ETHANOL PRODUCTION FROM SELECTED
CASSAVA VARIETIES IN FIJI AND TESTING OF
ETHANOL-PETROL FUEL BLENDS
by
Pritika Bijay
A thesis submitted in partial fulfilment of the
requirements for the degree of Master of Science in Physics
Copyright © 2013 by Pritika Bijay
School of Engineering and Physics
Faculty of Science, Technology and Environment
The University of the South Pacific
Fiji
January 2013
i
Declaration of Originality
I, Pritika Bijay, hereby declare that this thesis is my original work and wherever the
work of others has been used, it has been clearly referenced.
Signature
Date
Name Pritika Bijay
Student ID S11022830
Statement by Principal Supervisor
The research in this thesis was performed under my supervision and to my
knowledge is the sole work of Ms Pritika Bijay.
Signature __________________
Date __________________
Name Dr. Anirudh Singh
Designation Principal Supervisor
ii
Acknowledgments
The successful compilation of this thesis would not have been possible through the
assistance, support and guidance of many individuals who have helped me
throughout my research work. Therefore, I would like to take this opportunity to
express my sincere gratitude and heartfelt appreciation to the following individuals
whose help has been very much appreciated.
Firstly, I would like to express profound gratitude to my supervisor, Dr. Anirudh
Singh, for his invaluable support, encouragement, supervision and useful suggestions
throughout this research work. Also my sincere gratitude to Dr. Jagjit Khurma and
Mr. Villimone Vosarogo as co-supervisors for providing their help wherever needed.
My sincere appreciation also goes to the technical staff of School of Engineering and
Physics; Mr. Viti Buadromo, Mr. Amit Deo, Mr. Shanil Deo, Mr. Joape Cawanibuka,
Mr. Neil Singh, Mr. Rohit Lal and Mr. Abhinay Shandil for helping me during the
experimental stages of my thesis especially the technical assistance with operation of
the instruments. My special thanks also go to Mr. Steven Sutcliffe, Mr. Shelvin
Prasad, Ms. Roslyn Lata, Mr. Dinesh Kumar and Mr. Hirdesh Singh of School of
Biological and Chemical Sciences for providing me with the necessary equipment
and instruments. My most sincere gratitude also goes to Koronivia Research Station
and Dobuilevu Research Station for providing me with the different cassava
varieties. Also a special thanks to Mr. Poasa Nauluvula for providing the relevant
information on the cassava varieties. Special thanks also go to my dear friends; Mr.
Shivneel Prasad, Mr. Rajneel Prasad, Mr. Naveendra Reddy, Mr. Pranil Singh, Ms
Monishka Narayan, Ms Esha Chetty, Ms Priti Maharaj, Ms. Pritika Reddy, Mr. Atesh
Gosai, Mr. Sunil Chand, Mr. Aman Deo, Mr. Imraan Jannif and Mr. Malvin Nadan
for the words of encouragement and support during every stage of my thesis.
Finally, I would like to thank my parents, for their continuous support throughout my
life and always encouraging me to further my knowledge and studies. Thanks also to
my sister, Asnita. Furthermore, the backing and continual encouragement given by
my husband was a source of inspiration to my work. He has been a pillar of strength
for me and I am deeply obliged to him for standing by my side.
iii
Abstract
Ethanol production from renewable resources has received worldwide attention due
to increasing petroleum shortage. One such renewable resource that has been
identified is cassava starch, which can be extracted from root crop cassava (Manihot
esculenta (Crantz)) and is readily available in Fiji. Ethanol may be used as a fuel for
spark-ignition engines either in its original form, or as blends with petrol. The most
feasible way of expanding the use of ethanol as a fuel, however, is by using ethanol-
petrol blends in vehicles already on the road, without the need to modify the engines.
The main objective of this study was to produce ethanol from some of the locally
available cassava varieties in Fiji, and to test the operation of spark ignition (SI)
engines on various ethanol-petrol blends.
