Predicting sporulation events in a bioreactor using an electronic nose

An electronic nose (EN) based on a nonspecific multi-sensor array was used to accurately estimate sporulation events and the spore concentration of Bacillus subtilis cultures. The array included 6 metal oxide sensors (MOS), 10 metal oxide semiconductor field effect transistors (MOSFET), one CO2 infrared sensor and One humidity sensor. The EN was used to monitor the gas emissions from B. subtilis bioreactions during both batch and fed-batch operation. The signal pattern produced by the sensors was evaluated by principal component analysis (PCA) and training Cultivations were used to build a model. The arc length of the PCA trajectories was Successfully correlated to 2 the off-line spore count; a strong linear correlation (R-2 = 0.992) between the numerical integration of the curves and the measured spore concentration was established. The fast responses of the sensors in combination with the robust correlation with the off-line determination of spore concentration establish this EN device as a convenient tool for monitoring sporulation events in bioprocesses.