Comparison of growth curve models in partridge

Sarıyel, Vahdettin; Aygün, Ali; Keskin, İsmail

doi:10.3382/ps/pew472

Cited by 28 publications

(34 citation statements)

References 16 publications

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“…The use of such models in avian research was promoted by Ricklefs (1967) and the most common models used in poultry science are the Brody, Gompertz, logistic, Richards, and von Bertalanffy models (c.f. Gao et al, 2016; Sariyeel et al, 2017; Gonçalves Gotuzzo et al, 2018; Tompić et al, 2011). Typical applications for practitioners (mentioned in the cited literature) include the monitoring of the health status (comparing observed weights with the growth curve) or the optimization of the slaughtering age.…”

Section: Introductionmentioning

confidence: 99%

Best-fitting growth curves of the von Bertalanffy-Pütter type

et al. 2019

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Introduction: A large body of literature aims at identifying growth models that fit best to given mass-at-age data. The von Bertalanffy-Pütter differential equation is a unifying framework for the study of growth models. Problem: The most common growth models used in poultry science literature fit into this framework, as these models correspond to different exponent-pairs (e.g., Brody, Gompertz, logistic, Richards, and von Bertalanffy models). Here, we search for the optimal exponent-pairs ( a and b ) amongst all possible exponent-pairs and expect a significantly better fit of the growth curve to concrete mass-at-age data. Method: Data fitting becomes more difficult, as there is a large region of nearly optimal exponent-pairs. We therefore develop a fully automated optimization method, with computation time of about 1 to 2 wk per data-set. For the proof of principle, we applied it to literature data about 217 male meat-type chickens, Athens Canadian Random Bred, that were reared under controlled conditions and weighed 28 times during a time span of 170 D. Results: We compared 2 methods of data fitting, least squares using the sum of squared errors ( SSE ), which is common in literature, and a variant using the sum of squared log-errors SSElog . For these data, the optimal exponent-pairs were (0.43, 4.06) for SSE = 2,208.6 (31% improvement over literature values for the residual standard deviation) and (0.89, 0.93) for SSElog = 0.04599. Both optimal exponents were clearly distinct from the exponent-pairs of the common models in literature. This finding was reinforced by considering the region of nearly optimal exponents. Discussion: We explain, why we recommend using SSElog for data fitting and we discuss prognosis, where data from the first 8 wk of growth would not be enough.

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Section: Introductionmentioning

confidence: 99%

Best-fitting growth curves of the von Bertalanffy-Pütter type

et al. 2019

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“…The three-parameter growth curves such as Brody, Von Bertalanffy, Gompertz and Logistic curves have been widely and frequently used for modeling animal and forest growth [22,23,27,28]. In this study, we introduced these growth curves for modeling the physical growth from infancy to middle-adolescence.…”

Section: Discussionmentioning

confidence: 99%

From Infancy to Middle-Adolescence Nonlinear Physical Growth in Low- and Middle-Income Countries

Wake

Zewotir

Muluneh

2021

Preprint

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Background: Modeling the growth curve of height has a significant role in understanding the growth trajectories over time and generated mathematical functions that depict the expected height of children at a particular age. However, modeling the mathematical growth functions for physical height is not well studied in low- and middle-income countries. Modeling and identifying nonlinear growth curves that adequately describe the growth trajectories in low- and middle-income countries were the aims of this study. Methods: The data were obtained from the Young Lives study. Longitudinal measures of height from infancy to middle-adolescence were collected from low- and middle-income countries. A number of nonlinear growth trajectories were studied through the family of three-parameter nonlinear mixed-effects models. Results: This study examined the performances of different growth curves for the height growth trajectories. The Logistic curve was chosen among the three-parameter nonlinear growth curves for modeling the growth trajectories from infancy to middle-adolescence. Gender and country have significant effects on the three parameters of growth curves. Males had higher asymptotic height and a lower rate of growth than females. Females reached asymptotic height earlier and shorter at asymptotic height than males. Children with low asymptotic height grow faster than those with higher asymptotic height. Compared to Ethiopian children, Indian and Peruvian children had lower asymptotic height, but Vietnamese children had higher asymptotic height. Ethiopian children approached adult height earlier than Indian children, but later than Peruvian children. However, there was no significant difference in the rate of growth between Ethiopian and Vietnamese children. Conclusions: This study concludes that the Logistic growth curve was found to be the best growth curve to describe the height growth trajectories. Children in Ethiopia, India, Peru and Vietnam showed different growth parameters. Further enhancements may be attained with the incorporation of other plausible covariates.

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“…So, growth pattern usually is typically fitted by models with sigmoidal structure. The study of the growth of a breed and how certain factors such as variety or sex influence it, is necessary to establish the potential for meat productivity (Sariyel et al 2017). Growth can be explained through mathematical functions, which could also predict for the age of sexual maturity or the suitable age for commercial slaughter, while helping monitoring general health conditions and nutritional requirements (Kaplan and G€ urcan 2018).…”

Section: Introductionmentioning

confidence: 99%