Genotype x environment interaction and biplot analysis of multi-environment trials data from low erucic acid indian mustard (brassica juncea l.) Genotypes.
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Date
2016
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Punjab Agricultural University, Ludhiana
Abstract
The present study was conducted on sixteen mustard genotypes evaluated across three locations of Punjab with the objective to assess stability of performance using Eberhart and Russell model and GGE biplot analysis in visualization of interrelationships of genotypes, environments and their interactions for seed yield per plant (g), oil content (%), seed size (1000 seed weight), number of siliquae on main shoot, seeds per siliqua and other yield contributing characters. In terms of utility of GGE biplot, the association between environments was stratified under positive and negative correlations. Two environments E1( Bathinda): E2 (Faridkot) were positively correlated for most of the traits, hence same information about the genotypes could be obtained from fewer test environments, depicting the potential to reduce testing cost by dropping one of them. However, for two traits viz. oil content (%) and seed size, all the three environments were positively correlated. The ideal test environments (most discriminative and also most representative) were E1 (Bathinda) and E2 (Faridkot) for seed yield per plant, oil content, seed size, no. of siliquae on main shoot and main shoot length, therefore, be considered the best for evaluation of genotypes for these traits. ELM 123 (G4) was identified as an ideal genotype with high mean performance for seed yield per plant, oil content, seeds per siliqua and early flowering, thereby suggesting that this variety can be commercially exploited for the Punjab state. This quality mustard genotype ELM 123 (RLC 2) has also been identified at national level for Zone II that includes Punjab in the year 2011. Genotype JC 37-6-1-2 (G5) has high mean and is responsive to favourable environment for seed yield per plant, no. of siliquae on main shoot and early maturity, so it can be used as a donor parent for improvement of these traits. Similarly genotype JC 75-8-2 (G6) has high mean and is responsive to favourable environment for oil content, no. of siliquae on main shoot and early maturity. One of the unique features of GGE biplot technique was which-won-where pattern of genotype x environment interactions. GGE biplot is more logical than AMMI in terms of explanation of PC1 score, which represents genotypic effects rather than additive main effects. So, it is better to exploit GGE biplot technique for estimation of G x E interactions, which is also depicted from the variances captured by different models in the present study. The GGE Biplot has captured maximum variance for each trait showing its efficacy for stability for all traits.
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Keywords
mustard, genotype, Brassica Juncea L., biplot, Genotypes