Starch was extracted from the roots of ten different cassava varieties available at two
different research stations in Fiji using the sedimentation technique, and the yields
were determined. In the case of Koronivia Research Station (KRS) the variety
Nadelei had the highest starch yield (23.1 %) whereas Coci had the highest starch
yield (23.3 %) for Dobuilevu Research Station (DRS). The extracted starch was then
used to produce ethanol via the technique of Simultaneous Saccharification and
Fermentation (SSF), with the yeast Saccharomyces cerevisiae being used as the
fermentation agent. Ethanol yield was in the range of 0.35-0.40 L of ethanol per kg
of starch and 0.35-0.41 L of ethanol per kg of starch for KRS and DRS respectively.
Ethanol-petrol blends, E10, E15 and E20 were prepared from alcohol with varying
degrees of water content. It was found that 96 % ethanol could be used to prepare
blends that did not phase separate at temperatures typical of the tropics.
The prepared blends were tested on a SI engine for engine efficiency, fuel
consumption and exhaust emissions. An increase in fuel consumption was noted as
the engine load was increased and also as the ethanol content in petrol was increased.
The latter effect was identified as being due to the lower gross calorific value (GCV)
of ethanol as compared to petrol. Hence, as the ethanol fraction in ethanol-petrol
iv
blend increased, the GCV decreased, and as a result more fuel was required. At
maximum load, there is a decrease in carbon monoxide (CO) emission by 34, 61 and
78 % with the E10, E15 and E20 blends respectively when compared to petrol.
Reductions in exhaust emissions of hydrocarbons (HC) by approximately 10, 30, and
34 % were noted for E10, E15, and E20 blends respectively at maximum engine
loadings. Reductions were also observed in carbon dioxide (CO2) emissions at
maximum engine load for E10 (7 %), E15 (17 %) and E20 (20 %) when compared to
petrol.
v
List of Abbreviations, Units and Nomenclature
LIST OF ABBREVIATIONS
AFR Air-fuel ratio
B Biomass
B5 5 % biodiesel with 95 % diesel
CF Calibration Factor
CI Compression Ignition
CIAT Centro Internacional de Agricultural Tropical
CO Carbon Monoxide
CO2 Carbon Dioxide
DMC Dry matter content
DNS 3, 5 – dinitrosalicylic acid
DRS Dobuilevu Research Station
E Ethanol
E10 10 % ethanol with 90 % petrol
E15 15 % ethanol with 85 % petrol
E20 20 % ethanol with 80 % petrol
E22 20-24 % ethanol blended with 80-76 % petrol
E85 85 % ethanol blended with 15 % petrol
E100 100 % ethanol
ECU Electronic Control Unit
FAO Food and Agriculture Organization
FDOE Fiji Department of Energy
FFT Flexible Fuel Technology
GC Gas Chromatography
GCV Gross calorific value
HC Hydrocarbons
KRS Koronivia Research Station
LOS Left over sugar
NOx Nitrogen oxide
PM Particulate matter
vi
S Substrate
SD Standard Deviation
SI Spark Ignition
SFC Specific Fuel Consumption
US United States
WOT Wide Open Throttle
LIST OF UNITS
% Percent
° Degree
°C Degrees Celcius
µm Micrometre
atm Atmosphere
cm Centimetre
div Division
g Gram
g l-1 Gram per litre
