The construction of a sheepmeat eating quality prediction model for Australian lamb.

Autor: Pannier L; Murdoch University, School of Agricultural Science, Western Australia 6150, Australia; Australian Cooperative Research Centre for Sheep Industry Innovation, Armidale 2350, New South Wales, Australia. Electronic address: l.pannier@murdoch.edu.au., Tarr G; The University of Sydney, School of Mathematics and Statistics, Sydney 2006, New South Wales, Australia., Pleasants T; Pleasants Analytics, Hamilton 3214, New Zealand., Ball A; Rural Analytics, Armidale NSW Australia, New South Wales 2350, Australia; Australian Cooperative Research Centre for Sheep Industry Innovation, Armidale 2350, New South Wales, Australia., McGilchrist P; University of New England, School of Environmental and Rural Science, Armidale 2350, New South Wales, Australia; Australian Cooperative Research Centre for Sheep Industry Innovation, Armidale 2350, New South Wales, Australia., Gardner GE; Murdoch University, School of Agricultural Science, Western Australia 6150, Australia; Australian Cooperative Research Centre for Sheep Industry Innovation, Armidale 2350, New South Wales, Australia., Pethick DW; Murdoch University, School of Agricultural Science, Western Australia 6150, Australia; Australian Cooperative Research Centre for Sheep Industry Innovation, Armidale 2350, New South Wales, Australia.
Jazyk: angličtina
Zdroj: Meat science [Meat Sci] 2025 Feb; Vol. 220, pp. 109711. Date of Electronic Publication: 2024 Nov 14.
DOI: 10.1016/j.meatsci.2024.109711
Abstrakt: The current sheep Meat Standards Australia (MSA) model is a pathways system designed to improve the overall eating quality of Australian lamb, yet it is unable to predict individual consumer-based eating quality scores for specific cuts. This paper describes the methodology of using consumer sensory scores to create an objective composite eating quality prediction score linked to individual quality grades for different cuts. This methodology accounts for objective carcass measures that are being commercialised within the industry, such as intramuscular fat percentage and a measure of lean meat yield percentage. The model demonstrated that through utilising these carcass grading traits, an eating quality prediction can be made with an accuracy of 75 % and 72 % for the grill and roast cooking method respectively, however individual consumer variation remained substantial. The model will allow the supply chain to allocate cuts to different marketing strategies (branding) based on their eating quality performance whilst also reducing the chances of consumers being offered products that do not meet their expectations.
Competing Interests: Declaration of competing interest None.
(Copyright © 2024. Published by Elsevier Ltd.)
Databáze: MEDLINE
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