Prediction of dry matter intake and average daily gain of the LRNS (1.0.33) and NRC (2000) nutritional models in confined bulls in Paraguay


This work was carried out between August and December 2018, with the objective of contrasting the predictions of dry matter intake (DMI) and average daily gain (ADG) of the LRNS (1.0.33) and NRC (2000) nutritional models in bulls finished in confinement from the perspective of precision and accuracy in relation to the observed data. For this, performance data of 61 Brangus bulls and 55 Brahman bulls with initial live weights of 383.20±10.39 kg and 348.45±18.54 kg and average ages of 21±3 months for both breeds were used. The animals were weighed at the beginning and at the end of confinement with a previous fast of 14 hours. They were fed during confinement with a totally mixed ration (TMR) ad libitum formulated with a forage-concentrate ratio of 40:60. The observed DMI in kg was established from the reading of trays, collection and weighing of excess feed per pen during the confinement period that was then taken to an average per individual, while the observed ADG was determined from the difference of the initial weight and the final weight of the animals, divided by the days of confinement. A Simple Regression Analysis was performed between observed and predicted values. Both models predicted the DMI with precision and accuracy for the Brangus breed, however they underestimated by 3.08% (NRC 2000) and 6.16% (LRNS 1.0.33) in the Brahman breed. Regarding ADG, the LRNS (1.0.33) predicted with precision and accuracy for both races, while the NRC (2000) underestimated by 11.68% (Brangus) and 8.57% (Brahman). The NRC (2000) turned out to be a better estimator of the DMI, while the LRNS (1.0.33) was it for the ADG in bulls of both breeds (Brangus and Brahman) confined in climatic conditions of Paraguay.


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Anderson, R. V., Rasby, R. J., Klopfenstein, T. J., Clark, R. T. 2005. An evaluation of production and economic efficiency of two beef systems from calving to slaughter. Journal of Animal Science, 83: 694–704.

Andriguetto, J.M.; Perly, L.; Minardi, I.;Gemael, A.; Flemming, J.S.; Souza, G.A. De; Bona Filho, A. 1982. Nutrição Animal: As bases e os fundamentos da nutrição animal: os alimentos. São Paulo: Nobel, 257-268p.

Arrigoni, M. B., Martins, C. L., Sarti, L. M. N., Barducci, R. S. B., Franzói, M. C., Vieira Júnior, L. C., Perdigão, A., Ribeiro, F. A., Factori, M. A. 2013. Níveis elevados de concentrado na dieta de bovinos em confinamento. Veterinaria e Zootecnia, 20(4): 539-551.

Association of Official Analytical Chemists (AOAC). 1990. Official methods of analysis. 15.ed. Arlington, 1: 1117

Azevêdo, J. A., Valadares Filho, S., PINA, D., Chizotti, M. L., Valadares, R. F. 2010. A meta-analysis of dry matter intake in Nellore and Zebu-crosses cattle. Revista Brasileira de Zootecnia, 39(8): 1801-1809.

Azevêdo, J. A. G., Valadares Filho, S. C., Costa e Silva, L. F., Dos Santos, A. B., Souza, L. L., Rotta, P. P., Rennó, L. N., Do Prado, I. N. 2016. Regulação e predição de consumo de matéria seca.

Chingala, G. 2018. Beef production and quality of Malawi Zebu steers fed diets containing rangeland-based protein sources under feedlot conditions. Tesis Doctoral. Faculty of AgriSciences at Stellenbosch University, 200p.

Dent, J. B., Blackie, M. J. 1979. Systems Simulation in Agriculture. Applied Science, London. Elsevier Applied Science, 180p. ISBN: 0853348278.

Elyas, A. C. W., Paiva, P. C. A., Lopes, F. C. F., Vilela, D., Arcuri, P. B., Morenz, M. J. F. 2009. Avaliação do modelo CNCPS na predição do consumo de matéria seca em vacas da raça Holandesa em pastejo. Revista Brasileira de Zootecnia, 38(6): 1096-1103.

Ferreira, M. A. S. 2019. Consumo observado e predito pelos sistemas nutricionais em bovinos de corte confinados. Dissertação (mestrado). Universidade Federal de Uberlândia. Brasil, MG: UFU, 67p.

Fox, D. G., Tylutki, T. P. 1998. Accounting for the effects of environment on the nutrient requirements of dairy cattle. Journal of Dairy Science, 81: 3085-3095.

Fox, D. G., Tylutki, T. P., Tedeschi, L. O., Van Amburgh, M. E., Chase, L. E., Pell, A. N., Overton, T. R., and Russell, J. B. 2003. The Net Carbohydrate and Protein System for evaluating herd nutrition and nutrient excretion: Model documentation. Mimeo. No. 213. Animal Science Dept., Cornell University, Ithaca, NY. 292 p.

