학술논문
Mexican Creole chickens: effect of data collection periods on goodness-of-fit and parameter precision of growth models.
Document Type
Academic Journal
Author
Zárate-Contreras D; College of Postgraduates Campus Montecillo, Texcoco, State of Mexico CP 56230, Mexico.; González-Cerón F; Department of Animal Science, Chapingo Autonomous University, Texcoco, State of Mexico CP 56230, Mexico.; Cuca-García JM; College of Postgraduates Campus Montecillo, Texcoco, State of Mexico CP 56230, Mexico.; Pro-Martínez A; College of Postgraduates Campus Montecillo, Texcoco, State of Mexico CP 56230, Mexico. Electronic address: aproma@colpos.mx.; Ramírez-Valverde G; College of Postgraduates Campus Montecillo, Texcoco, State of Mexico CP 56230, Mexico.; Aggrey SE; Poultry Genetics and Biotechnology Laboratory, Department of Poultry Science and Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA.; Hernández-Mendo O; College of Postgraduates Campus Montecillo, Texcoco, State of Mexico CP 56230, Mexico.; Gallegos-Sánchez J; College of Postgraduates Campus Montecillo, Texcoco, State of Mexico CP 56230, Mexico.; Sosa-Montes E; Department of Animal Science, Chapingo Autonomous University, Texcoco, State of Mexico CP 56230, Mexico.
Source
Publisher: Elsevier Country of Publication: England NLM ID: 0401150 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1525-3171 (Electronic) Linking ISSN: 00325791 NLM ISO Abbreviation: Poult Sci Subsets: MEDLINE
Subject
Language
English
Abstract
The objective of this study was to estimate the good-of-fitness and precision of parameters of the Gompertz-Laird, Logistic, Richards, and Von Bertalanffy growth models, using different data collection periods (DCP). Two hundred and sixty-two Mexican Creole chicks (116 females and 146 males), were individually weighed to form the following sets of data for each sex: DCP 1 (weights recorded weekly from hatching to 63 d, and every 2 wk, from 63 to 133 d of age), DCP 2 (weights recorded weekly from hatching to 133 d of age), DCP 3 (weights recorded every third day, from hatching to 63 d, and every 14 d, from 63 to 133 d of age), and DCP 4 (weights recorded every third day, from hatching to 63 d, and weekly, from 63 to 133 d of age). Data were analyzed using the NLIN procedure of SAS (Marquardt algorithm). For all growth models, the width of confidence interval (CI) of each parameter, was estimated (α = 0.05). The adjusted coefficient of determination (AR 2 ), as well as the Akaike (AIC) and Bayesian information criteria (BIC) were used to select the best model. The higher the AR 2 , and the lower the width of CI, as well as the AIC and BIC values, the better the model. The Gompertz-Laird model, more frequently showed the highest AR 2 , and the lowest AIC and BIC values compared to the other models. Moreover, for all models, both sexes and all parameters, most confidence interval widths (all with the Gompertz-Laird model) were the lowest with DCP 3 when compared to the other sets of data. In conclusion, the Gompertz-Laird model was the best provided that the chickens are weighed every third day from hatching until 63 d of age, and every 2 wk thereafter.
Competing Interests: Disclosures The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the study reported.
(Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)
Competing Interests: Disclosures The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the study reported.
(Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)