g cm-3 Gram per cubic centimetre
hrs Hours
K
kJ g-1
Kelvin
Kilojoules per gram
kJ ml-1 Kilojoules per millilitre
L litre
L t-1 Litre per tonne
kg ha-1 year-1 Kilograms per hectare per year
M Molar
m Metre
ml Millilitre
min Minute
ml min-1 Millilitre per minute
nm Nanometer
ppm Parts per million
vii
rpm Revolutions per minute
t ha-1 Tonne per hectare
t ha-1 year-1 Tonnes per hectare per year
W Watt
LIST OF NOMENCLATURE
inE Energy input to the generator
outE Energy output of the generator
ε Compression ratio
1L Power loss from the engine
2L Power loss from the alternator
E� Engine Efficiency
S� System Efficiency
A� Alternator Efficiency
λ Air-fuel equivalence ratios
FS� Density of fuel sample
outP Power output of the alternator
inP Power input of the engine
1P Power input of alternator
QP Volumetric ethanol productivity
YX/S Conversion rate of starch to biomass
YP/S Yield factor of ethanol on substrate
YP/X Yield factor of ethanol on biomass
viii
Table of Contents
Declaration of Originality i
Acknowledgments ii
Abstract iii
List of Abbreviations, Units and Nomenclature v
Table of Contents viii
List of Figures xi
List of Tables xiii
Chapter 1 Introduction 1
1.1 Ethanol as a Biofuel for Transportation 1
1.2 Objectives 8
1.3 Structure of the Thesis 9
1.4 Relevance of the Thesis 10
Chapter 2 Literature Review 11
2.0 Overview 11
2.1 Cassava 11
2.1.1 Cassava Breeding 12
2.1.2 Effect of Environmental Factors on Cassava 13
2.1.3 Cassava Varieties 14
2.2 Production of Ethanol 15
2.3 Ethanol as Fuel 20
Chapter 3 Methodology 28
3.0 Overview 28
3.1 Cassava Varieties in Fiji 28
3.1.1 Dry Matter Content of Cassava Roots 29
3.1.2 Starch Extraction from Cassava Roots 29
ix
3.1.2.1 Moisture Content of Starch 31
3.1.2.2 Ash Content of Starch 31
3.1.2.3 pH Determination of Starch 31
3.2 Ethanol Production from Cassava Starch 32
3.2.1 List of Equipment and Reagents 32
3.2.2 Preparation of Cassava Starch Solution 33
3.2.3 Treatment of Cassava Starch Solution to Simple Sugars 34
3.2.3.1 Pre-treatment of Gelatinized Starch with α-amylase 35
3.2.4 Simultaneous Saccharification and Fermentation 36
3.2.5 Analytical Analysis 37
3.2.5.1 Reducing Sugar Analysis 37
3.2.5.2 Determination of Ethanol Concentration 39
3.3 Preparation of Ethanol-Petrol Blends 40
3.3.1 Stability Testing of Ethanol-Petrol Blends 41
3.4 Physical Properties 41
3.4.1 Gross Calorific Value 42
3.4.1.1 Calibrating the Bomb Calorimeter 43
3.4.1.2 Determination of Gross Calorific Value 43
3.4.2 Density 44
3.4.2.1 Determine the Volume of the Picnometer 45
3.4.2.2 Determine the Density of Fuel Sample 46
3.5 Engine Efficiency, Fuel Consumption and Emission Testing 46
3.5.1 The Testing Equipment 48
3.5.2 The Testing Procedure 50
3.6 Engine Efficiency 50
3.6.1 Power Loss from the System 53
3.7 Emission Testing 55
3.7.1 Instrument Start-up 55
3.7.2 Measurement of Emission 56
Chapter 4 Results and Discussions 58
4.0 Overview 58
4.1 Cassava Varieties in Fiji 58
x
4.2 Ethanol Production from Cassava Starch 67
4.3 Preparation of Ethanol-Petrol Blends 82
4.4 Physical Properties of Ethanol-Petrol Blends 85
