Assessment of ecological plasticity and stability of sunflower hybrids (Helianthus annuus L.) in Ukrainian Steppe

O. A. Eremenko, V. V. Kalitka, S. M. Kalenska, V. M. Malkina

Abstract


Modern hybrids of sunflower show a pronounced response to changes in agrometeorological conditions of their growing. The
research was carried out during 2013-2015 under conditions of insufficient moisture in the Southern steppe of Ukraine. Field
and mathematical-statistical methods were used. A comparative assessment of levels of ecological stability was made for 7
sunflower hybrids (the company “Pioneer”). The application of plasticity and stability analysis by the Eberhard-Russell method
allows carrying out an integrated assessment of new hybrids in terms of their adaptability to growing conditions and a reaction
norm of genotypes to cultivation technology. In the dry steppe zone the sunflower realizes 45% of its genetic yield potential.
The highest yield of the studied hybrids was observed in 2013 when, despite the unfavourable hydrothermal index of the year,
the minimum relative air humidity during the flowering period was optimal (61.8%). A certain number of genotypes are
characterized by the average group value of the plasticity index of yield (i.e. close to 1), namely: PR64LE19, PR64LE71, PR64LE11, PR64A71. Stability ranges from 0.29 in the hybrid PR64LE11 to 32.51 in the hybrid PR64LE19. The hybrids PR64LE71 and PR64LE19 change their ecological plasticity under varying growing conditions. The hybrid PR64F66 is less responsive to varying environments than the whole set of hybrids on average but, compared to others, exhibits average stability. The best results were shown by the hybrids PR64F50 and PR64A89, since they are more sensitive to varying environments and more stable than other hybrids. Growing hybrids of different levels of intensity, genetically and biologically diverse, allows the effective exploitation of agroecological potential of different zones.

Keywords


sunflower; agrometeorological conditions; adaptability; stable yield; mathematical-statistical methods

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References


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DOI: http://dx.doi.org/10.15421/2018_214

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