International Conference on Global Trends in Engineering, Technology and Management (ICGTETM-2016)
Process Optimization of Ethanol Production from Damaged
Sorghum Grains
Sheetal B. Gawande 1, Dr. I. D. Patil 2
1
Research Student, SSBT`s, COET, Bambhori, Jalgaon and Assistant Professor, Department of Food
Technology, L.I.T., RTMNU, Nagpur, MS, India
2
Professor and Head, Department of Biotechnology, SSBT`s, COET, Bambhori, Jalgaon (MS),
India
Abstract- Purpose of this work is to optimize ethanol
production process from damaged sorghum grains
with specific objective to study process parameters of
ethanol production by fermentation. Experiments are
conducted for ethanol production by fermentation of
damaged sorghum grains to test and refine the various
process variables that is Inoculum size, pH,
Temperature and their different combinations. To
determine the optimum response, surface plots for
desirability and overlay plots are generated. Flour
from damaged sorghum grains yielded 2.30 (g/100ml)
ethanol by fermentation with co-culture of A. Niger
(NCIM 1248) and S. Cerevisiae (MTCC 170) under
optimized conditions of pH 5.5, temperature (300C),
and inoculum level (7.5 % v/v).Thereby damaged
sorghum grains those are non-edible could be utilized
optimally for ethanol production.
Keywords- Ethanol production, Optimize, Damaged
Sorghum Grains
I. INTRODUCTION
Bio-fuels are liquid fuels derived from plant materials.
They are entering in the market very rapidly. Bio-fuels
provided 1.8 % of the world’s transport fuel in
2008.Ethanol fuel is the most common bio-fuel
worldwide. Among all bio-fuels used worldwide,
ethanol is the most common bio-fuel. The air and
underground water pollution caused due to Lead or
methyl-tert-butyl ether (MTBE) of petroleum can be
reduced by replacing bio-ethanol. MTBE is used as a
fuel additive to increase the octane number also
known as fuel oxygenate. MTBE is possible human
carcinogen and is highly soluble in water. Ethanol has
biodegradable nature, low toxicity, persiwastence and
regenerative characteristic; hence it is chief substitute
for MTBE [1].
Major crops such as Corn, barley, oat, rice, wheat,
sorghum, and sugar cane are used for the bio-ethanol
production.[2] Sorghum is an important crop that is
widely grown in dry climates across the world.
Sorghum and corn grains are having highest potential
ethanol production. The grain is used for food, feed
and industrial purpose. Grain quality affects the
relative usefulness for each specific use. In several
applications including production of grain ethanol and
brewing, waxy endosperm and the high protein
ISSN: 2231-5381
digestibility characteristic in sorghum grain have the
potential to significantly alter conversion efficiencies.
Edible parts of plants and animals that are produced or
harvested for human consumption but that are not
ultimately consumed by people is called as food loss
and waste. Food loss and damaged grain have many
negative economic and environmental impacts. Based
on weight the Food grain and Agriculture
Organization of the United Nations (FAO) observed
that in the world, Out of all food produced 32 percent
food is lost or wasted in 2009. Approximately 24
percent of all produced food is waste or lost when
converted to calories. Farmer’s incomes can be
reduced economically because of waste investment in
production of damaged food grain. Particularly food
loss is defined as food that gets lost before it reaches
the consumer or spills, spoils, and incurs an abnormal
reduction in quality such as bruising or wilting [2].
Grain damaged by sprouting may lose value for food
applications but may not affect ethanol production and
final ethanol yield. Utilization of cereal grains for
bioethanol production can be the best option after food
application. The ability to predict future fermentation
behaviour, application to design, advanced control of
fermentation and optimization for economical ethanol
production is possible [3, 4, 5].
Phutela et al. Optimized ethanol production from
sweet sorghum juice of variety, CSV19SS using
response surface methodology with the help of
statistical software Statgraphics Centurian XVI.I.
During optimization process, effect of three factors i.e.
inoculums size, agitation rate and temperature on three
response variables i.e. ethanol content, total acidity
and pH are studied [1].
II. MATERIALS AND METHODS
A. Microorganisms
The amylase-producing fungus A. Niger (NCIM
1248) is obtained from the National Collection of
Industrial Microorganisms, National Chemical
Laboratory, Pune, India. The stock cultures are
maintained on potato dextrose agar slants. A standard
strain of S. Cerevisiae MTCC 170 is obtained from the
Microbial Type Culture Collection, Institute of
Microbial Technology, Chandigarh, India, for using as
a control organism. The strains are maintained on
slants of YPD agar medium.
