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Title: Aligning price signals throughout the beef value chain to reflect consumer preferences by assigning economic weights to the Meat Standards Australia (MSA) model inputs
Contributor(s): Doljanin, Ivan Andrew (author); Thompson, John (supervisor); Griffith, Garry (supervisor)orcid ; Fleming, Euan (supervisor)
Conferred Date: 2013
Copyright Date: 2012
Open Access: Yes
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Abstract: The international measure of beef quality has largely been associated with the increased presence of intramuscular fat, also known as marbling. Using a palatability analysis critical control point (PACCP) process, consumer research collated by Meat Standards Australia (MSA) over the last 20 years has demonstrated the interconnectivity of pre and post-slaughter treatments with the traditional measurements in relation to consumer palatability scores. This has enabled consumer grading of beef - predicting the consumers' assessment of the specified meal as either 3 star (good everyday), 4 star (better than everyday), or 5 star (premium) eating quality for six cooking methods (grilling, roasting, stir-frying strips, slow cooking cubes, thin sliced, corned). A commercial dataset (n=3,735) was collated over an eight year period that described the eating quality and yield of beef product offered to consumers using the MSA grading matrix of eating quality and cooking method. This dataset created an opportunity to overlay financial terminology to the various steps of beef production by aligning consumer choice about the predicted quality of beef with the production input variables. This financial information can overlay the PACCP process with economic weights for the production input variables, thereby contributing toward the creation of its financial equivalent (FACCP) for the beef industry. Generating effective long-term financial modelling by accurately linking consumer demand to production variables would help to secure future investment. Ongoing investment in the industry is essential to keep beef a competitive source of protein. In this thesis, six measures of carcase yield - primal, trim, waste and fat, bone, loss, and saleable meat (SMY%) - were assessed to determine the most appropriate indicator of carcase value. The analysis found SMY% was the best indicator of carcase value, with a 0.85 coefficient of determination (R²). SMY% was followed by waste and fat, trim, primal, loss, and bone with an R² of 0.72, 0.69, 0.42, 0.29, 0.28 respectively.
Publication Type: Thesis Masters Research
Field of Research Codes: 140201 Agricultural Economics
Rights Statement: Copyright 2012 - Ivan Andrew Doljanin
HERDC Category Description: T1 Thesis - Masters Degree by Research
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Appears in Collections:Thesis Masters Research
UNE Business School

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