuearticles values(2);, Siinsert ignore into journalissuearticles values(3);, Siinsert ignore into journalissuearticles values(6);, Npiinsert ignore into journalissuearticles values(1);, Npiinsert ignore into journalissuearticles values(2);, Npiinsert ignore into journalissuearticles values(3);, Npiinsert ignore into journalissuearticles values(4);, KR and TOP have also investigated. Based on ‎AMMI, parametric, and non-parametric stability statistics, genotypes G2 insert ignore into journalissuearticles values(SRL-95-7); and G9 ‎‎insert ignore into journalissuearticles values(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 insert ignore into journalissuearticles values(high-yielding genotypes in various environments); and unstable insert ignore into journalissuearticles values(high-‎yielding genotypes in low-yielding environments); ones. Furthermore, a significant Spearman ‎correlation was observed between yield mean and GSI, Pi, Siinsert ignore into journalissuearticles values(3);, Siinsert ignore into journalissuearticles values(6);, Npiinsert ignore into journalissuearticles values(3);, Npiinsert ignore into journalissuearticles values(4);, and KR. ‎Therefore, different efficient strategies were identified in this study‏ ‏and since we looked up ‎high-yielding and stable genotypes, G2 insert ignore into journalissuearticles values(SRL-95-7); and G9 insert ignore into journalissuearticles values(SRL-95-16);‎‏ ‏were finally ‎selected.‎
Keywords : AMMI, Brassica napus, Genotype by environment interaction GEI, Parametric and non ‎parametric stability statistics, Principal component analysis

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