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Comparison of four nonlinear growth models in Creole chickens of Mexico

Animal growth is a complex and dynamic process that involves physiological and morphological changes from hatching to maturity. It is defined as the increase in body size per time unit. Mathematical functions, called growth models, have been used to explain growth patterns. The aim of this study was...

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Autores principales: Mata-Estrada, Analy, González-Cerón, Fernando, Pro-Martínez, Arturo, Torres-Hernández, Glafiro, Bautista-Ortega, Jaime, Becerril-Pérez, Carlos M., Vargas-Galicia, Artemio J., Sosa-Montes, Eliseo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7587683/
https://www.ncbi.nlm.nih.gov/pubmed/32241482
http://dx.doi.org/10.1016/j.psj.2019.11.031
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author Mata-Estrada, Analy
González-Cerón, Fernando
Pro-Martínez, Arturo
Torres-Hernández, Glafiro
Bautista-Ortega, Jaime
Becerril-Pérez, Carlos M.
Vargas-Galicia, Artemio J.
Sosa-Montes, Eliseo
author_facet Mata-Estrada, Analy
González-Cerón, Fernando
Pro-Martínez, Arturo
Torres-Hernández, Glafiro
Bautista-Ortega, Jaime
Becerril-Pérez, Carlos M.
Vargas-Galicia, Artemio J.
Sosa-Montes, Eliseo
author_sort Mata-Estrada, Analy
collection PubMed
description Animal growth is a complex and dynamic process that involves physiological and morphological changes from hatching to maturity. It is defined as the increase in body size per time unit. Mathematical functions, called growth models, have been used to explain growth patterns. The aim of this study was to compare the Gompertz-Laird, logistic, Richards, and Von Bertalanffy growth models to determine which best fits the data of the Creole chickens (CC). Three hundred forty-seven CC were individually weighed from hatching until 177 D of age. Birds were fed a starter diet (0–18 D of age; 19% crude protein (CP) and 3,000 kcal of ME/kg) and grower diet (19–177 D of age; 18% CP and 2,800 kcal of ME/kg). Data were analyzed using PROC NLIN to fit the nonlinear growth curve. The coefficient of determination (R(2)), Akaike information criteria (AIC), and Bayesian information criteria (BIC) were used to compare the goodness of fit of the models. The Von Bertalanffy (R(2): 0.9382, 0.9415; AIC: 2,224.1, 2,424.8; BIC: 2,233.5, 2,434.3, for females and males, respectively) was the model that best explained growth of the birds. On the other hand, both the Gompertz-Laird and logistic models overestimated hatching BW and underestimated the final BW of CC. Females reached age of maximum growth faster than males. The asymptotic weight was higher in males (3,011 g) than in females (2,011 g). Body weight at inflection point was 892 g at 64 D of age for males and 596 g at 54 D for females. In conclusion, the best fit of the data was obtained with the Von Bertalanffy growth model; the information is intended to serve as the basis for utilizing CC.
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spelling pubmed-75876832020-10-27 Comparison of four nonlinear growth models in Creole chickens of Mexico Mata-Estrada, Analy González-Cerón, Fernando Pro-Martínez, Arturo Torres-Hernández, Glafiro Bautista-Ortega, Jaime Becerril-Pérez, Carlos M. Vargas-Galicia, Artemio J. Sosa-Montes, Eliseo Poult Sci Management and Production Animal growth is a complex and dynamic process that involves physiological and morphological changes from hatching to maturity. It is defined as the increase in body size per time unit. Mathematical functions, called growth models, have been used to explain growth patterns. The aim of this study was to compare the Gompertz-Laird, logistic, Richards, and Von Bertalanffy growth models to determine which best fits the data of the Creole chickens (CC). Three hundred forty-seven CC were individually weighed from hatching until 177 D of age. Birds were fed a starter diet (0–18 D of age; 19% crude protein (CP) and 3,000 kcal of ME/kg) and grower diet (19–177 D of age; 18% CP and 2,800 kcal of ME/kg). Data were analyzed using PROC NLIN to fit the nonlinear growth curve. The coefficient of determination (R(2)), Akaike information criteria (AIC), and Bayesian information criteria (BIC) were used to compare the goodness of fit of the models. The Von Bertalanffy (R(2): 0.9382, 0.9415; AIC: 2,224.1, 2,424.8; BIC: 2,233.5, 2,434.3, for females and males, respectively) was the model that best explained growth of the birds. On the other hand, both the Gompertz-Laird and logistic models overestimated hatching BW and underestimated the final BW of CC. Females reached age of maximum growth faster than males. The asymptotic weight was higher in males (3,011 g) than in females (2,011 g). Body weight at inflection point was 892 g at 64 D of age for males and 596 g at 54 D for females. In conclusion, the best fit of the data was obtained with the Von Bertalanffy growth model; the information is intended to serve as the basis for utilizing CC. Elsevier 2020-02-24 /pmc/articles/PMC7587683/ /pubmed/32241482 http://dx.doi.org/10.1016/j.psj.2019.11.031 Text en © 2019 Published by Elsevier Inc. on behalf of Poultry Science Association Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Management and Production
Mata-Estrada, Analy
González-Cerón, Fernando
Pro-Martínez, Arturo
Torres-Hernández, Glafiro
Bautista-Ortega, Jaime
Becerril-Pérez, Carlos M.
Vargas-Galicia, Artemio J.
Sosa-Montes, Eliseo
Comparison of four nonlinear growth models in Creole chickens of Mexico
title Comparison of four nonlinear growth models in Creole chickens of Mexico
title_full Comparison of four nonlinear growth models in Creole chickens of Mexico
title_fullStr Comparison of four nonlinear growth models in Creole chickens of Mexico
title_full_unstemmed Comparison of four nonlinear growth models in Creole chickens of Mexico
title_short Comparison of four nonlinear growth models in Creole chickens of Mexico
title_sort comparison of four nonlinear growth models in creole chickens of mexico
topic Management and Production
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7587683/
https://www.ncbi.nlm.nih.gov/pubmed/32241482
http://dx.doi.org/10.1016/j.psj.2019.11.031
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