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1998, Number 3

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Vet Mex 1998; 29 (3)

Technology for the objective evaluation of animal carcasses

López PMG, Rubio LMS

Language: English/Spanish
References: 61
Page: 279-289
PDF size: 1164.74 Kb.


ABSTRACT

The knowledge of the differences among animal carcasses has been of great economic significance for the meat industry. The most valuable carcasses are those that meet the highest quality standards (most wanted by the consumers) and highest yields. To evaluate quality and yield it is required to estimate and measure some characteristics on the carcass. These measures can be evaluated objectively or subjectively. Within the objective methodology, various instruments have had a great deal of acceptance. These instruments are used to measure one or more of the following attributes like: amount of fat, bone and/or muscle. This study checked some of the most significant technologies such as ultrasound, electrical conductivity and video image analysis. The main advantage found for these methods is the extend to minimize human subjectivity in the process of measuring. However, their great disadvantages are the lack of applicability and the routine use in the conditions of the slaughterhouse. It is important that these instruments enable the user to register exact, precise and repetitive measures. The development and application of these evaluation techniques must concentrate efforts to develop the methodology at the slaughter line speed, and to present the data in a way that does not require interpretation.


REFERENCES

  1. Kauffman RG. Electronic evaluation of meat quality. Proceedings of the International Symposium of Electronic Evaluation of Meat in Support of Value-Based Marketing; 1991 March 27-28; West Lafayette (IN). West Lafayette (IN): Purdue University, 1991:99-221.

  2. Kempster AJ, Cuthbertson A, Harrington G. Carcass evaluation in livestock breeding, production and marketing. London (UK): Granada Publishing Limited, 1982.

  3. Sorensen SE. Danish work on automated carcass measurements with emphasis on beef classification. In: Brownlie LE, Hall WJA, Fabiansson SU, editors. The automated measurement of beef. Sydney, Australia: Australian Meat and Livestock Corp., 1989:75-80.

  4. Johnson ER, Ball B. Prediction of the commercial yield of beef from carcass destined for the Japanese market by using measurements from the carcass and non-carcass parts. Austr J Exp Agric 1989;29:489-496.

  5. Méndez MD, Rubio LMS. Importancia y necesidad de la evaluación de canales. Memorias del Curso de Actualización: Ganadería, Industria y Ciencia de la Carne en México; 1996 mayo 27-31; México (DF). México (DF): Facultad de Medicina Veterinaria y Zootecnia, UNAM, 1996:162-166.

  6. Jensen WK. Optical probes: single probes and classification system. Proceedings of the Symposium of Electronic Evaluation of Meat in Support of Value-Based Marketing; 1991 March 27-28; West Lafayette (IN). West Lafayette (IN): Purdue University, 1991:11-22.

  7. López-Palacios MG. Validación y aplicación de sensores de medición en procesos de transformación y conservación de alimentos (tesis de licenciatura). Cuautitlán, Edo. de México, México: Facultad de Estudios Superiores Cuautitlán. UNAM, 1995.

  8. Brethour JR. The repeatability and accuracy of ultrasound in measuring backfat of cattle. J Anim Sci 1992;70:1039-1044.

  9. Swatland HJ. Objective measurement of physical aspects of meat quality. Proceedings of the Reciprocal Meat Conference; 1989 June 11-14; Guelph, Canada. Guelph, Canada: American Meat Science Association, 1989;42:65-74.

  10. Sorensen SE. Possibilities for application of video image analysis in beef carcass classification. In: Lister D, editor. In vivo measurements of body composition in meat animals. London (UK): Elsevier Applied Science Publisher, 1984:113-122.

  11. Rubio LMS, Méndez MD, Noricumbo SJL. Evaluación de las canales de bovino (II). Acontecer Bovino 1998;3:4-8.

  12. Phillips D. Carcass classification in Australia. In: Brownlie LE, Hall WJA, Fabiansson, SU, editors. The automated measurement of beef. Sydney, Australia: Australian Meat and Livestock Corp., 1989:187-195.

  13. Cross HR, Gilliland DA, Durland PR, Seideman S. Beef carcass evaluation by use of a video image analysis system. J Anim Sci 1988;57:908-917.

  14. Cross HR, Smith GC, Murphey CE, Stiffer DM, Savell JW, Douglas LW. USDA beef grades: an evaluation of the accuracy and uniformity of their application. J Food Qual 1984;7:107-120.

  15. Cross HR, Belk KE. Objective measurement of carcass and meat quality. Meat Sci 1994;36:191-202.

  16. Allen P. New approaches to measuring body composition in live meat animals. In: Wood JD, Fisher AV, editors. Reducing fat in meat animals. London (UK): Elsevier Applied Science Publisher Limited, 1990:201-253.

  17. Cross HR, Rosenthal EM, Whittaker D, Savell JW. The objective measurement of value in meat animals. In: Brownlie LE, Hall WJA, Fabiansson, SU, editors. The automated measurement of beef. Sydney, Australia: Australian Meat and Livestock Corp., 1989:1-13.

