Authors : C.O. Aremu , T.A Adebayo , M. Oyekunle and O.J. Ariyo
Abstract: The prediction and interpretation of quantitative traits complimenting the yield of crop genotype is a major problem in Genotype by Environment (G�E) interaction. Four different statistics were used. These are Regression models using Coefficient of determination and Mallows’ statistics, Genotype-grouping technique, Ecovalence mean square and Additive Main effect and Multiplicative Interaction (AMMI) model. The Multiple Regression model, Mallows’ statistics and Ecovalence mean square technique identified number of branch per plant and number of pods per plant as important components contributing meaningfully to the yield of soybean across environments. Genotype grouping-technique identified TG�1627-IF,TGx1448-DE and TG�1019-2E-N with above average yield to have stable performance across the environments. In addition to these three genotypes, (AMMI) model revealed TG�1519-1D, TG�1019-2EB and TG�1649-1F to show stable performance. AMMI model, Regression and Mallows’ statistics gave wide and specific genotype adaptation where Ecovalence mean square and Genotype-grouping technique showed only wide genotype adaptation. But regression model and mallows’ statistics deviated from AMMI model and genotype grouping technique in that while AMMI and Genotype grouping technique identified genotype adaptation with respect to yield character only, Regression and Mallows’ statistics based genotype adaptation with respect to performance of other characters apart from yield. Regression and Mallows’ statistics and AMMI model identified Ogbomoso environment to be most suitable for soybean adaptation. The use of Regression model, Mallows’ statistics along side with AMMI model will reveal overall genotype performance better than only AMMI model which structures genotype performance based only on yield.
C.O. Aremu , T.A Adebayo , M. Oyekunle and O.J. Ariyo , 2007. The Relative Discriminatory Abilities of Techniques Measuring Genotype x Environmental Interaction in Soybean (Glycine Max (L) Merr.) in Semi-Arid and Rain Forest Environments of Nigeria . Agricultural Journal, 2: 210-215.