Modelling ethanol production from cellulose: separate hydrolysis and fermentation versus simultaneous saccharification and fermentation

Drissen, R.E.T.; Maas, R.H.W.; Tramper, J.; Beeftink, H.H.

doi:10.1080/10242420802564358

Cited by 26 publications

(32 citation statements)

References 24 publications

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“…For all three reactions, v 1 , v 2 , and v 3 in Figure , the zero‐order rate constant is given as a function of temperature (activation energy E a ); in addition, all enzyme activity is assumed to be subject to thermal inactivation ( K D ). Moreover, inhibition of cellulase by ethanol is assumed to affect the rates of reaction v 1 and v 3 by inhibition constant K 1,EtOH . The thermal inactivation constant ( K D ) follows an Arrhenius type relationship, K D ( T ) = A D · e −Δ H / T .…”

Section: Case Study: Bio‐ethanol From Cane Bagasse By Ssf Processmentioning

confidence: 99%

“…The investigation of dynamics of biochemical pathways based on mathematical modeling and supported by quantitative experimental data has been increasingly adopted . This approach is suitable for supporting the biologists in the process of hypothesis generation and the design of experiments, decreasing the experimental effort necessary to characterize a biological system .…”

Section: Introductionmentioning

confidence: 99%

“…The SSF process combines enzymatic hydrolysis with ethanol fermentation to keep the concentration of glucose low. Among the various cellulose bioconversion schemes, this process is considered to be the most promising regarding its efficiency . If fermentation occurs simultaneously with saccharification, glucose produced during the saccharification will be rapidly converted into ethanol, reducing the inhibition caused by high sugar concentration, and therefore, the hydrolysis rate can be accelerated .…”

Section: Introductionmentioning

confidence: 99%

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Model‐based identifiable parameter determination applied to a simultaneous saccharification and fermentation process model for bio‐ethanol production

López

Barz

Peñuela

et al. 2013

Biotechnology Progress

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In this work, a methodology for the model-based identifiable parameter determination (MBIPD) is presented. This systematic approach is proposed to be used for structure and parameter identification of nonlinear models of biological reaction networks. Usually, this kind of problems are over-parameterized with large correlations between parameters. Hence, the related inverse problems for parameter determination and analysis are mathematically ill-posed and numerically difficult to solve. The proposed MBIPD methodology comprises several tasks: (i) model selection, (ii) tracking of an adequate initial guess, and (iii) an iterative parameter estimation step which includes an identifiable parameter subset selection (SsS) algorithm and accuracy analysis of the estimated parameters. The SsS algorithm is based on the analysis of the sensitivity matrix by rank revealing factorization methods. Using this, a reduction of the parameter search space to a reasonable subset, which can be reliably and efficiently estimated from available measurements, is achieved. The simultaneous saccharification and fermentation (SSF) process for bio-ethanol production from cellulosic material is used as case study for testing the methodology. The successful application of MBIPD to the SSF process demonstrates a relatively large reduction in the identified parameter space. It is shown by a cross-validation that using the identified parameters (even though the reduction of the search space), the model is still able to predict the experimental data properly. Moreover, it is shown that the model is easily and efficiently adapted to new process conditions by solving reduced and well conditioned problems.

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Section: Case Study: Bio‐ethanol From Cane Bagasse By Ssf Processmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Model‐based identifiable parameter determination applied to a simultaneous saccharification and fermentation process model for bio‐ethanol production

López

Barz

Peñuela

et al. 2013

Biotechnology Progress

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show abstract

“…This approach also facilitates to identify the impact of individual factor and find out the link between variables and operational conditions ). In addition, for better efficiency of ethanol production, the approach of separate hydrolysis and fermentation are preferred over the simultaneous saccharification and fermentation (Olsson and Hahn-Hagerdal, 1993;Drissen et al, 2009). In the present work, a lignin degrading fungus, Cryptococcus albidus, isolated from degrading wood of pulp and paper mill effluent was used for preparation of cellulolytic hydrolysate from sugarcane bagasse initially treated in alkaline condition, and Saccharomyces cerevisiae was subsequently applied for enhanced fermentation and production of ethanol.…”

