Abstract:
The purpose of this study was to develop an advanced investigation strategy for shelf life estimation of
carbonated soft drinks. The strategy was based on the training capability of an Artificial Neural Networks and it has proves
to be very successful. The model developed by using the Back-Propagation Neural Networks and simulations, was used to
predict the variation in the CO2 content of carbonated soft drinks, bottled in PET containers.