Kinetic of the gibberellic acid and bikaverin production in an airlift bioreactor

Chávez-Parga, Ma. del Carmen; González‐Ortega, Omar; Negrete-Rodríguez, Ma. de la Luz X.; Vallarino, Irma Galindo; Alatorre, Guillermo González; Escamilla‐Silva, Eleazar M.

doi:10.1016/j.procbio.2008.04.007

Cited by 19 publications

(8 citation statements)

References 12 publications

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“…However, the oxygen yields are similar to (even smaller than) those previously reported in SSF-between 3.8 and 2.7 g/g- (Soccol et al 1993;Rodríguez-León et al 1999;Brand et al 2001;Brand et al 2002). Furthermore, a recent publication by Chavez-Parga et al (2008) reported yields similar (Yx/s = 0.22-1.87 g/g and Yx/n = 11-49.4 g/g) to the ones reported by Gelmi et al (2002). The confidence intervals shown in Figure 6 show that the estimated biomass/nitrogen yields are reliable.…”

Section: Identifiability Analysissupporting

confidence: 84%

Improved calibration of a solid substrate fermentation model

Sacher

Saa

Cárcamo

et al. 2011

Electro Journal of Biotech

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Background: Calibration of dynamic models in biotechnology is challenging. Kinetic models are usually complex and differential equations are highly coupled involving a large number of parameters. In addition, available measurements are scarce and infrequent, and some key variables are often nonmeasurable. Therefore, effective optimization and statistical analysis methods are crucial to achieve meaningful results. In this research, we apply a metaheuristic scatter search algorithm to calibrate a solid substrate cultivation model. Results: Even though scatter search has shown to be effective for calibrating difficult nonlinear models, we show here that a posteriori analysis can significantly improve the accuracy and reliability of the estimation. Conclusions: Sensibility and correlation analysis helped us detect reliability problems and provided suggestions to improve the design of future experiments.

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Section: Identifiability Analysissupporting

confidence: 84%

Improved calibration of a solid substrate fermentation model

Sacher

Saa

Cárcamo

et al. 2011

Electro Journal of Biotech

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“…Shukla, Chand and Srivastava (2005a) developed a mathematical model to describe biomass growth, substrate consumption and product formation in a stirred tank bioreactor with Gibberella fujikuroi. Chavez-Parga et al (2008) proposed a mathematical model for the GA 3 and bikaverin production in an airlift bioreactor. Despite its complexity, the gibberellin (GA) biosynthetic pathway has been well characterized using biochemical techniques as well as by studying mutants (Hedden and Kamiya, 1997;Bomke and Tudzynski, 2009).…”

Section: Biosynthesis Pathwaymentioning

confidence: 99%

“…Recently, studies have been carried out to decrease GA 3 production costs using several approaches, such as screening fungi (Kumar and Lonsane, 1986;Machado et al, 2001;Uthandi, Karthikeyan and Sabarinathan, 2010), optimizing the nutrients and culture conditions (Kumar and Lonsane, 1990;Machado et al, 2001, Machado, Soccol andPandey, 2002;Corona, Sanchez and Agostin, 2005), using agro-industrial residues as a substrate, developing new processes (immobilizes cells, fed-batch culture, airlift bioreactor) and minimizing the extraction procedure costs (Kumar and Lonsane, 1987;Tang, Zhou and Duan, 2000;Chavez-Parga et al, 2008;Meleigy and Khalaf, 2009;Berrios, Pyle and Aroca, 2010). Therefore, in recent years, the possibility of using solid-state fermentation (SSF) has attracted a great deal of attention (Kumar and Lonsane, 1990;Pastrana, Gonzalez and Murado, 1993;Bandelier, Renaud and Durand, 1997;Gelmi et al, 2000;Corona, Sanchez and Agostin, 2005 the SSF technique has shown a number of economic advantages over the SmF process in the production of microbial biomass and metabolites and adding value to the agro-industrial by-products (Pandey, 1992;Soccol, 1996;Pandey et al, 2001;Soccol and Vandenberghe, 2003;Soccol et al, 2006).…”

Section: Ga 3 Productionmentioning

confidence: 99%

New perspectives of gibberellic acid production: a review

Rodrigues

Vandenberghe

Oliveira

et al. 2011

Critical Reviews in Biotechnology

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The gibberellins (GAs) are an important group of hormones which exert various effects on promoter and regulator of plant growth. Gibberellic acid (GA(3)) is a natural plant hormone, with great economical and industrial importance. It affects stem elongation, germination, elimination of dormancy, flowering, sex expression, enzyme induction and leaf and fruit senescence. Despite its diverse applications, the use of GA(3) is limited due to its high production costs. The industrial process currently used for the production of GA(3) is based on submerged fermentation (SmF) techniques. As an alternative for its production, solid state fermentation (SSF) has also been investigated for its ability to increase the yields of GA(3) with the use of agro-industrial wastes as support/substrate, which contributes to the decreased production costs. This review describes GA(3)'s physical, chemical and biological properties, its production by fermentation and new advances that are being carried out with special interest on the SSF technique.

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“…The coupled CFD-PBM simulations of ALR are relatively rare, especially with the viscous or non-Newtonian fluid. In industrial applications, many processes [16][17][18] are operated in the viscous mediums or with catalysts showing non-Newtonian behavior.…”

Section: Introductionmentioning

confidence: 99%

CFD-PBM Coupled Simulation of an Airlift Reactor with Non-Newtonian Fluid

Han

Sha

Лаари

et al. 2017

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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-Hydrodynamics of an AirLift Reactor (ALR) with tap water and non-Newtonian fluid was studied experimentally and by numerical simulations. The Population Balance Model (PBM) with multiple breakup and coalescence mechanisms was used to describe bubble size characteristics in the ALR. The interphase forces for closing the two-fluid model were formulated by considering the effect of Bubble Size Distribution (BSD). The BSD in the ALR obtained from the coupled Computational Fluid Dynamics (CFD)-PBM model was validated against results from digital imaging measurements. The simulated velocity fields of both the gas and liquid phases were compared to measured fields obtained with Particle Image Velocimetry (PIV). The simulated results show different velocity field profile features at the top of the ALR between tap water and nonNewtonian fluid, which are in agreement with experiments. In addition, good agreement between simulations and experiments was obtained in terms of overall gas holdup and bubble Sauter mean diameter. NOMENCLATURE SymbolsVolume fraction of gas/liquid phase, 1 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Kinetic of the gibberellic acid and bikaverin production in an airlift bioreactor

Cited by 19 publications

References 12 publications

Improved calibration of a solid substrate fermentation model

Improved calibration of a solid substrate fermentation model

New perspectives of gibberellic acid production: a review

CFD-PBM Coupled Simulation of an Airlift Reactor with Non-Newtonian Fluid

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