Some novel growth functions and their application with reference to growth in ostrich

Multiphasic mixed growth models for turkeys

Growth models are important for optimization of feed formulation and breeding programs in turkeys. The objectives of this study were 1) to compare sex and line differences in turkeys in parameter estimates of mono- and di-phasic Gompertz growth models, and 2) to evaluate mono and diphasic mixed Gompertz growth models to determine the variation in parameter estimates in a group of female line turkey toms. A total of 1,056 manually recorded weekly average body weight (BW) observations from male and female turkeys of a male and female line from weeks 1 to 20 were used for objective 1. Daily median values of automatically collected individual BW of female line turkey toms were used for objective 2 and random components associated with individual subject animals related to mature weight and/or timing of maximum gain during each phase were introduced in the Gompertz model. Growth curve shapes were different between male line toms, male line hens, female line toms, and female line hens (P < 0.001). However, inflection points were similar between male and female line toms and between male and female line hens (14.06 vs. 13.72 wk and 11.22 and 10.71 wk, respectively), while mature BW differed between lines by 6.49 and 3.81 kg for toms and hens, respectively. The normalized growth rate constant (growth rate constant corrected for mature weight) was around the same magnitude between male and female line toms (0.0031 vs. 0.0038, respectively), but slightly lower in male line hens compared to female line hens (0.0072 vs. 0.0091, respectively). Diphasic Gompertz models described growth better in all line × sex combinations compared to the monophasic models (P < 0.001) and mixed diphasic Gompertz models showed improved fit over mixed monophasic Gompertz models. The correlation structure of the random components identified that individuals with a higher mature weight had a later inflection point and lower growth rate coefficients. These results provide tools for improved breeding practices and a structure to evaluate the effects of dietary or environmental factors on growth trajectories.

A sinusoidal function and the Nelder-Mead simplex algorithm applied to growth data from broiler chickens

There has been much recent interest in mathematical developments for the analysis of growth in poultry. In this paper, we present a sinusoidal function to describe the evolution of growth as a function of time based on real life experiments. The function was evaluated with regard to its ability to describe the relationship between body weight and age in broilers and was compared to 4 standard growth functions: Gompertz, logistic, Lopez, and Richards. In order to estimate the model parameters, we adopted a global optimization method based on a direct search method instead of using gradient-based techniques. The results of this study show that both the sinusoidal function and the direct search method precisely describe the growth dynamics of broiler chickens. Fitting the growth functions to different data profiles nearly always led to the same or less maximized log-likelihood values for the sinusoidal equation, which is an indication of its superiority in describing growth data from broiler chickens.