Comparison of three non-linear models
for describing Japanese quail growth curve

Sezer, Metin; Tarhan, Sefa

doi:10.22358/jafs/67020/2005

Cited by 7 publications

(15 citation statements)

References 12 publications

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“…Overall, regardless of genotype, male chicken had higher adult body weights W f , lower maturing rates and reached the point of maximum growth later than female chicken. This finding is in agreement with the results of Narinc et al(2010) and Ali et al (2002) who reported that irrespective of genotype or the rearing system, male birds had higher adult body weights W f and lower maturing rates k. Such a negative correlation between W f and k could be expected (Mignon-Grasteau et al 2000) for the growth curves that have similar shape parameters because the rate of maturation together with the shape parameter determines the speed of the curve to reach the asymptotic body weight (Sezer and Tarhan 2005).…”

Section: Discussionsupporting

confidence: 92%

“…Age and weight at the inflection point were estimated high for male populations in this study compared to the females. This extension of the acceleration time may also explain the increase in the estimated mature body weight W f for the males (Sezer and Tarhan 2005 (Knížetová et al 1991) but higher than the 44.4 days (Goliomytis et al 2003) and48.9 days (N'dri et al 2006) estimated for male broilers, label-type chickens and White Leghorns, respectively, which all however used the Gompertz model. Generally, purebreds and unselected populations take a relatively longer time to reach the point of maximum growth or inflection than broilers and random-bred chickens due to the different genetic constitutions (Goliomytis et al 2003).…”

Section: Discussionmentioning

confidence: 87%

“…On the other hand, n parameters for females SASSO T44 chicken were closer to the Gompertz model than the logistic model (Sezer and Tarhan 2005). Brisbin et al (1987) suggested that n has a greater propensity to change in response to environmental changes than the asymptotic weight or growth rate and may be used to study the effects of environmental stress on growth.…”

Section: Discussionmentioning

confidence: 94%

“…Although there is no data on the growth performance of SASSO T44 chickens in Ghana, the average body weight of SASSO T44 in this study at 12 weeks was 1.5 kg compared to 2 kg at the same age in France (SASSO 2010) and this can be attributed to the effect of genotype-environment interaction. Differences between specific growth rates of local and SASSO T44 chicken in early part of developmental period may indicate correlated differences in asymptotic weight W f (Sezer and Tarhan 2005). The forest and Savannah chicken like most tropical chicken are adapted to the local environment.…”

Section: Discussionmentioning

confidence: 99%

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Characterisation of local Ghanaian chickens: growth performance evaluation based on Richards growth model and genetic size scaling

Osei-Amponsah

Kayang

Naazie

et al. 2011

Trop Anim Health Prod

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The Richards growth model was fitted to body weight-age data of local and SASSO T44 chickens to describe their growth performance. Males had higher (P < 0.05) asymptotic mature weights than females. Within the local chicken population, birds from the savannah zone had higher (P < 0.05) asymptotic mature weights compared to forest chicken which ironically had higher body weights at hatch. Male local chicken had lower maturing rates compared to the females. Female local chicken were superior to SASSO T44 females in terms of maturing rate. On the average, local chickens took relatively longer time (78.4-83.3 days) to reach the point of inflection than the SASSO T44 population (74.2-79.8 days). However, there were no significant differences (P > 0.05) in the age at inflection among local chicken populations. The shape parameter for SASSO T44 chicken (0.053-0.370) and maturation rate for local chicken (0.177-0.198) were the most critical parameters. Scaling the body weights into degree of maturity highlighted the degree to which genotypes matured over time. Female chickens had the highest (P < 0.05) degree of maturity at all ages. The local chicken populations were also metabolically older than SASSO T44 chickens. Results of this study provide an opportunity to develop breeding strategies for local chicken by modifying either management practices or their genetic makeup to positively affect their growth and productivity.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 87%

Section: Discussionmentioning

confidence: 94%

Section: Discussionmentioning

confidence: 99%

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Characterisation of local Ghanaian chickens: growth performance evaluation based on Richards growth model and genetic size scaling

Osei-Amponsah

Kayang

Naazie

et al. 2011

Trop Anim Health Prod

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“…It is supposed that these marker genes do not affect the growth pattern in poultry (12), whereas the effect of the roux plumage color mutation on growth was reported by Minvielle et al (16). The results of several studies showed that selection of the growth function must be strainspecific (12,20). The present study was undertaken to compare growth patterns of quail strains using nonlinear functions.…”

mentioning

confidence: 99%

Comparative study of growth patterns in seven strains of Japanese quail using nonlinear regression modeling

