Evaluation of mathematical models to describe growth of grazing young bulls
The objective of this study was to evaluate the use of different mathematical models to describe growth of grazing beef cattle. Data of 20 Nellore bulls with initial weight of 129±28.1 kg and final weight of 405±62.0 kg were used. The animals were randomly divided into four plots and placed on B. decumbens Stapf pastures. Three plots received concentrate supplement with different protein profiles and the fourth plot received only mineral supplement. Animals were weighed every 28 days to design growth curve of full body weight. Five mathematical models were evaluated to describe animal growth: Multiphase, Linear, Logarithmic, Gompertz and Logistic models. Assessment of adequacy of the models was performed by using coefficient of determination, simultaneous F-test for identity of parameters, concordance correlation coefficient, root of the mean square error of prediction and partition of the mean square error of prediction. The analysis of the pairwise mean square error of prediction and the delta Akaike's information criterion were used to compare the models for accuracy and precision. Evaluation of all the tested models showed that all of them were able to predict variability among animals. However, Gompertz, Logarithmic and Logistic models created individual predictions that were not satisfactory. Models differed from each other concerning accuracy and precision; the best were in the following order: Multiphase, Linear, Gompertz, Logarithmic and Logistic. The Multiphase model was more efficient than the others for description of grazing beef cattle growth.
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Sociedade Brasileira de Zootecnia
2012
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oai:scielo:S1516-359820120002000202012-03-19Evaluation of mathematical models to describe growth of grazing young bullsFernandes,Henrique JorgeTedeschi,Luis OrlindoPaulino,Mário FonsecaDetmann,EdenioPaiva,Luisa MelvilleValadares Filho,Sebastião de CamposSilva,Aline Gomes daAzevêdo,José Augusto Gomes grazing beef cattle modeling seasonality The objective of this study was to evaluate the use of different mathematical models to describe growth of grazing beef cattle. Data of 20 Nellore bulls with initial weight of 129±28.1 kg and final weight of 405±62.0 kg were used. The animals were randomly divided into four plots and placed on B. decumbens Stapf pastures. Three plots received concentrate supplement with different protein profiles and the fourth plot received only mineral supplement. Animals were weighed every 28 days to design growth curve of full body weight. Five mathematical models were evaluated to describe animal growth: Multiphase, Linear, Logarithmic, Gompertz and Logistic models. Assessment of adequacy of the models was performed by using coefficient of determination, simultaneous F-test for identity of parameters, concordance correlation coefficient, root of the mean square error of prediction and partition of the mean square error of prediction. The analysis of the pairwise mean square error of prediction and the delta Akaike's information criterion were used to compare the models for accuracy and precision. Evaluation of all the tested models showed that all of them were able to predict variability among animals. However, Gompertz, Logarithmic and Logistic models created individual predictions that were not satisfactory. Models differed from each other concerning accuracy and precision; the best were in the following order: Multiphase, Linear, Gompertz, Logarithmic and Logistic. The Multiphase model was more efficient than the others for description of grazing beef cattle growth.info:eu-repo/semantics/openAccessSociedade Brasileira de ZootecniaRevista Brasileira de Zootecnia v.41 n.2 20122012-02-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982012000200020en10.1590/S1516-35982012000200020 |
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Fernandes,Henrique Jorge Tedeschi,Luis Orlindo Paulino,Mário Fonseca Detmann,Edenio Paiva,Luisa Melville Valadares Filho,Sebastião de Campos Silva,Aline Gomes da Azevêdo,José Augusto Gomes |
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Fernandes,Henrique Jorge Tedeschi,Luis Orlindo Paulino,Mário Fonseca Detmann,Edenio Paiva,Luisa Melville Valadares Filho,Sebastião de Campos Silva,Aline Gomes da Azevêdo,José Augusto Gomes Evaluation of mathematical models to describe growth of grazing young bulls |
author_facet |
Fernandes,Henrique Jorge Tedeschi,Luis Orlindo Paulino,Mário Fonseca Detmann,Edenio Paiva,Luisa Melville Valadares Filho,Sebastião de Campos Silva,Aline Gomes da Azevêdo,José Augusto Gomes |
author_sort |
Fernandes,Henrique Jorge |
title |
Evaluation of mathematical models to describe growth of grazing young bulls |
title_short |
Evaluation of mathematical models to describe growth of grazing young bulls |
title_full |
Evaluation of mathematical models to describe growth of grazing young bulls |
title_fullStr |
Evaluation of mathematical models to describe growth of grazing young bulls |
title_full_unstemmed |
Evaluation of mathematical models to describe growth of grazing young bulls |
title_sort |
evaluation of mathematical models to describe growth of grazing young bulls |
description |
The objective of this study was to evaluate the use of different mathematical models to describe growth of grazing beef cattle. Data of 20 Nellore bulls with initial weight of 129±28.1 kg and final weight of 405±62.0 kg were used. The animals were randomly divided into four plots and placed on B. decumbens Stapf pastures. Three plots received concentrate supplement with different protein profiles and the fourth plot received only mineral supplement. Animals were weighed every 28 days to design growth curve of full body weight. Five mathematical models were evaluated to describe animal growth: Multiphase, Linear, Logarithmic, Gompertz and Logistic models. Assessment of adequacy of the models was performed by using coefficient of determination, simultaneous F-test for identity of parameters, concordance correlation coefficient, root of the mean square error of prediction and partition of the mean square error of prediction. The analysis of the pairwise mean square error of prediction and the delta Akaike's information criterion were used to compare the models for accuracy and precision. Evaluation of all the tested models showed that all of them were able to predict variability among animals. However, Gompertz, Logarithmic and Logistic models created individual predictions that were not satisfactory. Models differed from each other concerning accuracy and precision; the best were in the following order: Multiphase, Linear, Gompertz, Logarithmic and Logistic. The Multiphase model was more efficient than the others for description of grazing beef cattle growth. |
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Sociedade Brasileira de Zootecnia |
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2012 |
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http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982012000200020 |
work_keys_str_mv |
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