Faculty of Chemical and Food Engineering
MSc. Thesis presentation
On
“Optimization of yeast propagation and molasses fermentation process to
increase ethanol production efficiency” (The case of Metehara sugar factory)
Prepared by Legese Asmamaw
Advisor : Dr Solomon Workneh
Faculty of Chemical and Food Engineering
Outlines
Introduction
Statement of Problem
Objectives
Materials and Methods
 Result and Discussion
Conclusion and Recommendations
Faculty of Chemical and Food Engineering
Introduction
 The limited resources of fossil fuels, the increasing costs of these fuels and the concerns
about climate change are the main reasons to trend towards bio fuel production
 Global ethanol market grew from 125 billion liters in 2019 and is expected to reach 137
billion liters by 2026
 Among the widely used substrates for ethanol production are the molasses, the wastes and
byproduct of sugar industries .
 The yeast propagation and molasses fermentation processes are optimized simultaneously
to increase ethanol production
 In case of Metahara sugar factory yeast propagation and fermentation processes has
encountered with problems to get the required yeasts to produce alcohol and needs
research to be solved.
Faculty of Chemical and Food Engineering
Statement of Problem
 In yeast propagation and molasses fermentation processes, the required yeast cell &
ethanol can not be obtained in Metahara Sugar Factory since 2016 G.C.
 This is due to process optimization problems and the current Metahara ethanol production
efficiency is below 7% v/v alcohol .
 As a result, optimization is required to assure the sustainability and to maximize
production
 Therefore, this problem can be solved by optimization of propagation and fermentation
processes simultaneously
Faculty of Chemical and Food Engineering
Objectives of the study
General Objective
To optimize yeast propagation and molasses fermentation processes parameters to get optimum
yeast cell counts and maximum ethanol production efficiency.
Specific objectives
 To characterize the physicochemical compositions of the input raw materials
 To optimize yeast propagation process parameters
 To optimize molasses fermentation process parameters
Faculty of Chemical and Food Engineering
Materials and methods
Materials
Material Samples
Equipments (Aparatus)
 Molasses
 Air conditioners,
 Process water
Obtained from
Metahara
Sugar Factory
 Compound Microscope
 Nutrients
 Inoculation Chamber
 Yeasts obtained from Metahara Microbial Lab
 Autoclave
Chemical Regents
 Chemicals obtained from Metahara Sugar
Factory and Sugar Research center
 Refractometer and pH meter
 Refrigerator
 Incubator etc
Faculty of Chemical and Food Engineering
Methods
Input raw material physicochemical characterization
Molasses Analysis such as
 Total Reducing sugar
 Un fermentable sugar (UFS)
 Total Fermentable sugar (FS)
Process water Analysis such as
 Hardness as CaCO3
 pH
 Calcium as (CaO)
 Free chlorine before activated carbon and
 Reducing Sugar
 Free chlorine after activated carbon were
 Sulfated Ash etc were checked
checked
Faculty of Chemical and Food Engineering
Yeast propagation process
Methods
Yeast cells
Nutrients
Molasses
Process
water
Media
preparation
Substrate
(Media)
Yeast
propagation
Yeast
culture
Faculty of Chemical and Food Engineering
Methods
Molasses fermentation process
Yeast culture
Nutrients
Molasses
Process
water
Media
preparation
Substarte
(Media)
Molasses
fermentation
Fermented
wash
Faculty of Chemical and Food Engineering
Methods
Yeast propagation optimization process generated data by Expert design 7.0 software
S
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4
Key factors
Response
S
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Key factors
Initial brix [o Initial pH
brix].
[pH]
Response
Inoculums
size [%]
Initial brix [o
brix].
Initial
pH
[pH]
1
11
4.3
20
17
11
11.75
4.4
37.87415
20
2
12.5
4.5
33.33
1
12
11.75
4.4
26.665
6
3
11
4.5
20
16
13
13.011
4.4
26.665
2
4
11.75
4.4
26.665
18
14
11.75
4.232
26.665
13
5
11.75
4.4
26.665
11
15
12.5
4.3
33.33
3
6
12.5
4.3
20
15
16
12.5
4.5
20
5
7
11.75
4.4
26.665
10
17
11.75
4.4
26.665
9
8
11.75
4.568
26.665
14
18
11
4.5
33.33
19
9
11.75
4.4
26.665
7
19
11.75
4.4
15.45585
8
10
10.489
4.4
26.665
12
20
11
4.3
33.33
Inoculum Viable Yeast Cells
s size [%]
*106 [V]
10
Viable Yeast
Cells *106
[V]
Faculty of Chemical and Food Engineering
Methods
Molasses fermentation optimization process generated data by Expert design 7.0 software
S
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Key factors
Intial brix [o
brix].
