Features to be aware of when using the model

The model simulates the growth of one bird, representative of the breed, and not a population. This has important implications in measuring the response of the bird to increasing inputs of an amino acid, for example, where the shape of the response curve will not be asymptotic, as is typical of a population response (see Fisher, Morris and Jennings, 1973).

If the growth of a population of birds is required, the model can be run several times. This can be accomplished using the experiment option, and using different values for the parameters of the bird that are thought to vary between individuals (see Emmans and Fisher, 1986, for estimates of the coefficients of variation of these parameters). By accumulating the results from these simulations, copying them to the clipboard and then pasting them to a spreadsheet, the necessary calculations can be done outside of the model.

One of the advantages of simulation modelling is that the available information on the subject is collected together in a usable form. However, there are certain aspects of the simulation process for which little or no information is available. This means that the model cannot be regarded as being absolutely accurate under all conditions. This problem is currently being addressed, with the aid of specific experiments that are designed to test the theory, and to provide numbers that will make the theory work more accurately. The model will be updated continually, whenever such information becomes available.

The potential growth rate of the bird is a critical feature of the model. It is essential therefore that the user accurately assesses the genotype of the breed being simulated. The parameters needed to describe the genotype are given in a breed. If values for these parameters are not known, it is dangerous to guess them. Rather use default values, or attempt to obtain values for the breed from the breeding company or from EFG Software.

Because the mortality within a flock of broilers is unlikely to be the same from batch to batch, the anticipated mortality has been simplified in this model by means of a process that describes mortality as a pattern. This pattern is based on a paper by Grosskopf and Matthäus (1990).

The rate of mortality is often highest at the beginning of the rearing period (due to such factors as chilling, inability to find food or water, mushy chick disease, etc.). It declines as the birds age, and then increases once more as the birds become bigger and older, due to factors such as overcrowding, leg weakness, stress due to vaccinations and diseases. It is important to differentiate between mortality that occurs early in the growing period and that which occurs towards the end of the growth period as these make substantial differences to the profitability of the enterprise as well as determining whether stocking density will limit growth rate.