Faraji-Arough¹,

Rokouei²,

Maghsoudi³

et al. 2018

Turk J Vet Anim Sci

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The aim of this study was to compare the growth pattern of seven strains of Japanese quail including Wild, Italian Speckled, Tuxedo, Scarlett, English white, White button, and A&M Texas by nonlinear growth functions including Gompertz, Richards, logistic, Lopez, and Weibull functions. The body weights of the unselected randomly bred populations of these strains were measured weekly from 1 to 42 days of age and then used to fit functions. The fitness of each function was assessed by statistics including the mean square error, Akaike information criterion, Bayesian information criterion, and adjusted coefficient of determination. The results showed that Gompertz was the best function for describing the growth curve in Italian Speckled and Wild strains; however, the best function for the other strains was the logistic function. The maximum and minimum values for age and weight at the inflection point were obtained for the White button and Scarlett strains, respectively. The weight to age ratio at the inflection point was maximized for Italian Speckled. The best growth rate was observed for the Italian Speckled strain, whereas the White button strain exhibited the worst growth rate. In conclusion, the Italian Speckled strain had the best properties among the tested strains for breeding as broiler poultry. Research ArticleThis work is licensed under a Creative Commons Attribution 4.0 International License. 442FARAJI-AROUGH et al. / Turk J Vet Anim Sci specific fixed marker genes for plumage color, eggshell color, and brooding groups making similar colonies. It is supposed that these marker genes do not affect the growth pattern in poultry (12), whereas the effect of the roux plumage color mutation on growth was reported by Minvielle et al. (16). The results of several studies showed that selection of the growth function must be strainspecific (12,20). The present study was undertaken to compare growth patterns of quail strains using nonlinear functions. Materials and methodsThe experiment was performed in the Research Center of Special Domestic Animals (RCSDA), Research Institute at University of Zabol, Zabol, Iran. A total of 470 one-day-old Japanese quails including Wild (n = 83), Italian Speckled (n = 136), Scarlett (n = 41), Tuxedo (n = 44), White button (n = 31), English white (n = 64), and A&M Texas (n = 71) strains were obtained from the genetic stock of the RCSDA hatchery from unselected and randomly mating parents. On hatching day, all chicks were identified by wing bands, and they were fed a normal diet containing 250 g CP/kg and 2900 kcal J ME/kg. The birds had ad libitum access to feed and water throughout the experiment. A lighting schedule of 23:1 h (light:dark) was used during the experiment. Room temperature was scheduled to drop gradually from 35 °C the first week to 20-25 °C for the following weeks. Body weights of the birds were recorded weekly. The records for quails that died before 42 days of age were excluded from the analyses.Five nonlinear functions including the Gompertz, Richards, logistic, ...

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Multiphasic nonlinear mixed growth models for laying hens

et al. 2020

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Appropriate evaluation of BW and gain during rearing is required for optimal extended laying performance in laying hens. The objective of this study was to compare monophasic, diphasic, and triphasic Gompertz and logistic models describing BW and gain in individually fed free-run laying hens and to study the variation between individuals in shape parameters. Fifteen Lohmann Brown Lite hens were fed ad libitum from week 0 to 43 with a precision feeding system, measuring feed intake and BW individually in a group housed setting. Random variables related to mature weight and timing of maximum gain during the pubertal growth phase were introduced into the multiphasic model for BW with the best fit. For both the weight-age and gain-age functions, the diphasic and triphasic Gompertz and logistic model models fitted the data better than the monophasic models. The Gompertz model was able to identify the ages at the highest gain at similar time points for both BW and gain, whereas the logistic models failed to do so. The derivative of the multiphasic Gompertz models for the gain-age relationship identified age at the highest gain at similar ages as compared with the logistic models for gain. The mixed models predicted that the individual mature BW ranged from 1.83 kg to 2.10 kg and the variability in the timing of the highest rate of gain during the pubertal growth spurt ranged from 15.26 wk to 19.79 wk. Including random terms associated with the mature BW and the second inflection point of the diphasic Gompertz growth model allowed for identification of variability in the growth curve shape between individuals, which can be a tool to study the relationship between the individual growth curve shape and performance parameters.

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Comparison of three non-linear models for describing Japanese quail growth curve

Cited by 7 publications

References 12 publications

Characterisation of local Ghanaian chickens: growth performance evaluation based on Richards growth model and genetic size scaling

Characterisation of local Ghanaian chickens: growth performance evaluation based on Richards growth model and genetic size scaling

Comparative study of growth patterns in seven strains of Japanese quail using nonlinear regression modeling

Multiphasic nonlinear mixed growth models for laying hens

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