4.4.1 Density 85
4.4.2 Gross Calorific Value 87
4.5 Engine Performance and Emission Characteristics of Ethanol-Petrol 87
Blends
4.5.1 Engine Efficiency 88
4.5.1.2 Engine Losses 90
4.5.2 Fuel Consumption 91
4.5.3 Specific Fuel Consumption 92
4.5.4 Engine Exhausts Emission Analysis 93
4.5.4.1 CO Emission 94
4.5.4.2 HC Emission 95
4.5.4.3 CO2 Emission 96
4.5.4.4 The Effects of Various Fuels on Exhaust Emissions at Constant 97
Load
4.5.5 Prospects and Challenges for Bio-ethanol Use in Vehicles 99
Chapter 5 Conclusions 102
5.1 Recommendations and Suggestions for Future Work 104
REFERENCES 106
APPENDIX A 122
APPENDIX B 123
APPENDIX C 124
APPENDIX D 125
xi
List of Figures
CHAPTER 1
Figure 1.1 Schematic diagram of fuel system of an SI Engine 3
Figure 1.2 A four stroke spark ignition cycle 4
Figure 1.3 Fiji’s fuel import bills as compared with total
import bills
7
CHAPTER 3
Figure 3.1 Map of Fiji showing the collection points of
cassava varieties
28
Figure 3.2 Flowchart for cassava starch production 30
Figure 3.3 Gelatinized cassava starch solution 34
Figure 3.4 Starch hydrolysis using α-amylase 36
Figure 3.5 Setup for Simultaneous Saccharification and
Fermentation
37
Figure 3.6 Setup for Ballistic Bomb Calorimeter 42
Figure 3.7 Picnometer with Fuel Sample 45
Figure 3.8 Equipment for testing engine efficiency, fuel
consumption and emission
49
Figure 3.9 Generalised flowchart of the systems input, output
and losses
52
CHAPTER 4
Figure 4.1 Rainfall and Temperature data at KRS 60
Figure 4.2 Rainfall and Temperature data at DRS 61
Figure 4.3 Ethanol Concentration and remnant reducing sugars
concentration from (a) Niumea, (b) Sokobale, (c)
Beqa, (d) New Guinea, (e) Coci, (f) Vula Tolu, (g)
Yabia Damu, (h) Merelesita, (i) Nadelei, (j)
Navolau cassava variety starch obtainedat KRS
72
Figure 4.4 Ethanol Concentration and remnant reducing sugars
concentration from (a) Niumea, (b) Beqa, (c) New
77
xii
Guinea, (d) Coci, (e) Vula Tolu, (f) Yabia Damu,
(g) Merelesita, (h) Nadelei, (i) Navolau cassava
variety starch obtained at DRS
Figure 4.5 Density of Petrol, E10, E15 and E20 86
Figure 4.6 GCV of Petrol, E10, E15 and E20 on mass and
volume basis
87
Figure 4.7 Engine efficiency using Petrol and Ethanol-Petrol
blends under varying loads
89
Figure 4.8 Fuel consumption of Petrol, E10, E15, E20 under
varying loads
91
Figure 4.9 Specific Fuel Consumption of Petrol, E10, E15,
E20 under varying load
93
Figure 4.10 Effect of varying loads on CO emissions for Petrol,
E10, E15 and E20
94
Figure 4.11 Effect of varying loads on HC emissions for Petrol,
E10, E15 and E20
95
Figure 4.12 Effect of varying loads on CO2 emissions for
Petrol, E10, E15 and E20
97
Figure 4.13 CO emissions for various fuels at maximum load 98
Figure 4.14 HC emissions for various fuels at maximum load 98
Figure 4.15 CO2 emissions for various fuels at maximum load 99
xiii
List of Tables
CHAPTER 1
Table 1.1 Modifications required for different ethanol contents
in ethanol-petrol blends
6
CHAPTER 2
Table 2.1 Kinetics parameters of ethanol production from
starch following growth of C. tropicalis, S.
