Loya-Olguín JL, Zinn RA, Aguirre-Ortega J, Gómez-Danés AA, Ramírez-Ramírez JC, Loya-Olguín F, Ulloa-Castañeda RR

Language: Spanish
References: 37
Page: 48-58
PDF size: 361.61 Kb.

ABSTRACT

The prediction of body composition of livestock, both alive and in carcass, it is important, in every segment of the beef industry, as it has usefulness in: progeny test development, carcass evaluation, nutrition experiments, estimating energy requirements, an individualized allocation of the feeding cost, and animal production with optimal body composition, to obtain maximum financial compensation. Fat is the most variable body component in amount and distribution during growth, therefore, this it is used for determining the body composition. The body weight of cattle, when they arrive at the feedlot (initial weight) influences on weight and carcass characteristics used to estimate body composition. Initial weight of lightweight animals (calves) have a greater amount of subcutaneous fat compared to the (heavy) yearlings. For this reason, it should not be used the equations made with yeralings to determine body composition of calves to avoid overestimation.

REFERENCES

1. BAKER MJ, Tedeschi LO, Fox DG, Henning WR, Ketchen DJ. Using ultrasound measurements to predict body composition of yearling bulls. J. Anim. Sci. 2006; 84:2666-2672.

2. BERG RT, Butterfield RM. New Concepts of Cattle Growth. Sidney University Press. Australia. 2006.

3. BRETHOUR JR. Using serial ultrasound measures to generate models of marbling and backfat thickness changes in feedlot cattle. J. Anim Sci. 2000; 78:2055-2061.

4. BRETHOUR JR. The relationship of average backfat thickness of feedlot steers to performance and relative efficiency of fat and protein retention. J. Anim Sci. 2004; 82:3366-3372.

5. COMERFORD JW, House RB, Harpster HW, Henning WR, Cooper JB. Effects of forage and protein source on feedlot performance and carcass traits of Holstein and crossbred beef steers. J. Anim. Sci. 1992; 70:1022.

6. DEVILLIER JE. The Louisiana calf-to-carcass program: Growth and carcass traits. Ph. D. Dissertation. Louisiana State University. 2003.

7. DOLEZAL HG, Tatum JD, Williams FL Jr. Effects of feeder cattle frame size, muscle thickness, and age class on days fed, weight and carcass composition. J. Anim. Sci. 1993; 71:2975.

8. GARRETT WN. Relationship between energy metabolism and the amounts of protein and fat deposited in growing cattle. Energy Metab. Proc. Symp. 1987; 26:3.

9. GREINER SP, Rouse GH, Wilson DE, Cundiff LV, Wheeler TL. The relationship between ultrasound measurements and carcass fat thickness and longissimus muscle area in beef cattle. J. Anim. Sci. 2003; 81:676-682.

10. GUIROY PJ, Fox DG, Tedeschi LO, Baker MJ, Cravey MD. Predicting individual feed requirements of cattle fed in groups. J. Anim. Sci. 2001; 79:1983.

11. GUIROY PJ, Tedeschi LO, Fox DG, Hutcheson JP. The effects of implant strategy on finished body weight of beef cattle. J. Anim. Sci. 2002; 80:1791.

12. HAMLIN KE, Green RD, Perkins TL, Cundiff LV, Miller LF. Real-time ultrasonic measurements of fat thickness and longissimus muscle area: I. Description of age and weight effects. J. Anim. Sci. 1995; 73:1713-1724.

13. HERSOM MJ, Horn GW, Krehbiel CR, Phillips WA. Effect of live weight gain of steers during winter grazing: I. Feedlot performance, carcass characteristics, and body composition of beef steers. J. Anim. Sci. 2004; 82:262-272.

14. KARNUAH AB, Moriya K, Nakanishi N, Nade T, Mitsuhashi T, Sasaki Y. Computer image analysis for prediction of carcass composition from cross-sections of Japanese black steers. J. Anim. Sci. 2001; 79:2851.

15. KEMPSTER AJ. Fat partition and distribution in carcass of cattle, sheep and pigs: A review. Meat Sci. 1981; 5:83.

16. KORVER S, Tess MW, Johnson T, Anderson BB. Size scaled lean and fat growth patterns of serially slaughtered beef animals. J. Anim. Sci. 1987; 64:1292.

