Dataset on growth curves of Boer goats fitted by ten non-linear functions

Application of growth models to South African Boer goat castrates and does under feedlot conditions

Mathematical models may aid researchers in describing biological processes, like growth, in animals. This study aimed to collect the body weight data of 18 Boer goat castrates and 20 Boer goat does, from birth until maturity, to model growth and determine growth trends. This is a novel investigation as sufficient information on an age-weight database for these two Boer goat sexes from birth to maturity, is lacking. Using age-weight data, four nonlinear models, namely the Brody, Gompertz, Logistic and Von Bertalanffy growth models, were plotted and evaluated. The model parameters of each growth model were compared for differences between the two sexes. The statistical effectiveness of fit was determined for each model using AIC and RMSE, with R2 also being considered. All models except the Brody model, predicted significantly heavier mature weights for castrates. The Brody model was deemed unfit to describe Boer goat growth as the function severely over-predict weights from birth until maturity for both sexes. The Von Bertalanffy (R2 = 91.3) and Gompertz functions (R2 = 91.3) showed the best fit for Boer goat castrates, while the Gompertz model (R2 = 95.1) showed the best fit for Boer goat does. The Gompertz function is the preferred model to depict Boer goat growth overall, as it accurately characterized growth of both sexes. According to the Gompertz model the age at which the inflection point of the growth curve was reached, did not differ significantly between castrates and does (141.80 days versus 136.31 days). There was also no significant difference in maturation rate between the two sexes.

Determination of the effect of the dam age, birth type, and sex on growth curve traits of hair goat kids

This study was conducted to investigate the best-fit growth curve and dam age, sex, and birth type effect on growth curve traits of hair goat kids. Monthly 3858 test day body weight (BW) records of 643 hair goat kids from birth to 150 days of age were used to determine the best-fit growth curve and estimate growth curve parameters with Gompertz and Von Bertalanffy models. The BW records were assigned to three groups: dam age (3, 4, 5, 6, 7 years), sex (female, male), and birth type (single, twin). The Gompertz model gave more consistent results than the Von Bertalanffy model according to the goodness of fit criteria. Dam age had no significant effect on any of the growth curve traits. Sex of kids showed a significant effect on maturity index (parameter K) (P < 0.001), estimated mature body weight (parameter A), and weight at point of inflection (IPW) (P < 0.01). Also, birth type had a significant effect on initial/birth weight (parameter B) and parameter K (P < 0.001). Age at point of inflection (IPT) was not affected by any of the factors. Twin kids had a higher maturity index than singles while females higher than males. In conclusion, the Gompertz model was the most suitable model for hair goat kids for selection strategies. For proper selection, the effect of sex and birth type on growth curve traits should be considered by hair goat breeders.

The growth of domestic goats and sheep: A meta study with Bertalanffy-Pütter models

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We studied 122 mass-at-age data for goats, sheep, and wildlife.

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We used Bertalanffy-Pütter models to obtain better fitting growth curves.

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The Brody model had an acceptable fit to 70% of the data.

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For 39% of data the best-fitting BP-model had a discernable inflection-point.

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For these models, maximal weight gain per day was 55% higher than natal weight gain.

Growth literature often uses the Brody, Gompertz, Verhulst, and von Bertalanffy models. Is there a rationale for the preference of these classical named models? The versatile five-parameter Bertalanffy-Pütter (BP) model generalizes these models. We revisited peer-reviewed publications from the years 1970–2019 that fitted growth models to together 122 mass-at-age data of sheep and goats from 19 countries and studied the best-fit BP-models using the least-squares method. None of the named models was ever best-fitting. However, for 70% of the data a single non-sigmoidal model had an acceptable fit (normalized root mean squared error 〈 5% and F-ratio test 〉 5% in comparison to the best-fit): the Brody model. The inherently non-sigmoidal character was further underlined, as there were only 39% of the data, where the best-fitting BP-model had a discernible inflection point. For these data, conclusions of biological interest could be drawn from the sigmoidal best-fit BP-models: the maximal weight gain per day was about 55% higher than the natal weight gain per day.

Evaluation of Growth Curve Models for Body Weight in American Mink

Modelling the growth curves of animals is important for optimizing the management and efficiency of animal production; however, little is known about the growth curves in American mink (Neovison vison). The study evaluated the performances of four three-parameter (Logistic, Gompertz, von Bertalanffy, and Brody), four four-parameter (Richards, Weibull, Bridges, and Janoscheck) and two polynomial models for describing the growth curves in mink. Body weights were collected from the third week of life to the week 31 in 738 black mink (373 males and 365 females). Models were fitted using the nls and nlsLM functions in stats and minpack.lm packages in R software, respectively. The Akaike's information criterion (AIC) and Bayesian information criterion (BIC) were used for model comparison. Based on these criteria, Logistic and Richards were the best models for males and females, respectively. Four-parameter models had better performance compared to the other models, except Logistic model. The estimated maximum weight and mature growth rate varied among the models and differed between males and females. The results indicated that males and females had different growth curves as males grew faster and reached to the maximum body weight later compared to females. Further studies on genetic parameters and selection response for growth curve parameters are required for development of selection programs based on the shape of growth curves in mink.

A unified-models analysis of the development of sexual size dimorphism in Damaraland mole-rats, Fukomys damarensis

Individual variation in growth rates often generates variation in fitness. However, the ability to draw meaningful inferences from growth data depends on the use of growth models that allow for direct comparisons of growth between the sexes, between populations, and between species. Unlike traditional sigmoid functions, a recently parameterized family of unified growth models provides a reliable basis for comparisons since each parameter affects a single curve characteristic and parameters are directly comparable across the unified family. Here, we use the unified-models approach to examine the development of sexual size dimorphism in Damaraland mole-rats (Fukomys damarensis), where breeding males are larger than breeding females. Using skeletal measurements, we show here that the larger size of male Damaraland mole-rats arises from an increased growth rate across the entire period of development, rather than through sex differences in the duration or timing of growth. Male-biased skeletal size dimorphism is not unusual among rodents, and our measures of sex differences in size in captive mole-rats are close to sexual size differences in the wild, where size dimorphism = 1.04 (male:female). We hope our study will encourage the wide use of unified growth models by mammalogists.