Modeling of growth and sporulation of Bacillus thuringiensis in an intermittent fed batch culture with total cell retention

Atehortúa, Paula; Álvarez, Hernán; Ordúz, Sergio

doi:10.1007/s00449-007-0141-0

Cited by 28 publications

(32 citation statements)

References 17 publications

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“…This research has been done with the same process and fermentation conditions used in Atehortúa et al (2007). The microorganism used in this work was Bacillus thuringiensis serovar.…”

Section: Microorganism and Bioprocess Characteristicsmentioning

confidence: 99%

“…The duration of the batch fermentation is limited and depends on the initial conditions of the microorganism culture. All the fermentations were initialized with the same inocula and different substrate concentration conditions (Atehortúa et al, 2007). When the medium is inoculated, the biomass concentration increases at the expense of reducing the nutrients.…”

Section: [L Min ]mentioning

confidence: 99%

“…This is done with the aim of performing a later on-line biomass estimation and designing an adequate process controller. The extended batch model for growth and sporulation of Bacillus thuringiensies on which this work is based is described in Atehortúa et al (2007). Equations for the model are:…”

Section: [L Min ]mentioning

confidence: 99%

“…These works, nevertheless, point out the need of considering in future research the oxygen dynamics and its limiting effect on cell growth. In the present study, the oxygen concentration is assumed to be in excess, but it decreases to values that are even smaller than the critical one (10%) (Atehortúa et al, 2007). In some fermentations, DO can also be used for estimating the microorganism concentration in the medium if the O 2 consumption is known (Amicarelli et al, 2006;di Sciascio and Amicarelli, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…The paper is organized as follows: next Section presents the microorganism's characteristics and the model based on first principles, with the dynamics as it actually appears in the model of Rivera et al (1999) and Atehortúa et al (2006Atehortúa et al ( , 2007. In the same Section, the DO dynamics for δ-endotoxins from the Bacillus thuringiensis production process are modeled and the parameters estimation is described.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Including dissolved oxygen dynamics into the Bt δ-endotoxins production process model and its application to process control

Amicarelli

Sciascio

Toibero

et al. 2010

Braz. J. Chem. Eng.

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-This paper proposes a model to characterize the Dissolved Oxygen Dynamics (DO) for the Bacillus thuringiensis (Bt) δ-endotoxins production process. The objective of this work is to include this dynamics into a phenomenological model of the process in order to facilitate the biomass estimation from the knowledge of oxygen consumption; and for control purposes, by allowing the addition of a new control variable in order to favorably influence the bioprocess evolution. The mentioned DO model is based on first principles and parameter estimation and model verification are supported by real experimental data. Finally, a control strategy is designed based on this model with its corresponding asymptotic stability and robustness analysis.

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“…This research has been done with the same process and fermentation conditions used in Atehortúa et al (2007). The microorganism used in this work was Bacillus thuringiensis serovar.…”

Section: Microorganism and Bioprocess Characteristicsmentioning

confidence: 99%

Section: [L Min ]mentioning

confidence: 99%

Section: [L Min ]mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Including dissolved oxygen dynamics into the Bt δ-endotoxins production process model and its application to process control

Amicarelli

Sciascio

Toibero

et al. 2010

Braz. J. Chem. Eng.

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Behavior comparison for biomass observers in batch processes

Amicarelli

Quintero

Sciascio

2013

Asia-Pacific J Chem Eng

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On‐line estimation of biomass concentration in batch biotechnological processes is an active area of research because normally, the biomass is the desired process product output, and also because it is necessary for control purposes to replace the unavailable biomass concentration measurements with reliable and robust on‐line estimations. This work presents five different alternatives to face the problem of biomass estimation in a particular batch bioprocess (δ‐endotoxins production of Bacillus thuringiensis), namely: a phenomenological estimator based on dissolved oxygen balance, an extended Kalman filter estimator, a Gaussian process regression‐based estimator, an artificial neural networks‐based estimator, and finally, an estimator based on information fusion by a decentralized Kalman filter. Each proposed biomass estimation method has its own advantages and drawbacks according to their ability to take into account the model uncertainties and the measurement errors. First, the design techniques of these five biomass estimators are exposed, and finally, the behavior of each estimation method is compared. The availability of efficient biomass estimators is of great importance for engineers because, on the one hand, it allows developing new control strategies for other bioprocess variables such as for instance: the growth rate of the microorganism, the dissolved oxygen concentration, and so on. On the other hand, it is also important to improve the performance of the bioprocess optimization procedure. This work also aims to show the evolution on biomass estimation techniques from classical to more contemporary approaches, such as the design based on neural networks and Gaussian processes regression. © 2013 Curtin University of Technology and John Wiley & Sons, Ltd.

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Life‐cycle kinetic model for endospore‐forming bacteria, including germination and sporulation

Park

Rittmann

Bae

2009

Biotech & Bioengineering

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We develop a mechanistic life-cycle model for endospore-forming bacteria (EFB) and test the model with experiments with a Bacillus mixed culture. The model integrates and quantifies how sporulation and germination are triggered by depletion or presence of a limiting substrate, while both substrates affect the rate of vegetative growth by a multiplicative model. Kinetic experiments show the accumulation of small spherical spores after the triggering substrate is depleted, substantially more rapid decay during sporulation than for normal decay of vegetative cells, and a higher specific substrate utilization rate for the germinating cells than that for growth of vegetative cells. Model simulations capture all of these experimental trends. According to model predictions, when a batch reactor is started, seeding with EFB spores instead of active EFB delays the onset of rapid chemical oxygen demand (COD) utilization and biomass growth, but the end points are the same. Simulated results with low aeration intensity show that germination can consume some substrate without dissolved oxygen (DO) depletion.

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Modeling of growth and sporulation of Bacillus thuringiensis in an intermittent fed batch culture with total cell retention

Cited by 28 publications

References 17 publications

Including dissolved oxygen dynamics into the Bt δ-endotoxins production process model and its application to process control

Including dissolved oxygen dynamics into the Bt δ-endotoxins production process model and its application to process control

Behavior comparison for biomass observers in batch processes

Life‐cycle kinetic model for endospore‐forming bacteria, including germination and sporulation

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