17. LAWRENCE TLJ, Fowler VR. Growth of farm animals. CABI Publishing. 2002.

18. LAWRENCE TE, Farrow RL, Zollinger BL, Spivey QS. 2008. Technical note: The United States Deparment of Agriculture beef yield grade equation requires modification to reflect the current longissimus muscle area to hot carcass weight relationship. J. Anim. Sci. 2008; 86:1434-1438.

19. LOYA-OLGUIN JL. Predicción de la grasa corporal de novillos livianos de engorda. (Tesis Doctoral). Mexicali, Baja California; México. Universidad Autónoma de Baja California. 2011.

20. MAY SG, Dolezal HG, Gill DR, Ray FK, Buchanan DS. Effects of days fed, carcass grade traits, and subcutaneous fat removal on post-mortem muscle characteristics and beef palatability. J. Anim. Sci. 1992; 70:444.

21. MILLER MF, Cross HR, Baker JF, Byers FM, Recio HA. 1988. Evaluation of live and carcass techniques for predicting beef carcass composition. Meat Sci. 1988; 23:111.

22. NRC. Nutrient requirements of beef cattle (Update 2000). National Academy Press, Washington, DC. 2000.

23. OWENS FN, Gill DR, Secrist DS, Coleman SW. Review of some aspects of growth and development of feedlot cattle. J. Anim. Sci. 1995; 73:3152.

24. OWENS FN, Dubeski P, Hanson CF. Factors that alter the growth and development of ruminants. J. Anim. Sci. 1993; 73:3138.

25. PRIYANTO R, Johnson ER, Taylor DG. Investigations into the accurancy of prediction of beef carcass composition using subcutaneous fat thickness and carcass weight I. Identifying problems. Meat Science. 1997; 46:147.

26. ROMPALA RE, Jones SDM, Buchanan-Smith JG, Bayley HS. Feedlot performance and composition of gain in late-maturing steers exhibiting normal and compensatory growth. J. Anim. Sci. 1985; 61:637.

27. SALINAS CJ, Yado R, Lerma DEC. Nutrición básica. Primera edición. Departamento de Fomento Editorial. Tamaulipas, México. 1997.

28. SCHOONMAKER JP, Loerch SC, Fluharty FL, Zerby HN, Turner TB. Effect of age at feedlot entry on performance and carcass characteristics of bulls and steers. J. Anim. Sci. 2002; 80:2247.

29. SIMPFENDORFER S. 1974. Relationship of body type, size, sex, and energy intake to the body composition of cattle. Ph. D. dissertation. Cornell Univ., Ithaca, NY.

30. TAYLOR RE. Scientific farm animal production: an introduction to animal science. Fourth edition. Macmillan Publishing Company. U.S.A. 1992.

31. TEDESCHI LO, Fox DG, Guiroy PJ. A decision support system to improve individual cattle management. 1. A mechanistic, dynamic model for animal growth. Agric. Sis. J. 2004; 79:171.

32. THONNEY ML, Perry TC, Armbruster G, Beermann DH, Fox DG. Comparison of steaks from Holstein and Simmental x Angus steers. J. Anim. Sci. 1991; 69: 4866-4870.

33. TORRENTERA N. Modelo de predicción del rendimiento de canales de ganado bovino de engorda (Tesis Doctoral). Mexicali, Baja California; México. Universidad Autónoma de Baja California. 2005.

34. TYLUTKI TP, Fox DG, Anrique RG. Predicting net energy and protein requirements for growth of implanted and no implanted bulls varying in body size. J. Anim. Sci. 1994; 72:1806.

35. WALDMAN RC, Tyler WJ, Brungardt VH. Estimation of body composition in young calves. J. Anim. Sci. 1969; 29:426-428.

36. WALL PB, Rouse GH, Wilson DE, Tait RG Jr. Use of ultrasound to predict body composition changes in steers at 100 and 65 days before slaughter. J. Anim. Sci. 2004; 82:1621-1629.

37. ZINN RA, Barreras A, Owens FN, Plascencia A. Performance by feedlot steers and heifers: Daily gains, mature weight, dry matter intake, and dietary energetics. J. Anim. Sci. 2008; 86:2680-26.