Shedding light on phototrophic biomass production of Chlorella variabilis: The importance of dissolved CO2, light intensity and duty cycle.

Abstract

Chlorella variabilis NC64A has recently gathered significant scientific attention due to its unique relationship with the PBCV-1 virus which can potentially simplify downstream processing and reduce associated costs for the bio-production of ethanol or hyaluronan. However, photoautotrophic process optimisation is far from trivial due to the unique characteristics of incident light as a critical process parameter (CPP) and its complex interactions with other CPPs. In the present work, a formalised statistical Design of Experiments (DoE) approach is employed for the multiparametric optimisation of phototrophic growth of C. variabilis in closed, controlled and artificially illuminated batch cultures. Initially, the process design space comprising six CPPs, three related to the quality of incident light and three related to the culture environment, was explored using a fractional factorial screening design. Subsequently, a higher resolution face-centred central composite design involving the three most influential parameters identified from the screening round was used for process optimisation. The optimal growth conditions obtained in the present study (light intensity: 600 µE, spectral composition: white LED, duty cycle: 60%, temperature: 28 °C, pH: 7.1, dissolved inorganic carbon [DIC]: 16.3 mM) resulted in a biomass concentration of 0.749 g/L which represents a 70% increase compared to previously reported efforts.