首页> 外文期刊>Bioresource Technology: Biomass, Bioenergy, Biowastes, Conversion Technologies, Biotransformations, Production Technologies >Strategic enhancement of algal biomass, nutrient uptake and lipid through statistical optimization of nutrient supplementation in coupling Scenedesmus obliquus-like microalgae cultivation and municipal wastewater treatment
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Strategic enhancement of algal biomass, nutrient uptake and lipid through statistical optimization of nutrient supplementation in coupling Scenedesmus obliquus-like microalgae cultivation and municipal wastewater treatment

机译:通过统计优化营养补充来优化斜藻象藻微藻培养与城市污水处理相结合的策略优化,从而战略性地提高藻类生物量,营养吸收和脂质的含量

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摘要

Supplementing proper nutrients could be a strategy for enhancing algal biomass, nutrients uptake and lipid accumulation in the coupling system of biodiesel production and municipal wastewater treatment. However, there is scant information reporting systematic studies on screening and optimization of key supplemented components in the coupling system. The main factors were scientifically screened and optimized using statistical methods. Plackett-Burman design (PBD) was used to explore the roles of added nutrient factors, whereas response surface methodology (RSM) was employed for optimization. Based on the statistic analysis, the optimum added TP and FeCl_3?6H_2O concentrations for Scenedesmus obliquus-like microalgae growth, nutrients uptake and lipid accumulation were 4.41 mg L~(-1) and 6.48 mg L~(-1), respectively. The corresponding biomass, lipid content and TN/TP removal efficiency were 1.46 g L~(-1), 36.26% and >99%. The predicted value agreed well with the experimental value, as determined by validation experiments, which confirmed the availability and accuracy of the model.
机译:在生物柴油生产和城市废水处理的耦合系统中,补充适当的养分可能是提高藻类生物量,养分吸收和脂质积累的一种策略。但是,很少有信息报道对偶联系统中关键补充组分的筛选和优化进行系统研究。使用统计方法对主要因素进行了科学筛选和优化。 Plackett-Burman设计(PBD)用于研究添加的营养因子的作用,而响应面方法(RSM)用于优化。根据统计分析,斜生象藻微藻生长,养分吸收和脂质积累的最佳添加TP和FeCl_3?6H_2O浓度分别为4.41 mg L〜(-1)和6.48 mg L〜(-1)。相应的生物量,脂质含量和TN / TP去除效率分别为1.46 g L〜(-1),36.26%和> 99%。预测值与通过验证实验确定的实验值非常吻合,证实了模型的可用性和准确性。

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