Non-Linear Model to Describe Growth Curves of Commercial Turkey in the Tropics of Mexico

Segura-Correa, JC; Santos-Ricalde, Ronald; Palma-Ávila, Israel

doi:10.1590/1806-9061-2016-0246

Cited by 7 publications

(14 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The same authors reported residual mean square error (RMSE) to be higher for male turkeys, for which a lower record number was used. By contrast, Richards model fails to converge for males in the present study, which resembles which was previously reported by other authors, such as Segura-Correa et al (2017), for male and female hybrid turkeys and Porter et al (2010) for turkey hens who considered larger samples during longer study periods. This suggests sample limitations in the aforementioned studies may have been a source for erroneous convergence in Richards model.…”

Section: Fitting and Flexibility Criteria Model Comparisonsupporting

confidence: 89%

“…The same trend was reported for mature weight, with it being 50-85% lower in females than in males. In addition, native breeds' weights at 35 weeks (5,553.76 and 11,085.37 g, for females and males, respectively) were lower than those of hybrid genotypes (14.63 and 25.88 g, at 22 weeks for female and males, respectively) (Segura-Correa et al 2017). Higher mature weights in hybrid genotypes may be a consequence of intensive genetic selection.…”

Section: Observed and Predicted Curve Shape Parameter Comparisonmentioning

confidence: 87%

“…In this regard, recent studies have reported Brody model not to converge (Segura-Correa et al 2017), which suggested this model not to be appropriate to estimate growth performance in turkeys. Similarly, Brody model has been deemed as inappropriate to fit for growth performance in other species (Lupi et al 2015).…”

Section: Observed and Predicted Curve Shape Parameter Comparisonmentioning

confidence: 98%

“…Non-linear models have been widely contrasted as suitable methods to fit for growth in turkey hens and sires (Porter et al 2010;P erez-Lara et al 2013;Segura-Correa et al 2017). However, other alternatives, such as mixed models with random and fixed effects, have been formerly suggested in the literature to fit for the same aim (Testik et al 1999).…”

Section: Model Choice Decision Rationalementioning

confidence: 99%

“…Recent studies in turkeys reported better fitting properties, such as for Morgan Mercer Floding, polynomial regression, or Von Bertalanffy (Porter et al 2010;P erez-Lara et al 2013;Segura-Correa et al 2017). Such differences may derive from the specific growth patterns described by the species used in each particular case, breeds considered, or the rearing period during which the study took place (Segura-Correa et al 2017).…”

Section: Fitting and Flexibility Criteria Model Comparisonmentioning

confidence: 99%

See 4 more Smart Citations

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

View full text Add to dashboard Cite

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.

show abstract

Section: Fitting and Flexibility Criteria Model Comparisonsupporting

confidence: 89%

Section: Observed and Predicted Curve Shape Parameter Comparisonmentioning

confidence: 87%

Section: Observed and Predicted Curve Shape Parameter Comparisonmentioning

confidence: 98%

Section: Model Choice Decision Rationalementioning

confidence: 99%

Section: Fitting and Flexibility Criteria Model Comparisonmentioning

confidence: 99%

See 3 more Smart Citations

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

View full text Add to dashboard Cite

show abstract

Guajolote – A poultry genetic resource native to Mexico

Portillo-Salgado

Herrera-Haro

Bautista-Ortega

et al. 2022

World's Poultry Science Journal

View full text Add to dashboard Cite

The effects of feed and energy costs on broiler farm decisions: A dynamic programming approach

Padilla

Liverpool‐Tasie

Myers

2021

Agricultural Economics

View full text Add to dashboard Cite

We explore the decision‐making process of commercial poultry enterprises facing rising input costs in Nigeria. Using a cross‐sectional dataset and a 1‐year weekly panel of farm inputs and prices, we employ a discrete time, discrete control and state space dynamic programming (DP) model, disaggregated by farm size, to determine optimal decisions. In the presence of high feed costs and increased energy use, the optimal strategy for medium‐sized farms is to sell and exit the industry. However, it remains profitable for large firms to stay in the sector. The findings indicate that broiler farms need larger batch sizes to withstand input price increases and rising energy costs. While Nigeria has seen a rapid growth of commercial livestock enterprises, the sensitivity of the poultry industry to changes in feed prices is a major threat to the sector and highlights the importance of acquiring higher batch sizes and employing other risk management tools, such as contracts to forward price input.

show abstract

Non-Linear Model to Describe Growth Curves of Commercial Turkey in the Tropics of Mexico

Cited by 7 publications

References 8 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

Guajolote – A poultry genetic resource native to Mexico

The effects of feed and energy costs on broiler farm decisions: A dynamic programming approach

Contact Info

Product

Resources

About