cerevisiae, and S. occidentalis in the presence and
absence of α-amylase treatment
16
Table 2.2 Ethanol concentration and left over sugar in solid
substrate fermentation from various starchy
substrates using thermotolerant yeast (VS3)
18
CHAPTER 3
Table 3.1 Reagents used for ethanol production 33
Table 3.2 Specification of the petrol engine 47
Table 3.3 Specification of the generator 48 Table 3.4 Specifications of the Horiba Automotive Emission
Gas Analyser
55
CHAPTER 4
Table 4.1 Starch Yield from Cassava Varieties 59
Table 4.2 Dry Matter Content of Cassava Varieties 62
Table 4.3 Ash Content of Cassava Starch from Various
Varieties
63
Table 4.4 pH of Cassava Starch from Various Varieties 64
Table 4.5 Moisture Content of Cassava Starch from Various
Varieties
65
Table 4.6 Comparison of ethanol yield made from various
energy crops
66
Table 4.7 Final ethanol concentration and ethanol yield from 78
xiv
cassava varieties from two different locations
Table 4.8 Cassava required for producing 1 L ethanol from
each cassava variety studied
80
Table 4.9 Composition of Obtained Ethanol Yield with
Literature Results
81
Table 4.10 Composition of ethanol-petrol blended samples used
for analysis
83
Table 4.11 Stability testing using absolute ethanol in ethanol-
petrol blends
83
Table 4.12 Stability testing using 97 % ethanol in ethanol-petrol
blends
83
Table 4.13 Stability testing using 95 % ethanol in ethanol-petrol
blends
84
Table 4.14 Stability testing using 93 % ethanol in ethanol-petrol
blends
84
1
Chapter 1 Introduction
1.1 Ethanol as a Biofuel for Transportation
With the rapid development of industrialised society, the demand for fossil fuel has
been growing every day. The resulting escalation of oil prices coupled with a
forecast shortage of fossil fuel reserves has been the cause of great anxiety. These
factors and the increasing energy demand for transportation to keep the pace of
economic development are alerting many countries to the need to find alternative
energy sources. Biofuels is amongst the principal candidates for such alternative
fuels, especially for the transport sector.
One such biofuel is bio-ethanol or simply ethanol. Bio-ethanol’s greatest benefit lies
in its potential to reduce greenhouse gas emissions by partial replacement of oil as a
transport fuel (IEA, 2004). It can also reduce the burden of foreign currency
expenditure for poor countries that import petroleum products but have the potential
to produce and use bio-ethanol (WWI, 2006).
Brazil’s success story in using sugarcane based ethanol is quite well known. Many
advocates of biofuel subsidies and mandates frequently cite their experience. Brazil
is the world’s number two ethanol producer and the leading ethanol exporter, using
sugarcane as its feedstock (Hofstrand, 2009). In 2011 Brazil contributed to 24 % of
global ethanol production, when compared to 30 % in 2010 (REN21, 2012). After
being number one exporter for many years, the decline in ethanol production is
attributed to the decline in investment in new sugarcane assets and plantations since
the 2008 financial crisis, poor sugarcane harvests due to unfavorable weather and
high world sugar prices (OECD, 2011; Colitt and Nielson, 2012). Authorities in
Brazil had made it mandatory to have 20-25 % ethanol blended in petrol. However,
since the decline in ethanol production Brazil announced new policies to stimulate
sugar production and to reduce the amount of ethanol required in gasoline to 20 %
(Biofuels Digest, 2012). Bio-ethanol is an excellent substitute for gasoline, the main
Chapter 1: Introduction
2
car fuel used by spark ignition (SI) engines around the globe. Bio-ethanol can be
used in SI engines, either in its pure form or blended with conventional petroleum-
derived fuels.
