Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2015 | nr 4, CD 3 | 9922--9929
Tytuł artykułu

The Objective Evaluation of Beef Carcasses

Warianty tytułu
Języki publikacji
The objective evaluation of beef carcasses. WSVIA (whole side video image analysis) is a technology for the evaluation of the lateral parts of the carcass, which can be applied to industrial and commercial lines. For various reasons existing method of the objective assessment of beef carcass have limitation for scientific and commercial applications. Currently used method of classification of beef carcasses in the EUROP system is biased of an subjective assessment of the classifier. WSVIA is the method that can improve the precision and accuracy of beef carcasses evaluation. Consumption of beef has decreased over the recent years and the quality of meat which mainly originates from the dairy cattle is unsatisfactory for the consumers. Additional reason of lowering beef consumption is the high price of beef and the relatively low profitability of cattle fattening. Improved precision and accuracy of beef carcasses evaluation through the consolidation of the final product can guarantee the growth of both beef producers and consumer satisfaction and induce growth both demand and production of beef on the basis of terminal crossbreeds.(original abstract)
Słowa kluczowe
Opis fizyczny
  • Warsaw University of Life Sciences
  • Warsaw University of Life Sciences
  • Warsaw University of Life Sciences
  • Polish Association of Beef Cattle Producers
  • Polish Association of Beef Cattle Producers
  • [1] Augustini, C., Dobrowolski, A., Spindler, M. 1997. Zur Videobildauswertung an Schlachtkörpern von Jungbullen. Mitteilungsblatt BAFF, der Bundesanstalt für Fleischforschung, 36, 117-122.
  • [2] Belk, K. E., R. C. Cannell, J. D. Tatum, And G. C. Smith. 1997. Video imaging systems for composition and quality. Paper presented at the Meat Industry Research Conf., October 28, Chicago, IL.
  • [3] Belk, K. E., J. A. Scanga, J. D. Tatum, J. W. Wise, G. C. Smith. 1998. Simulated instrument augmentation of USDA yield grade application to beef carcasses. J. Anim. Sci. 76:522.
  • [4] Belk, K. E., M. H. George, J. D. Tatum, G. G. Hilton, R. K. Miller, M. Koohmaraie, J. O. Reagan, and G. C. Smith. 2001. Evaluation of the Tendertec beef grading instrument to predict the tenderness of steaks from beef carcasses. J. Anim. Sci. 79:688.
  • [5] Borggaard, C., Madsen, N. T., and Thodberg, H. H. 1996. In-line image analysis in the slaughter industry, illustrated by Beef Carcass Classification. Meat Science, 43, S151-S163.
  • [6] Branscheid, W., Dobrowolski, A., Spindler, M., & Augustini, C. 1999. Application of video image analysis in grading of cattle - Instrumental determination of the slaughter value. Fleischwirtschaft International, 99, 12-15.
  • [7] Brinkmann, D., & Eger, H. 2008. Ensure objectivity from stable to table. Fleischwirtschaft International, 2008, 48-52.
  • [8] Cannell, R. C., Tatum, J. D., Belk, K. E., Wise, J. W., Clayton, R. P., Smith, G. C. 1999. Dual-component video image analysis system (VIASCAN) as a predictor of beef carcass red meat yield percentage and for augmenting application of USDA yield grades. Journal of Animal Science, 77, 2942-2950.
  • [9] Cannell, R. C., Belk, K. E., Tatum, J. D., Wise, J. W., Champain, P. L., Scanga, J. A., ET AL. 2002. Online evaluation of a commercial video image analysis system (computer vision system) to predict beef carcass red meat yield and for augmenting the assignment of USDA yield grades. Journal of Animal Science, 80, 1195-1201.
  • [10] Cegiełka A. 2013. Przegląd rozwoju i wykorzystania analizy obrazu wideo (VIA) do oceny tusz wołowych jako alternatywy wobec systemu EUROP i innych subiektywnych systemów. Gospodarka. Gospodarka mięsna. 01:22-23.
