Response surface methodology as a statistical model for nutrient optimization to enhance biomass and bioactive phycobiliproteins production in cyanobacterium Nostoc sp. SW02
DOI:
https://doi.org/10.55674/cs.v17i3.261776Keywords:
Response surface methodology, Nutrient optimization, Biomass production, Phycobiliproteins, CyanobacteriaAbstract
Phycobiliproteins (PBPs) are water-soluble pigments involved in the photosynthesis of cyanobacteria. They are valuable natural colorants for biotechnological applications due to their significant biological properties. This research was the first to study the impact of NaNO3, Na2CO3, and K2HPO4 nutrient variations on the production of biomass and PBPs in the cyanobacterium Nostoc sp. SW02. The experiments utilized the response surface methodology with the Box-Behnken design for nutrient optimization. The quadratic equations showed that the models sufficiently aligned with the experimental data and could explain the combined influence of factors with statistical significance. The addition of NaNO3, Na2CO3, and K2HPO4 at concentrations of 2.0, 0.02, and 0.035 g L-1, respectively, provided the maximum biomass and PBPs production at 0.967 g L-1 and 13.89% yield, representing increases of 30.67% and 8.86%, compared to normal culture medium. The validity of the predicted model was confirmed, indicating its potential application in both small and large-scale cultivations. This study developed a model that could be applied for the commercial production of natural cyanobacterial colorants for their potential use in food and cosmetics industries.
GRAPHICAL ABSTRACT
HIGHLIGHTS
- Key nutrient factors (NaNO3, Na2CO3, and K2HPO4) were analyzed for their impact on productions of biomass and phycobiliproteins.
- Statistical modeling of response surface methodology used for nutrient optimization.
- The quadratic equations could explain the combined influence of factors with statistical significance.
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