Section: Introductionmentioning

confidence: 99%

Ethanol from Sugar Cane Bagasse of Pulp and Paper Mill Effluent byCryptococcus albidusandSaccharomyces cerevisiae

Thakur

Ray

Singhal

2015

Energy Sources, Part A: Recovery, Utilization, and Environmenta

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Cryptococcus albidus and Saccharomyces cerevisiae was used for separate hydrolysis and fermentation of sugar cane bagasse for production of ethanol. Lignocellulolytic enzymes, CMCase (34 U/ml), FPase (3 U/ml), β-glucosidase (2.3 U/ml), laccase (32 U/ml), and xylanase (12 U/ml), were assayed by fungus, however, after optimization of process parameters, an increase of 1.5-fold sugar (375 mg/ g) from bagasse and production of lignocellulolyic enzymes were determined. The sugar produced by sugar cane bagasse was subsequently treated by Saccharomyces cerevisiae, indicating enhanced production of ethanol at 40 h was 38.4 g/L, reached to a maximum at 50 h, and then it was decreased.

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“…the main disadvantage is that usually the compromise conditions are suboptimal for both hydrolysis and fermentation. Models suggest, however, that SSF might be the most effi cient procedure, at least for bioethanol production from wheatstraw 6. Rice straw has an incredible potential for bioethanol production due to the enormous amount of lignocellulosic biomass produced worldwide every year.…”

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confidence: 99%

Rice straw management: the big waste

Domínguez-Escribá

Porcar

2009

Biofuels Bioprod Bioref

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Rice is one of the major foods, with consumption per capita of 65 kg per year, accounting for 20% of global ingested calories. Rice production is expected to increase signifi cantly in the near future in order to feed the rising human population. Today, paddy rice culture produces 660 million tons of rice, along with 800 million dry tons of agricultural residues, mainly straw. This biomass is managed predominantly through rice straw burning (RSB) and soil incorporation strategies. RSB leads to signifi cant air pollution and has been banned in some regions, whereas stubble and straw incorporation into wet soil during land preparation is associated with enhanced methane emissions. Therefore, both strategies have important deleterious environmental effects and fail to take advantage of the huge energy potential of rice straw. Using rice straw as lignocellulosic biomass to produce bioethanol would appear to be a promising and ambitious goal to both manage this agricultural waste and to produce environmentally friendly biofuel. Technical diffi culties, however, associated with the conversion of lignocellulose into simple, fermentable sugars, have hampered the massive development of rice-straw-derived bioethanol. Recent technical advances in straw pre-treatment, hydrolysis and fermentation may, however, overcome these limitations and facilitate a dramatic turnover in biofuels production in the near future. R ice is a key crop for human consumption. In 2008, 155 million hectares worldwide were devoted to rice culture. Th is area has only slightly increased in the last 30 years, but paddy rice production almost doubled in the same period, mainly due to large-scale adoption of improved varieties. Th ere are more than 100 000 cultivated varieties of rice belonging to only two species: Oryza sativa, the Asian cultivated rice grown all over the world; and O. glaberrima, an African cultivated rice limited to West Africa. Varieties of O. sativa are classifi ed into two major groups: (i) indica, which includes most of the varieties of the tropical ecotype; and (ii) japonica, representing the temperate ecotype. Today, more than 660 million tons of rice are produced every year and rice accounts for 20% of total ingested calories (30% in Asia). In certain developing countries, such as Bangladesh or Cambodia, consumption can reach more than 70%. Rice consumption per capita was 50 kg in 1960; 57 kg in 1978; and about 65 kg in 2008. Th is increasing rate of Dr Laura Domínguez-Escribà Laura Domínguez-Escribà is a researcher in the

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Modelling ethanol production from cellulose: separate hydrolysis and fermentation versus simultaneous saccharification and fermentation

Cited by 26 publications

References 24 publications

Model‐based identifiable parameter determination applied to a simultaneous saccharification and fermentation process model for bio‐ethanol production

Model‐based identifiable parameter determination applied to a simultaneous saccharification and fermentation process model for bio‐ethanol production

Ethanol from Sugar Cane Bagasse of Pulp and Paper Mill Effluent byCryptococcus albidusandSaccharomyces cerevisiae

Rice straw management: the big waste

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