Editing Tree breeding (section)

==Optimisation==
Tree breeders try to improve their operation's efficiency by optimising tree breeding. Scientists develop tools aimed at improving the efficiency of tree breeding programmes. Optimising can mean adapting strategies and methods to certain species, groups of populations, structures of genetic variation and modes of inheritance of the important traits to obtain the highest benefit per unit of time. Optimising is usually carried out at the following levels: 
* breeding strategy (appropriate intensity of breeding, breeding population structure and size, plan for maintenance of genetic diversity),
* breeding methods ([[mating]] type, testing and selection methods, testing population size and time) and
* deployment methods of the genetically improved material ([[seed orchard]]s<ref>Lindgren, D. and Prescher, F. 2005. Optimal clone number for seed orchards with tested clones. Silvae Genetica 54: 80-92.</ref> and clonal forestry: genetic contribution, size).

Computer simulations, based on defined algorithms, are frequently used: either incorporating random variations (stochastic) or not (deterministic).{{cn|date=September 2024}}

Selection strategies have been compared for annual progress in long-term breeding at a given annual cost considering genetic gain, gene diversity, cost components, and time components. For Norway spruce it seems favourable to clone full sib families and then select based on clonal performance<ref>Danusevičius D & Lindgren D 2002. Efficiency of Selection Based on Phenotype, Clone and Progeny Testing in Long-term Breeding. Silvae Genetica 51:19-26.</ref> while for Scots pine a two-stage strategy seems best, first phenotypic pre-selection and then progeny-testing the selections.<ref>Danusevičius D & Lindgren D 2002. Two-stage selection strategies in tree breeding considering gain, diversity, time and cost. Forest Genetics. 9:145-157.</ref>