A typical fuel system of an SI engine consists of the following parts, arranged
sequentially (Stephenson, 1973; Stone, 1999):
� Fuel tank- for storage of fuel (petrol)
� Fuel pump- to supply fuel to the carburetor or fuel injection system
� Fuel filter- to remove particles and impurities from fuel
� Fuel lines- tubes through which fuel passes from the tank to carburetor or fuel
injection system
� Carburetor- a (now outdated) device that atomizes the fuel and mixes it with
the correct amount of air (this device has now been replaced by a modern
electronic fuel injection (EFI) system)
� Intake manifold- where fuel is added to the air either by fuel injectors or the
carburetor
� Fuel injectors- devices that inject precise amounts of fuel into the incoming
air ensuring maintenance of the stoichiometric ratio
� Fuel pressure regulator- a device that controls fuel pressure
A schematic diagram of the fuel system for the SI engine is shown in Figure 1.1:
Chapter 1: Introduction
3
Figure 1.1: Schematic diagram of fuel system of an SI Engine
Recent developments have seen the complete computerization of engine controls and
fuel delivery systems (Fergerson and Kirkpatrick, 2001). In the 1980s conventional
carburetors were replaced by throttle body fuel injectors and later in 1990s these
were replaced by port fuel injectors (Fergerson and Kirkpatrick, 2001).
SI engines are also referred to as Otto cycle engines and these operate as four or two
stroke cycle. In a four stroke SI engine, a charge of premixed fuel-air mixture
(delivered by the fuel system) is drawn into the combustion chamber through intake
valves where the charge is then compressed by the motion of the piston. The
compressed fuel-air mixture is then ignited by one or more spark plugs; a turbulent
flame develops and propagates through the mixture, raising the temperature and
pressure of the cylinder. The flame extinguishes when it reaches the cylinder walls.
The burned gasses exit the engine past the exhaust valves, through the exhaust
manifold and into a central exhaust pipe. Figure 1.2 shows the spark ignition cycle of
a four stroke cylinder.
Unused Fuel Returned to Tank
FUEL TANK
FUEL PUMP
FUEL FILTERS
CARBURETOR OR FUEL
INJECTION SYSTEM
FUEL PRESSURE
REGULATOR
INTAKE MANIFOLD
ENGINE COMBUSTION
CHAMBER
Chapter 1: Introduction
4
Figure 1.2: A four stroke spark ignition cycle (Source: Ferguson an Kirkpatrick,
2001)
Bio-ethanol, a clear, colourless liquid made from renewable sources such as
sugarcane, molasses and starch is being considered for use in SI engines. Bio-
ethanol’s characteristics enable cleaner combustion and better engine performance,
which contribute to reduced pollutant emissions, even when it is mixed with petrol.
Bio-ethanol is considered particularly attractive as an alternative fuel because it is a
renewable bio-based resource and is oxygenated, which provides the potential to
reduce particulate emissions in SI engines (Gravalos et al, 2011).
Bio-ethanol has several advantages as a transportation fuel. It has high octane
number (i.e. has a high anti-knock quality). This enables it to operate at high
compression ratios which improve engine efficiency, power output and fuel
consumption (Lin et al, 2010). It also has high heat of vaporization when compared
Chapter 1: Introduction
5
to petrol. This enables the engine volumetric efficiency to increase (Bayraktar,
2005), which means it freezes the air, allowing more mass (fuel) to be drawn in the
cylinder resulting in increased power output (Lin et al, 2010). In addition, the use of
ethanol can reduce significantly carbon monoxide (CO) and hydrocarbon (HC)
emissions. This is due to the leaning effect caused by ethanol addition (Koç et al,
2009).
The simplest and fastest way of expanding the use of ethanol as a fuel is by using
ethanol-petrol blends in vehicles already on the road, without the need for modifying
engines. Developing countries that currently have a limited capacity to produce cost-
efficient ethanol with good energy and environmental balances can diversify their
liquid fuels options by importing ethanol from regions with favorable conditions for
biofuel production. These developing countries in the meantime can consider suitable
resources to be used for bio-ethanol production in their country which can then be
used locally.
