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首页> 外文期刊>Advances in Environmental Technology >Predictive modeling of biomass production by Chlorella vulgaris in a draft-tube airlift photobioreactor
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Predictive modeling of biomass production by Chlorella vulgaris in a draft-tube airlift photobioreactor

机译：小球藻气举式光生物反应器中小球藻生产生物量的预测模型

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The objective of this study was to investigate the growth rate of Chlorella vulgaris for CO2 biofixation and biomass production. Six mathematical growth models (Logistic, Gompertz, modified Gompertz, Baranyi, Morgan and Richards) were used to evaluate the biomass productivity in continuous processes and to predict the following parameters of cell growth: lag phase duration (λ), maximum specific growth rate (μmax), and maximum cell concentration (Xmax). The low root-mean-square error (RMSE) and high regression coefficients (R2) indicated that the models employed were well fitted to the experiment data and it could be regarded as enough to describe biomass production. Using statistical and physiological significance criteria, the Baranyi model was considered the most appropriate for quantifying biomass growth. The biological variables of this model are as follows: μmax=0.0309 h?1, λ=100 h, and Xmax=1.82 g/L.
机译：这项研究的目的是调查小球藻的生长速度，用于CO2生物固定和生物量生产。六个数学增长模型（Logistic，Gompertz，改良的Gompertz，Baranyi，Morgan和Richards）用于评估连续过程中的生物量生产力并预测以下细胞生长参数：滞后期持续时间（λ），最大比生长率（ μmax）和最大细胞浓度（Xmax）。低的均方根误差（RMSE）和高的回归系数（R2）表明，所采用的模型与实验数据非常吻合，可以被认为足以描述生物量的生产。使用统计学和生理显着性标准，认为Baranyi模型最适合量化生物量的增长。该模型的生物学变量如下：μmax＝0.0309h≤1，λ＝ 100h和Xmax ＝ 1.82g / L。

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