Active control of the growth trajectory of broiler chickens based on online animal responses.

The objective of the research reported here was to control the growth trajectory of broiler chickens during the production process based on an adaptive compact dynamic process model. More specifically, the daily feed supply was calculated, based on a model-based control algorithm, with the aim of following a previously defined target growth trajectory as close as possible. For the modeling of the dynamic growth response of broiler chickens to the control input, feed supply, an online parameter estimation was used. The developed control algorithm was able to grow the birds according to different target trajectories ranging from restricted (final BW of 1,800 g and 1,945 g in experiments 1 and 3, respectively) to compensatory growth trajectories (final BW of 2,400 g and 2,100 g in experiments 2 and 4, respectively). The mean relative error (MRE) between the different predefined target growth trajectories and the realized growth trajectories ranged from 3.7% to 6.0%. With a few exceptions, the numerical values of feed conversion ratio and mortality after wk 1 were lower and the values of uniformity index were higher in the controlled groups compared with animals fed ad libitum. As a conclusion, it can be stated that integration of dynamic data-based modeling approaches with new hardware and sensing techniques to measure information from the animals should make it possible to control broiler growth trajectories.