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在烧结盘色谱玻璃泡柱中使用氮磷钾肥料培养基对杜氏盐藻的生长和脂类生产进行建模。

Modelling of microalgal growth and lipid production in Dunaliella tertiolecta using nitrogen-phosphorus-potassium fertilizer medium in sintered disk chromatographic glass bubble column.

机构信息

Department of Petroleum Engineering, Indian School of Mines, Dhanbad 826 004, India.

Department of Petroleum Engineering, Indian School of Mines, Dhanbad 826 004, India.

出版信息

Bioresour Technol. 2016 Oct;218:1021-36. doi: 10.1016/j.biortech.2016.07.055. Epub 2016 Jul 14.

Abstract

A comprehensive mathematical model involving NPK-10:26:26 fertilizer, NaCl, NaHCO3, light and temperature operating variables for Dunaliella tertiolecta cultivation is formulated to predict microalgae-biomass and lipid productivity. Proposed model includes Monod/Andrews kinetics for the absorption of essential nutrients into algae-biomass and Droop model involving internal nutrient cell quota for microalgae growth, assuming algae-biomass is composed of sugar, functional-pool and neutral-lipid. Biokinetic model parameters are determined by minimizing the residual-sum-of-square-errors between experimental and computed microalgae-biomass and lipid productivity using genetic algorithm. Developed model is validated with the experiments of Dunaliella tertiolecta cultivation using air-agitated sintered-disk chromatographic glass-bubble column and the effects of operating variables on microalgae-biomass and lipid productivity is investigated. Finally, parametric sensitivity analysis is carried out to know the sensitivity of model parameters on the obtained results in the input parameter space. Proposed model may be helpful in scale-up studies and implementation of model-based control strategy in large-scale algal cultivation.

摘要

建立了一个综合的数学模型,涉及 NPK-10:26:26 肥料、NaCl、NaHCO3、光照和温度等操作变量,用于预测杜氏盐藻的生物量和产油量。所提出的模型包括用于将必需养分吸收到藻生物质中的 Monod/Andrews 动力学和涉及微藻生长的内部养分细胞配额的 Droop 模型,假设藻生物质由糖、功能池和中性脂质组成。通过使用遗传算法最小化实验和计算得到的藻生物质和产油量之间的残差平方和,确定生物动力学模型参数。使用空气搅拌烧结盘色谱玻璃泡柱对杜氏盐藻的培养实验进行了模型验证,并研究了操作变量对藻生物质和产油量的影响。最后,进行了参数灵敏度分析,以了解模型参数在输入参数空间中对获得结果的敏感性。该模型可用于放大研究和在大规模藻类培养中实施基于模型的控制策略。

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