Fox, D. G., Tedeschi, L. O., Tylutki, T. P., Russell, J. B., Van Amburgh, M. E., Chase, L. E., Pell, A. N., and Overton, T. R. 2004. The Cornell Net Carbohydrate and Protein System model for evaluating herd nutrition and nutrient excretion. Animal Feed Science Technology, 112: 29-78.

Gesualdi Júnior, A., Queiroz, A. C., Resende, F. D., Lana, R., de Souza Gesualdi, A. C., Alleoni, G. F., Detmann, E., Razook, A. G., y de Figueiredo, L. 2005. Validação dos sistemas Viçosa, CNCPS e NRC para formulação de dietas para bovinos Nelore e Caracu, não-castrados, selecionados em condições brasileiras. Revista Brasileira de Zootecnia, 34(3): 997-1005.

Lin, L. I. K. 1989. A concordance correlation coefficient to evaluate reproducibility. Biometrics. 45: 255-268.

Lofgreen, G. P., Garrett, W. N. 1968. A system for expressing net energy requirements and feed values for growing and finishing beef cattle. Journal of Animal Science, 27(3): 793-806.

Machado-Neto, O. R. 2008. Consumo, desempenho e características de carcaça de novilhos Nelore e Red Norte terminados em confinamento e avaliação de sistemas de exigências nutricionais. Dissertação (Mestrado em Zootecnia). Universidade Federal de Lavras, 76p.

National Research Council (NRC). 1996. Nutrient requirements of beef cattle. 7th ed. Nutrient requirements of domestic animals. National Academy Press, Washington, DC.

National Research Council (NRC). 2000 update. Nutrient Requirements of Beef Cattle. 7 Revised ed. Washington D.C.; USA: National Academy Press, 248p.

Neter, J., Kutner, M. H., Nachtsheim, C. J., Wasserman, W. (1996). Applied Linear Statistical Models, 1.ed. McGraw-Hill, Boston.

Rezende, P. L. P., Neto, M. D. F., Restle, J., Fernandes, J. J. R., Pádua, J. T., y Queiroz, G. A. B. 2011. Validação de modelos matemáticos para predição de consumo voluntário e ganho em peso de bovinos. Archivo de Zootecnia, 60(232): 921-930.

Ribeiro, J. 2008. Consumo e desempenho de grupos genéticos zebuínos confinados. Dissertação (Mestrado em Zootecnia). Universidade Federal de Lavras, 107p.

Ribeiro, J. S., Ladeira, M. M., Machado Neto, O. R., Campos, F. R. 2012. Consumo alimentar e sua predição pelos sistemas NRC, CNCPS e BR-CORTE, para tourinhos zebuínos confinados. Revista Ciência Agronômica, 43(4): 802-810.

Silva, D. J., Queiroz, A. C. 2002. Análise de alimentos (métodos químicos e biológicos). 3.ed. Viçosa, MG: Universidade Federal de Viçosa, 235p.

Souza, H. M. 2006. Modelagem matemática e proposta de resoluçao do Problema da dieta alimentar para gado bovino de Corte. Dissertação (M.Sc.). Universidade Federal do Rio de Janeiro, Rio de Janeiro, BR: UFRJ, 105p.

Souza, R. A de., Tempelman, R. J., Allen, M. S., Weiss, W. P., Bernard, J. K., y Vande Haar, M. J. 2018. Predicting nutrient digestibility in high-producing dairy cows. Journal of Dairy Science, 101: 1123–1135.

Tedeschi, L. O., Fox, D. G., Guiroy, P. J. 2004. A decision support system to improve individual cattle management. 1. A mechanistic, dynamic model for animal growth. Agricultural Systems, 79: 171-204.

Tedeschi, L. O., Pas, D., Fox, D. G., Doane, P. H. 2005. Evaluation of the Tabular Feed Energy and Protein Undegradability Values of the National Research Council Nutrient Requirements of Beef Cattle. The Professional Animal Scientist 21: 403–415.

Tedeschi, L. O. 2006. Assessment of the adequacy of mathematical models. Agricultural Systems, 89(02/03): 225-247.

Van Soest, P. J. 1994. Nutritional ecology of the ruminant. 2. ed. New York: Cornell University Press, 476p.

Weiss, W. P. 1993. Predicting energy values of feeds. J. Dairy Sci., 76: 1802-1811.

How to Cite
Portillo, Guido Arnaldo, Diego Avilio Ocampos Olmedo, Pedro Luis Paniagua Alcaraz, and Luis Alberto Alonzo Griffith. 2021. “Prediction of Dry Matter Intake and Average Daily Gain of the LRNS (1.0.33) and NRC (2000) Nutritional Models in Confined Bulls in Paraguay”. Latin American Archives of Animal Production 30 (1), 9-17.
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