Recursive prediction of broiler growth response to feed intake by using a time-variant parameter estimation method

Abstract

The objective of this study was to explore whether time-variant parameter estimation procedures allow modeling and predicting the dynamic growth response of broiler chickens to feed intake in real time. A recursive linear model was used that estimated the model parameters every 24 h based on a fixed number of actual and past measurements (i.e., time window). Based on 48 datasets, it was concluded that the mean relative prediction error (MRPE) of the recursive linear modeling approach had a minimum for a window size of 5 d. Weight of the birds could be predicted during the growth process 3 to 7 d ahead with a mean relative prediction error of 5% or less. In comparison with the prediction results of three static empirical growth models (one linear and two nonlinear models), the recursive modeling technique had a similar accuracy to the nonlinear empirical models (MRPE of 1.4% to 2.3% vs. 1.1% to 2.8%), but it was less accurate for larger prediction horizons (2 to 7 d). The compact recursive linear model was more accurate than the static linear growth model for prediction horizons of one up to 4 d, depending on the feeding strategy. Since such recursive modeling approach allows the prediction of broiler growth without any prior knowledge of the system and takes into account the time-variant (nonlinear) nature of the growth process based on only a small window of measured information, it is suitable for real-time integration in process management.

Growth characteristics of commercial broiler and native chickens as predicted by different growth functions

“…Dietary ME is a key input that controls broiler growth trajectory (Aerts et al, 2003). In addition, mathematical functions of growth in poultry have played a key role in poultry improvement programmes (Nahashon et al, 2010).…”

“…Growing birds must eat extra feed to provide additional energy for the synthesis of body tissues. On the other hand, dietary energy has been suggested to be the key input that controls broiler growth trajectory (Aerts et al, 2003). Recently, Nahashon et al (2010) demonstrated that dietary protein and energy can affect the growth parameters of the French guinea fowl based on the Gompertz-Laired function.…”

Gompertz-Laird model prediction of optimum utilization of crude protein and metabolizable energy by French guinea fowl broilers

“…Dietary CP and ME have been suggested to be the key inputs that control broiler growth trajectory (Aerts et al, 2003). In addition, mathematical models of growth in poultry have played a key role in poultry improvement programs.…”

Effects of Different Target Trajectories on the Broiler Performance in Growth Control

“…It has been shown that feed restriction resulted in alterations of organs and activities of digestive enzymes, confirming a functional adaptation to feed restriction. Aerts et al (2003a) introduced a procedure that modeled and predicted the dynamic growth response of broiler chickens to feed intake in real time. This approach allowed the prediction of broiler growth without any prior knowledge of the system and took into account the time-variant nature of the growth process of each flock of birds.…”