of genetic gains did deviate (in both directions) from those realised, although these deviations may be explained as functions of imperfect modelling. On average, however, the predicted genetic gains for tree volume over three generations was 13% between generations, whereas the average realised genetic gain in the genetic gains trial was 14%. It is therefore assumed that the E. grandis breeding population is indeed performing as expected, following classical tree breeding assumptions.
Genetic variances and heritabilities of a 66-month old cloned Eucalyptus grandis breeding population of families, derived from open-pollinated selections, were estimated. The genetic variance for the growth traits was largely additive genetic variance, whereas the proportion of non-additive genetic variance was notably higher for stem form and disease tolerance. A notably larger proportion of non-additive variance was observed for the growth traits and stem form among the F 2 families. This is probably due to the reduction in additive variance through selection for general combining ability for these traits in the previous generations. No selection for disease took place in earlier generations and the proportion of non-additive genetic variance for this trait remains approximately the same for families of different generations.
SYNOPSISA deterministic modelling algorithm was developed for the prediction of genetic gains of six breeding and 11 (seed and clone) production strategies. This algorithm can run iteratively over ranges of parameters which affect the genetic gains. These parameters are the selection intensities, number of families, family sizes, number oframets per clone, duration of the strategy and heritability ranges. The genetic gains per year over these ranges are presented graphically by the algorithm. In assessing the graphs of.some ofthe above parameters, it is apparent that commonly used selection intensity tables can result in an uneven transition in predicted genetic gain when moving from the finite to the infinite selection intensity table.
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