Evaluation of mathematical models to describe growth of grazing young bulls

Abstract

-The objective of this study was to evaluate the use of different mathematical models to describe growth of grazing beef cattle. Data of 20 Nellore bulls with initial weight of 129±28.1 kg and final weight of 405±62.0 kg were used. The animals were randomly divided into four plots and placed on B. decumbens Stapf pastures. Three plots received concentrate supplement with different protein profiles and the fourth plot received only mineral supplement. Animals were weighed every 28 days to design growth curve of full body weight. Five mathematical models were evaluated to describe animal growth: Multiphase, Linear, Logarithmic, Gompertz and Logistic models. Assessment of adequacy of the models was performed by using coefficient of determination, simultaneous F-test for identity of parameters, concordance correlation coefficient, root of the mean square error of prediction and partition of the mean square error of prediction.The analysis of the pairwise mean square error of prediction and the delta Akaike's information criterion were used to compare the models for accuracy and precision. Evaluation of all the tested models showed that all of them were able to predict variability among animals. However, Gompertz, Logarithmic and Logistic models created individual predictions that were not satisfactory. Models differed from each other concerning accuracy and precision; the best were in the following order: Multiphase, Linear, Gompertz, Logarithmic and Logistic. The Multiphase model was more efficient than the others for description of grazing beef cattle growth.

Effect of supplementation of ewes in the final third of gestation on the development of their lambs

“…The lamb growth curve was adjusted using the Gompertz model. This model is part of a group of non-linear models that have long been employed to describe the growth of living beings (Fernandes et al, 2012) and is one of the most used to describe the growth curve of small ruminants (Sarmento et al, 2006;Sousa et al, 2021). Lewis et al (2002) chose the Gompertz model to adjust the growth curve of Suffolk sheep, because, according to the authors, this model has desirable properties of a growth function.…”

Aspectos relacionados con la importancia del uso de modelos predictivos en la producción ovina. Revisión

“…Dynamic models are those that describe changes that have occurred and the obtained responses as a function of time. The non-linear models used to describe animal growth have a dynamic character (27,28) . Static models, on the other hand, are those that generate a response for a fixed instant, that is, they do not include time as a variable (8) .…”