A Growth Performance and Nonlinear Growth Curve Functions of Large- and Normal-Sized Japanese Quail (&lt;i&gt;Coturnix japonica&lt;/i&gt;)

Haqani, Mohammad Ibrahim; Kawamura, Kensuke; Takenouchi, Atsushi; Kabir, Mohammad Humayun; Nakamura, Yatsuka; Ishikawa, Akira; Tsudzuki, Masaoki

doi:10.2141/jpsa.0200020

Cited by 9 publications

(4 citation statements)

References 34 publications

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“…The R 2 value obtained in the present study and the results of the study are close to each other. Haqani et al (2021) were performed Weibull, Logistic, Gompertz, Richards, and Brody growth curve models for determining the growth male and female Japanese quails. In the study, R 2 , R 2 adj, AIC, BIC, and RMSE were used as goodness-of-fit criteria.…”

Section: Resultsmentioning

confidence: 99%

The Use of Some Nonlinear Functions to Explain Growth in Japanese Quails with Multivariate Adaptive Regression Splines Algorithm

Tirink

Alkan

Arıcı

2022

Turkish JAF Sci.Tech.

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The study aimed was to determine the best nonlinear function describing the growth stages of the Japanese quail breed. To this aim, growth functions such as exponential, logistic, von Bertalanffy, Brody, and Gompertz were used as nonlinear functions is used in the description of the body weight-age relationship of male and female Japanese quails. The Multivariate Adaptive Regression Splines (MARS) data mining algorithm was applied to the individual growth parameters obtained from the determined as the best fit model, and the relationship between sex and growth parameters with it has been revealed. The study dataset was 1267 body weight-age records collected from the hatching to the 6th week of age of 181 Japanese quails consisting of 90 females and 91 males. Each model was applied separately for both males and females. Model fit criteria such as coefficient of determination (R2), adjusted coefficient of determination (R2adj), Akaike's information criterion (AIC), and Bayes information criterion (BIC) were used to evaluate the performances of the growth functions used individually. All the statistical analyses were made by the R package program. The growth curve models were ranked in the form of Logistic > Gompertz > von Bertalanffy > Brody > Exponential according to the goodness of fit criteria. The most suitable model among the non-linear models in terms of performance was logistic. When the relationship between the growth curve parameters and body weight of the logistic model was explained with the MARS algorithm, the goodness of fit criteria showed that the obtained MARS model showed reliable performance. In addition, Pearson’s correlation coefficient between real and estimated body weight was found quite strong for the MARS algorithm (r=0.935). The results showed that the MARS algorithm can be presented as a good reference for breeders to establish breed standards and selection strategies for Japanese quails in growth parameters for breeding purposes.

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Section: Resultsmentioning

confidence: 99%

The Use of Some Nonlinear Functions to Explain Growth in Japanese Quails with Multivariate Adaptive Regression Splines Algorithm

Tirink

Alkan

Arıcı

2022

Turkish JAF Sci.Tech.

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“…In addition to the above three parents and nine F 1 females, the phenotypic values of 97 parents and 16 F 1 females were used for comparison. Chick management and food supply were in accordance with a previous study [ 61 ]. Newly hatched chicks were leg-banded and weighed before being moved to heated brooders, where they were reared until 4 weeks of age.…”

Section: Methodsmentioning

confidence: 99%

Mapping of Quantitative Trait Loci Controlling Egg-Quality and -Production Traits in Japanese Quail (Coturnix japonica) Using Restriction-Site Associated DNA Sequencing

