Animal breeding and the agricultural sciences overall started back in the 19th century to develop mathematical functions to simulate growth of organisms. Many models had been introduced and additionally modified in thousands of varieties. But until now nothing proofed to be the best.
The aim of this thesis was to test the main growth models on a multitude of heterogeneous datasets from the main groups of farm animals, poultry, cattle and pigs possible, to show their intrinsic properties with changing qualities of the datasets.
Therefore it was also originally intended to add static datasets to the dynamic ones, but was given up, because they didnt bring any further information. May be they were simply substituted by the measured time and not focused on a special scope of the growing process e.g. tissues like fat or bones.
The main rules for the choice of the selected models were provided by WELLOCK et al. (2004). The limitations of parameters which are enough for a calculated growth process are an important part for a useful handling of the problem.