ABSTRACT
This study was on modeling and optimization of bioethanol
production process from a lignocellulosic material. The process entailed
separate hydrolysis and fermentation (SJ{F) of corn stover to produce
bioethanol. Corn stover is the left over portion of the maize or non-grain
portion of maize, usually above the ground, after harvest. It is a
lignocellulosic material because it has a tough lignin covering over the
cellulose and hemicellulose layers. The corn stover used in this study was from
the yellow variety of sweet corn; it was analyzed in the Central Laboratory,
Nigerian Institute for Oil Palm Research (NIFOR). The corn stover was cleaned,
chopped, oven-dried at 60 °C for 48 hours (to moisture content of 10 %),
milled, sieved to produce uniform particle size range of 0.18 — 0.25 mm and
analyzed for its composition. The corn stover was then pretreated with 2% (w/w)
Sodium Hydroxide (NaOH) solution followed by hydrolysis with dilute Sulfuric
acid (H2SO4;v/v) of 1, 2.5 and 4 % respectively. Yeast, Saccharomyces
cerevisiae was used for the fermentation and at fermentation time of 12, 30 and
48 hrs. Fermented samples were withdrawn for bioethanol content analysis using
gas chromatography. Box-Behnken design (BBD), a statistical tool and feature of
the Design Expert software (7.0.0 Trial version) was used in the design of the
experiments and a total of 54 experimental runs was obtained. The response
variable, Bioethanol yield (mg/i) was represented with Y, while the six
independent variables; Sulfuric acid concentration, Hydrolysis time,
Fermentation time, Concentration of yeast, Fermentation temperature and pH of
Hydrolysate samples were represented by A, B, C, D, E & F respectively. The
results obtained from the experiments were inputed into the Design Expert software,
for model equation development, using the analysis of variance (ANOVA) feature
of the Design Expert software. From the ANOVA, only A, F, AF, CD, A2were
significant (having P-value S 0.05), resulting in a reduced Model Equation (i.e
adjusted), in terms of actual faôtors. The optimum predicted process parameters
for the optimum bioethariol yield of 149.41 mg/l were 1.08 %, 3.32 hrs, 14.32
hrs, 6.43 gIl, 39.34 °C and 7.64 for A, B, C, D, E and F respectively, while an
average bioethanol yield of 143.15 mg/i was obtained experimentally in three
replicates using the optimum process parameters. The experimental bioethanol
yield obtained was 95.8 1% close to the predicted optimum bioethanol yield. The
values of R, R2, adjusted R2and Adeq Precision were 0.8747, 0.7651, 0.5212 and
8.309 respectively. The value of R2indicates a good degree of correlation
between the experimental and predicted bioethanol yields, being close to one.
Since the "Adeq Precision" was greater than 4, it implies that the
model was adequate.
OHIMOR, O (2021). Modeling And Optimization Of Bioethanol Production Process From Lignocellulosic Material. Mouau.afribary.org: Retrieved Nov 24, 2024, from https://repository.mouau.edu.ng/work/view/modeling-and-optimization-of-bioethanol-production-process-from-lignocellulosic-material-7-2
ONOGHWARITE, OHIMOR. "Modeling And Optimization Of Bioethanol Production Process From Lignocellulosic Material" Mouau.afribary.org. Mouau.afribary.org, 27 Oct. 2021, https://repository.mouau.edu.ng/work/view/modeling-and-optimization-of-bioethanol-production-process-from-lignocellulosic-material-7-2. Accessed 24 Nov. 2024.
ONOGHWARITE, OHIMOR. "Modeling And Optimization Of Bioethanol Production Process From Lignocellulosic Material". Mouau.afribary.org, Mouau.afribary.org, 27 Oct. 2021. Web. 24 Nov. 2024. < https://repository.mouau.edu.ng/work/view/modeling-and-optimization-of-bioethanol-production-process-from-lignocellulosic-material-7-2 >.
ONOGHWARITE, OHIMOR. "Modeling And Optimization Of Bioethanol Production Process From Lignocellulosic Material" Mouau.afribary.org (2021). Accessed 24 Nov. 2024. https://repository.mouau.edu.ng/work/view/modeling-and-optimization-of-bioethanol-production-process-from-lignocellulosic-material-7-2