Malt Barley Genotypes Assessed by Analytic Adaptability Measures for NWPZ of the Country

Abstract

Ajay Verma, RPS Verma, J Singh, L Kumar and GP Singh

Highly significant effects of the environment (E), genotypes (G), and GxE interaction had been observed by AMMI analysis. Environment explained 51.4% whereas GxE interaction accounted for 22.1% of treatment variations in yield during first year. Harmonic Mean of Genotypic Values (HMGV) expressed higher values for DWRB160, DWRB184, and BH902. Ranking of genotype as per IPCA-1 were BH902, DWRB182, DWRB101. While IPCA-2, selected DWRB101, DWRB123, DWRB184 genotypes. Values of ASV1 selected DWRB101, DWRB182, BH902 and ASV identified DWRB101, DWRB123, DWRB182 barley genotypes. Adaptability measures Harmonic Mean of Relative Performance of Genotypic Values (HMPRVG) and Relative Performance of Genotypic Values (RPGV) identified DWRB160, DWRB184, and BH902 as the genotypes of performance among the locations. Biplot graphical analysis exhibited adaptability measures PRVG, HMPRVG along with IPC3, mean, GM, HM grouped in a cluster. During 2019-20 cropping season Environment effects accounted 79.7% whereas GxE interaction contributed for 7.7% % of treatment variations in yield. HMGV expressed higher values for DWRB196, DWRB123, and RD2849. IPCA-1 scores, desired ranking of genotypes was DWRB182, PL908, RD2849. While IPCA-2 pointed towards PL908, RD2849, DWRB196, as genotypes of choice. Analytic measures ASV and ASV1 selected PL908, RD2849, DWRB123 barley genotypes. HMRPGV along with PRVG settled for DWRB196, DWRB123, and RD2849. Adaptability measures PRVG, HMPRVG clustered with mean, GM, HM and observed in different quadrant of biplot analysis.

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