Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-12-01T00:11:56.107Z Has data issue: false hasContentIssue false
  • English
  • Français

Biochemical measurements of beef are a good predictor of untrained consumer sensory scores across muscles

Published online by Cambridge University Press:  23 September 2014

S. P. F. Bonny ,
G. E. Gardner ,
D. W. Pethick ,
I. Legrand ,
R. J. Polkinghorne  and
J. F. Hocquette
S. P. F. Bonny
Affiliation:
School of Veterinary and Life Sciences, Murdoch University, 90 South St, Murdoch, WA 6150, Australia 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
G. E. Gardner*
Affiliation:
School of Veterinary and Life Sciences, Murdoch University, 90 South St, Murdoch, WA 6150, Australia
D. W. Pethick
Affiliation:
School of Veterinary and Life Sciences, Murdoch University, 90 South St, Murdoch, WA 6150, Australia
I. Legrand
Affiliation:
Institut de l’Elevage, Service Qualiteí des Viandes, MRAL, 87060 Limoges Cedex 2, France
R. J. Polkinghorne
Affiliation:
Polkinghornes Pty Ltd, 431 Timor Road, Murrurundi, NSW 2338, Australia
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
*
†E-mail: [email protected]
Get access

Abstract

The ability of the biochemical measurements, haem iron, intramuscular fat (IMF%), moisture content, and total, soluble and insoluble collagen contents, to predict untrained consumer sensory scores both across different muscles and within the same muscle from different carcasses were investigated. Sensory scores from 540 untrained French consumers (tenderness, flavour liking, juiciness and overall liking) were obtained for six muscles; outside (m. biceps femoris), topside (m. semimembranosus), striploin (m. longissimus thoracis), rump (m. gluteus medius), oyster blade (m. infraspinatus) and tenderloin (m. psoas major) from each of 18 French and 18 Australian cattle. The four sensory scores were weighted and combined into a single score termed MQ4, which was also analysed. All sensory scores were highly correlated with each other and with MQ4. This in part reflects the fact that MQ4 is derived from the consumer scores for tenderness, juiciness, flavour and overall liking and also reflects an interrelationship between the sensory scores themselves and in turn validates the use of the MQ4 term to reflect the scope of the consumer eating experience. When evaluated across the six different muscles, all biochemical measurements, except soluble collagen, had a significant effect on all of the sensory scores and MQ4. The average magnitude of impact of IMF%, haem iron, moisture content, total and insoluble collagen contents across the four different sensory scores are 34.9, 5.1, 7.2, 36.3 and 41.3, respectively. When evaluated within the same muscle, only IMF% and moisture content had a significant effect on overall liking (5.9 and 6.2, respectively) and flavour liking (6.1 and 6.4, respectively). These results indicate that in a commercial eating quality prediction model including muscle type, only IMF% or moisture content has the capacity to add any precision. However, all tested biochemical measurements, particularly IMF% and insoluble collagen contents, are strong predictors of eating quality when muscle type is not known. This demonstrates their potential usefulness in extrapolating the sensory data derived from these six muscles to other muscles with no sensory data, but with similar biochemical parameters, and therefore reducing the amount of future sensory testing required.

