Mathematical modelling and statistical optimization of fast cultivation of Agardhiella subulata: Response surface methodology

Abstract

The production of algae within a short period has become an emerging issue among researchers due to its diversified usage. At the same time, researchers are working extensively on how to upsurge algae production using carbon dioxide. The motto of this study is to develop a fast algae production system utilizing carbon dioxide and employing mathematical as well as statistical analysis to optimize production. Response surface methodology (RSM) constructed on the central composite design (CCD) was applied to assess the potential contributions of cultivation time, irradiance light, and carbon dioxide concentration during the cultivation process. In addition, their interaction effects were evaluated in the cultivation period. In this study, the cultivation period was the most significant contributor to algae cultivation, followed by light and carbon dioxide. The highest A. Subulata of 0.24 g was attained with 418 μmol/m2/s, 7 days, and 19 mg/l for light intensity, cultivation time, and carbon dioxide concentration, respectively. The experimental data were analyzed using the modified Logistics, modified Gompertz, modified Schnute, and modified Richards models, and it was determined that the modified Logistics model fits the experimental data better than the other three models, as evidenced by the low values of RMSD (0.0286), AIC (-2.409), and BIC (-4.251) and high value of R2 (0.98). Increasing algae production employing carbon dioxide will help to promote a sustainable environment and attain sustainable development goals (SDGs).

Keywords

• Algae
• Agardhiella subulata
• Carbon dioxide
• Central composite design
• Optimization