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International Conference on Global Trends in Engineering, Technology and Management (ICGTETM-2016)
B. Media
The yeast strain S. Cerevisiae is maintained on YPD
medium containing 0.5% yeast extract; 0.5% peptone;
2% dextrose; 2 percent agar; pH 5.5. The yeast culture
is grown for inoculums development in a controlled
environment shaker (150 r.min-1) at 35°C for two days
in liquid medium containing glucose 2%; peptone
0.5%; yeast extract 0.3%; KH2PO4 0.1%; MgSO4
7H2O 0.05%; pH 5.5, 1 N HCl or 1 N NaOH is used to
obtain the desired pH for testing the effect of pH on
fermentation.
C. Substrates
The study is carried at Laxminarayan Institute of
Technology, Nagpur, India. The damaged sorghum
grains are obtained from local market Nagpur, India.
The grains had 40% sounds and 60% damaged grains,
categorized as industrial use. The damage includes
broken, cracked, and attacked by insects, dirty,
discoloured. The composition of damaged grains used
is given in Table 1. The grains are washed with water,
sun dried and powdered. The fine sorghum grains
flour is obtained from flour industries and local
market, Nagpur and used as control experiments to
compare with damaged grains.
Table No 1. Composition (% W/W) of fine and damaged (60%)
sorghum grain
Starch
Reducing sugar
Crude protein
Crude fiber
Fine
sorghum
69
5.9
10.7
3.1
Damaged
sorghum
44.6
4.6
9.2
1.4
D. Amylase production
The amylase-producing fungus A. Niger (NCIM 1248)
is grown in a medium containing soluble starch 2%
peptone 1% yeast extract 0.5% (NH4)2SO4 0.1%
MgSO4 7H2O 0.05%. Fifty ml of this medium is
prepared and sterilized at 121 °C/15 lb for 20 minutes.
After sterilization the medium is inoculated with 2 ml
of fungal suspension and incubated at 37 °C for 48 hrs
under a shaking condition of 150 r.min-1 and this is
used as an enzyme source for the fermentation process.
All experiments are replicated twice and the average
values are obtained.
F. Measurements
Amylase activity is assayed by reducing sugars
released from starch. The reaction mixture containing
2 ml of 1% starch in deionized water, 1 ml of 0.1 M
acetate buffer (pH 5.8) and 1 ml of enzyme solution is
incubated at 35°C in water bath for 10 minutes. After
incubation the amount of reducing sugars are
estimated by 3, 5-DNS method. Estimation of total
reducing in enzymatic hydrolysate of damaged
sorghum grain flour is done by DNS method [6]. The
estimation of ethanol is done by spectrophotometer [7].
III. EXPERIMENTAL DESIGN AND STATISTICAL
ANALYSIS
The factors affecting the ethanol yield from
damaged grain flour using a coculture of A. Niger
and S. Cerevisiae is studied using CCD experiments.
Variables pH and temperature (°C) and Inoculum Size
(%) are chosen as independent variables and is shown
in Table 2. Ethanol production (g/100ml) is used as
dependent output variable. Twenty experiments based
on the CCD are carried out with different
combinations of variables and results are presented in
Table 3. A second order polynomial model is
predicted with DOE (equation 1) indicating linear,
interaction and quadratic effect of variables on system
response as either positive or negative. ANOVA
analysis of the model is performed to evaluate its
statistical significance (refer table 4).
Table 2 Factors with their coded levels
Sr.
No.
1
2
3
Variable
-1.682
-1
0
1
1.682
pH
Temperature
(°C)
Inoculum
Size (%)
4.5
5
5.5
6
6.5
26
28
30
32
34
2.5
5
7.5
10
12.5
Table 3 Three-level central composite design and experimental
response
Factor Variables
E. Simultaneous Saccharification and Fermentation
process
Saccharification and fermentation of raw starch is
carried out simultaneously in one vessel. The crude
amylase broth (10 ml) of A. Niger is dispensed into
500 ml Erlenmeyer flasks with 100 ml fermentation
medium containing 10 g of damaged sorghum grain
flour and 0.3% peptone 0.1% KH2PO4 and 0.1 percent
(NH4)2SO4; pH 5.8. The medium is inoculated with S.
Cerevisiae suspension and incubated for 5 days.
