Modeling and Optimizing the Effect of Light Color, Sodium Chloride and Glucose Concentration on Biomass Production and the Quality of Arthrospira platensis Using Response Surface Methodology (RSM)

Abstract

Arthrospira platensis (Spirulina) biomass is a valuable source of sustainable proteins, and the basis for new food and feed products. State-of-the-art production of Spirulina biomass in open pond systems only allows limited control of essential process parameters, such as light color, salinity control, or mixotrophic growth, due to the high risk of contaminations. Closed photobioreactors offer a highly controllable system to optimize all process parameters affecting Spirulina biomass production (quantity) and biomass composition (quality). However, a comprehensive analysis of the impact of light color, salinity effects, and mixotrophic growth modes of Spirulina biomass production has not been performed yet. In this study, Response Surface Methodology (RSM) was employed to develop statistical models, and define optimal mixotrophic process conditions yielding maximum quantitative biomass productivity and high-quality biomass composition related to cellular protein and phycocyanin content. The individual and interaction effects of 0, 5, 15, and 30 g/L of sodium chloride (S), and 0, 1.5, 2, and 2.5 g/L of glucose (G) in three costume-made LED panels (L) where the dominant color was white (W), red (R), and yellow (Y) were investigated in a full factorial design. Spirulina was cultivated in 200 mL cell culture flasks in different treatments, and data were collected at the end of the log growth phase. The lack-of-fit test showed that the cubic model was the most suitable to predict the biomass concentration and protein content, and the two-factor interaction (2FI) was preferred to predict the cellular phycocyanin content (p > 0.05). The reduced models were produced by excluding insignificant terms (p > 0.05). The experimental validation of the RSM optimization showed that the highest biomass concentration (1.09, 1.08, and 0.85 g/L), with improved phycocyanin content of 82.27, 59.47, 107 mg/g, and protein content of 46.18, 39.76, 53.16%, was obtained under the process parameter configuration WL4.28S2.5G, RL10.63S1.33G, and YL1.00S0.88G, respectively.