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通过营养强化策略优化微藻培养:生物炼制模式

Optimisation of microalgal cultivation via nutrient-enhanced strategies: the biorefinery paradigm.

作者信息

Figueroa-Torres Gonzalo M, Pittman Jon K, Theodoropoulos Constantinos

机构信息

Department of Chemical Engineering and Analytical Science, Biochemical and Bioprocess Engineering Group, The University of Manchester, Manchester, M13 9PL, UK.

Department of Earth and Environmental Sciences, The University of Manchester, Manchester, M13 9PL, UK.

出版信息

Biotechnol Biofuels. 2021 Mar 12;14(1):64. doi: 10.1186/s13068-021-01912-2.

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.

摘要

背景

尽管微藻生物燃料具有可持续且广为人知的潜力,但与当前传统燃料技术相比,其生产成本仍不具有效益。然而,生物精炼概念增加了微藻生物质作为一种经济上可行的原料的前景,这种原料适合于联产多种生物燃料以及增值化学品。为了将生物燃料生产整合到微藻生物精炼框架内,不仅需要开发多产品平台,还需要确定最佳的微藻培养策略,以最大限度地提高用于生产生物燃料的微藻代谢产物:淀粉和脂质。虽然营养限制因增加淀粉和脂质形成而广为人知,但这种培养策略会大大降低微藻生长。这项工作提出了一个结合预测建模和实验方法的优化框架,以有效地模拟和预测微藻生长动态,并确定最佳培养策略。

结果

通过开发一个适用于预测受氮和磷共同限制的混合营养型微藻生长动态的多参数动力学模型,成功建立了使淀粉和脂质形成最大化的微藻培养策略。该模型的高预测能力通过针对从莱茵衣藻CCAP 11/32C实验室规模培养物中获得的各种数据集进行实验验证,这些培养物处于不同的初始营养状态。通过实验进一步验证了基于模型确定的最佳培养策略,与未优化的策略相比,淀粉(+270%)和脂质(+74%)产量显著增加。

结论

本文提出的动力学模型确定的使淀粉和脂质最大化的优化微藻培养方案,突出了利用建模框架作为优化工具的好处,这些工具有助于微藻制燃料技术的开发和商业化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7e70/7953610/c726b866e79c/13068_2021_1912_Fig1_HTML.jpg

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