Evaluation of optimization techniques for parameter estimation: Application to ethanol fermentation considering the effect of temperature

Rivera, Elmer Ccopa; Costa, Aline Carvalho da; Atala, Daniel Ibraim Pires; Maugeri, Francisco; Maciel, Maria Regina Wolf; Filho, Rubens Maciel

doi:10.1016/j.procbio.2006.02.009

Cited by 77 publications

(41 citation statements)

References 19 publications

(21 reference statements)

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“…cerevisiae is reported to grow well within the temperature range 28-40 ºC (Rivera et al, 2006). The increase in temperature accelerates the inhibition effect of the RSC and ethanol on the cell activities, thereby lowering both cell and ethanol yields (Phisalaphong et al, 2005).…”

Section: Response Surface Plots and Optimization Conditionsmentioning

confidence: 99%

Optimization of operational parameters for ethanol production from Korean food waste leachate

Man

Behera

Park

2009

Int. J. Environ. Sci. Technol.

151

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ABSTRACT:Recently, research on the production of ethanol from waste has been accelerating for both ecological and economical reasons, primarily for its use as an alternative to petroleum based fuels. In this study, response surface methodology based 2 3 -full factorial central composite design was employed to optimize the parameters of ethanol production from Korean food waste leachate. The reducing sugar concentration of the food waste leachate determined by the dinitrosalicylic acid method was 75 g/L. A second order polynomial model was developed to evaluate the quantitative effects of temperature, pH and reducing sugar concentration in order to find an optimum condition for the ethanol production from food waste leachate. From the experimental result, maximum ethanol concentration of 24.17 g/L was obtained at the optimum condition of temperature (38 ºC), pH (5.45) and reducing sugar concentration (75 g/L). The experimental value (24.17 g/L) agreed very well with the predicted one (23.66 g/L), indicating the suitability of the model employed and the success of response surface methodology in optimizing the conditions of ethanol production from food waste leachate. Canonical analysis indicated that the stationary point was a saddle point for the ethanol yield. Despite being a waste, an ethanol yield of 0.32 g ethanol/g reducing sugar demonstrated the potential of food waste leachate as a promising biomass resource for the production of ethanol.

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Section: Response Surface Plots and Optimization Conditionsmentioning

confidence: 99%

Optimization of operational parameters for ethanol production from Korean food waste leachate

Man

Behera

Park

2009

Int. J. Environ. Sci. Technol.

151

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“…Parameters in dynamic fermentation models are commonly estimated using the sequential solution/optimization (SeqSO) procedure (Rivera et al 2006). Though simple, this procedure may be severely limited when fitting complex models with many parameters or constraints that violate standard numerical regularity conditions, as is the case of more mechanistic SSF kinetic models.…”

Section: Abbreviations: Nlp: Non-linear Programmentioning

confidence: 99%

Fast and reliable calibration of solid substrate fermentation kinetic models using advanced non-linear programming techniques

Araya¹,

Arrieta²,

Biegler³

et al. 2007

Electron. J. Biotechnol.

