Enhancement of growth and biomolecules (carbohydrates, proteins, and chlorophylls) of isolated Chlorella thermophila using optimization tools

Abstract

The production of multiple products from microalgae is essential for economic sustainability and the knowledge of optimum cultivation conditions for high growth and biomolecule synthesis of a microalgal strain is the prerequisite for its commercial production. In this work, optimization of nutrient concentrations for the cultivation of isolated Chlorella thermophila was performed by manipulating nine nutrients with the objectives of maximization of growth, carbohydrate, protein, and chlorophyll contents. Experiments were designed and effects of the parameters were studied using Taguchi orthogonal array (TOA). Experimental results of TOA were used for modeling artificial neural networks (ANN) followed by the optimization using genetic algorithm (GA) to find global optimal solutions. Results showed an increase of 36, 88, 36, and 88% for growth, carbohydrates, proteins, and chlorophylls, respectively, at optimal combinations of parameters given by TOA. Results obtained through the ANN-GA optimization were 9, 10, and 3% more compared to the TOA for biomass, carbohydrates, and chlorophylls, respectively with experimental verification. Nitrates and bicarbonate were found to play the most pivotal role in biomass and biomolecule synthesis of the isolated microalgal strain. Results of the current investigation can be used in the industrial scale-up for the production of multiple products using the biorefinery approach.

Keywords:

• Artificial neural network
• Chlorella thermophila
• design of experiment
• genetic algorithm
• optimization
• Taguchi orthogonal array

Disclosure statement

The authors declare no competing interests.

Author contributions

SS and KG conceptualized the research. SS and KG analyzed the data. SS did the experimental work and wrote the manuscript. JM, NP, KG, and SS did computational work of modeling and optimization. KG, MS, and TKB reviewed and corrected the manuscript.

Additional information

Funding

The authors thankfully acknowledge financial support from the Science and Engineering Research Board (SERB), Department of Science and Technology, Government of India (Project Number: CRG/2018/002479).