Experimental design for integrated research projects to estimate genetic and numerous treatment effects

Abstract

There is a trend towards integrated research, where experimenters aim to make the best possible use of available resources, and individuals or institutions pool their expertise, make use of common resources and collaborate towards a common set of scientific goals. This allows a larger number of factors to be investigated, enabling the most influential or important ones to be identified as well as providing information on how the different factors interact or fit together. The issues involved in generating complex multi-factor designs are described and discussed, using as examples the entire series of experiments in the Australian Beef Cattle CRC and a simpler experiment to estimate genetic marker effects. An algorithm to generate suitable designs is presented. For the genetic marker experiment, the resultant designs were up to 10% more efficient than less sophisticated designs. In the case of the Beef Cattle CRC, achieving the same accuracy of estimating treatment and sire effects without sophisticated designs would have required 5-10% more animals, at a cost of $150,000-300,000 for purchase, transport and feeding of animals. If all additional costs of experimentation were included, the total savings from use of efficient designs were estimated to lie between $0.5 and $1 million.