  We present an algorithm for the continuous monitoring of the biomass and
ethanol concentrations and moreover the kinetic rate in the Mezcal fermentation
process. This algorithm performs its task having only available the on-line
measurements of the redox potential. The procedure includes an artificial
neural network (ANN) that relates the redox potential to the ethanol and
biomass concentrations. Then a nonlinear-observer-based algorithm uses the
biomass estimations to infer the kinetic rate of this fermentation process. The
method shows that the redox potential is a valuable indicator of microorganism
metabolic activity during the Mezcal fermentation. In addition, the estimated
kinetic rate can be considered as a direct evidence of the presence of mixed
culture growth in the process. In this work, the detailed design of the
software-sensor is presented, as well as its experimental application at the
laboratory level
