The key objective for the optimisation of recombinant protein production in bacteria is to optimize the exploitation of the host cell's synthesis potential. Recent studies show that the novel concept of transcription rate control allows the tuning of recombinant gene expression in relation to the metabolic capacity of the host cell. To adjust the inducer-biomass ratio to a tolerable level, real-time knowledge about key process variables is paramount. Since there are no reliable online-sensors for key variables such as biomass or recombinant product, it is necessary to relate available online signals to process variables by mathematical models. To improve chemometric modelling of process variables, dielectric spectroscopy and a multi-wavelength online fluorescence sensor for two-dimensional fluorescence spectroscopy were applied in a series of recombinant Escherichia coli fed-batch cultivations applying two different process operation states. Dielectric spectroscopy signals were closely correlated to biomass, while two-dimensional fluorescence spectroscopy allowed the monitoring of fluorescent biogenic components. Chemometric modelling of key process variables with two different modelling techniques showed that this sensor combination greatly improved the estimation (i.e. reduce error magnitude) of process variables in recombinant E. coli cultivations, thereby enhancing process monitoring capabilities.