Comparison of noninvasive, in-situ and external monitoring of microbial growth in fed-batch cultivations in Corynebacterium glutamicum

Automated bioprocess systems rely on accurate online measurements of cellular growth. In the present study, six sensors representing five different technologies, namely near-infrared absorbance, external non-invasive light scattering, back scattering reflectance, dielectric spectroscopy and exhaust gas analysis were evaluated in monitoring growth microbial cell factory Corynebacterium glutamicum. The signal outputs monitored during stationary phase cells under conditions agitation aeration, that pose potential interference with in-situ signals. random noise was filtered using a Gaussian filter time derivatives computed to obtain information rate. Surprisingly, signals most probes fed-batch cultivations C. glutamicum highly correlated stirring, but mostly unaffected by airflow, despite increase air bubbles can cause measurement interference. Taken together, we show an estimation based sensor possible linear multiple regression, correcting for effect rate made implementation filter.