Abstract
BackgroundThe production of microalgal biofuels, despite their sustainable and renowned potential, is not yet cost-effective compared to current conventional fuel technologies. However, the biorefinery concept increases the prospects of microalgal biomass as an economically viable feedstock suitable for the co-production of multiple biofuels along with value-added chemicals. To integrate biofuels production within the framework of a microalgae biorefinery, it is not only necessary to exploit multi-product platforms, but also to identify optimal microalgal cultivation strategies maximising the microalgal metabolites from which biofuels are obtained: starch and lipids. Whilst nutrient limitation is widely known for increasing starch and lipid formation, this cultivation strategy can greatly reduce microalgal growth. This work presents an optimisation framework combining predictive modelling and experimental methodologies to effectively simulate and predict microalgal growth dynamics and identify optimal cultivation strategies.ResultsMicroalgal cultivation strategies for maximised starch and lipid formation were successfully established by developing a multi-parametric kinetic model suitable for the prediction of mixotrophic microalgal growth dynamics co-limited by nitrogen and phosphorus. The model’s high predictive capacity was experimentally validated against various datasets obtained from laboratory-scale cultures of Chlamydomonas reinhardtii CCAP 11/32C subject to different initial nutrient regimes. The identified model-based optimal cultivation strategies were further validated experimentally and yielded significant increases in starch (+ 270%) and lipid (+ 74%) production against a non-optimised strategy.ConclusionsThe optimised microalgal cultivation scenarios for maximised starch and lipids, as identified by the kinetic model presented here, highlight the benefits of exploiting modelling frameworks as optimisation tools that facilitate the development and commercialisation of microalgae-to-fuel technologies.
Highlights
The production of microalgal biofuels, despite their sustainable and renowned potential, is not yet cost-effective compared to current conventional fuel technologies
Evaluating microalgal responses to media composition In order to build a predictive model capable of portraying nutrient-limited mixotrophic dynamics, we first quantified the effects of initial nutrient availability on microalgal growth and starch and lipid accumulation
Laboratory-scale cultivation experiments were carried out with the model green microalgae Chlamydomonas reinhardtii subject to different initial concentrations (Additional file 1: Table S1) of nitrogen, phosphorus, and acetic acid until the stationary phase was achieved (8 days)
Summary
The production of microalgal biofuels, despite their sustainable and renowned potential, is not yet cost-effective compared to current conventional fuel technologies. The potential of microalgae is highlighted by the typical fast growth rate of many strains, leading to high biomass production, and the ability to accumulate carbohydrate (mainly in the form of starch) and lipids, precursor molecules for sugar-based and oil-based biofuels [8, 9]. Since their cellular composition includes other industrially important biomolecules (e.g. proteins, pigments, vitamins, and other bioactive compounds) [5, 10], microalgae are positioned as a viable biomass feedstock for biorefineries [5, 11, 12]. The implementation of such a framework can help increase energy efficiency and process profitability by optimally integrating all possible bioprocessing routes along with waste re-valorisation scenarios [5, 11]
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