Quail growth curve model identity
DOI:
https://doi.org/10.33448/rsd-v9i10.9328Keywords:
Coturnix coturnix coturnix; Logistic model; Nonlinear model; Equality of parameters; Likelihood ratio.Abstract
In this study, we sought to apply the model identity technique to compare the influence of eight treatments on growth parameters for three broiler quail lines, estimated using a logistic nonlinear regression model. For the analysis, we used the weight and age data obtained for three lines of European broiler quails (Coturnix coturnix coturnix) in a completely randomized 2×4 factorial scheme, with two levels of metabolizable energy (2900 and 3100 kcal of ME kg-1 of diet), four levels of raw protein (22%, 24%, 26% and 28% crude protein), and six repetitions. Results obtained for model identity tests indicated that although there were no significant differences among the parameters of the model between the treatments evaluated in each strain, there were, with the exception of Treatment 5 (3100 kcal of ME kg-1 and 22% crude protein), significant differences with respect to the adult weight parameter between lines within each treatment.
References
Arango, J. A. & Van Vleck, L. D. (2002). Size of beef cows: early ideas, new developments. Genetics and Molecular Research, 1, 51-63.
Bonafé, C. M., Torres, R. A., Sarmento, J. L. R., Silva, L. P., Ribeiro, J. C., Teixeira, R. B., Silva, F. G. & Sousa, M. F. (2011). Random regression models for description of growth curve of meat quails. Brazilian Journal of Animal Science, 40, 765-771.
Brusamarelo, E., da Silva Pereira, T. V., Brusamarelo, D., Souza, C. S., de Oliveira, H. C., Corrêa, G. S. S., Corrêa, A. B. & de Oliveira, C. F. S. (2020). Modelo de crescimento de Gompertz na avicultura: algumas considerações. Research, Society and Development, 9(8), e508985208-e508985208.
Grieser, D. O., Marcato, S. M., Furlan, A. C., Zancanela, V., Ton, A. P. S., Batista, E., Perine, T. P., Pozza, P. C. & Sakomura, N. C. (2015). Comparison of growth curve parameters of organs and body components in meat (Coturnix coturnix coturnix) and laying-type (Coturnix coturnix japonica) quail show interactions between gender and genotype. Journal of British Poultry Science, 56, 6-14.
Kaplan, S. & Gürcan, E. K. (2018). Comparison of growth curves using non-linear regression function in Japanese quail. Journal of Applied Animal Research, 46, 112-117.
Karadavut, U., Taskin, A. & Genc, S. (2017). Comparison of growth curve models in Japanese quail raised in cages enriched with different colored lights. Brazilian Journal of Animal Science, 46, 839-846.
Mota, L. F. M., Abreu, L. R. A., Silva, M. A., Pires, A. V., Lima, H. J. D., Bonafé, C. M. & Martins, P. G. M. A. (2015). Genotype × dietary (methionine+cystine):Lysine ratio interaction for body weight of meat-type quails using reaction norm models. Livestock Science, 182, 137–144.
Puiatti, G. A., Cecon, P. A., Nascimento, M., Nascimento, A. C. A., Carneiro, A. P. S., Silva, F. F., Puiatti, M. & Cruz, C. D. (2020). Nonlinear quantile regression to describe the dry matter accumulation of garlic plants. Ciência Rural 50: 1-e20180385.
Regazzi, A. J. (2003). Teste para verificar a igualdade de parâmetros e a identidade de modelos de regressão não-linear. Revista Ceres 50, 9-26.
Regazzi, A. J. & Silva, C. H. O. (2010). Testes para verificar a igualdade de parâmetros e a identidade de modelos de regressão não-linear em dados de experimento com delineamento em blocos casualizados. Revista Ceres, 57, 315-320.
Safari, S. & Erfani, A. R. (2020). A new method for fuzzification of nested dummy variables by fuzzy clustering membership functions and its application in financial economy. Iranian Journal of Fuzzy Systems, 17, 13-27.
Santos, T. C., Murakami, A. E., Oliveira, C. A. L. & Costa, P. D. (2012). Body and testicular development in males of meat- and egg-type quails of 25 to 360 days. Pesquisa Veterinária Brasileira, 32, 1205-1212.
Santos, H. B., Vieira, D. A., Souza, L. P., Santos, A. L., Santos, F. R. & Araújo Neto, F. R. (2018). Application of non-linear mixed models for modelling the quail growth curve for meat and laying. Journal of Agricultural Science, 156, 1216-1221.
Sezer, M. & Tarhan, S. (2005). Model parameters of growth curves of three meat type lines of Japanese quail. Czech Journal of Animal Science, 50, 22–30.
Silva, F. L., Alencar, M. M., Freitas, A. R., Packer, I. U. & Mourão, G. B. (2011). Growth curves in beef cows of different biological types. Pesquisa Veterinária Brasileira, 46, 262-271.
Silveira, F. G., Silva, F. F., Carneiro, P. L. S., Malhado, C. H. M. & Muniz, J. A. (2011). Cluster analysis applied to nonlinear regression models selection to growth curves of crossed lambs. Ciência Rural, 41, 692-698.
Souza, L. A., Caires, D. N., Carneiro, P. L. S., Malhado, C. H. M. & Martins Filho, R. 2010. Growth rate curves of Indubrasil cattle raised at Sergipe State. Revista Ciência Agronômica, 41, 671-676.
Zancanela, V., Marcato, S. M., Furlan, A. C., Grieser, D. O., Ton, A. P. S., Batista, E. & Pozza, P. C. (2015). Models for predicting energy requirements in meat quail. Livestock Science, 171, 12-19.
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Copyright (c) 2020 Marta Jeidjane Borges Ribeiro; Fabyano Fonseca e Silva; Claudson Oliveira Brito; Ana Paula Del Vesco; Maise Santos Macário; Camilla Mendonça Silva; Leandro Teixeira Barbosa
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