RESUMO
Carbon-to-nitrogen ratio (CNR) has shown to be a relevant factor in microorganisms growth and metabolites production. It is usual that this factor compromises the productivity yield of different microorganisms. However, CNR has been rarely modeled and therefore the nature of its specific influence on metabolites production has not been understood clearly. This paper describes a parametric characterization of the CNR effect on the Escherichia coli metabolism. A set of parameters was proposed to introduce a mathematical model that considers the biomass, substrate and several byproducts dynamical behavior under batch regimen and CNR influence. Identification algorithm used to calculate the parameters considers a novel least mean square strategy that formalizes the CNR influence in E. coli metabolism. This scheme produced a step-by-step method that was suitable for obtaining the set of parameters that describes the model. This method was evaluated under two scenarios: (a) using the data from a set of numerical simulations where the model was tested under the presence of artificial noises and (b) the information obtained from a set of experiments under different CNR. In both cases, a leave-one-experiment-out cross-validation study was considered to evaluate the model prediction capabilities. Feasibility of the parametric identification method was proven in both considered scenarios.