Decipher GXE Interaction of Wheat Genotypes by Multivariate, BLUP and Non Parametric Measures Evaluated in NEPZ

Author: Ajay Verma* and Gyanendra Pratap Singh

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Abstract

Quite numbers of studies have compared with AMMI with BLUP or AMMI with non parametric measures, the present study made comparative analysis considering all type of analytic measures. AMMI analysis observed highly significant variations due to environments, GxE interactions, and genotypes with respective percent share 63.3% 20.7% 2.8% towards total sum square of variation for yield. Absolute IPCA-1 scores pointed for G1, G3 as per IPCA-2, genotypes G8, G7 would be of choice First two IPCAs in ASV & ASV1 measures utilized 50.1% of G×E interaction sum of squares. Set of genotypes (G1, G7) and (G7, G6) recommended ASV1 and ASV. All seven significant IPCAs considered by MASV and MASV1 measures pointed towards G4, G2 genotypes. BLUP-based simultaneous selections, such as HMGV identified G8, G4, values of RPGV favored G8, G1 and HMRPGV estimates selected G8, G4 genotypes. Non parametric composite measure NPi (1) observed suitability of G6, G2 while NPi(2) selected G6, G9 whereas N

Keywords

AMMI, BLUP, Si(s), NPi(s), Spearman rank Coefficient, Biplot analysis.

Conclusion

Environment and G x E interaction effects contributed were the most important with 63.3% and 20.7% of the variation, respectively. The results of the biplot and correlation analysis indicated weak and strong both types of relationships among the measures. However the nonparametric measures can be used to assess the stable behavior of genotypes over various environments.

References

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How to cite this article

Ajay Verma and Gyanendra Pratap Singh (2022). Decipher GXE interaction of Wheat genotypes by Multivariate, BLUP and Non Parametric measures evaluated in NEPZ. Biological Forum – An International Journal, 14(1): 1308-1315.