Deployment to plantations of numbers and proportions of clones with special emphasis on maximizing gain at a constant diversity

Abstract

The value of a mixture of genetic entries present in different proportions is defined. A measure of the disadvantage of reduced diversity is defined as the sum of the squares of the proportions of the different entries. An algorithm for maximizing genetic gain of the mixture under the constraint of a constant disadvantage is developed. The optimal deployment strategy is one that lets the proportion of the genetic entries be linearly dependent on their genetic value. By use of rankits as entries for genetic values, optimal solutions for deployment were calculated for a range of values of available entries (from 10 to 5,000) and preset diversity-related disadvantage-factors (the preset values correspond to mixtures of between 2 and 100 entries in identical proportions). The values are tabulated so they can be used by breeders. The superiority of the proposed strategy increases with the proportion of the available entries which are selected. In the situation that around half would have been selected if truncation selection was applied, the improvement in genetic gain compared to classical truncation selection is up to 18%. Thus, considerable improvements in gain are possible without any sacrifice in diversity. Applications are discussed with particular reference to clonal forestry.