  18. Jones SDM. Potential and available electronic technologies for quantitative carcass evaluation. Introductory comments. Proceedings of the Symposium of Electronic Evaluation of Meat in Support of Value-Based Marketing; 1991 March 27-28; West Lafayette (IN). West Lafayette (IN): Purdue University, 1991:7-9.

  19. Standal N. Establishment of computed tomography for farm animals. In: Lister D, editor. In vivo measurement of body composition in meat animals London (UK): Elsevier Applied Science Publisher, 1984:43-51.

  20. Robinson DE. Ultrasonic scanning technology. Sydney, Australia: Ultrasonics and Medical Technology Group, Division of Radiophysics, CSIRO, 1989.

  21. Bailey CM, Jensen J , Andersen BB. Ultrasonic scanning and body measurements for predicting composition and muscle distribution in young Holstein x Friesian bulls. J Anim Sci 1986;93:1337-1346.

  22. Ozutsumi K, Chikuni K, Koishikawa T, Kato S, Ito K, Kobayashy M, et al. Improved method for estimating m. longissimus thoracis fat and area in live beef cattle with a color scanning scope. Jpn J Zootech Sci 1988;59:916-921.

  23. Cross HR, Whittaker AD. The role of instrument grading in a beef value-based marketing system. J Anim Sci 1992;70:984-989.

  24. Swatland HJ. Physical measurements of meat quality: optical measurements. Pros and cons. Meat Sci 1994;36:251-259.

  25. Thane BT, Whittaker AD. Automated assessment of marbling in ultrasound images of beef animals. Paper No 7055. Proceedings for the International Summer Meeting of the ASAE; 1990 June 24-27; Columbus, Ohio. Columbus, Ohio: American Society of Agricultural Engineers, 1990:1-20.

  26. Lake RJW. Ultrasonics in meat quality. In: Brownlie LE, Hall WJA, Fabiansson SU, editors. The automated measurement of beef. Sydney, Australia: Australian Meat and Livestock Corp., 1989:157-163.

  27. Miles CA, Fursey GAJ, Fisher AV, Brown AJ. Predicting carcass composition from the speed of ultrasound in live Hereford bulls. Proceedings of the 80th Meeting of the British Society of Animal Production; 1983 March 21-23; Harrogate (UK). Harrogate (UK): British Society of Animal Production, 1983;36:526.

  28. Edwards JW, Cannell RC, Garrett RP, Savell JW, Cross HR, Longnecker MT. Using ultrasound, linear measurements and live fat thickness estimates to determine the carcass composition of market lambs. J Anim Sci 1989;67:3322-3330.

  29. Wood JD. Objective approaches to carcass classification. UK perspective. In: Brownlie LE, Hall WJA, Fabiansson SU, editors. The automated measurement of beef. Sydney, Australia: Australian Meat and Livestock Corp., 1989:67-73.

  30. Denoyelle C, Fisher A, Quilichini Y. Application in the meat industry of velocity of sound to predict beef carcass composition. Proceedings of the 4lst Annual International Congress of Meat Science and Technology; 1995 August 20-25; San Antonio (TX). San Antonio (TX): American Meat Science Association, 1995;2:189-190.

  31. Park B, Whittaker AD, Miller RK, Hale DS. Predicting intramuscular fat in beef longissimus muscle from speed of sound. J Anim Sci 1994;72:109-116,

  32. Thwaites CJ. Ultrasonic estimation of carcass composition. Austr Meat Res Committee Rev 1984;47:1-32.

  33. Greer EB, Most PC, Lowe TW, Giles LR. Accuracy of ultrasonic backfat tester in predicting carcass P2 fat depth from live pigs measurement and the effect on accuracy of mislocating the P2 site on the live pig. Austr J Exp Agric 1987;27:27-34.

  34. Simm G. The use of ultrasound to predict the carcass composition of live cattle- a review. Anim Breed Abstr 1983;51:55-65.

  35. Upton WH, Ryan DM, Mansfield BW, Sundstrom B. An evaluation of the Scanoprobe for measuring fat depth of beef cattle. Anim Prod Austr 1984;15:764 (Abstr.).

  36. Eveleigh CF, Thwaites CJ, Hassab PB, Paton PG, Smith JR, Upton WH. A note on the ability of three portable ultrasonic probes to predict backfat thickness in cattle. Anim Prod 1985;41:247-248.

  37. McLaren DG, Novakofski J, Parrett DF, Lo LL, Singh SD, Neumann KR, McKeith FK. A study of operator effects on ultrasonic measures of fat depth and longissimus muscle area in cattle, sheep and pigs. J Anim Sci 1991;69:54-66.

  38. Whittaker AD, Park BS, Thane BR, Miller RK, Savell JW. Principles of ultrasound and measurement of intramuscular fat. J Anim Sci 1992;70:942-952.

  39. Ferguson DM. Evaluation of the efficacy of real time ultrasound for predicting carcass lean in pork and beef preliminary results. In: Brownlie LE, Hall WJA, Fabiansson SU, editors. The automated measurement of beef. Sydney, Australia: Australian Meat and Livestock Corp., 1989:165-173.

