Kinetic modelling of starch and lipid formation during mixotrophic, nutrient-limited microalgal growth

•We developed a new kinetic model to predict microalgal starch and lipid formation.•Model dynamics were experimentally validated for a range of conditions.•The model can account for coupled acetate and nitrogen concentration changes.•Optimal initial feed strategies are computed to maximise starch &a...

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Veröffentlicht in:Bioresource technology 2017-10, Vol.241, p.868-878
Hauptverfasser: Figueroa-Torres, Gonzalo M., Pittman, Jon K., Theodoropoulos, Constantinos
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Sprache:eng
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Zusammenfassung:•We developed a new kinetic model to predict microalgal starch and lipid formation.•Model dynamics were experimentally validated for a range of conditions.•The model can account for coupled acetate and nitrogen concentration changes.•Optimal initial feed strategies are computed to maximise starch & lipid production.•Experimental validation of optimal results showed excellent agreement. Microalgal starch and lipids, carbon-based storage molecules, are useful as potential biofuel feedstocks. In this work, cultivation strategies maximising starch and lipid formation were established by developing a multi-parameter kinetic model describing microalgal growth as well as starch and lipid formation, in conjunction with laboratory-scale experiments. Growth dynamics are driven by nitrogen-limited mixotrophic conditions, known to increase cellular starch and lipid contents whilst enhancing biomass growth. Model parameters were computed by fitting model outputs to a range of experimental datasets from batch cultures of Chlamydomonas reinhardtii. Predictive capabilities of the model were established against different experimental data. The model was subsequently used to compute optimal nutrient-based cultivation strategies in terms of initial nitrogen and carbon concentrations. Model-based optimal strategies yielded a significant increase of 261% for starch (0.065gCL−1) and 66% for lipid (0.08gCL−1) production compared to base-case conditions (0.018gCL−1 starch, 0.048gCL−1 lipids).
ISSN:0960-8524
1873-2976
DOI:10.1016/j.biortech.2017.05.177