Curva De Crescimento De Codornas De Corte Por Meio De Modelos De Regressão Não-Lineares

Silva, Mérik Rocha; Araújo, Cláudio Vieira; Pires, Aldrin Vieira; Paula, Edson Júnior Heitor de; Ferreira, Eric Batista; Silva, Felipe Gomes da

doi:10.5380/avs.v21i4.41571

Cited by 7 publications

(7 citation statements)

References 4 publications

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“…Mota et al (2015) also reported that Gompertz was able to predict growth rate and weight at adulthood of all quail genotypes evaluated, among a total of seven different strains of meat-type and one laying quail strain. In addition to these authors, several others in the literature (Marcato et al, 2010;Narinc et al, 2010;Sakomura et al, 2011;Mazucheli et al, 2011;Grieser et al, 2015b;Rocha-Silva et al, 2016) consider the Gompertz function to be the most adequate for describing growth and deposition of body nutrients in birds.…”

Section: Discussionmentioning

confidence: 99%

Adjustment of nonlinear models and growth parameters and body nutrient deposition in meat-type and laying quail

et al. 2018

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The objective of this study was to determine the adjustment quality of non-linear models and estimate the growth parameters and body chemical composition of a meat-type quail strain (Coturnix coturnix coturnix) and two laying quail strains (Coturnix coturnix japonica), designated yellow and red. The study used 1500 quail, not sexed, distributed in a completely randomized design with three treatments and five repetitions. The experimental period was from 1-42 days of age. The birds were raised in a conventional system and fed ad libitum with a diet formulated to meet their nutritional requirements. Quail were weighed weekly, and a representative sample was slaughtered to evaluate their body chemical composition. The adjustment quality of the models was evaluated by means of the residual mean square (RMS), regression residue squares sum (SSRR), and number of iterations required for convergence. In evaluating the adjustment quality for the body weight of the three strains, the Gompertz, Logistic, and Von Bertalanffy models gave good fit, with Gompertz providing the best adjustment among them. For body composition, the Gompertz and Logistic models were the best, with Gompertz showing a slight superiority. Gompertz is the best model for describing growth curves and body chemical composition of body weight, protein, water, and ash in meat-type quail. In addition, it is the best model for describing growth curves and body chemical composition of body weight of yellow laying quail and of body weight, protein, and ash in red laying quail. Logistic was the best model for describing growth curves and body chemical composition of water, protein, and ash in yellow laying quail, and of water in red laying quail.

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Section: Discussionmentioning

confidence: 99%

Adjustment of nonlinear models and growth parameters and body nutrient deposition in meat-type and laying quail

et al. 2018

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“…DIC statistics of the above-mentioned models indicated that both Gompertz and Richards's functions presented a good fit to the data, being superior to the Logistic model considering the goodness of fit. Gompertz function has also been considered by many authors in the literature as the best option to describe bird growth, relating weight and age (MARCATO et al, 2010;MAZUCHELI et al, 2011;SANTOS, 2014;GRIESER et al, 2015b;MOTA et al, 2015;FINCO et al, 2016;ROCHA-SILVA et al, 2016).…”