Operating conditions of medium inoculum level (%),
pH and temperature maintained during fermentation
are kept at three different levels as shown in Table 2.
ISSN: 2231-5381
Sr.
No.
1
2
3
4
5
6
7
8
9
10
pH
T0C
Inoculum
size (%)
-1.682
0
1
0
-1
0
0
1
0
-1
0
0
1
0
1
0
0
1
1.682
-1
0
0
-1
0
1
0
0
1
0
1
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Response
Variable
Ethanol
production
(g/100ml)
0.85
2.30
1.98
2.30
1.48
2.32
2.31
1.25
1.81
1.05
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International Conference on Global Trends in Engineering, Technology and Management (ICGTETM-2016)
11
12
13
14
15
-1
0
0
1
1
16
0
17
18
19
20
0
-1
1.682
0
-1
0
0
-1
-1
1.682
0
1
0
0
-1
0
-1.682
1
-1
0.99
2.31
1.35
1.17
1.23
0
0.94
1.682
-1
0
0
1.01
1.85
1.42
2.31
pH *Inoculum level
Temperature*
Inoculum level
IV. RESULTS AND DISCUSSIONS
1) Optimization of physical parameters and media
components for ethanol production is carried out.
CCD matrix with response is shown in Table 3. A
second order polynomial model fit to the experimental
data for optimizing ethanol production via response
surface method (RSM) predicts response as a function
of three variables and their interactions in terms of
their coded values.
% Ethanol = 2.3015 + 0.089 pH + 0.262 Temperature
- 0.1224 Inoculum level - 0.3704 pH * pH - 0.2856
Temperature * Temperature - 0.3545 Inoculum level *
Inoculum level -0.0575 pH * Temperature - 0.06 pH *
Inoculum level - 0.1375 Temperature * Inoculum
level
0.0519
-0.06
0.0519
-0.1375
-1.16
0.275
-2.65
0. 024
ANOVA calculations listed in Table 4 shows that the
model F and P values. The analysis of variance
(ANOVA) is carried out for ethanol production. This
gives good correlation between input factors and their
responses. Analysis of variance and Significance of
term coefficients for ethanol content are determined.
The ANOVA result of quadratic regression model for
ethanol production is described in table 4. ANOVA of
the regression model demonstrated that the model is
significant due to an F-value of 28.96 and a very low
probability value (p < 0.001). Results obtained in table
5 shows that the regression coefficients of all linear
term and quadratic coefficients are significant at less
than 1% level. Determined p-values are used as a tool
to check significance of each coefficient, which in turn
indicate the pattern of the interactions between
variables. Smaller value of p it is more significant to
the corresponding coefficient.
Response Surface Methodology for two variable
interaction Studies is done. Surface plots for different
interaction of any two independent variables, while
holding the third variable constant, on ethanol
production are generated using software.
Surface Plot of ethanol (g/100ml) vs Inoculum level(%), Temperature
Table 4 ANOVA table for CCD model
Source of
Variation
Degree of
Freedom (DF)
Mean Square
(MS)
FValue
PValue
Model
9
0.6242
28.96
<0.001
Linear Effects
3
0.4178
19.38
<0.001
Hold
Values
pH 0
2
ethanol (g/100ml)
1
1
0
Quadratic Effects
3
1.3859
64.29
<0.001
Interaction Effects
3
0.0683
3.19
0.071
residual error
10
0.0215
-
-
5
5
0.04306
0.000
-
-
19
-
-
-
lack- of -fit
Pure error
Total
Table 5 Significance of term coefficients for CCD
Standard
Term
Coefficient
Error
T-Value
Coefficient
0
-2
-1
-1
0
Temperature
Inoculum level(%)
-2
1
Figure No: 1 Surface plots showing effect of inoculum level (%)
and temperature on ethanol content at fixed pH value 5.5
Surface Plot of ethanol (g/ 100ml) vs pH , Temperature
Hold Values
Inoculum level(%) 0
P-Value
Constant
2.3015
0.0599
38.44
0.0001
pH
0.089
0.0397
2.25
0.049
Temperature
0.262
0.0397
6.60
0.0001
-0.1224
0.0397
-3.08
0.012
2
Inoculum level (%)
pH*pH
Temperature *
Temperature
Inoculum level *
Inoculum level
pH * Temperature
-0.3704
-0.2856
-0.3545
-0.0575
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0.0387
0.0387
0.0387
0.0519
-9.58
-7.38
-9.17
-1.11
ethanol (g/100ml)
1
1
0
0
-2
0.0001
-1
0
Temperature
-1
1
pH
-2
0.0001
0.0001
Figure No: 2 Surface plots showing effect of temperature and
pH on ethanol content at fixed inoculums level (%)
0.294
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International Conference on Global Trends in Engineering, Technology and Management (ICGTETM-2016)
Surface Plot of ethanol (g/ 100ml) vs Inoculum level(%), pH
Hold Values
Temperature 0
2
ethanol (g/100ml)
1
1
0
0
-2
-1
-1
pH
0
1
Inoculum level(% )
-2
Figure No: 3 Surface plots showing effect of pH versus inoculum
level (%) on ethanol content at fixed temperature of 300C
Graphical representation provides a method to
visualize the relationship between the response and
experimental levels of each variable in order to deduce
the optimum conditions. The individual effect of all
the four parameters studied, quadratic effects, and
interaction effects between the temperature and
inoculums level are found to be significant from the
response surface plots shown in figures 1, 2, and 3.
