AMMI, BLUP, and WAASB Stability Models for the Selection of Stable Chickpea (Cicer arietinum L.) Genotypes in Different Agroecological Regions

Abstract

The effect of genotype×environment interaction (GEI) presents a challenge in identifying 
genotypes that are stable across diverse environments. Present study was undertaken to check 
adaptability and stability of 16 chickpea genotypes in 10 different agro-ecological regions of 
Pakistan. Further, the importance of stability models like additive main effects and multiplicative 
interaction analysis, weighted average of absolute scores from singular value decomposition of 
BLUPs and best linear unbiased prediction was assessed to identify stable genotypes. AMMI 
ANOVA showed that main effects of genotype, environment along with GEI were significant and 
first two principal components explained about 64.2% of GEI variance. LMM-BLUP found that 
98.8% phenotypic variance was due to GEI variance. G1 with low PC1 score in AMMI biplot 
analysis proved to be the most high yielding and stable genotype. Cross-validation conducted for 
BLUP and AMMI models identified BLUP as the most accurate model for the current dataset. 
Graphical display using BLUP based predicted grain yield ranked genotypes regarding stability and 
adaptability.  However, Y× WAAS graphs were more useful as they categorized genotypes and 
environments into clear cut groups based on their productivity and stability. We concluded that 
AMMI, BLUP, and WAASB methods can be used to select well adapted and stable genotypes.