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Título : Modelación de las funciones de crecimiento aplicadas a la producción animal
Otros títulos : Modeling of growth functions applied to animal production
Autor : Agudelo Gómez, Divier Antonio
Cerón Muñoz, Mario Fernando
Restrepo Betancur, Luis Fernando
metadata.dc.subject.*: Biomodelación zootecnia
Crecimiento animal
Estadísitica
Modelos estadísticos
Animal growth
Livestock biomodeling curves
Statistical models
Fecha de publicación : 2008
Editorial : Universidad de Antioquia, Facultad de Ciencias Agrarias
Citación : Agudelo Gómez DA, Cerón Muñoz MF, Restrepo Betancur LF. Modelación de funciones de crecimiento aplicadas a la producción animal. Rev. Colomb. Cienc. Pecu; 2008;21(1):39-58.
Resumen : nimal growth is one of the most important aspect for evaluating animal productivity in beef cattle enterprises and in some cases it is used as a criterion of selection, nevertheless, the fact that animal growth is not exclusively due to genetic factors but also, to environmental effects must be keep in mind. Measurement of animal growth have been performed by lineal and no-lineal mathematical models, choosing they for their fitness of adjustment and the feasibility for biological interpretation of their parameters. Recently the mixed models have been used in which their parameters are composed of fixed and random effects representing the expected values and variance of the fixed ones, respectively, which permits to evaluate the variability of different curves between individuals of a population, as well as the covariance between parameters. The most used criteria for selection of the curve that best fit data are: determination coefficient and the percent of significant and atypical curves found for each function. In addition, other models as the Akaike information criteria and Bayesian information criteria can also be applied. The objective of the present review is to provide the criteria for application of linear and non linear models in analyzing animal growth.
ISSN : 01200690
22652958 E
Aparece en las colecciones: CIAG (Centro de investigaciones Agrarias)

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