Quantification of G × E interaction for feed barley genotypes by parametric and non-parametric measures
DOI:
https://doi.org/10.3329/bjb.v48i1.47414Keywords:
Parametric, Non-parametric measures, Rank correlation, Biplot analysis, Hierarchical clusteringAbstract
Genotype × environment (G × E) interaction of 28 feed barley genotypes in 12 environments was quantified by the parametric and non-parametric measures. Significant differences among G × E, environments and genotypes were observed as 42.3% of the total variance accounted for interaction effect. Interaction Principal Component Axes (IPCA1, IPCA2, IPCA3 and IPCA4) contributed 32.2, 20.3, 15.6 and 10.5% of the interaction sum of squares. Crossover interaction among genotypes and environments was confirmed by positive and negative values IPCAs. RD2786 followed by RD2876 had large negative IPCA1 score along with positive IPCA3 and IPCA4 values. Desirable genotypes were arranged in ascending order by D values as G23 (1.32) < G2 (1.42) < G20 (1.47) < G21 (1.63). The least AMMI Stability Value (ASV) score was observed for KB1367 followed by JB290 for yield performance. Smallest Pi was satisfied by BH 946, HUB 113 and RD2552. Environmental variance and CV identified non-stable performance of RD2874 and NDB1578 along with RD2876. Wricke’s ecovalence showed UPB1040 and UPB1042 as promising genotypes. Nonparametric measures (Si1, Si2 , Si3, Si4) pointed towards UPB1040 and PL881 for stable and unstable genotypes, however, Si5, Si6 selected UPB1040 and UPB1042 as of stable yield. More or less similar results were observed by parametric as well as non-parametric measures.
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