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Growth curve mixed nonlinear models in quails.

Raimundo Nonato Colares Camargo Júnior1, Cláudio Vieira de Araújo2, Flávio Luiz de Menezes2

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The Morgan-Mercer-Flodin nonlinear model best described meat-type quail growth, identifying optimal slaughter times for males and females to improve animal yield and genetic quality.

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Area of Science:

  • Animal Science
  • Quantitative Genetics
  • Statistical Modeling

Background:

  • Accurate growth curve modeling is crucial for optimizing animal production and genetic selection.
  • Nonlinear mixed models offer a flexible approach to account for individual variation in growth patterns.

Purpose of the Study:

  • To evaluate and compare nonlinear mixed models for describing meat-type quail growth curves by gender.
  • To identify the best-fitting model for predicting optimal slaughter timing and enhancing genetic quality.

Main Methods:

  • Utilized 15,002 male and 15,408 female quail records.
  • Applied nonlinear models (Brody, Gompertz, Logistic, Morgan-Mercer-Flodin, Richards, Von Bertalanffy) with fixed and random effects.
  • Employed the Bayesian Information Criterion (BIC) for model selection.

Main Results:

  • The Morgan-Mercer-Flodin model with asymptotic weight as a random effect was the best fit for both genders.
  • This model demonstrated reduced residual variance and increased accuracy in growth prediction.
  • Male quails exhibited lower absolute growth rates and velocities than females.

Conclusions:

  • The Morgan-Mercer-Flodin model provides a superior framework for analyzing quail growth dynamics.
  • Findings suggest later slaughter for males to maximize yield.
  • This research aids in optimizing slaughter timing and improving quail genetic populations.