Abstract
Genetic evaluations are predicated on routine access to large quantities of data on a range of performance traits from individual animals, their genetic relationships, as well as data on factors other than additive genetic merit that influence phenotypic performance. Based on the well-established breeding pyramid, far more commercial animals generally exist relative to seedstock animals. Despite this, performance data from commercial animals is not always used in genetic evaluations. These data are not utilized for many reasons such as 1) no individual animal data actually exists or is recorded in a useful format from commercial animals, 2) no ancestry is recorded, 3) systematic environmental effects are not recorded, 4) infrastructure is not in place to collate such data, and 5) issues relating to data ownership, governance, and use. Given the end customer of elite germplasm is the commercial producer, systems that only consider seedstock data in the genetic evaluations are sub-optimal for several reasons: 1) assumes a genetic correlation of one between performance in seedstock herds and performance in commercial settings, 2) fails to benefit from additional (commercial) data to increase the accuracy of selection, 3) omits data for traits that are profit drivers for commercial enterprises, and 4) misses an opportunity to provide commercial producers with genetic-based management tools. Two contrasting case studies relating to beef genetic evaluations are explored: 1) US where generally only data from seedstock animals are used and many different genetic evaluations and breeding objectives exist for the multitude of breeds, and 2) Ireland which has a national database of all bovines and uses data from both seedstock and commercial producers to generate multi-breed genetic evaluations which are then applied to and disseminated to all bovines in the country both as breeding and management support indexes.