  40. Hamlin KE, Green RD, Perkins TL, Cundiff LV, Miller MF. Real-time ultrasound measurement of fat thickness and longissimus muscle area: I. Description of age and weight effects. J Anim Sci 1995;73:1713-1724.

  41. Hamlin KE, Green RD, Cundiff LV, Wheeler TL, Dikeman ME. Real-time ultrasound measurement of fat thickness and longissimus muscle area: II. Relationship between real-time ultrasound and carcass retail yield. J Anim Sci 1995;73:1725-1734.

  42. Ophir J , Cespedes I, Ponnekanti E,YazdiY, Li X. Elastography: a quantitative method of imaging the elasticity of biological tissues. Ultrasonic Imaging 1991;13:111.

  43. Rubio-Lozano MS. Ultrasonic elastography to evaluate beef and pork quality (Ph. D. Dissertation). College Station, (TX): Texas A&M University, 1995.

  44. Allen DM. Automated grading of beef and pork carcasses. Proceedings of the Reciprocal Meat Conference; 1984 June 17-20; Lubock, Texas. Lubock, Texas: Texas Tech University, American Meat Science Association, 1984;37:94-98.

  45. Eldridge GA. Image analysis for meat and carcass description. In: Brownlie LE, Hall WJA, Fabiansson SU, editors. The automated measurement of beef. Sydney, Australia: Australian Meat and Livestock Corp., 1989:179-186.

  46. Fisher AV. New approaches to measuring fat in the carcasses of meat animals. In: Wood JD, Fisher AV, editors. Reducing fat in meat animals. London (UK): Elsevier Applied Science Publisher Limited, 1990.

  47. Cross HR, Gililand DA, Durland PR, Seideman S. Beef carcass evaluation by use of a video image analysis system. J Anim Sci 1983;57:908-917.

  48. Nielsen T. Vision image analysis for on-line colour measurements on pork loins. Proceedings of the 41st Annual International Congress of Meat Science and Technology; 1995 August 20-25; San Antonio (TX). San Antonio (TX): American Society of Animal Science, 1995;2:185-186.

  49. Ferguson DM, Thompson JM, Barrett-Lennard D, Sorensen B. Prediction of beef carcass yield using whole carcass VIASCAN. Proceedings of the 41st Annual Inter national Congress of Meat Science and Technology; 1995 August 20-25; San Antonio (TX). San Antonio (TX): American Society of Animal Science, 1995;2:183-184.

  50. Hopkins DL. An evaluation of the Hennessy grading probe for measuring fat depth in beef carcasses. Austr J Exp Agric 1989;29:781-784.

  51. Swatland HJ, Anantharayanan SP, Goldenberg AA. A review of probes and robots; implementing new technologies in meat evaluation. J Anim Sci 1994;72:1475-1486.

  52. Akridge JT, Brorse BW, Wipker LD, Forrest JC, Kuei CH, Schinckel AP. Evaluation of alternative techniques to determine pork carcass value. J Anim Sci 1992;70:18-28.

  53. Gwartney BL, Calkins CR, Lin RS, Forrest JC, Parkhurst AM, Lemnager RP. Electromagnetic scanning of beef quarter to predict carcass and primal lean content. J Anim Sci 1994;72:2836-2842.

  54. Berg EP, Forrest JC, Thomas DL, Nusbaum N, Kauffman RG. Electromagnetic scanning to predict lamb carcass composition. J Anim Sci 1994;72:1728-1736.

  55. Meseck NL, Gwartney BL, Calkins CR, Miller PS. Influence of sample orientation on prediction of fresh ham lean content by electromagnetic scanning. J Anim Sci 1997;75:3169-3173.

  56. Glodek P. The measurement of body composition. Opportunities and requirements in animal production. In: Lister D, editor. In vivo measurements of body composition in meat animals. London (UK): Elsevier Applied Science Publisher, 1984:8-21.

  57. Robelin J. Prediction of body composition in vivo by dilution technique. In: Lister D, editor. In vivo measurements of body composition in meat animals. London (UK): Elsevier Applied Science Publisher, 1984:106-112.

  58. Lake R. Ultrasonic evaluation: image analysis and industrial applications. Proceedings of the Symposium of Electronic Evaluation of Meat in Support of Value-Based Marketing; 1991 March 27-28; West Lafayette (IN). West Lafayette (IN): Purdue University, 1991:25-47.

  59. Marchello MJ, Slanger WD. Use of biolectrical impedance to predict leanness of Boston bulls. J Anim Sci 1992;70:3443-3450.

  60. Berg EP, Marchello MJ. Bioelectrical impedance analysis for the prediction of fat-free mass in lambs and lamb carcasses. J Anim Sci 1994;72:322-329.

  61. Marchello MJ, Slanger WD. Bioelectrical impedance can predict skeletal muscle and fat-free skeletal muscle of beef cows and their carcasses. J Anim Sci 1994;72:3118-3123.




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