Section: Resultsmentioning

confidence: 99%

Growth curves in meat-type and laying quail: a Bayesian perspective

Rossi

Grieser

Conselvan

et al. 2017

SCA

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The aim of this study was to assess the goodness of fit for nonlinear models, using the best model to describe body growth curves, comparing the parameters obtained for gender and one meat-type (Coturnix coturnix coturnix) and two laying (Coturnix coturnix japonica) quail strains, as well as nesting via MCMC (Markov chain Monte Carlo processes) methods under a Bayesian approach. A total of 1,350 one-day-old mixed quail were used: 400 of meat-type, 450 of yellow laying, and 500 of red laying strains distributed in a completely randomized design with three treatments (each treatment corresponded to one strain) and five replications. The experimental period consisted of 1 to 42 days of age. At 21 days of age, quail sexing was performed by means of sexual dimorphism, being individually identified at one day of age with numbered rings, allowing determining growth curves by gender. Birds were reared in a conventional system, fed ad libitum with diets formulated to meet nutritional requirements. Body weight was determined weekly and assessed using nonlinear models: Logistic, Brody, Von Bertalanffy, and Gompertz. DIC (Deviance Information Criterion) criterion was used to select the best nonlinear model, i.e. the lower the DIC value is, the better the model goodness of fit to the data. Gompertz model was better adjusted to the data regardless the gender or strain. Meat-type quail had the highest asymptotic weights and the highest age at which growth rate was maximum, followed by red and yellow strains. All nestings presented significant differences (p < 0.05) between gender for contrasted parameters. Meat-type, yellow, and red females presented values significantly (p < 0.05) higher for asymptotic weight (370, 203, and 215 g, respectively) when compared to males (274, 131, and 143 g, respectively), which were earlier in body growth. Key words: Deviance information criterion. Gompertz equation. Nonlinear models. Body weight. ResumoO objetivo deste trabalho foi avaliar a qualidade de ajuste dos modelos não lineares aos dados, utilizando o melhor modelo para descrever as curvas de crescimento corporal, comparando os parâmetros obtidos para gênero e uma linhagem de codornas de corte (Coturnix coturnix coturnix) e duas de postura (Coturnix coturnix japonica), bem como o aninhamento, via método MCMC (Cadeias de Markov em processos de Monte Carlo), sob o enfoque Bayesiano. Foram utilizadas 1.350 codornas mistas, com um dia de idade, sendo: 400 da linhagem de corte, 450 de postura amarela e 500 de postura vermelha, distribuídas por um delineamento inteiramente casualizado, com três tratamentos (cada tratamento corresponde a uma linhagem) e cinco repetições. O período experimental foi de 1 a 42 dias de idade. Aos 21 dias de idade foi realizada a sexagem por dimorfismo sexual, sendo que elas foram identificadas individualmente com um dia com anilhas numeradas, possibilitando a determinação das curvas de crescimento por gênero. As aves foram criadas em um sistema convencional, alimentadas ad libitum com rações formuladas p...

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“…Eleroğlu, Yıldırım, Şekeroğlu, Çoksöyler, and Duman (2014) verified that logistic model was more suitable to explain the weight of poultry reared in organic systems. On the other hand, in coturniculture, stands out the works of Narinc, Karaman, Firat, and Aksoy (2010), Mota et al (2015) and Rocha-Silva et al (2016), in which they verified that Gompertz model was indicated as the most suitable to explain the weight growth of quails. Mota et al (2015) observed that the logistic model was the most weight growth to explain the weight of quails.…”

Section: Introductionmentioning

confidence: 90%

“…The main phenotypic characteristic of commercial interest in meat quail farming is body weight, which has medium to high heritability mainly during the growth phase (Knížetová, Hyánek, Hyankova, & Bělíček, 1995). Japanese quails are excellent laying, but males have been studied for meat production (Raji, Mbap, & Aliyu, 2014;Rocha-Silva et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Adjusting weight growth curve of male quails <i>Coturnix japonica</i> reared in the semi-arid region of the State of Pernambuco

Lucena

Holanda

et al. 2018

Acta Sci. Anim. Sci.

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This study adjusted different regression models to describe the growth pattern of meat quails from birth to 42 days of age. Data of 300 male quails were used. Weight and height information of all quails were collected weekly from the 1st to the 42nd day of age. Body weight of poultry was subjected to the polynomial, logistic, Gompertz, Weibull, and log-normal regression models. The criteria used to choose the best model to explain the growth curve of quails were the coefficient of determination of the model, Akaike’s information criterion, sum of squared residuals and Willmott’s index. For all the models used, the variables age and height were significant to explain the weight of quails. The polynomial (R² = 99.99%, AIC = 24.68, SSR = 27.5, d = 0.9999) and log-normal (R² = 99.60%, AIC = -17.5, SSR = 107.15, d = 0.9989) models presented the best fit criteria and were recommended to explain the growth of quails.

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Curva De Crescimento De Codornas De Corte Por Meio De Modelos De Regressão Não-Lineares

Cited by 7 publications

References 4 publications

Adjustment of nonlinear models and growth parameters and body nutrient deposition in meat-type and laying quail

Adjustment of nonlinear models and growth parameters and body nutrient deposition in meat-type and laying quail

Growth curves in meat-type and laying quail: a Bayesian perspective

Adjusting weight growth curve of male quails <i>Coturnix japonica</i> reared in the semi-arid region of the State of Pernambuco

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