Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/14260
Title: The use of genomics in the management of livestock
Contributor(s): Kinghorn, Brian  (author)
Publication Date: 2012
Open Access: Yes
DOI: 10.1071/AN11092Open Access Link
Handle Link: https://hdl.handle.net/1959.11/14260
Abstract: Variation among animals exists at all stages of our livestock supply chains. In contrast, most manufacturing supply chains possess little, if any, unintended variation within each segment. This variation is generally an unwanted nuisance. However, when properly managed, it can provide opportunities to target multiple product end-points and turn-off dates in a dynamic manner. Moreover, optimal management can lead to high degrees of compliance with the needs of the processing segment of the supply chain and/or end-users. Management decisions can be divided into initial group formation (e.g. mating groups, feedlot entry groups) and ongoing changes to the management plan in the light of new information (including market forces, weather and genetic status of animals). In both cases, the best pattern of decision making depends, explicitly or implicitly, on the predicted effect of these decisions on future animal and processing performance. The present paper provides an overview of key factors that affect these predictions, and hence optimal management, and emphasises the potential role of genetic and genomic information for increasing focus and improving profitability in the beef supply chain.
Publication Type: Journal Article
Source of Publication: Animal Production Science, 52(2-3), p. 78-91
Publisher: CSIRO Publishing
Place of Publication: Australia
ISSN: 1836-5787
1836-0939
Fields of Research (FoR) 2008: 060408 Genomics
070203 Animal Management
Fields of Research (FoR) 2020: 310509 Genomics
300302 Animal management
Socio-Economic Objective (SEO) 2008: 830301 Beef Cattle
Socio-Economic Objective (SEO) 2020: 100401 Beef cattle
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article

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