COMPARATION OF NONLINEAR MODELS TO FIT GROWTH CURVE AND ESTIMATION OF PRODUCTIVE PARAMETERS IN COBB 500 CHICKENS

COMPARATION OF NONLINEAR MODELS TO FIT GROWTH CURVE AND ESTIMATION OF PRODUCTIVE PARAMETERS IN COBB 500 CHICKENS

The objective of this study was to compare the goodness of fit of four nonlinear and two polynomial linear models to response variable body weight (g) in Cobbs 500 chicken, to estimate parameters related to biological process respect to time (days), considering three different residual covariance structure sitiation. A dataset of 1000 body weight records measured in 2023 from 200 Cobb 500 chicken in age: 1, 7 21, 33 and 42 days of life. Assuming a residual heterocedastyc by day and autocorrelated AR(1) by chicken covariance structure improved the goodness of fit of the models respect a residual independient and homocedastyc structure, due the heterogeneity of variance found when the age of the chicken grew up (p < 0.05) and the high residual correlation () within each animal. From all models, Gompertz and Logistic models have the best fit, according with AIC and BIC values. Parameters ? and ? have a negative correlation (? < – 0.80), similar with ? y TI (? = – 0.7054) and finally, ? and TM (? = – 0.8464). In conclusion, fitting growth curves through nonlinear models with heterocedastic and correlated residual covariance structure allows estimating parameters related with life cicle stages and then, to obtain decision criteria in management programas and carry on productives systems in a efficient way. 

