Dynamic Data-based Modelling of Heat Production and Growth of Broiler Chickens: Development of an Integrated Management System

An application of modern process control techniques to poultry production is outlined. Compact dynamic data-based models are proposed to describe and control the metabolic response of broiler chickens to the micro-environment. The dynamic response of heat production to step changes in air temperature and light intensity could be modelled with an average coefficient of determination RT2 of 0·83 and 0·93, respectively. Using recursive parameter estimation techniques, the time-variant response of animal growth to food supply could be predicted on-line with a maximum prediction error of 5%, 3–7 days ahead depending on the type of feeding schedule. Compact data-based models were shown to be suitable for control of broiler growth. Overall, the studies suggest that the potential conflicts between the environmental, financial and biological pressures on sustainable poultry production can be resolved through the development of integrated management systems using modern process control techniques.