Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/7038
Title: Increasing efficiency and adding value to Australian feedlot beef production through supply chain alliances
Contributor(s): Slack-Smith, Andrew (author); Thompson, John (supervisor); Griffith, Garry (supervisor)orcid 
Conferred Date: 2010
Copyright Date: 2009
Open Access: Yes
Handle Link: https://hdl.handle.net/1959.11/7038
Abstract: The Australian beef feedlot industry is inefficient in the way it sources livestock and allocates them to market endpoints resulting in out of specification costs for the carcass traits, carcass weight, external fat depth, marble score and quality grade resulting in more than a quarter of all Australian cattle failing to meet market specification (McKiernen 'et al.' 2007; Hobson 2009). These inefficiencies arise because no account is taken of the individual variation in an animal's initial conditions (i.e. at feedlot induction) or its potential to grow and deposit muscle, fat and bone throughout the feeding period. If initial composition and potential changes over the feeding period can be predicted with sufficient accuracy it would be possible to use sorting strategies to optimize the allocation of animals into groups to improve production efficiency and product consistency. Slaughtering groups of cattle with a common endpoint increases carcass uniformity (Tatum 1996; Trenkle 2001) and if managed correctly will increase the proportion of carcasses that meet market specifications at slaughter. Supply chain alliances can help resolve some of the inefficiencies of the traditional fragmented beef production systems and increase competitive performance by using information feedback systems and moving from a product and sales philosophy to a marketing philosophy (Kotler and Keller 2006). Supply chain alliances ultimately create and increase value along a supply network by identification of weaknesses and strengths within the system; and by generating increased value through identification and targeting of key performance indicators.
Publication Type: Thesis Masters Research
Field of Research Codes: 060412 Quantitative Genetics (incl Disease and Trait Mapping Genetics)
Rights Statement: Copyright 2009 - Andrew Slack-Smith
HERDC Category Description: T1 Thesis - Masters Degree by Research
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