GGE biplot analysis of genotype × environment interaction in rabi grain sorghum [Sorghum bicolor (L.) Moench]

  • Sujay Rakshit Directorate of Sorghum Research, Rajendranagar, Hyderabad 500 030, Telangana
  • K. N. Ganapathy Directorate of Sorghum Research, Rajendranagar, Hyderabad 500 030, Telangana
  • S. S. Gomashe Directorate of Sorghum Research, Rajendranagar, Hyderabad 500 030, Telangana
  • M. Swapna Directorate of Sorghum Research, Rajendranagar, Hyderabad 500 030, Telangana
  • A. More Directorate of Sorghum Research, Rajendranagar, Hyderabad 500 030, Telangana
  • S. R. Gadakh Directorate of Sorghum Research, Rajendranagar, Hyderabad 500 030, Telangana
  • R. B. Ghorade Directorate of Sorghum Research, Rajendranagar, Hyderabad 500 030, Telangana
  • S. T. Kajjidoni Directorate of Sorghum Research, Rajendranagar, Hyderabad 500 030, Telangana
  • B. G. Solanki Directorate of Sorghum Research, Rajendranagar, Hyderabad 500 030, Telangana
  • B. D. Biradar Directorate of Sorghum Research, Rajendranagar, Hyderabad 500 030, Telangana
  • Prabhakar Directorate of Sorghum Research, Rajendranagar, Hyderabad 500 030, Telangana
Keywords: GGE biplot, GxE interaction, sorghum, mega-environment

Abstract

Nature and complexity of genotype × environment interaction (GEI) was studied among eight rabi grain sorghum cultivars across 11 locations during rabi 201112 and 201213 using GGE biplot analysis. Location (L) contributed for 89.9% of variation for grain yield, while genotypes (G) and G × L interactions accounted for 1% and 9% of variation only. The first two principal components (PCs) of GGE biplot accounted for 50% of variation in data for grain yield, which not ideally explained overall variation in the data. However, the biplot clearly demonstrated that across environments, SPH 1721 was the highest yielding stable genotype followed by CSH 15R. High crossover GEI was recorded among the testing locations and close correlation among these locations was not detected. ‘Which-won-where’ analysis detected three mega-environments (ME) among the testing locations, with ME1 represented by 5 locations, ME2 with 4 locations and ME3 with 2 locations. The study indicated the possibility to reduce the number of testing locations.
Published
2014-11-25