Optimisation of microalgal cultivation via nutrient-enhanced strategies: the biorefinery paradigm
Abstract Background The 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 feedstoc...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-03-01
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| Series: | Biotechnology for Biofuels |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13068-021-01912-2 |
| _version_ | 1817976783324053504 |
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| author | Gonzalo M. Figueroa-Torres Jon K. Pittman Constantinos Theodoropoulos |
| author_facet | Gonzalo M. Figueroa-Torres Jon K. Pittman Constantinos Theodoropoulos |
| author_sort | Gonzalo M. Figueroa-Torres |
| collection | DOAJ |
| description | Abstract Background The 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. Results Microalgal 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. Conclusions The 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. |
| first_indexed | 2024-04-13T22:08:16Z |
| format | Article |
| id | doaj.art-9b31aaea545d4c3ca544ef21ee90531b |
| institution | Directory Open Access Journal |
| issn | 1754-6834 |
| language | English |
| last_indexed | 2024-04-13T22:08:16Z |
| publishDate | 2021-03-01 |
| publisher | BMC |
| record_format | Article |
| series | Biotechnology for Biofuels |
| spelling | doaj.art-9b31aaea545d4c3ca544ef21ee90531b2022-12-22T02:27:52ZengBMCBiotechnology for Biofuels1754-68342021-03-0114111610.1186/s13068-021-01912-2Optimisation of microalgal cultivation via nutrient-enhanced strategies: the biorefinery paradigmGonzalo M. Figueroa-Torres0Jon K. Pittman1Constantinos Theodoropoulos2Department of Chemical Engineering and Analytical Science, Biochemical and Bioprocess Engineering Group, The University of ManchesterDepartment of Earth and Environmental Sciences, The University of ManchesterDepartment of Chemical Engineering and Analytical Science, Biochemical and Bioprocess Engineering Group, The University of ManchesterAbstract Background The 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. Results Microalgal 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. Conclusions The 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.https://doi.org/10.1186/s13068-021-01912-2ModellingBiofuelsStarchLipidsBiorefineryMicroalgae |
| spellingShingle | Gonzalo M. Figueroa-Torres Jon K. Pittman Constantinos Theodoropoulos Optimisation of microalgal cultivation via nutrient-enhanced strategies: the biorefinery paradigm Biotechnology for Biofuels Modelling Biofuels Starch Lipids Biorefinery Microalgae |
| title | Optimisation of microalgal cultivation via nutrient-enhanced strategies: the biorefinery paradigm |
| title_full | Optimisation of microalgal cultivation via nutrient-enhanced strategies: the biorefinery paradigm |
| title_fullStr | Optimisation of microalgal cultivation via nutrient-enhanced strategies: the biorefinery paradigm |
| title_full_unstemmed | Optimisation of microalgal cultivation via nutrient-enhanced strategies: the biorefinery paradigm |
| title_short | Optimisation of microalgal cultivation via nutrient-enhanced strategies: the biorefinery paradigm |
| title_sort | optimisation of microalgal cultivation via nutrient enhanced strategies the biorefinery paradigm |
| topic | Modelling Biofuels Starch Lipids Biorefinery Microalgae |
| url | https://doi.org/10.1186/s13068-021-01912-2 |
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