Kinetic modelling of batch ethanol production from sugar beet raw juice

Dodić, Jelena; Vučurović, Damjan; Dodić, Siniša; Grahovac, Jovana; Popov, Stevan; Nedeljković, Nataša

doi:10.1016/j.apenergy.2012.05.016

Cited by 92 publications

(51 citation statements)

References 30 publications

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“…These data Data on the specific growth rate (µ) values and initial substrate concentrations were used to estimate K S and µ max (Figure 2). A maximum specific growth rate (µ max ) value of 0.176 h −1 was obtained, which was close to the value of 0.169 h −1 previously reported by Dodić et al [19] using S. cerevisiae cells grown on raw sugar beet juice. As cell growth rate is largely dependent on substrate concentration, it is expected that a higher initial sugar concentration will result in higher Monod coefficients [28].…”

Section: Monod Kinetic Model Of S Cerevisiae On Waste Sorghum Leavessupporting

confidence: 61%

“…A similar observation was reported by Lin et al [34], where a steady increase in ethanol was observed over a duration of 48 h at 30 and 40 • C. An average ethanol yield of 0.49 g-ethanol/g-glucose was obtained, corresponding to a 96% fermentation efficiency during this period. Fermentation efficiencies between 72.78% and 78.43% have been reported by Srimachai et al [25] using oil palm frond juice as a substrate, whilst ethanol yields between 0.40 and 0.49 g/g have been obtained from raw sugar beet juice [19]. Waste sorghum leaves show excellent potential for lignocellulosic bioethanol production.…”

Section: Bioethanol Productionmentioning

confidence: 75%

“…The Gompertz coefficients for maximum potential bioethanol concentration (P m ), maximum bioethanol production rate (r p,m ), and lag time were 17.15 g/L, 0.52 g/L/h, and 6.31 h, respectively, from waste sorghum leaves. Very few studies have reported a lag time of longer than one hour [19]. This suggests that a duration of at least 6 h was required for yeast cells to adapt to fermentation medium derived from waste sorghum leaves.…”

Section: Bioethanol Productionmentioning

confidence: 99%

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Kinetics of Bioethanol Production from Waste Sorghum Leaves Using Saccharomyces cerevisiae BY4743

Rorke

Kana

2017

Fermentation

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Kinetic models for bioethanol production from waste sorghum leaves by Saccharomyces cerevisiae BY4743 are presented. Fermentation processes were carried out at varied initial glucose concentrations (12.5-30.0 g/L). Experimental data on cell growth and substrate utilisation fit the Monod kinetic model with a coefficient of determination (R 2 ) of 0.95. A maximum specific growth rate (µ max ) and Monod constant (K S ) of 0.176 h −1 and 10.11 g/L, respectively, were obtained. The bioethanol production data fit the modified Gompertz model with an R 2 value of 0.98. A maximum bioethanol production rate (r p,m ) of 0.52 g/L/h, maximum potential bioethanol concentration (P m ) of 17.15 g/L, and a bioethanol production lag time (t L ) of 6.31 h were observed. The obtained Monod and modified Gompertz coefficients indicated that waste sorghum leaves can serve as an efficient substrate for bioethanol production. These models with high accuracy are suitable for the scale-up development of bioethanol production from lignocellulosic feedstocks such as sorghum leaves.

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Section: Monod Kinetic Model Of S Cerevisiae On Waste Sorghum Leavessupporting

confidence: 61%

Section: Bioethanol Productionmentioning

confidence: 75%

Section: Bioethanol Productionmentioning

confidence: 99%

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Kinetics of Bioethanol Production from Waste Sorghum Leaves Using Saccharomyces cerevisiae BY4743

Rorke

Kana

2017

Fermentation

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“…On the basis of the obtained res ults, a good correlation coefficient (R 2 = 0.91) and a significant ANOVA test shows that the proposed logistic model is adequate to explain the sigmoidal profile of the yeast growth. According to the literature, the study proposed by Dodic et al (2012), was carried out used logistic empirical kinetic model to describe batch fermentation of raw juice. The results show a good agreement with experimental data (R 2 = 0.99), thus, the logistic equation was found to be an appropriate kinetic model for successfully describing yeast cell growt h in batch fermentation of raw juice system.…”

Section: Microbial Growthmentioning

confidence: 99%

Kinetic models and parameters estimation study of biomass and ethanol production from inulin by Pichia caribbica (KC977491)

Ali¹,

Hiligsmann²,

Outili³

et al. 2017

Afr. J. Biotechnol.

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The growth kinetics and modeling of ethanol production from inulin by Pichia caribbica (KC977491) were studied in a batch system. Unstructured models were proposed using the logistic equation for growth, the Luedeking-Piret equation for ethanol production and modified Leudeking-Piret model for substrate consumption. Kinetic parameters (X 0 , μ m , m, n, p and q) were determined by nonlinear regression, using Levenberg-Marquart method implemented in a Mathcad program. Since the production of ethanol was associated with P. caribbica cell growth, a good agreement between model predictions and experimental data was obtained. Indeed, significant R 2 values of 0.91, 0.96, and 0.95 were observed for biomass, ethanol production and substrate consumption, respectively. Furthermore, analysi s of variance (ANOVA) w as also used to validate the proposed models. According to the obtained results, the predicted kinetic values and experimental data agreed well . Finally, it is possible to predict the development of P. caribbica using these models.

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“…Modified Gompertz's equation was used to determine the fermentation kinetics of the M. glaziovii starch [28], which is expressed as:…”

Section: Fermentation Kineticsmentioning

confidence: 99%

Optimization of Reducing Sugar Production from Manihot glaziovii Starch Using Response Surface Methodology

et al. 2017

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Abstract:Bioethanol is known as a viable alternative fuel to solve both energy and environmental crises. This study used response surface methodology based on the Box-Behnken experimental design to obtain the optimum conditions for and quality of bioethanol production. Enzymatic hydrolysis optimization was performed with selected hydrolysis parameters, including substrate loading, stroke speed, α-amylase concentration and amyloglucosidase concentration. From the experiment, the resulting optimum conditions are 23.88% (w/v) substrate loading, 109.43 U/g α-amylase concentration, 65.44 U/mL amyloglucosidase concentration and 74.87 rpm stroke speed, which yielded 196.23 g/L reducing sugar. The fermentation process was also carried out, with a production value of 0.45 g ethanol/g reducing sugar, which is equivalent to 88.61% of ethanol yield after fermentation by using Saccharomyces cerevisiae (S. cerevisiae). The physical and chemical properties of the produced ethanol are within the specifications of the ASTM D4806 standard. The good quality of ethanol produced from this study indicates that Manihot glaziovii (M. glaziovii) has great potential as bioethanol feedstock.

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Kinetic modelling of batch ethanol production from sugar beet raw juice

Cited by 92 publications

References 30 publications

Kinetics of Bioethanol Production from Waste Sorghum Leaves Using Saccharomyces cerevisiae BY4743

Kinetics of Bioethanol Production from Waste Sorghum Leaves Using Saccharomyces cerevisiae BY4743

Kinetic models and parameters estimation study of biomass and ethanol production from inulin by Pichia caribbica (KC977491)

Optimization of Reducing Sugar Production from Manihot glaziovii Starch Using Response Surface Methodology

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