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Architecture of broiler breeder energy partitioning models

A robust model that estimates the ME intake over broiler breeder lifetime is essential for formulating diets with optimum nutrient levels. The experiment was conducted as a randomized controlled trial with 40 Ross 708 broiler breeder pullets reared on 1 of 10 target growth trajectories, which were d...

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Detalles Bibliográficos
Autores principales: Afrouziyeh, Mohammad, Zukiwsky, Nicole M., You, Jihao, Kwakkel, René P., Korver, Douglas R., Zuidhof, Martin J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627977/
https://www.ncbi.nlm.nih.gov/pubmed/34823174
http://dx.doi.org/10.1016/j.psj.2021.101518
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author Afrouziyeh, Mohammad
Zukiwsky, Nicole M.
You, Jihao
Kwakkel, René P.
Korver, Douglas R.
Zuidhof, Martin J.
author_facet Afrouziyeh, Mohammad
Zukiwsky, Nicole M.
You, Jihao
Kwakkel, René P.
Korver, Douglas R.
Zuidhof, Martin J.
author_sort Afrouziyeh, Mohammad
collection PubMed
description A robust model that estimates the ME intake over broiler breeder lifetime is essential for formulating diets with optimum nutrient levels. The experiment was conducted as a randomized controlled trial with 40 Ross 708 broiler breeder pullets reared on 1 of 10 target growth trajectories, which were designed with 2 levels of cumulative BW gain in prepubertal growth phase and 5 levels of timing of growth around puberty. This study investigated the effect of growth pattern on energy efficiency of birds and tested the effects of dividing data into daily, 4-d, weekly, 2-wk, and 3-wk periods and the inclusion of random terms associated with individual maintenance ME and ADG requirements, and age on ME partitioning model fit and predictive performance. Model [I] was: MEI(d) = a × BW(b) + c × ADG(p) + d × ADG(n) + e × EM + ε, where MEI(d) was daily ME intake (kcal/d); BW in kg; ADG(p) was positive ADG; ADG(n) was negative ADG (g/d); EM was egg mass (g/d); ε was the model residual. Models [II to IV] were nonlinear mixed models based on the model [I] with inclusion of a random term for individual maintenance requirement, age, and ADG, respectively. Model [II] – 3 wk was chosen as the most parsimonious based on lower autocorrelation bias, closer fit of the estimates to the actual data (lower model MSE and closer R(2) to 1), and greater predictive performance among the models. Estimated ME partitioned to maintenance in model [II] – 3 wk was 100.47 ± 7.43 kcal/kg(0.56), and the ME requirement for ADG(p), ADG(n), and EM were 3.49 ± 0.37; 3.16 ± 3.91; and 2.96 ± 0.13 kcal/g, respectively. Standard treatment had lower residual heat production (RHP; -0.68 kcal/kg BW(0.56)) than high early growth treatment (0.79 kcal/kg BW(0.56)), indicating greater efficiency in utilizing the ME consumed. Including random term associated with individual maintenance ME in a 3-wk chunk size provided a robust, biologically sound life-time energy partitioning model for breeders.
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spelling pubmed-86279772021-12-06 Architecture of broiler breeder energy partitioning models Afrouziyeh, Mohammad Zukiwsky, Nicole M. You, Jihao Kwakkel, René P. Korver, Douglas R. Zuidhof, Martin J. Poult Sci MANAGEMENT AND PRODUCTION A robust model that estimates the ME intake over broiler breeder lifetime is essential for formulating diets with optimum nutrient levels. The experiment was conducted as a randomized controlled trial with 40 Ross 708 broiler breeder pullets reared on 1 of 10 target growth trajectories, which were designed with 2 levels of cumulative BW gain in prepubertal growth phase and 5 levels of timing of growth around puberty. This study investigated the effect of growth pattern on energy efficiency of birds and tested the effects of dividing data into daily, 4-d, weekly, 2-wk, and 3-wk periods and the inclusion of random terms associated with individual maintenance ME and ADG requirements, and age on ME partitioning model fit and predictive performance. Model [I] was: MEI(d) = a × BW(b) + c × ADG(p) + d × ADG(n) + e × EM + ε, where MEI(d) was daily ME intake (kcal/d); BW in kg; ADG(p) was positive ADG; ADG(n) was negative ADG (g/d); EM was egg mass (g/d); ε was the model residual. Models [II to IV] were nonlinear mixed models based on the model [I] with inclusion of a random term for individual maintenance requirement, age, and ADG, respectively. Model [II] – 3 wk was chosen as the most parsimonious based on lower autocorrelation bias, closer fit of the estimates to the actual data (lower model MSE and closer R(2) to 1), and greater predictive performance among the models. Estimated ME partitioned to maintenance in model [II] – 3 wk was 100.47 ± 7.43 kcal/kg(0.56), and the ME requirement for ADG(p), ADG(n), and EM were 3.49 ± 0.37; 3.16 ± 3.91; and 2.96 ± 0.13 kcal/g, respectively. Standard treatment had lower residual heat production (RHP; -0.68 kcal/kg BW(0.56)) than high early growth treatment (0.79 kcal/kg BW(0.56)), indicating greater efficiency in utilizing the ME consumed. Including random term associated with individual maintenance ME in a 3-wk chunk size provided a robust, biologically sound life-time energy partitioning model for breeders. Elsevier 2021-10-10 /pmc/articles/PMC8627977/ /pubmed/34823174 http://dx.doi.org/10.1016/j.psj.2021.101518 Text en © 2021 The Authors https://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
Afrouziyeh, Mohammad
Zukiwsky, Nicole M.
You, Jihao
Kwakkel, René P.
Korver, Douglas R.
Zuidhof, Martin J.
Architecture of broiler breeder energy partitioning models
title Architecture of broiler breeder energy partitioning models
title_full Architecture of broiler breeder energy partitioning models
title_fullStr Architecture of broiler breeder energy partitioning models
title_full_unstemmed Architecture of broiler breeder energy partitioning models
title_short Architecture of broiler breeder energy partitioning models
title_sort architecture of broiler breeder energy partitioning models
topic MANAGEMENT AND PRODUCTION
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627977/
https://www.ncbi.nlm.nih.gov/pubmed/34823174
http://dx.doi.org/10.1016/j.psj.2021.101518
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