The INRA dynamic and mechanistic growth model predicts the daily deposition of protein and
fat in growing cattle, based on metabolizable energy (ME) intake (main driven force) and
animal age. Originally developed for specific animal types (breed and sex), the aim of this study
was to calibrate the INRA growth model at the individual level by adjusting coefficients for
either rates of protein and lipid synthesis (α and β) or degradation (γ and δ), or modulation of
the ME use efficiency (cMEU). The relationship between the adjusted model parameters and
residual feed intake (RFI) or feed conversion efficiency (FCE) was further assessed. Individual
performance data (daily ME intake and fortnightly recording of body weight) and estimations
of body composition (d0, d84, d200) were obtained from an in vivo trial on 32 extreme RFI
Charolais bulls fed two contrasting silage-based diets (maize vs grass). The three sets of INRA
growth model parameters (α and β, γ and δ, and cMEU) were adjusted for each animal using
daily ME intake as input, and minimizing model deviation from body lipid and protein masses
estimations (Pay-Off procedure, Vensim 7.3.5). The five adjusted parameters were analyzed by
ANOVA for the effects of RFI, or alternatively by ANCOVA for the covariable FCE. No effect
of diet or its interaction with RFI or FCE was found (P>0.05). The model accuracy was higher
when α and β (average RMSEP of 4.0 kg body lipids or proteins) or γ and δ (3.9 kg) were
adjusted, compared to only cMEU (4.4 kg). As the FCE increased, greater synthesis (α and β)
and lower degradation (γ and δ) rates for both protein (P<0.05) and lipids (P<0.10) were found.
A trend for lower cMEU (greater efficiency of ME use) as FCE increased (r = -0.30; P<0.10)
was also observed. The RFI ranking only impacted the protein synthesis (greater in efficient;
P<0.05) and degradation (lower in efficient; P<0.10) rates in agreement with observations made
during the in vivo study. In conclusion, based on ME inake and body composition estimates,
metabolic parameters adjusted at the individual level in the INRA growth model were
significantly impacted by feed efficiency ranking, especially FCE.
