Abstract
Abstract. The aim of this study was to determine a mathematical model which can be used to describe the growth of the pig. The study was conducted on 60 pigs (30 barrows and 30 gilts) in the interval between the age of 49 and 215 days. All animals were weighed at 49th day after birth. For the purpose of growth measurements pigs were weighted every 7th day during the experiment. Every 21th day four pigs were selected for the slaughter according to average live weight. By applying the generalised logistic function, the growth of live weight and tissues were described. Thereby optimal parameters in the model were estimated on the basis of measurement data by means of the robust least absolute deviations principle. The prediction of optimum slaughter age/weight, on the basis of such model represent a contribution of this paper to the practice.
Highlights
The pork industry pays for a meat unit exclusively, it is desirable to know until what age/ body weight it is rational to fatten an animal
There are many mathematical models succesfully used for analysis and accurate prediction of the animal growth like logistic (Jukić & Scitovski 2003), von Bertalanfy (Köhn et al 2007), Gompertz (Vouri et al 2006), and various forms of generalised logistic functions (López et al 2000, Scitovski et al 2006)
In some investigations of pig growth which is based on the maximum growth capacity the final weight is determined experimentally
Summary
The pork industry pays for a meat unit exclusively, it is desirable to know until what age/ body weight it is rational to fatten an animal. The changes of body composition during growth are studied using the methods such as dissection of the carcass, computed tomography, magnetic resonance imaging and some other useful techniques at varying age or body weight (Giles et al 2009). It is a complex problem, especially when it comes to a modelling of the growth patterns. There are many mathematical models succesfully used for analysis and accurate prediction of the animal growth like logistic (Jukić & Scitovski 2003), von Bertalanfy (Köhn et al 2007), Gompertz (Vouri et al 2006), and various forms of generalised logistic functions (López et al 2000, Scitovski et al 2006).
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