Stability analysis of soybean [Glycine max (L.) Merrill] genotypes under multi-environments rainfed condition of North Western Himalayan hills

Anuradha Bhartiya, J. P. Aditya, Vedna Kumari, Naval Kishore, J. P. Purwar, L. Kant, A. Pattanayak
2018 Indian Journal of Genetics and Plant Breeding (The)  
In the present study, performance of five promising soybean genotypes over 4 locations during kharif 2013, 2014 and 2015 were investigated using GGE biplot analysis. Location attributed the highest proportion of the variation for all the traits except 100 seed weight ranging from 26.97-86.81% whereas, genotype contributed only 3.01-60.51% and genotype x location interaction contributed 6.01-31.42% of total variation. For 100 seed weight genotype has contributed major proportion of variation
more » ... on of variation (66.26%) than location (31.08%) and genotype x location interaction (2.65%). Superior genotypes for key traits viz., grain yield (VLS 86) and 100 seed weight (Himso 1685) were effectively identified using GGE biplot graphical approach. It may be stated from present study that, VLS 86 was the closest to ideal genotype with stability for high grain yield as well as earliness. 'Which-won-where' study partitioned the testing locations into two mega-environments: first with three locations with VLS 86 as the winning genotype; second mega environment encompassed only one location with Himso 1685 as the winning genotype. Existence mega environments was found correlated with the rainfall pattern and clearly suggested that different entries need to be selected and deployed for realising maximum grain yield in hill zone.
doi:10.31742/ijgpb.78.3.6 fatcat:lgampssuzvcufpokyijmnwrw7e