Modeling of microbial growth and ammonia consumption at different temperatures in the production of a polyhydroxyalkanoate (PHA) biopolymer

Ocampo-López, Carlos; Colorado-Arias, Santiago; Ramírez-Carmona, Margarita

doi:10.1016/j.jart.2015.10.001

Cited by 13 publications

(4 citation statements)

References 17 publications

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“…Additional model fitness indicators such as adjusted R 2 , cross‐validation R 2 , external validation, parameter confidence interval (Maiwald et al, 2011), and relative sensitivity (Huong et al, 2017; Porras et al, 2019) are useful tools offering a quality check on those estimates. The use of large‐scale composite data in regression offers reliable parameter estimates (Ocampo‐López et al, 2015; Yang et al, 2006). Model discretization, where only a subset of parameters is conveniently estimated from appropriately designed batch experiments, could be another invaluable strategy.…”

Section: Model Selection Parameter Estimation and Quality Indicatorsmentioning

confidence: 99%

Structural variability, implementational irregularities in mathematical modelling of polyhydroxyalkanoates (PHAs) production—A state‐of‐the‐art review

Lhamo

Mahanty

2022

Biotech & Bioengineering

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The rate and extent of microbial polyhydroxyalkanoates (PHAs) production rely on the availability of substrates, growth of microbial biomass, and intracellular accumulation of polymer under nitrogen‐limited conditions. The dynamics of PHAs production captured through various structured or unstructured models can be extended to design an optimal feeding strategy for process intensification. Large variability in process assumptions, choices of kinetics, and model complexity is expected depending on substrate(s), microbial metabolism, and discretization of the process under consideration. This communication attempts to review the estimation of stoichiometric yield coefficients, metabolic modelling, and choices of unstructured kinetics in microbial PHA production. Implementational irregularities in parameter estimation and quality check in modelling exercises have also been reviewed. It is observed that the scope of the majority of the “modelling” studies is confined to the estimation of stoichiometric parameters with limited utility. In dynamic models, microbial growth is often described using either Monod or logistic variants, while PHAs production adopts a Luedeking–Piret expression with or without substrate inhibition. Though model selection, regression with experimental data, parameter estimation, and model validation are integral parts of the exercise, very few provide sufficient coverage on all those aspects. Application of the model to control or optimize the bioprocess has rarely been attempted.

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Section: Model Selection Parameter Estimation and Quality Indicatorsmentioning

confidence: 99%

Structural variability, implementational irregularities in mathematical modelling of polyhydroxyalkanoates (PHAs) production—A state‐of‐the‐art review

Lhamo

Mahanty

2022

Biotech & Bioengineering

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“…The specific growth rate (m, or SGR, day À1 ) and biomass productivity (P, g dw L À1 day À1 ) were determined from cell concentration and dry biomass weight data by using the following equations (1) and 2, respectively [15][16][17][18][19][20]:…”

Section: Measurement Of Algae Growth Kinetic Parametersmentioning

confidence: 99%

“…Among these, temperature and nitrogen concentration are considered the main parameters. It is well known that models of cell culture are useful tools to predict growth kinetics as well as better information in aquatic resource management [13][14][15]. To our knowledge there is no mathematical model for Chlorella kessleri (one of the green microalgae sp.)…”

Section: Introductionmentioning

confidence: 99%

Mathematical modeling of temperature effect on algal growth for biodiesel application

Hossain

Al-Bastaki

Alnoaimi

et al. 2019

Renew. Energy Environ. Sustain.

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Microalgae biomass is promising feedstock for the industrial production of biodiesel. Hence, research and development are required in various domains especially optimizations of growth conditions including temperature effect for mass scale operation (production of biomass, harvesting, extraction of lipid, etc). Since in middle east region, seasonal temperature variation and more rapid daily fluctuations are amenable to alter the growth kinetics of microalgae in outdoor culture and hence affect algae biomass production efficiency. Therefore, in this study, a mathematical model was developed to calculate how the algae sp. (Chlorella kessleri) will react at different temperatures. The model integrates Monod model and Arrhenius equation, and as such it describes the relationship of algal growth rate with culturing temperature and limiting nutrient concentration. The apparent activation energy and pre-exponential factors were calculated to be 2537 cal/mol and 0.0077 day−1, respectively. The developed models could be useful to anticipate the effective impacts of temperature on outdoor algae culture.

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“…Presently the biodegradable polymer available in the largest quantity on the market is poly(lactic acid), but it is produced by traditional chemical synthesis [4][5][6][7][8][9][10]. However, in the past few decades, several fermentation techniques were developed in order to facilitate the production of microbial polyesters [11][12][13][14][15][16][17] and reduce the price of the product. One of the most important and most frequently studied microbial polyesters is poly-[(R)-3-hydroxybutyrate].…”

Section: Introductionmentioning

confidence: 99%

Enzymatic degradation of poly-[(R)-3-hydroxybutyrate]: Mechanism, kinetics, consequences

Polyák

Dohovits

Nagy

et al. 2018

International Journal of Biological Macromolecules

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Poly-[(R)-3-hydroxybutyrate] (PHB) films prepared by compression molding and solvent casting, respectively, were degraded with the intracellular depolymerase enzyme natively synthetized by the strain Bacillus megaterium. Quantitative analysis proved that practically only (R)-3-hydroxybutyric acid (3-HBA) forms in the enzyme catalyzed reaction, the amount of other metabolites or side products is negligible. The purity of the product was verified by several methods (UV-VIS spectroscopy, liquid chromatography, mass spectroscopy). Degradation was followed as a function of time to determine the rate of enzymatic degradation. Based on the Michaelis-Menten equation a completely new kinetic model has been derived which takes into consideration the heterogeneous nature of the enzymatic reaction. Degradation proceeds in two steps, the adsorption of the enzyme onto the surface of the PHB film and the subsequent degradation reaction. The rate of both steps depend on the preparation method of the samples, degradation proceed almost twice as fast in compression molded films than in solvent cast samples. The model can describe and predict the formation of the reaction product as a function of time. The approach can be used even for the commercial production of 3-HBA, the chemical synthesis of which is complicated and expensive.

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Modeling of microbial growth and ammonia consumption at different temperatures in the production of a polyhydroxyalkanoate (PHA) biopolymer

Cited by 13 publications

References 17 publications

Structural variability, implementational irregularities in mathematical modelling of polyhydroxyalkanoates (PHAs) production—A state‐of‐the‐art review

Structural variability, implementational irregularities in mathematical modelling of polyhydroxyalkanoates (PHAs) production—A state‐of‐the‐art review

Mathematical modeling of temperature effect on algal growth for biodiesel application

Enzymatic degradation of poly-[(R)-3-hydroxybutyrate]: Mechanism, kinetics, consequences

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