Introduction to the EFG Broiler model

Features of the EFG Broiler Growth Model

This broiler growth simulation model integrates information about genotype, feed and feeding programme, including controlled feeding, and the environment, allowing the user to answer ‘what-if’ questions about each of these aspects of broiler production. The answers are in terms of growth rate, carcass composition, food consumed and profitability. The model calculates various indices of performance, thus allowing the user to find the most profitable or the most biologically sound method of rearing broilers, depending on the objectives. A diagnostic facility is available which indicates the factors limiting performance during growth.

In addition to simulating growth under different conditions, the model also provides information about potential growth rate and carcass composition of broilers reared under non-limiting conditions. This information is used to determine amino acid requirements on each day of the growing period.

The model is based on theories of food intake and growth which have mostly been published (e.g. Emmans and Fisher, 1986). The best available estimates of the model parameters were obtained from published knowledge, and in some instances, experiments have been conducted, and are currently being conducted, specifically to improve the predictions of the model.

Brief overview of the model

The details required to predict growth and feed intake consist of a description of the breed of bird, the environment in which it will grow, the feeds which will be fed and the method of feeding. Economic details used to analyse financial performance are also optionally included.

Each of these items defined in the current data files is represented by an entry in the inputs tree structure at the top left of the screen. When an item is selected, its details are displayed in the section to the right. Functions applicable to an item such as New, Duplicate or Delete are available by right-clicking the mouse on an item.

Once sufficient input items have been defined, an experiment may be designed by dragging at least one input item of each type into the experiment’s folder of the corresponding type. If more than one item of a particular type is dragged into the experiment, or more than one value is specified for a given variable, then the experiment will have more than one treatment. Once the necessary data have been specified in the experiment, it can be Run, and results viewed in tabular or graphical form.