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The variation in the eating quality of beef from different sexes and breed classes cannot be completely explained by carcass measurements

Published online by Cambridge University Press:  11 January 2016

S. P. F. Bonny*
Affiliation:
School of Veterinary and Life Sciences, Murdoch University, Murdoch, WA 6150, Australia INRA, UMR1213, Recherches sur les Herbivores, F-63122 Saint Genès Champanelle, France
J.-F. Hocquette
Affiliation:
INRA, UMR1213, Recherches sur les Herbivores, F-63122 Saint Genès Champanelle, France Clermont Université, VetAgro Sup, UMR1213, Recherches sur les Herbivores, F-63122 Saint Genès Champanelle, France
D. W. Pethick
Affiliation:
School of Veterinary and Life Sciences, Murdoch University, Murdoch, WA 6150, Australia
L. J. Farmer
Affiliation:
Agri-Food and Biosciences Institute, Newforge Lane, Belfast BT9 5PX, UK
I. Legrand
Affiliation:
Institut de l’Elevage, Service Qualite´ des Viandes, MRAL, 87060 Limoges Cedex 2, France
J. Wierzbicki
Affiliation:
Polish Beef Association Ul, Kruczkowskiego 3, 00-380 Warszawa, Poland
P. Allen
Affiliation:
Teagasac Food Research Centre, Ashtown, Dublin 15, Ireland
R. J. Polkinghorne
Affiliation:
431 Timor Road Murrurundi, NSW 2338, Australia
G. E. Gardner
Affiliation:
School of Veterinary and Life Sciences, Murdoch University, Murdoch, WA 6150, Australia
*
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Abstract

Delivering beef of consistent quality to the consumer is vital for consumer satisfaction and will help to ensure demand and therefore profitability within the beef industry. In Australia, this is being tackled with Meat Standards Australia (MSA), which uses carcass traits and processing factors to deliver an individual eating quality guarantee to the consumer for 135 different ‘cut by cooking methods’ from each carcass. The carcass traits used in the MSA model, such as ossification score, carcass weight and marbling explain the majority of the differences between breeds and sexes. Therefore, it was expected that the model would predict with eating quality of bulls and dairy breeds with good accuracy. In total, 8128 muscle samples from 482 carcasses from France, Poland, Ireland and Northern Ireland were MSA graded at slaughter then evaluated for tenderness, juiciness, flavour liking and overall liking by untrained consumers, according to MSA protocols. The scores were weighted (0.3, 0.1, 0.3, 0.3) and combined to form a global eating quality (meat quality (MQ4)) score. The carcasses were grouped into one of the three breed categories: beef breeds, dairy breeds and crosses. The difference between the actual and the MSA-predicted MQ4 scores were analysed using a linear mixed effects model including fixed effects for carcass hang method, cook type, muscle type, sex, country, breed category and postmortem ageing period, and random terms for animal identification, consumer country and kill group. Bulls had lower MQ4 scores than steers and females and were predicted less accurately by the MSA model. Beef breeds had lower eating quality scores than dairy breeds and crosses for five out of the 16 muscles tested. Beef breeds were also over predicted in comparison with the cross and dairy breeds for six out of the 16 muscles tested. Therefore, even after accounting for differences in carcass traits, bulls still differ in eating quality when compared with females and steers. Breed also influenced eating quality beyond differences in carcass traits. However, in this case, it was only for certain muscles. This should be taken into account when estimating the eating quality of meat. In addition, the coefficients used by the Australian MSA model for some muscles, marbling score and ultimate pH do not exactly reflect the influence of these factors on eating quality in this data set, and if this system was to be applied to Europe then the coefficients for these muscles and covariates would need further investigation.

Type
Research Article
Copyright
© The Animal Consortium 2016 

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