Keywords

beefbiochemistrymuscleuntrained consumerssensory scores
Type
Research Article
Information
animal , Volume 9 , Issue 1 , January 2015 , pp. 179 - 190
Copyright
© The Animal Consortium 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Allais, S, Levéziel, H, Payet-Duprat, N, Hocquette, JF, Lepetit, J, Rousset, S, Denoyelle, C, Bernard-Capel, C, Journaux, L, Bonnot, A and Renand, G 2010. The two mutations, Q204X and nt821, of the myostatin gene affect carcass and meat quality in young heterozygous bulls of French beef breeds. Journal of Animal Science 88, 446–454.CrossRefGoogle ScholarPubMed
Bailey, AJ 1985. The role of collagen in the development of muscle and its relationship to eating quality. Journal of Animal Science 60, 1580–1587.CrossRefGoogle Scholar
Bailey, AJ, Paul, RG and Knott, L 1998. Mechanisms of maturation and ageing of collagen. Mechanisms of Ageing and Development 106, 1–56.CrossRefGoogle ScholarPubMed
Barlocco, N, Vadell, A, Ballesteros, F, Galietta, G and Cozzolino, D 2006. Predicting intramuscular fat, moisture and Warner-Bratzler shear force in pork muscle using near infrared reflectance spectroscopy. Animal Science 82, 111–116.CrossRefGoogle Scholar
Chriki, S, Gardner, GE, Jurie, C, Picard, B, Micol, D, Brun, JP, Journaux, L and Hocquette, JF 2012. Cluster analysis application identifies muscle characteristics of importance for beef tenderness. BMC Biochemistry 13, 29.CrossRefGoogle ScholarPubMed
Dransfield, E, Martin, JF, Bauchart, D, Abouelkaram, S, Lepetit, J, Culioli, J, Jurie, C and Picard, B 2003. Meat quality and composition of three muscles from French cull cows and young bulls. Animal Science 76, 387–399.CrossRefGoogle Scholar
Garmyn, AJ, Hilton, GG, Mateescu, RG, Morgan, JB, Reecy, JM, Tait, RG, Beitz, DC, Duan, Q, Schoonmaker, JP, Mayes, MS, Drewnoski, ME, Liu, Q and VanOverbeke, DL 2011. Estimation of relationships between mineral concentration and fatty acid composition of longissimus muscle and beef palatability traits. Journal of Animal Science 89, 2849–2858.CrossRefGoogle ScholarPubMed
Hornsey, HC 1956. The colour of cooked cured pork. I. Estimation of the nitric oxide-haem pigments. Journal of the Science of Food and Agriculture 7, 534–540.CrossRefGoogle Scholar
Hornstein, I and Crowe, PF 1960. Meat flavor chemistry, flavor studies on beef and pork. Journal of Agricultural and Food Chemistry 8, 494–498.CrossRefGoogle Scholar
Jeremiah, LE and Martin, AH 1981. Intramuscular collagen content and solubility: their relationship to tenderness and alteration by post mortem aging. Canadian Journal of Animal Science 61, 53–61.CrossRefGoogle Scholar
Jurie, C, Picard, B, Hocquette, J-F, Dransfield, E, Micol, D and Listrat, A 2007. Muscle and meat quality characteristics of Holstein and Salers cull cows. Meat Science 77, 459–466.CrossRefGoogle ScholarPubMed
Kelman, KR, Pannier, L, Pethick, DW and Gardner, GE 2014. Selection for lean meat yield in lambs reduces indicators of oxidative metabolism in the longissimus muscle. Meat Science 96, 1058–1067.CrossRefGoogle ScholarPubMed
Legrand, I, Hocquette, J-F, Polkinghorne, RJ and Pethick, DW 2012. Prediction of beef eating quality in France using the Meat Standards Australia system. Animal 7, 524–529.CrossRefGoogle ScholarPubMed
Legrand, I, Hocquette, JF, Polkinghorne, RJ and Pethick, DW 2013. Prediction of beef eating quality in France using the Meat Standards Australia system. Animal 7, 524–529.CrossRefGoogle ScholarPubMed
Lengyel, Z, Husvéth, F, Polgár, P, Szabó, F and Magyar, L 2003. Fatty acid composition of intramuscular lipids in various muscles of Holstein-Friesian bulls slaughtered at different ages. Meat Science 65, 593–598.CrossRefGoogle ScholarPubMed
Light, N, Champion, AE, Voyle, C and Bailey, AJ 1985. The role of epimysial, perimysial and endomysial collagen in determining texture in six bovine muscles. Meat Science 13, 137–149.CrossRefGoogle ScholarPubMed
Listrat, A and Hocquette, J-F 2004. Analytical limits of total and insoluble collagen content measurements and of type I and III collagen analysis by electrophoresis in bovine muscles. Meat Science 68, 127–136.CrossRefGoogle ScholarPubMed
