Comparison of growth curves using non-linear regression function in Japanese quail

Kaplan, Selçuk; Gürcan, Eser Kemal

doi:10.1080/09712119.2016.1268965

Cited by 55 publications

(55 citation statements)

References 20 publications

(28 reference statements)

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“…The estimated values of 1.03 for m parameter in Richards model in male data ( Table 5) indicated that Richards model had close performance to Logistic model. The Richards model was also reported to be superior to other models for body mass in several studies in birds [35,36]. The same values of AIC and BIC were obtained for Weibull, Bridges and Janoscheck models in the current study.…”

Section: Discussionsupporting

confidence: 84%

Evaluation of Growth Curve Models for Body Weight in American Mink

Ngoc

Miar

2019

Animals

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Simple Summary: Understanding the animal growth is important for optimized management and feeding practices as well as genetic improvement of animals; however, little is known about the growth of mink raised in Canada. This study evaluated the performances of ten models to find the best models describing the growth curves in mink. The results showed that Logistic and Richards were the best model for males and females, respectively. Growth curves were different between males and females. These results suggested that Richards model can be used for modelling the mink growth and modelling might be performed separately for male and female individuals.Abstract: 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 for 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.

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Section: Discussionsupporting

confidence: 84%

Evaluation of Growth Curve Models for Body Weight in American Mink

Ngoc

Miar

2019

Animals

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“…In addition, they concluded that selection did not change the shape of the growth curve in females. Kaplan and Gürcan (2018) reported similar conclusions for the selection impact on the shape of the growth curve in Japanese quail.…”

Section: Growth Curve Parameters (Fixed)supporting

confidence: 61%

“…On the other hand, Beiki et al (2013) found that the Richards model was better than other models in fitting growth data of Japanese quail in both sexes. Kaplan and Gürcan (2018) suggested the Gompertz model as the second best, after the Richards model, for fitting growth data of Japanese quail.…”

Section: Goodness Of Fitmentioning

confidence: 99%

Modelling of growth alteration in Japanese quail after a selection experiment for body weight at 4 weeks of age

2018

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The current study investigated the influence of selection for body weight (BW) on growth curve parameters in two lines of Japanese quail through a mixed model approach. Live BWs of 1400 Japanese quail were recorded at 3-day intervals from hatching to 42 days of age. Birds were distributed equally across lines (selected and control) and sexes (male and female). The asymptotic weight parameter (β0) values were always higher in Gompertz than Richards models in both lines. The values of β0 were higher in the selected than control lines and in females than males across models. Differences were found in the inflection point for age and weight across lines and sexes. Values of the growth rate parameter (β2) ranged from 0.06 to 0.10 in both models, favouring males over females in both lines. Lower weights at the inflection point of both models were observed in the control line. Determination coefficient (R2) of both models in different genetic groups and sexes was similar. Mean square error (MSE) values of the Gompertz model were lower for females in selected v. control lines. In contrast, MSE values of the Richards model were lower for selected males v. control males. According to the criteria of choice (highest R2 and lowest MSE, Akaike information criterion and Bayesian information criterion), the Richards model was considered the best fitting model for the growth data of males, while the Gompertz model was the best for growth data of female quails in both lines.

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“…Animal growth is a complex physiological and morphological process from hatching to maturity. It is defined as the increase in BW and organ size per unit of time or age ( Yang et al., 2006 , Kaplan and Gürcan, 2018 ). Animal growth has been summarized using mathematical equations or growth curves that result in mathematical parameters that are biologically interpretable ( Tzeng and Becker, 1981 , Aggrey, 2002 , Yang et al., 2006 ).…”

Section: Introductionmentioning

confidence: 99%

Comparison of four nonlinear growth models in Creole chickens of Mexico

et al. 2020

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Animal growth is a complex and dynamic process that involves physiological and morphological changes from hatching to maturity. It is defined as the increase in body size per time unit. Mathematical functions, called growth models, have been used to explain growth patterns. The aim of this study was to compare the Gompertz-Laird, logistic, Richards, and Von Bertalanffy growth models to determine which best fits the data of the Creole chickens ( CC ). Three hundred forty-seven CC were individually weighed from hatching until 177 D of age. Birds were fed a starter diet (0–18 D of age; 19% crude protein ( CP ) and 3,000 kcal of ME/kg) and grower diet (19–177 D of age; 18% CP and 2,800 kcal of ME/kg). Data were analyzed using PROC NLIN to fit the nonlinear growth curve. The coefficient of determination ( R 2 ), Akaike information criteria ( AIC ), and Bayesian information criteria ( BIC ) were used to compare the goodness of fit of the models. The Von Bertalanffy (R 2 : 0.9382, 0.9415; AIC: 2,224.1, 2,424.8; BIC: 2,233.5, 2,434.3, for females and males, respectively) was the model that best explained growth of the birds. On the other hand, both the Gompertz-Laird and logistic models overestimated hatching BW and underestimated the final BW of CC. Females reached age of maximum growth faster than males. The asymptotic weight was higher in males (3,011 g) than in females (2,011 g). Body weight at inflection point was 892 g at 64 D of age for males and 596 g at 54 D for females. In conclusion, the best fit of the data was obtained with the Von Bertalanffy growth model; the information is intended to serve as the basis for utilizing CC.

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Comparison of growth curves using non-linear regression function in Japanese quail

Cited by 55 publications

References 20 publications

Evaluation of Growth Curve Models for Body Weight in American Mink

Evaluation of Growth Curve Models for Body Weight in American Mink

Modelling of growth alteration in Japanese quail after a selection experiment for body weight at 4 weeks of age

Comparison of four nonlinear growth models in Creole chickens of Mexico

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