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Financial support: Projects FONDECYT 1030325 and 7040084.Keywords: dynamic models, Gibberella fujikuroi, Gibberellic acid, nonlinear models, parameter estimation, secondary metabolites, solid substrate cultivation. Abbreviations: NLP: non-linear programSeqSO: sequential solution/optimization SimSO: simultaneous solution/optimization SSF: Solid substrate fermentationCalibration of mechanistic kinetic models describing microorganism growth and secondary metabolite production on solid substrates is difficult due to model complexity given the sheer number of parameters needing to be estimated and violation of standard conditions of numerical regularity. We show how *Corresponding author advanced non-linear programming techniques can be applied to achieve fast and reliable calibration of a complex kinetic model describing growth of Gibberella fujikuroi and production of gibberellic acid on an inert solid support in glass columns. Experimental culture data was obtained under different temperature and Araya, M.M. et al.2 water activity conditions. Model differential equations were discretized using orthogonal collocations on finite elements while model calibration was formulated as a simultaneous solution/optimization problem. A special purpose optimization code (IPOPT) was used to solve the resulting large-scale non-linear program. Convergence proved much faster and a better fitting model was achieved in comparison with the standard sequential solution/optimization approach. Furthermore, statistical analysis showed that most parameter estimates were reliable and accurate.Solid substrate fermentation (SSF) can be defined as the cultivation of microorganisms on solid substrates devoid of or deficient in free water (Pandey, 2003). SSF has several advantages (Hölker and Lenz, 2005) over more conventional submerged fermentation, and many promising lab-scale SSF processes are periodically reported in the literature (John et al. 2006; Krasniewski et al. 2006;Lechner and Papinutti, 2006;Sabu et al. 2006). Unfortunately, very few of these processes enter commercial production (Hölker and Lenz, 2005) due to the magnitude of the technical difficulties in operating and optimizing large scale SSF bioreactors. Since modern process control and optimization engineering techniques are model based, mathematical modelling should significantly improve the chances of successfully transforming an SSF process from laboratory to commercial production.Nevertheless, a number of factors make modelling SSF processes particularly trying: the absence of reliable on-line measurements of relevant cultivation variables (like biomass and nutrient concentration) and the system's inherent complexity, considering that microorganism interaction with the environment and its growth and production kinetics are still not well understood on a micro scale (Mitchell et al. 2004). In addition, the more useful mechanistic dynamic models proposed are highly complex and have many parameters that need to be estimated from extensive good quality experimental data. Acq...

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“…A classic example of this problem is thermotolerance, where the efficiency of biocatalysis, and therefore the economic viability of a particular process, is often hindered by the inability of the necessary microbe to thrive at the temperatures encountered during process scale-up (47). Consequently, there is significant interest in producing microbes whose thermal growth parameters match those needed for particular industrial applications.…”

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confidence: 99%

Experimental Evolution of a Facultative Thermophile from a Mesophilic Ancestor

Blaby¹,

Lyons²,

Wroclawska-Hughes³

et al. 2012

Appl Environ Microbiol

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Experimental evolution via continuous culture is a powerful approach to the alteration of complex phenotypes, such as optimal/ maximal growth temperatures. The benefit of this approach is that phenotypic selection is tied to growth rate, allowing the production of optimized strains. Herein, we demonstrate the use of a recently described long-term culture apparatus called the Evolugator for the generation of a thermophilic descendant from a mesophilic ancestor (Escherichia coli MG1655). In addition, we used whole-genome sequencing of sequentially isolated strains throughout the thermal adaptation process to characterize the evolutionary history of the resultant genotype, identifying 31 genetic alterations that may contribute to thermotolerance, although some of these mutations may be adaptive for off-target environmental parameters, such as rich medium. We undertook preliminary phenotypic analysis of mutations identified in the glpF and fabA genes. Deletion of glpF in a mesophilic wild-type background conferred significantly improved growth rates in the 43-to-48°C temperature range and altered optimal growth temperature from 37°C to 43°C. In addition, transforming our evolved thermotolerant strain (EVG1064) with a wild-type allele of glpF reduced fitness at high temperatures. On the other hand, the mutation in fabA predictably increased the degree of saturation in membrane lipids, which is a known adaptation to elevated temperature. However, transforming EVG1064 with a wildtype fabA allele had only modest effects on fitness at intermediate temperatures. The Evolugator is fully automated and demonstrates the potential to accelerate the selection for complex traits by experimental evolution and significantly decrease development time for new industrial strains.

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Evaluation of optimization techniques for parameter estimation: Application to ethanol fermentation considering the effect of temperature

Cited by 77 publications

References 19 publications

Optimization of operational parameters for ethanol production from Korean food waste leachate

Optimization of operational parameters for ethanol production from Korean food waste leachate

Fast and reliable calibration of solid substrate fermentation kinetic models using advanced non-linear programming techniques

Experimental Evolution of a Facultative Thermophile from a Mesophilic Ancestor

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