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Main Authors: Saavedra , Roberto, Mudarra , Richard, Cedeño , Héctor, Pimentel , Tamara
Format: Digital revista
Language:spa
Published: Universidad de Panamá, Facultad de Ciencias Agropecuarias 2024
Online Access:https://revistas.up.ac.pa/index.php/investigaciones_agropecuarias/article/view/5175
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spelling rev-inveagro-pa-article51752024-06-07T23:25:31Z COMPARATION OF NONLINEAR MODELS TO FIT GROWTH CURVE AND ESTIMATION OF PRODUCTIVE PARAMETERS IN COBB 500 CHICKENS COMPARACIÓN DE MODELOS NO LINEALES PARA EL AJUSTE DE CURVAS DE CRECIMIENTO Y ESTIMACIÓN DE PARÁMETROS PRODUCTIVOS EN POLLOS COBB 500 Saavedra , Roberto Mudarra , Richard Cedeño , Héctor Pimentel , Tamara heterocedasticidad autocorrelación madurez iteración asíntota heterocedasticity autocorrelation maturity iteration asymptote The objective of this study was to compare the goodness of fit of four nonlinear and two polynomial linear models to response variable body weight (g) in Cobbs 500 chicken, to estimate parameters related to biological process respect to time (days), considering three different residual covariance structure sitiation. A dataset of 1000 body weight records measured in 2023 from 200 Cobb 500 chicken in age: 1, 7 21, 33 and 42 days of life. Assuming a residual heterocedastyc by day and autocorrelated AR(1) by chicken covariance structure improved the goodness of fit of the models respect a residual independient and homocedastyc structure, due the heterogeneity of variance found when the age of the chicken grew up (p < 0.05) and the high residual correlation () within each animal. From all models, Gompertz and Logistic models have the best fit, according with AIC and BIC values. Parameters ? and ? have a negative correlation (? < – 0.80), similar with ? y TI (? = – 0.7054) and finally, ? and TM (? = – 0.8464). In conclusion, fitting growth curves through nonlinear models with heterocedastic and correlated residual covariance structure allows estimating parameters related with life cicle stages and then, to obtain decision criteria in management programas and carry on productives systems in a efficient way.  El objetivo de este estudio fue comparar la calidad del ajuste de cuatro funciones no lineales y dos funciones lineales polinómicas en la variable de respuesta peso vivo (g) en pollos de raza Cobbs 500, para la estimación de parámetros referentes al proceso biológico del crecimiento respecto a la edad del ave (días), considerando tres diferentes situaciones de estructura de covarianzas residuales. Se utilizo una base de datos tomada en 2023, de 1000 registros de 200 pollos de la raza Cobb 500 en los 1, 7, 21, 33 y 42 días de vida. Asumir una estructura de covarianza heterocedástica por día y autocorrelacionada AR(1) mejora la bondad de ajuste de los modelos respecto a una estructura de covarianza homocedástica e independiente, dada la heterogeneidad de varianza encontrada a medida que avanza la edad de las aves (p < 0.05) y la alta correlación () residual dentro de cada animal. Los modelos de Gompertz y Logística tuvieron mejor ajuste que el resto de las funciones evaluadas, en función a los AIC e BIC obtenidos. Los parámetros ? y ? tienen una correlación negativa (? < – 0.80), al igual que ? y TI (? = – 0.7054) y ? y TM (? = – 0.8464). En conclusión, ajustar curvas de crecimientos mediante modelos no lineales con estructuras de covarianzas residuales hererocedásticas y correlacionadas permite estimar parámetros relacionados al ciclo de vida y así, obtener criterios de decisión en programas de manejo y llevar sistemas productivos de forma eficiente. Universidad de Panamá, Facultad de Ciencias Agropecuarias 2024-06-07 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Artículo revisado por pares application/pdf https://revistas.up.ac.pa/index.php/investigaciones_agropecuarias/article/view/5175 10.48204/j.ia.v6n2.a5175 Revista investigaciones agropecuarias; Vol. 6 Núm. 2 (2024): Revista Investigaciones Agropecuarias; 97-119 2644-3856 2222-7903 spa https://revistas.up.ac.pa/index.php/investigaciones_agropecuarias/article/view/5175/4064 Derechos de autor 2024 Revista investigaciones agropecuarias http://creativecommons.org/licenses/by-nc-sa/4.0
institution UP PA
collection OJS
country Panamá
countrycode PA
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databasecode rev-inveagro-pa
tag revista
region America Central
libraryname Sistema de Bibliotecas de la UP
language spa
format Digital
author Saavedra , Roberto
Mudarra , Richard
Cedeño , Héctor
Pimentel , Tamara
spellingShingle Saavedra , Roberto
Mudarra , Richard
Cedeño , Héctor
Pimentel , Tamara
COMPARATION OF NONLINEAR MODELS TO FIT GROWTH CURVE AND ESTIMATION OF PRODUCTIVE PARAMETERS IN COBB 500 CHICKENS
author_facet Saavedra , Roberto
Mudarra , Richard
Cedeño , Héctor
Pimentel , Tamara
author_sort Saavedra , Roberto
title COMPARATION OF NONLINEAR MODELS TO FIT GROWTH CURVE AND ESTIMATION OF PRODUCTIVE PARAMETERS IN COBB 500 CHICKENS
title_short COMPARATION OF NONLINEAR MODELS TO FIT GROWTH CURVE AND ESTIMATION OF PRODUCTIVE PARAMETERS IN COBB 500 CHICKENS
title_full COMPARATION OF NONLINEAR MODELS TO FIT GROWTH CURVE AND ESTIMATION OF PRODUCTIVE PARAMETERS IN COBB 500 CHICKENS
title_fullStr COMPARATION OF NONLINEAR MODELS TO FIT GROWTH CURVE AND ESTIMATION OF PRODUCTIVE PARAMETERS IN COBB 500 CHICKENS
title_full_unstemmed COMPARATION OF NONLINEAR MODELS TO FIT GROWTH CURVE AND ESTIMATION OF PRODUCTIVE PARAMETERS IN COBB 500 CHICKENS
title_sort comparation of nonlinear models to fit growth curve and estimation of productive parameters in cobb 500 chickens
description The objective of this study was to compare the goodness of fit of four nonlinear and two polynomial linear models to response variable body weight (g) in Cobbs 500 chicken, to estimate parameters related to biological process respect to time (days), considering three different residual covariance structure sitiation. A dataset of 1000 body weight records measured in 2023 from 200 Cobb 500 chicken in age: 1, 7 21, 33 and 42 days of life. Assuming a residual heterocedastyc by day and autocorrelated AR(1) by chicken covariance structure improved the goodness of fit of the models respect a residual independient and homocedastyc structure, due the heterogeneity of variance found when the age of the chicken grew up (p < 0.05) and the high residual correlation () within each animal. From all models, Gompertz and Logistic models have the best fit, according with AIC and BIC values. Parameters ? and ? have a negative correlation (? < – 0.80), similar with ? y TI (? = – 0.7054) and finally, ? and TM (? = – 0.8464). In conclusion, fitting growth curves through nonlinear models with heterocedastic and correlated residual covariance structure allows estimating parameters related with life cicle stages and then, to obtain decision criteria in management programas and carry on productives systems in a efficient way. 
publisher Universidad de Panamá, Facultad de Ciencias Agropecuarias
publishDate 2024
url https://revistas.up.ac.pa/index.php/investigaciones_agropecuarias/article/view/5175
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