GGE biplot analysis of genotype × environment interaction in rabi grain sorghum [Sorghum bicolor (L.) Moench]
180 / 65
Authors
-
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
Marathwada Agricultural University, Parbhani 431 402, Maharashtra
-
S. R. Gadakh
Mahatma Phule Krishi Vidyapeeth, Rahuri 413722, Distt. Ahmednagar 413722, Maharashtra
-
R. B. Ghorade
Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola 444104, Maharashtra
-
S.T. Kajjidoni
Main Sorghum Research Station, Univ. of Agricultural Sciences, Dharwad 580005, Karnataka
-
B. G. Solanki
Navsari Agricultural University, Athwa Farm, Surat 395007, Gujarat
-
B. D. Biradar
Agricultural Research Station, University of agricultural Sciences, Bijapur 586101, Karnataka
-
1 Prabhakar
Directorate of Sorghum Research, Rajendranagar, Hyderabad 500 030, Telangana
Abstract
Nature and complexity of genotype × environment interaction (GEI) was studied among eight rabi grain sorghum cultivars across 11 locations during rabi 2011-12
and 2012-13 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.