  • [11] Craigie C. R., E. A. Navajas, R. W. Purchas, C. A. Maltin, L. Bünger, S. O. Hoskin, D. W. Ross, S. T. Morris, R. Roehe. 2012. A review of the development and use of video image analysis (VIA) for beef carcass evaluation as an alternative to the current EUROP system and other subjective systems. Meat science. 92, 307-318.
  • [12] Cross, H. R., Gilliland, D. A., Durland, P. R., and Seideman, S. 1983. Beef carcass evaluation by use of a video image analysis system. Journal of Animal Science, 57, 908-917.
  • [13] Cross, H. R., G. C. Smith, C. E. Murphey, D. M. Stiffler, L. W. Douglas, and J. W. Savell. 1984. USDA beef grades: An evaluation of the accuracy and uniformity of their application. J. Food Qual. 7:107.
  • [14] Cross, H. R. and A. D. Whittaker. 1992. The role of instrument grading in a beef value-based marketing system. J. Anim. Sci. 70:984.
  • [15] Cross, H. R. and K. E. Belk. 1994. Objective measurements of carcass and meat quality. Meat Sci. 36:191.
  • [16] Dolezal, H. G., G. C. Smith, B. W. Berry, and A. L. Carpenter. 1982. Comparison of subcutaneous fat thickness, marbling, and quality grade for predicting palatability of beef. J. Food. Sci. 47:397.
  • [17] Eldridge, G. A. (1994). New technologies - Video image analysis. Proceedings of the Australian Society of Animal Production, 20, 42-43.
  • [18] European Community 1991. Council Regulation (EEC) no 1026/91 of 22 April 1991amending regulation (EEC) no 1208/81 determining the Community scale for the classification of carcasses of adult bovine animals. Official Journal of the European Communities, 106/L, 2-3.
  • [19] European Community (2003). Commission Regulation (EC) no 1215/2003 of 7 July2003 amending Regulation (EEC) no 344/91 laying down detailed rules for applying Council Regulation (EEC) no 1186/90 to extend the scope of the community scale for the classification of carcasses of adult bovine animals. Official Journal of the European Communities, 169/L, 32-36.
  • [20] Ferguson, D. M. 2004. Objective on-line assessment of marbling: A brief review. Aust. J. Exper. Agr. 44:681.
  • [21] George, M. H., J. D. Tatum, H. G. Dolezal, J. B. Morgan, J. W. Wise, C. R. Calkins, T. Gordon, J. O. Reagen, and G. C. Smith. 1997. Comparison of USDA quality grade with Tendertec for the assessment of beef palatability. J. Anim. Sci. 75:1538.
  • [22] Jennings, T. G., B. W. Beery, A. L. Joseph. 1978. Influence of fat thickness, marbling, and length of aging on beef palatability and shelf-life characteristics. J. Anim. Sci. 46:658.
  • [23] Jones, S. D. M., D. Lang, A. K. W. Tong, and W. M. Robertson. 1992. A commercial evaluation of video image analysis in the grading of beef carcasses. Proc. 38th Int. Cong. Meat Sci. and Tech. 38:915.
  • [24] Jones, S. D., R. J. Richmond, and W. M. Robertson. 1995. Beef carcass grading or classification using video image analysis. Proc. Recip. Meat Conf. 48:81.
  • [25] Jones, S. D. M., A. K. W. Tong, W. M. Robertson. 1997. Technologies for objective grading/assessment. Proc. 50th Recip. Meat Conf. 50:106.
  • [26] Madsen, N. T., Thodberg, H. H., FIIG, T., Ovesen, E. 1996. BCC-2 for objective beef carcass classification and prediction of carcass composition. Proceedings 42nd International Congress of Meat Science and Technology, Lillehammer, Norway. (pp. 244-245).
