Author/Authors :
TOPAL, Mehmet Atatürk Üniversitesi - Ziraat Fakültesi - Zootekni Bölümü, Biyometri ve Genetik Anabilim Dalı, Turkey , YILDIZ, Necati Atatürk Üniversitesi - Ziraat Fakültesi - Zootekni Bölümü, Biyometri ve Genetik Anabilim Dalı, Turkey
Abstract :
Plant and animal yields are the result of the effect of genotype and environment. Phenotypic variation originates from genotype, environment and Genotype × Environment interaction. Genotype × Environment interaction is the most important issue for animal and plant breeding. Parametric and nonparametric methods used in determination of Genotype × Environment interaction are based on the yield values of genotypes and their ranks in each environment. Genotype × Environment interactions are individually established by stability methods. At the beginning of this research, variance analysis was applied to determine the interactions related to data simulated according to normal and discrete uniform distribution, and then S^(1) i, S^(2) i, S^(3) i, S^(6) i, Li, Ri and Kang’s yield – stability statistics from nonparametric methods were applied to present data. It was observed that differences among the methods applied for the data displaying normal and discrete uniform distribution were not significant. When the interactions obtained according to variance analysis in both normal and discreate uniform distribution were insignificant, coefficient values from nonparametric stability estimation methods were also found to be insignificant. In addition, when interaction was determined to be significant, difference among the coefficient values was significant. The highest correlation in nonparametric methods for normal and discreate uniform distributions was found between S1 and S2, S3 and S6, L, R, S1 and S2 methods. KSM method showed high and significant correlation with S3 and S6. KSM method had significant and negative correlation with the mean of genotype values. The highest correlations were found among the CV, VK, EV, SSV with S1, S2, L and R methods of parametric and nonparametric methods. A significant correlation was not determined between regression and nonparametric methods. It was observed that similar results may be obtained when any method showing high correlation with other methods was used to determine the Genotype × Environment interaction.
