Abstract A new method of selecting smoothing spline functions is presented and used to curve fit experimental fermentation data. From the curves generated, estimates for the specific growth rate, the specific rate of substrate utilization and the biomass energetic yield are made. Selection of the smoothness parameters is based on minimization of a response surface fit to the smoothness parameters used to generate the time profiles of biomass and substrate concentration. The response modelled is the extent of closure of the carbon balance and the available electron balance. Results obtained using cross validation for selection of the smoothness parameter are also presented, and compared to the results calculated using the response surface technique. Estimates made for specific growth rate and biomass energetic yield are used with the covariate adjustment procedure to calculate point and 95% confidence interval estimates for the true biomass energetic yield, ηmax, and the maintenance coefficient, me. The results show that the spline fit has an effect on the parameter estimates. The newly developed response surface method compares favorably with the cross validation method.