Haqani

Nomura

Nakano

et al. 2021

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This research was conducted to identify quantitative trait loci (QTL) associated with egg-related traits by constructing a genetic linkage map based on single nucleotide polymorphism (SNP) markers using restriction-site associated DNA sequencing (RAD-seq) in Japanese quail. A total of 138 F2 females were produced by full-sib mating of F1 birds derived from an intercross between a male of the large-sized strain with three females of the normal-sized strain. Eggs were investigated at two different stages: the beginning stage of egg-laying and at 12 weeks of age (second stage). Five eggs were analyzed for egg weight, lengths of the long and short axes, egg shell strength and weight, yolk weight and diameter, albumen weight, egg equator thickness, and yolk color (L*, a*, and b* values) at each stage. Moreover, the age at first egg, the cumulative number of eggs laid, and egg production rate were recorded. RAD-seq developed 118 SNP markers and mapped them to 13 linkage groups using the Map Manager QTX b20 software. Markers were spanned on 776.1 cM with an average spacing of 7.4 cM. Nine QTL were identified on chromosomes 2, 4, 6, 10, 12, and Z using the simple interval mapping method in the R/qtl package. The QTL detected affected 10 egg traits of egg weight, lengths of the long and short axes of egg, egg shell strength, yolk diameter and weight, albumen weight, and egg shell weight at the beginning stage, yellowness of the yolk color at the second stage, and age at first egg. This is the first report to perform a quail QTL analysis of egg-related traits using RAD-seq. These results highlight the effectiveness of RAD-seq associated with targeted QTL and the application of marker-assisted selection in the poultry industry, particularly in the Japanese quail.

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“…Similar findings of significant (p<0.01) sex effect on 5 week body weight was reported by Pourtorabi et al (2017) where males (206.73±1.23 g) had comparatively lower body weights than females (215.03±1.39 g). Recently Haqani et al, (2021) reported non-significant effect of sex on hatch weight across generations. However, significant differences were observed at 1wk in different generations with the exception of F1 (NS  LS ) generation.…”

Section: Effect Of Gendermentioning

confidence: 99%

“…Initial growth, age and weight at sexual maturity and egg production are major factors which draw particular attention in selection of the birds (Sezer et al 2006). Several studies in past highlighted the importance of non-genetic factors on different performance traits in quails (Bagh et al 2016, Chimezie et al 2017, Taskin et al 2017, Al-Kafajy et al 2018, Haqani et al 2021. However, these has to be reevaluated with time and place for making appropriate selection decisions pertaining to different environmental conditions.…”

Section: Introductionmentioning

confidence: 99%

Effect of Non-genetic Factors on Growth and Production Traits in Two Strains of Japanese Quails

Sharma¹,

Sahoo²,

Dash³

et al. 2023

ASD

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Background: The growth of birds is a function of both genetics and environment involving change leading into improvement in weight, shape, size, volume, etc. Study of important non-genetic factors is important in view of formulating future selection and breeding strategies in different poultry species. Methods: The present study was done on 1246 numbers of Japanese Quails (Coturnix coturnix japonica) of two strains i.e., black and white distributed in three generations during 2020-21. The fixed effects of gender, season of hatch, strain and generations on various fortnightly body weights (FNBW), average daily weight gain (ADWG), relative growth rate (RGR) and some production traits were studied. Result: Significant (p≤0.01) differences in black and white strain as well as male and female quails for hatch weights were observed. The maximum ADG was during 4th to 6th wk whereas the RGR was highest during first fortnight (hatch-2nd wk). Significantly (p≤0.01) higher average egg weights (AEW) were observed in white quails. Part egg production (PEP) and AEWs were higher during summer and winter hatches, respectively. The present investigation elucidates the significance of different non-genetic factors on important growth and production performances for further selection in quails.

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A Growth Performance and Nonlinear Growth Curve Functions of Large- and Normal-Sized Japanese Quail (<i>Coturnix japonica</i>)

Cited by 9 publications

References 34 publications

The Use of Some Nonlinear Functions to Explain Growth in Japanese Quails with Multivariate Adaptive Regression Splines Algorithm

The Use of Some Nonlinear Functions to Explain Growth in Japanese Quails with Multivariate Adaptive Regression Splines Algorithm

Mapping of Quantitative Trait Loci Controlling Egg-Quality and -Production Traits in Japanese Quail (Coturnix japonica) Using Restriction-Site Associated DNA Sequencing

Effect of Non-genetic Factors on Growth and Production Traits in Two Strains of Japanese Quails

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