Generation mean analysis technique for determining genetic parameters for some quantitative traits in two maize hybrids (Zea mays L.)‎

Abstract EN

This experiment was conducted at the Maize Researches Department, General Commission for Scientific Agriculture Researches (G.C.S.A.R.) Damascus, Syria during the summer growing seasons of 2010, 2011 to 2012.

Treatments were arranged in a Randomized Complete Blocks Design with three replications.

This research aimed to evaluate genetic parameters for days to 50 % silking, plant and ear height, ear length, ear diameter, number of rows per ear, number of kernels per row, 100 kernel weight and grain yield per plant using generations means analysis of two yellow maize hybrids (IL.292-06 × IL.565-06, IL.459-06 × IL.362-06) to detect epistasis and estimates of m, d, h, i, j and l parameters.

Results showed that the additive-dominance model was adequate to demonstrate the genetic variation and its importance in the inheritance of most studied traits.

Non-allelic gene interaction was operating in the control of genetic variation in most studied traits.

The signs of [h] and [l] were opposite in most studied traits for the two crosses.

Also, the inheritance of all studied traits was controlled by additive and non-additive genetic effects, but dominance gene effects play the major role in controlling the genetic variation of the most studied traits.

Suggesting that the improvement of those characters need intensive selection through later generations.

High phenotypic variations were composed of high genotypic variations and less of environmental variations, indicating the presence of high genetic variability for different traits and less influence of environment.

Highly significant heterosis relative to mid and better parents, respectively was found for all characters, correlated that with inbreeding depression for all traits.

Narrow sense heritability and genetic advance were low in most cases due to the dominance of non-additive gene action in controlling the genetic variation of the most studied traits.