Original Articles

Program for the deterministic modelling of genetic gains of tree breeding and seed and clone production strategies


Abstract

A 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 of ramets 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 of the 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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