Please use this identifier to cite or link to this item: http://earsiv.odu.edu.tr:8080/xmlui/handle/11489/1477
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dc.contributor.authorAlkan, Sezai-
dc.contributor.authorBirgul, Ozgur Baris-
dc.contributor.authorDemirarslan, Pinar Celebi-
dc.contributor.authorKucukonder, Hande-
dc.date.accessioned2022-08-15T13:30:12Z-
dc.date.available2022-08-15T13:30:12Z-
dc.date.issued2020-
dc.identifier.urihttp://doi.org/10.17582/journal.pjz/2020.52.1.347.354-
dc.identifier.urihttp://earsiv.odu.edu.tr:8080/xmlui/handle/11489/1477-
dc.description.abstractIn this study, it was aimed to model broiler growth curves of chickens with nonlinear regression analysis and grey prediction model. For this, the growth of 118 broilers was analyzed by using their weekly individual live weights from hatch to 49 day-old. In the analysis, nonlinear functions and Rolling-Grey Model (1,1) prediction method were used. The time-dependent growths of mixed sexes broilers were analyzed in the aspects of testing the parallelism of female and male growth samples, determining the best fitted growth model and designating the biological meaningful parameters (inflection point age, weight and growth rate) of growth functions. Analyses showed that the growth profiles of female and male chicks found not to be parallel using profile analysis, and the male chicks had a higher body weight than the females (P < 0.01) starting from 14-21st days until the end of experiment. For this reason, the prediction models were created separately and compared by MAPE (%) and accuracy rate (rho) criteria in order to find out the most consistent growth model for female and male broiler chicks. The results indicate that Rolling-Grey Model (1,1) is more consistent than Von Bertalanffy, Gompertz and Logistic and can be used as an alternative to nonlinear regression models in growth analysis.en_US
dc.language.isoengen_US
dc.publisherZOOLOGICAL SOC PAKISTAN, UNIV PUNJAB, NEW CAMPUS, C/O DEPT ZOOLOGY, LAHORE, PAKISTANen_US
dc.relation.isversionof10.17582/journal.pjz/2020.52.1.347.354en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectNonlinear regression; Growth functions; Grey System Theory; Rolling-Grey Model (1,1); Broileren_US
dc.subjectRELATIONAL ANALYSIS; BAYESIAN-ANALYSIS; PARAMETERS; DEPOSITION; DESCRIBE; PROFILE; TRAITSen_US
dc.titleCurve Fitting with Nonlinear Regression and Grey Prediction Model of Broiler Growth in Chickensen_US
dc.typearticleen_US
dc.relation.journalPAKISTAN JOURNAL OF ZOOLOGYen_US
dc.contributor.departmentOrdu Üniversitesien_US
dc.identifier.volume52en_US
dc.identifier.issue1en_US
dc.identifier.startpage347en_US
dc.identifier.endpage354en_US
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