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Review: The variability of the eating quality of beef can be reduced by predicting consumer satisfaction
Journal article   Peer reviewed

Review: The variability of the eating quality of beef can be reduced by predicting consumer satisfaction

S.P.F. Bonny, J.-F. Hocquette, D.W. Pethick, I. Legrand, J. Wierzbicki, P. Allen, L.J. Farmer, R.J. Polkinghorne and G.E. Gardner
animal, Vol.12(11), pp.2434-2442
2018
DOI: https://doi.org/10.1017/S1751731118000605
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Abstract

The Meat Standards Australia (MSA) grading scheme has the ability to predict beef eating quality for each ‘cut×cooking method combination’ from animal and carcass traits such as sex, age, breed, marbling, hot carcass weight and fatness, ageing time, etc. Following MSA testing protocols, a total of 22 different muscles, cooked by four different cooking methods and to three different degrees of doneness, were tasted by over 19 000 consumers from Northern Ireland, Poland, Ireland, France and Australia. Consumers scored the sensory characteristics (tenderness, flavor liking, juiciness and overall liking) and then allocated samples to one of four quality grades: unsatisfactory, good-every-day, better-than-every-day and premium. We observed that 26% of the beef was unsatisfactory. As previously reported, 68% of samples were allocated to the correct quality grades using the MSA grading scheme. Furthermore, only 7% of the beef unsatisfactory to consumers was misclassified as acceptable. Overall, we concluded that an MSA-like grading scheme could be used to predict beef eating quality and hence underpin commercial brands or labels in a number of European countries, and possibly the whole of Europe. In addition, such an eating quality guarantee system may allow the implementation of an MSA genetic index to improve eating quality through genetics as well as through management. Finally, such an eating quality guarantee system is likely to generate economic benefits to be shared along the beef supply chain from farmers to retailors, as consumers are willing to pay more for a better quality product.

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24 Times Cited - Web of Science

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Collaboration types
Domestic collaboration
International collaboration
Citation topics
3 Agriculture, Environment & Ecology
3.51 Dairy & Animal Sciences
3.51.206 Meat Quality
Web Of Science research areas
Agriculture, Dairy & Animal Science
Veterinary Sciences
ESI research areas
Plant & Animal Science
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