The clear elliptical shape of the curve shown in fig. 1
indicates that the interaction effect between the
temperature and inoculum level is significant with a p
value of 0.024.
A direct correlation is found between inoculum level
and temperature on ethanol production at fixed pH 5.5
as shown in figure 1. When the other variable is kept
constant, the interaction between the two variables
(inoculum level and temperature) showed that the
ethanol yield is sensitive even when substrate
concentration and temperature are subject to small
alterations (fig. 1). Figure 2 shows the surface plots of
pH and temperature at fixed inoculum level of 7.5%.
Figure 3 shows the surface plots of inoculum level (%)
versus pH at fixed temperature 300C. The pH is very
important for enzyme activity, pH influences the
metabolic activity of the organism and as the pH level
increases ethanol production increases. The pH also
has a strong positive effect on the biotechnological
process because the pH affects both the enzyme
activity and the yeast fermentation [8]. The inoculum
size has a positive effect on the process, a very small
inoculum concentration increases the fermentation
time and a too high concentration can lead to losses in
ethanol yield due to sugar consumption by the
multiplying yeast cells [9]. The results showed that
as the values of process variables increased, the
yield also increased, but only up to the midpoint of
the range of variables, and thereafter, the yield
decreased even though the values of variables
increased. The ethanol yield is significantly affected
by inoculums level, pH, and temperature. Based on
the model, the optimal working conditions are
obtained to attain high percentage conversion of
starch. Optimum values of parameters are found to
be temperature 300C, pH 5.5 and inoculum level 7.5 %
ISSN: 2231-5381
(v/v), respectively to get maximum ethanol
concentration.
Table 4 also shows that experimental yields fitted to
second-order polynomial equation well as indicated by
high R2 values (0.966). The starch content in the
damaged grains used is lower by 30% and 40% when
compared with fresh grains of sorghum [10] (Table 1).
But as these damaged grains are cheaper by 10 times
than fresh grains, it would still be cheaper to utilize
them for ethanol production in co-culture at 10%
substrate concentration [11, 12]. Studies on
simultaneous saccharification and fermentation (SSF)
of wheat bran flour, a grain milling residue as the
substrate using co-culture method are carried out with
strains of starch digesting Aspergillus niger, non
starch digesting and sugar fermenting Kluyveromyces
marxianus in batch fermentation [13].
In this paper efforts are done to optimize ethanol
production process from damaged sorghum grains
with specific objective to study process parameters of
ethanol production by fermentation by utilizing
damaged sorghum grain flour at 10% substrate
concentration.
V. CONCLUSIONS
Above results shows optimized conditions for
ethanol production from damaged sorghum grains that
is at temperature (30 0C), pH (5.5) and inoculum level
(7.5 %) (v/v) to get maximum ethanol concentration of
2.30 % (g/100 ml). Hence, damaged sorghum grains
are found to be a good substrate for ethanol production
and efforts shows vast potential use of damaged or
prone to be wasted food grains to be converted in to
fuel ethanol.
ACKNOWLEDGMENT
Authors are thankful to the SSBT`s, College of
Engineering and Technology, Bambhori, Jalgaon for
providing library facility and L.I.T., Nagpur for
providing laboratory facility. Authors would like to
thank the staff and colleagues for useful discussions.
[1]
[2]
[3]
[4]
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