RT - Journal Article T1 - The Necessity of Considering the Assumptions of Genetic Model in Diallel Analysis JF - JSTNAR YR - 1998 JO - JSTNAR VO - 2 IS - 1 UR - http://jstnar.iut.ac.ir/article-1-265-en.html SP - 45 EP - 63 K1 - Gene effect K1 - Variance analysis K1 - Genetic parameters K1 - Reciprocal K1 - Heredity K1 - Oat K1 - Avena sp AB - Diallel crosses among 6 Avena sativa L. and A. sterilis L. lines and introductions were used to evaluate the validity of the assumptions for the genetic model. Number of days to pollination, plant height at pollination and at maturity, as well as grain and stem protein percentages were evaluated. According to Griffing's method 1 the reciprocal mean squares for all the traits under study were significant. But based on Hayman's analysis, the maternal effects for all the traits studied were not significant. Therefore, reciprocal means were used to evaluate the validity of the absence of multiple alleles, linkage and epistasis effects using regression of Wr on Vr and analysis of variance for Wr + Vr and Wr - Vr. Based on the results of the 3 methods, the genetic models for plant height at maturity and days to pollination were unbiased. Therefore, Hayman's analysis was used to estimate the genetic parameters for these traits. For plant height at pollination and stem protein percentage, significant and nonsignificant differences of regression slope from one and zero (Ho: β = 1 and Ho: β = 0) were detected, respectively. For these traits the biasedness of the model was removed after elimination of one parent from the diallel table. Grain protein percentage was not analyzed as it necessitated the elimination of 2 parents from the diallel table. In general, regression of Wr on Vr compare to Wr + Vr and Wr - Vr analysis of variances showed to be a more valid inductive method for testing the accuracy of the genetic model assumptions. Also, results of the Hayman and Jinks analysis, both when the assumptions are valid and when not, showed that genetic parameters are affected by the biasedness of the model, and that different estimates will be obtained. The Griffing's method was less affected by the unbiasedness of the model than Hayman and Jinks method. Therefore, it seems that preliminary testing for validity of the assumptions is necessary in Hayman and Jinks genetic model. LA eng UL http://jstnar.iut.ac.ir/article-1-265-en.html M3 ER -