Lorenzen, CL, Miller, RK, Taylors, JF, Neely, TR, Tatum, JD, Wise, JW, Buyek, MJ, Reagan, JO and Savell, JW 2003. Beef customer satisfaction: trained sensory panel ratings and Warner-Bratzler shear force values. Journal of Animal Science 81, 143–149.CrossRefGoogle ScholarPubMed
Lyford, C, Thompson, J, Polkinghorne, R, Miller, M, Nishimura, T, Neath, K, Allen, P and Belasco, E 2010. Is willingness to pay (WTP) for beef quality grades affected by consumer demographics and meat consumption preferences? Australasian Agribusiness Review 18, 1–15.Google Scholar
Morgan, JB, Savell, JW, Hale, DS, Miller, RK, Griffin, DB, Cross, HR and Shackelford, SD 1991. National beef tenderness survey. Journal of Animal Science 69, 3274–3283.CrossRefGoogle ScholarPubMed
O’Quinn, TG, Brooks, JC, Polkinghorne, RJ, Garmyn, AJ, Johnson, BJ, Starkey, JD, Rathmann, RJ and Miller, MF 2012. Consumer assessment of beef strip loin steaks of varying fat levels. Journal of Animal Science 90, 626–634.CrossRefGoogle ScholarPubMed
Pannier, L, Gardner, GE, Pearce, KL, McDonagh, M, Ball, AJ, Jacob, RH and Pethick, DW 2014. Associations of sire estimated breeding values and objective meat quality measurements with sensory scores in Australian lamb. Meat Science 96, 1076–1087.CrossRefGoogle ScholarPubMed
Pflanzer, SB and de Felício, PE 2011. Moisture and fat content, marbling level and color of boneless rib cut from Nellore steers varying in maturity and fatness. Meat Science 87, 7–11.CrossRefGoogle ScholarPubMed
Polkinghorne, RJ and Thompson, JM 2010. Meat standards and grading: a world view. Meat Science 86, 227–235.CrossRefGoogle ScholarPubMed
Polkinghorne, R, Thompson, JM, Watson, R, Gee, A and Porter, M 2008. Evolution of the Meat Standards Australia (MSA) beef grading system. Australian Journal of Experimental Agriculture 48, 1351–1359.CrossRefGoogle Scholar
Purslow, PP 2005. Intramuscular connective tissue and its role in meat quality. Meat Science 70, 435–447.CrossRefGoogle ScholarPubMed
Renand, G, Picard, B, Touraille, C, Berge, P and Lepetit, J 2001. Relationships between muscle characteristics and meat quality traits of young Charolais bulls. Meat Science 59, 49–60.CrossRefGoogle ScholarPubMed
Riley, DG, Johnson, DD, JrChase, CC, West, RL, Coleman, SW, Olson, TA and Hammond, AC 2005. Factors influencing tenderness in steaks from Brahman cattle. Meat Science 70, 347–356.CrossRefGoogle ScholarPubMed
Schonfeldt, HC and Strydom, PE 2011. Effect of age and cut on tenderness of South African beef. Meat Science 87, 206–218.CrossRefGoogle ScholarPubMed
Thompson, J 2004. The effects of marbling on flavour and juiciness scores of cooked beef, after adjusting to a constant tenderness. Australian Journal of Experimental Agriculture 44, 645–652.CrossRefGoogle Scholar
Thompson, J, Polkinghorne, R, Gee, A, Motiang, D, Strydom, P, Mashau, M, Ng’ambi, J, deKock, R and Burrow, H 2010. Beef palatability in the Republic of South Africa: implications for niche-marketing strategies. In ACIAR Technical Reports, pp. 1–56. Australian Centre for International Agricultural Research (ACIAR), Canberra, ACT, Australia.Google Scholar
Torrescano, G, Sánchez-Escalante, A, Giménez, B, Roncalés, P and Beltrán, JA 2003. Shear values of raw samples of 14 bovine muscles and their relation to muscle collagen characteristics. Meat Science 64, 85–91.CrossRefGoogle ScholarPubMed
Turkki, PR and Campbell, AM 1967. Relation of phospholipids to other tissue components in two beef muscles. Journal of Food Science 32, 151–154.CrossRefGoogle Scholar
Verbeke, W, Van Wezemael, L, de Barcellos, MD, Kügler, JO, Hocquette, J-F, Ueland, Ø and Grunert, KG 2010. European beef consumers’ interest in a beef eating-quality guarantee: insights from a qualitative study in four EU countries. Appetite 54, 289–296.CrossRefGoogle Scholar
Watson, R, Gee, A, Polkinghorne, R and Porter, M 2008. Consumer assessment of eating quality – development of protocols for Meat Standards Australia (MSA) testing. Australian Journal of Experimental Agriculture 48, 1360–1367.CrossRefGoogle Scholar