EVALUATION OF SUNFLOWER HYBRIDS IN MULTI-ENVIRONMENT TRIAL (MET)

Abstract

Sunflower has been proposed as a potential crop model for an adaptation to a changing environment and special attention should be paid to testing hybrids under different environments. Additive main effects and multiplicative interaction model (AMMI) supplemented with genotype main effects and genotype by environment interaction effects (GGE) were used for dissection of genotype by environment interaction and evaluation of hybrids and testing environments. The research included 24 sunflower hybrids grown across twelve environments. AMMI analysis identified four significant interaction principal components (IPC), while in GGE biplot the first two IPCs accounted together for 44.59%. Environmental factors contributed the largest proportion in the total variation of seed yield (67.40%), followed by interaction and genotypes. High yielding hybrids H1, H14 and H11 showed specific adaptation to environments E10 and E1, respectively. The average environment coordination (AEC) view of GGE biplot indicated H17 as the most desirable genotype regarding seed yield. From the results of this study it can be concluded that MET trials are important not just for evaluation of stability and choosing the most stable genotypes, but also the genotypes that will perform well in low yielding environments and be able to take advantage of the favourable environmental conditions. 

Keywords

• Environmental factors,seed yield,sunflower

Supporting Institution

Ministry of Education, Science and Technological Development of the Republic of Serbia

Project Number

TR-31025 /114-451-2126/2016-03 / 451-03- 01732/2017-09/3

Thanks

This research is part of the project TR-31025, funded by the Ministry of Education, Science and Technological Development of the Republic of Serbia, provincial Secretariat for Higher Education and Science of Vojvodina, project 114-451-2126/2016-03 as well as a bilateral project between Serbia and Germany 451-03- 01732/2017-09/3 and COST Action CA 16212. Special thanks to Mr. Ilija Radeka and his team for efforts in carrying out the experiment.

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