The accurate description of the kinetics and robust modeling of biotechnological processes can only be achieved by incorporating reliable methodologies to easily update the model when there are changes in operational conditions. The purpose of this work is to provide a systematic approach with which to perform model parameters screening and updating in biotechnological processes. Batch experiments are performed to develop a mechanistic model, considering the effect of temperature on the kinetics, and further experiments (batch fermentations using sugar cane molasses from a different harvest) are used to validate the effectiveness of screening before parameters updating. The reduction in the number of kinetic parameters to be re-estimated enabled by the screening procedure reduces significantly the complexity of the optimization, which makes the updating procedure to be significantly quicker, while resulting in accurate performance of the updated model.