  • [27] Mcbee, J. L., JR. and J. A. Wailes. 1967. Influence of marbling and carcass grade on the physical and chemical characteristics of beef. J. Anim. Sci. 26:701.
  • [28] National Cattlemen's Beef Association. 2002. Meeting summary: National beef instrument assessment plan II: Focus ontenderness. Funded by The Beef Check off. Centennial, CO.
  • [29] National Cattlemen's Beef Association. 2007. National beef instrument assessment plan (NBIAP) III meeting: The next five years. Funded by The Beef Check off. Centennial, CO.
  • [30] National Livestock and Meat Board. 1994. National beef instrument assessment plan - 1994.
  • National Livestock and Meat Board. Chicago, IL. [31] Pawelec A. 2010. System EUROP klasyfikacja tusz zwierząt rzeźnych. Przemysł spożywczy. 03:12- 14.
  • [32] Seredyn K. 2006. Wartość rzeźna tusz wołowych w Polsce i ich pozycja na rynku wspólnotowym.
  • [33] Shackelford, S. D., Wheeler, T. L., Koohmaraie, M. 1998. Coupling of image analysis and tenderness classification to simultaneously evaluate carcass cutability, longissimus area, subprimal cut weights, and tenderness of beef. Journal of Animal Science, 76, 2631-2640.
  • [34] Shackelford, S. D., Wheeler, T. L., & Koohmaraie, M. 2003. On-line prediction of yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score using the MARC beef carcass image analysis system. Journal of Animal Science, 81, 150-155.
  • [35] Smith, G. C., J. W. Savell, H. G. Dolezal, T. G. Field, D. R. Gill, D. B. Griffin, D. S. Hale, J. B. Morgan, M. Smith, C. Lambert, and G. Cowman. 1995. Improving the quality, consistency, competitiveness and market-share of beef - the final report of the second blueprint for total quality management in the fed-beef (slaughter steer/heifer) industry - 1995. Colorado State University, Fort Collins, CO, Texas A&M University, College Station, TX, and Oklahoma State University, Stillwater, OK.
  • [36] Sørensen, S. E. 1984. Possibilities for application of video image analysis. In D. Lister (Ed.). In vivo measurement of body composition in meat animals (pp. 113-122). London and New York: Elsevier Applied Science.
  • [37] Sørensen, S. E., Klastrup, S., & PEtersen, F. 1988. Classification of bovine carcasses by means of video image analysis and reflectance probe measurements. Proceedings of the 34th International Congress of Meat Science and Technology. (pp. 635-638).
  • [38] Steiner, R., Wyle, A. M., Vote, D. J., Belk, K. E., Scanga, J. A., Wise, J. W., ET AL. 2003. Realtime augmentation of USDA yield grade application to beef carcasses using video image analysis. Journal of Animal Science, 81, 2239-2246.
  • [39] Tatum, J. D., G. C. Smith, B. W. Berry,C. E. Montgomery, F. L. Williams, and Z. L. Carpenter. 1980. Carcass characteristics, time on feed, and cooked beef palatability attributes. J. Anim. Sci. 50:833.
  • [40] Wassenberg, R. L., Allend. M., Kemp, K. E. 1986. Video image analysis prediction of total kilograms and percent primal lean and fat yield of beef carcasses. Journal of Animal Science, 62, 1609- 1616.
  • [41] Wyle, A. M., D. J. Vote, D. L. Roeber, R. C. Canel, K. E. Belk, J. A. Scanga, M. Goldberg, J. D. Tatum, and G. C. Smith. 2003. Effectiveness of the SmartMV prototype BeefCam System to sort beef carcasses into expected palatability groups. J. Anim. Sci. 81:441.
  • [42] Vote, D. J. 2003. Dissertation: Instrument grading of beef. Colorado State University, Department of Animal Sciences. Fort Collins, CO.
Typ dokumentu
Identyfikator YADDA

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.