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Assessing genotype-by-environment interactions and trait associations in forage sorghum using GGE biplot analysis

Published online by Cambridge University Press:  24 March 2015

C. ARUNA*
Affiliation:
Directorate of Sorghum Research, Hyderabad, India
S. RAKSHIT
Affiliation:
Directorate of Sorghum Research, Hyderabad, India
P. K. SHROTRIA
Affiliation:
G.B. Pant University of Agriculture & Technology, Pantnagar, India
S. K. PAHUJA
Affiliation:
C.C.S. Haryana Agricultural University, Hisar, India
S. K. JAIN
Affiliation:
Sardarkrushinagar Dantiwada Agricultural University, Deesa, India
S. SIVA KUMAR
Affiliation:
Tamil Nadu Agricultural University, Coimbatore, India
N.D. MODI
Affiliation:
Navsari Agricultural University, Surat, India
D. T. DESHMUKH
Affiliation:
PDKV, Akola, India
R. KAPOOR
Affiliation:
Punjab Agricultural University, Ludhiana, India
J. V. PATIL
Affiliation:
Directorate of Sorghum Research, Hyderabad, India
*
*To whom all correspondence should be addressed. Email: aruna@sorghum.res.in

Summary

Forage sorghum is an important component of the fodder supply chain in the arid and semi-arid regions of the world because of its high productivity, ability to utilize water efficiently and adaptability to a wide range of climatic conditions. Identification of high-yielding stable genotypes (G) across environments (E) is challenging because of the complex G × E interactions (GEI). In the present study, the performance of 16 forage sorghum genotypes over seven locations across the rainy seasons of 2010 and 2011 was investigated using GGE biplot analysis. Analysis of variance revealed the existence of significant GEI for fodder yield and all eight associated phenotypic traits. Location accounted for a higher proportion of the variation (0·72–0·91), while genotype contributed only 0·06–0·21 of total variation in different traits. Genotype-by-location interactions contributed 0·02–0·13 of total variation. Promising genotypes for fodder yield and each of the associated traits could be identified effectively using a graphical biplot approach. The majority of test locations were highly correlated. A ‘Which-won-where’ study partitioned the test locations into two mega-environments (MEs): ME1 was represented by five locations with COFS 29 as the best genotype, while ME2 had two locations with S 541 as the best genotype. The existence of two MEs suggested a need for location-specific breeding. Genotype-by-trait biplots indicated that improvement for forage yield could be achieved through indirect selection for plant height, leaf number and early vigour.

Type
Crops and Soils Research Papers
Copyright
Copyright © Cambridge University Press 2015 

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