Response
Initial pH Inoculums Alcohol content
[pH]
size [%]
(%)
S
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Key factors
Intial brix [o Initial pH Inoculums
brix].
[pH]
size [%]
Alcohol
content (%)
16
1
20
4.4
26.665
10
11
25.045
4.4
26.665
12
2
20
4.568
26.665
20
12
20
4.4
26.665
17
3
20
4.4
26.665
3
13
17
4.5
20
13
4
20
4.4
15.456
1
14
17
4.3
20
19
5
20
4.4
26.665
8
15
23
4.5
33.33
2
6
23
4.3
20
11
16
20
4.232
26.665
4
7
23
4.5
20
15
17
20
4.4
26.665
14
8
20
4.4
37.874
5
18
17
4.3
33.33
7
9
17
4.5
33.33
9
19
14.955
4.4
26.665
6
10
23
4.3
33.33
18
20
20
4.4
26.665
11
Response
Faculty of Chemical and Food Engineering
Results and Discussion
Input raw material physicochemical characterization
Molasses Analysis such as
Total Reducing sugar = 51 %
Process water Analysis such as
Hardness = 105 ppm
 pH =6.97 pH
Un fermentable sugar (UFS) = 3.92 %
 Free chlorine before activated carbon = 0.5-1.0ppm
 Total Fermentable sugar (FS) = 47.08 %  Free chlorine after activated carbon = Nil
Calcium as (CaO) = 22171ppm
Reducing Sugar =16.26 %
 Sulphated Ash =17.5%
calcium salts is above the standard values that
reduces the activity of yeasts! (std <1650ppm)
Faculty of Chemical and Food Engineering
Yeast propagation optimization process generated data results by Expert design 7.0 software
S
t
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4
Key factors
Response
Intial brix [o
brix].
Initial
pH
[pH]
1
11
4.3
20
455
20
2
12.5
4.5
33.33
570
6
3
11
4.5
20
545
2
4
11.75
4.4
26.67
565
13
5
11.75
4.4
26.67
550
3
6
12.5
4.3
20
465
5
7
11.75
4.4
26.67
550
9
8
11.75
4.57
26.67
565
19
9
11.75
4.4
26.67
475
8
10
10.49
4.4
26.67
590
Inoculum Viable Yeast Cells
s size [%]
*106 [V]
13
Faculty of Chemical and Food Engineering
Yeast propagation optimization data results cont ….
S
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Key factors
Response
Intial brix [o
brix].
Initial pH
[pH]
Inoculums
size [%]
Viable Yeast
Cells *106
[V]
11
11.75
4.4
37.87
1
12
11.75
4.4
26.67
16
13
13.01
4.4
26.67
18
14
11.75
4.23
26.67
11
15
12.5
4.3
33.33
15
16
12.5
4.5
20
10
17
11.75
4.4
26.67
14
18
11
4.5
33.33
445
735
485
495
615
550
515
495
7
19
11.75
4.4
15.46
12
20
11
4.3
33.33
Viable yeast cells obtained at this optimum
conditions
490
500
14
Faculty of Chemical and Food Engineering
Interaction effects of initial media brix , pH and cell size on viable yeast cell count
viable yeast cells
Design-Expert® Softw are
4.50
33.33
viable yeast cells
Design Points
735
viable yeast cells
Design Points
735
4.45
445
X1 = A: inital media brix
X2 = B: inital media pH
6
4.40
Initial media pH
30.00
504.758
X1 = A: inital media brix
X2 = C: inoculums size
498.845
a
520.343
Actual Factor
B: inital media pH = 4.40
524.441
4.35
550.037
575.634
601.23
4.30
Initial media pH
445
Actual Factor
C: inoculums size = 26.66
viable yeast cells
Design-Expert® Softw are
504.758
6
26.66
520.343
23.33
535.929
551.514
567.099
20.00
11.00
11.38
11.75
12.13
12.50
Initial media brix
X1: A: inital media brix
X2: B: inital media pH
Contour response plot for viable yeast cell
b
11.00
11.38
11.75
Inoculums
size
X1: A: inital media brix
X2: C: inoculums size
15
12.13
12.50
Faculty of Chemical and Food Engineering
Interaction effects of initial media (brix , pH) and cell size on viable yeast cell count
viable yeast cells
Design-Expert® Softw are
33.33
512.546
viable yeast cells
Design Points
735
445
30.00
X1 = B: inital media pH
X2 = C: inoculums size
c
6
26.66
Inoculums size
Actual Factor
A: inital media brix = 11.75
For all the three (a, b and c)interaction
effects, as each contour factors s,
viable yeast cells s
512.546
542.116
482.976
571.686
23.33
601.256
20.00
4.30
4.35
4.40
4.45
4.50
Initial media pH
X1: B: inital media pH
X2: C: inoculums size
Contour response plot for viable yeast cell
16
Faculty of Chemical and Food Engineering
Fermentation optimization process data results generated by Expert design 7.0 software
S
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Key factors
Response
Intial brix [o
brix].
