A sinusoidal equation as an alternative to classical growth functions to describe growth profiles in turkeys

Kuhi, H. Darmani; López, S.; Mohit, A.; Shabanpour, A.; Hosssein-Zadeh, Navid Ghavi; Falahi, S.

doi:10.4025/actascianimsci.v41i1.45990

Cited by 4 publications

(3 citation statements)

References 17 publications

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“…The Sinusoidal model did not converge for both sexes in the present study, even if contextually, recent studies conducted in turkeys have reported the Sinusoidal model to be the best-fitting model for growth (Kuhi et al 2019). These differences may be a consequence of the properties of the data that was used, since Kuhi et al (2019) used average values, while in the current study, the results were obtained from individual observations taken from the studied population.…”

Section: Fitting and Flexibility Criteria Model Comparisoncontrasting

confidence: 84%

“…Table 2 presents the functions for the seven non-linear models selected in the present study which were namely; Richards, Brody, Logistic, Verhulst (a variant of Logistic model), Gompertz, Sinusoidal, and Von Bertalanffy (Ersoy et al 2006;Nogales et al 2017;Kuhi et al 2019). The fitting procedure was developed using multiple observations of the dependent variable (weight) for each point of the independent variable (day of life).…”

Section: Model Developmentmentioning

confidence: 99%

“…The curve shape parameters considered (three for all models except from Richards model with four) were as follows: 'a', mature or asymptotic weight reached when time tends to infinity; 'b', integration constant that allows to calculate the inflexion age, that allows to calculate the inflexion age; 'k', which represents the exponential growth rate and 'm' which denotes the shape of the growth curve and determines the inflection point, when the animal starts the auto-deceleration stage until it reaches adult (Darmani . For the sinusoidal model, parameters were: 'a 1 ', weight at inflexion; 'a 2 ', the overall rate parameter of the total growth development; 'h', the phase shift (Kuhi et al 2019). The most appropriate model was chosen as suggested by Lupi et al (2015) and Pizarro et al (2020a ) considering the following best fitting and flexibility criteria:…”

Section: Model Developmentmentioning

confidence: 99%

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Comparison of non-linear models to describe the growth in the Andalusian turkey breed

Arbulu

Ariza

Lupi

et al. 2021

Italian Journal of Animal Science

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Seven non-linear growth models were compared in the Andalusian turkey, an endangered native breed. To this aim, turkeys were weekly weighted until they reached 35 weeks. The goodness-of-fit and flexibility criteria of Brody, Von Bertalanffy, Verhulst, Logistic, Gompertz, Richards, and Sinusoidal growth models were evaluated to quantify their ability to describe the biological growth curve. Goodness-of-fit criteria were assessed comparing the mean squared error (MSE) and adjusted determination coefficient (Pseudo-R 2 ), while the flexibility criteria of Akaike (AIC) and Bayesian information criteria (BIC) were evaluated to quantify the explanatory and predictive ability of the models tested. Afterward, all criteria were considered in a combined index to determine the most efficient model to describe and predict growth patterns. The best-fitting model for males growth was Logistic (MSE: 250,349.87; Pseudo-R 2 : 0.97) which also reported the best explanatory and predictive properties (AIC: 18,949.25; BIC: 18,963.24), while best goodnessof-fit criteria, explanatory and predictive capacity in females were reported for the Richards model (MSE: 144,432.45; Pseudo-R 2 : 0.95; AIC: 17,529.83; BIC: 17,549.02, respectively). Von Bertalanffy and Richards models underestimated the weight at early age stages, contrary to Logistic and Verhulst models. The asymptotic weight was higher in males than in females at all evaluated models, being 11,085.37 g for Logistic and 5,706.38 g for Richards, respectively. In conclusion, a marked sexual dimorphism is evident, with females reaching maturity earlier than males. The higher inflection point in males may enable their relatively easier commercial standardisation than in turkey hens. HIGHLIGHTSLogistic was the best fitting model for males' growth and Richards for females. Females reach maturity earlier than males with higher rates of maturity. Andalusian turkey breed shows an intense sexual dimorphism.

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Section: Fitting and Flexibility Criteria Model Comparisoncontrasting

confidence: 84%

Section: Model Developmentmentioning

confidence: 99%

Section: Model Developmentmentioning

confidence: 99%

See 1 more Smart Citation

Comparison of non-linear models to describe the growth in the Andalusian turkey breed

Arbulu

Ariza

Lupi

et al. 2021

Italian Journal of Animal Science

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Introducing a sinusoidal equation to describe lactation curves for cumulative milk yield and composition in Holstein cows

Hossein-Zadeh

Kuhi

López

2020

Journal of Dairy Research

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The aim of the work reported here was to investigate the appropriateness of a sinusoidal function by applying it to model the cumulative lactation curves for milk yield and composition in primiparous Holstein cows, and to compare it with three conventional growth models (linear, Richards and Morgan). Data used in this study were 911 144 test-day records for milk, fat and protein yields, which were recorded on 834 dairy herds from 2000 to 2011 by the Animal Breeding Centre and Promotion of Animal Products of Iran. Each function was fitted to the test-day production records using appropriate procedures in SAS (PROC REG for the linear model and PROC NLIN for the Richards, Morgan and sinusoidal equations) and the parameters were estimated. The models were tested for goodness of fit using adjusted coefficient of determination $\lpar {R_{{\rm adj}}^2 } \rpar $, root mean square error (RMSE), Akaike's information criterion (AIC) and the Bayesian information criterion (BIC). $R_{{\rm adj}}^2 $ values were generally high (>0.999), implying suitable fits to the data, and showed little differences among the models for cumulative yields. The sinusoidal equation provided the lowest values of RMSE, AIC and BIC, and therefore the best fit to the lactation curve for cumulative milk, fat and protein yields. The linear model gave the poorest fit to the cumulative lactation curve for all production traits. The current results show that classical growth functions can be fitted accurately to cumulative lactation curves for production traits, but the new sinusoidal equation introduced herein, by providing best goodness of fit, can be considered a useful alternative to conventional models in dairy research.

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Comparison of nonlinear functions to describe lactation curves for cumulative milk production in buffalo

Darmani Kuhi,

López,

Ghavi Hossein-Zadeh

et al. 2024

Journal of Dairy Research

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The aim of this study was to examine the suitability of different growth functions (linear, sinusoidal, Gompertz, Schumacher and Richards) to fit cumulative milk production data from buffalo cows. Cumulative milk production at each day in milk was calculated from two published datasets reporting (i) fortnightly test-day milk yield records of the first lactation of Murrah buffalo that had calved during 1977–2012 and (ii) the first lactation records of Jaffarabadi buffalo collected from history-cum-pedigree registers for each quinquennium between 1991 and 2010. Each function was fitted to the lactation curves using nonlinear regression procedures. The Richards and sinusoidal equations provided the smallest root mean square error values, Akaike's and Bayesian information criteria and, therefore, the best fit for the cumulative lactation curves for milk yield. The Richards equation appeared to provide the most accurate estimate of the cumulative milk production at peak milk yield. Sinusoidal and flexible classical growth functions are appropriate to describe cumulative milk production curves and estimate lactation traits in buffalo.

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A sinusoidal equation as an alternative to classical growth functions to describe growth profiles in turkeys

Cited by 4 publications

References 17 publications

Comparison of non-linear models to describe the growth in the Andalusian turkey breed

Comparison of non-linear models to describe the growth in the Andalusian turkey breed

Introducing a sinusoidal equation to describe lactation curves for cumulative milk yield and composition in Holstein cows

Comparison of nonlinear functions to describe lactation curves for cumulative milk production in buffalo

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