Process intensification for the enhancement of growth and chlorophyll molecules of isolated Chlorella thermophila: A systematic experimental and optimization approach

Abstract

In our current work, we have optimized six physicochemical parameters (light intensity, light period, pH, inoculum size, culture period, and salt concentration) toward growth and chlorophyll synthesis using isolated fresh water microalgae Chlorella thermophila [contains ∼6% (w/w on dry biomass basis) chlorophyll]. Here, both experimental and computational [Taguchi orthogonal array (TOA), artificial neural network (ANN), and genetic algorithm (GA)] approaches were employed for the process intensification. Results revealed that the content of biomass and chlorophyll were enhanced by 118% and 95%, respectively, with productivity enhancement of 30% for biomass and 61% for chlorophyll from the optimization of physicochemical parameters. Further, optimum light intensity was found to be 128 µmol m⁻² s⁻¹ after conducting experiments in optimized chemical and physicochemical conditions, contributing to the enhancement of productivity of 46% for biomass and 106% for chlorophyll. Urea was found to be the most effective nitrogen source with an increase of 70% and 160% biomass and chlorophyll productivity, respectively. Moreover, sucrose as a carbon source contributed to an increase of 97% and 264% biomass and chlorophyll productivity.

Keywords:

• Artificial neural network
• Chlorella thermophila
• genetic algorithm
• chlorophyll
• process engineering
• Taguchi orthogonal array

Disclosure statement

All authors declare that there is no conflict of interest for current research work.

Additional information

Funding

The present work was financially supported by the Science and Engineering Research Board (SERB), Department of Science and Technology, Government of India [Project No. CRG/2018/002479].