16
1
20
4.4
26.67
12
2
20
4.57
26.67
17
3
20
4.4
26.67
13
4
20
4.4
15.46
19
5
20
4.4
26.67
2
6
23
4.3
20
4
7
23
4.5
20
14
8
20
4.4
37.87
7
9
17
4.5
33.33
6
10
23
4.3
33.33
Initial pH Inoculums Alcohol content
[pH]
size [%]
(%)
8.17
8.73
7.76
8.86
8.08
8.9
7.99
8.21
8.19
8.79
Ebuliometer Or Alcoholometer
17
Faculty of Chemical and Food Engineering
Fermentation optimization data results cont…..
S
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Key factors
Intial brix [o Initial pH Inoculums
brix].
[pH]
size [%]
Response
Alcohol
content (%)
10
11
25.05
4.4
26.67
20
12
20
4.4
26.67
3
13
17
4.5
20
1
14
17
4.3
20
8
15
23
4.5
33.33
11
16
20
4.232
26.67
15
17
20
4.4
26.67
5
18
17
4.3
33.33
9
19
14.96
4.4
26.67
18
20
20
4.4
26.67
8.77
8.98
8.03
10.42
9.62
10.05
8.78
8.81
8.89
8.67
Alcohol content (%) obtained at this optimum
conditions
18
Interaction effects of initial media brix , pH and cell size on alcohol % content
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Alcohol content
Design-Expert® Softw are
4.50
Alcohol content
Design-Expert® Softw are
33.33
Alcohol content
Design Points
10.42
8.6369
8.73503
Alcohol content
Design Points
10.42
8.28886
8.5863
7.76
7.76
4.45
X1 = A: Intial media brix
X2 = B: Initial media pH
X1 = A: Intial media brix
X2 = C: Inoculums size
8.38522
6
Initial media pH
a
4.35
8.88859
9.14028
9.39197
4.30
18.50
20.00
21.50
6
26.66
Actual Factor
B: Initial media pH = 4.40
8.6369
17.00
8.43758
8.43758
Initial media pH
4.40
Actual Factor
C: Inoculums size = 26.66
30.00
23.00
Initial media brix
X1: A: Intial media brix
X2: B: Initial media pH
Contour Surface Response plot for alcohol (%) content
8.5863
23.33
8.73503
8.88375
8.28886
20.00
17.00
b
18.50
20.00
Inoculums size
X1: A: Intial media brix
X2: C: Inoculums size
19
21.50
23.00
Interaction effects of initial media (brix , pH) and cell size on alcohol % content
Faculty of Chemical and Food Engineering
Alcohol content
Design-Expert® Sof tw are
33.33
Alcohol content
Design Points
10.42
8.5576
7.76
30.00
X1 = B: Initial media pH
X2 = C: Inoculums size
c
6
26.66
Inoculums size
Actual Factor
A: Intial media brix = 20.00
8.5576
8.83345
8.28174
As each contour factors s
Alcohol content s
9.10931
23.33
9.38516
20.00
4.30
4.35
4.40
4.45
4.50
Initial media pH
X1: B: Initial media pH
X2: C: Inoculums size
Contour Response plot for alcohol (%) content
20
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Conclusion and Recommendation
Conclusion
 Optimization of yeast propagation and molasses fermentation processes parameters can
produce yeast cells and ethanol
 At the optimum condition of initial brix (11.75o brix), initial pH (4.4 pH) and inoculums size
(26.67 %), 735 million yeast cells per ml was obtained and higher compared with the current
result of Metahara which is below 240 million per ml
 At the optimum condition of initial brix (17 o brix), initial pH (4.3 pH) and inoculums size (20
%), 10.42 alcohol % was obtained and higher compared with the current result of Metahara
below 7 % alcohol (v/v)
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Recommendation
Further study is recommended on the following areas:
 The optimization of other molasses fermentation process parameters such as
fermentation time, temperature and agitation speed (rpm) etc should be
taken as key factors for further fermentation study.
 The optimization of distillation process parameters should be done to
separate the maximum alcohol coming from fermentation section
Faculty of Chemical and Food Engineering
cont…..
 The optimization of water treatment plant processes parameters should be
done to get contamination free water for yeasts not affected in both yeast
propagation and fermentation optimization processes
 The feasibility study of Metahara Sugar Factory Ethanol plant should be
done for ethanol production optimizations
Faculty of Chemical and Food Engineering
24
Faculty of Chemical and Food Engineering
Metahara
Ethanol
Factory
Distillery
Plant