It is important to consider the consequences of adopting ethanol-petrol blends on
engine performance, drivability and durability of vehicles, as well as the associated
environmental impacts. Table 1.1 shows the modifications to vehicle engines
required for different ethanol contents in petrol
Chapter 1: Introduction
6
Table 1.1: Modifications required for different ethanol contents in ethanol-petrol
blends (Source: ANFAVEA, 2005)
% of bio-ethanol in gasoline
Changes to a pure gasoline vehicle
Car
bure
tor
Fuel
inje
ctio
n
Fuel
pum
p
Fuel
filte
r
Igni
tion
syst
em
Fuel
tank
Cat
alyt
ic c
onve
rter
Bas
ic e
ngin
e
Eng
ine
oil
Inta
ke h
eade
r
Exh
aust
syst
em
Col
d-st
art s
yste
m
≤ 5 % Any Vehicle
≤ 10 % Vehicles produced from 1990 onwards
≤ 25 % Brazilian gasoline vehicle
≤ 85 % Flexible vehicle used in the USA and in Canada
≥ 85 % Flexible vehicle used in Brazil
No changes are necessary
Changes are probably necessary
Ethanol is an attractive alternative fuel for SI engine and can be used as a pure fuel or
blended with petrol. Using neat ethanol in SI engines will require modifications of
engine design and fuel systems. However, using ethanol in lower percentages
blended with petrol does not (see Table 1.1). Therefore, using ethanol-petrol blends
in SI engines is generally more expedient than using pure ethanol.
Biofuels offer a realistic option for Fiji to minimize some of its energy challenges
(Cloin et al., 2007) as evident in the fossil fuels import bills of the country. As seen
in Figure 1.3 fuel imports form a major part of the country’s total import bills. With
the successful production and use of biofuel, there will be a reduction in the
country’s fossil fuel import bills. Successful use of biofuels will also see a reduction
in greenhouse gas emissions that is caused by burning fossil fuels.
Chapter 1: Introduction
7
Figure 1.3: Fiji’s fuel import bills as compared with total import bills (Source:
Fiji (Bureau of Statistics, 2011)
Biofuels can play a fundamental role in the transportation sector of Fiji (Singh,
2012). The transportation needs of Fiji can be satisfied by using biodiesel and its
blends with diesel for Compression Ignition (CI) engine vehicles or by using bio-
ethanol and its blends with petrol for SI engine vehicles (Singh, 2012).
Fiji has the necessary resources available for bio-ethanol production (Singh, 2012).
Over the past years interest has been shown in bio-ethanol production in Fiji. The
possible feedstock identified was sugarcane and cassava. When considering
sugarcane, there are two options: either to use sugarcane juice, or molasses for
ethanol production. In a presentation made by the Director of Fiji Department of
Energy (Nakavulevu, 2011) during a workshop organized by International
Renewable Agency indicated that Fiji would require 7, 466, 242 L of ethanol for
blending with petrol for E10. His presentation also indicated that of the 100, 000 t of
molasses that Fiji Sugar Corporation produces, could produce 34 M L of ethanol
annually of which 8 M L will be require for blending to produce E10 while the rest
cold be imported. For developing the biofuel or bio-ethanol industry in Fiji it is
important to have available resources. These include feedstock plantations and also
available land area for the further development. Fiji has about 1.8 million ha of
0
500000
1000000
1500000
2000000
2500000
3000000
3500000
4000000
Fuel
and
tota
l nat
ioin
al im
port
s ($
000)
Year
Fiji's fuel imports (2000-2010)
Total fuel imports ($FJ000)
Total national imports ($FJ000)
Chapter 1: Introduction
8
available land, of which less than 19 % is available for agriculture. Since very small
portion of the land is arable, biofuels development needs careful investigation
beyond the technical investigation.
Fiji has recently made significant strides in developing its human capacity for
development of renewable energy resources, especially in the biofuel area. As
discussed by Singh (2012), the Fiji Department of Energy (FDOE) has established
biofuels units with staff experienced in biofuels research. The local universities have
started producing graduates with scientific training in biofuels, and the FDOE’s
biofuel unit has developed a biofuels standard for Fiji. In addition, legislation is now
in place to enforce these standards. This includes the use of 5 % biodiesel with 95 %
diesel (B5) in CI engine vehicles and 10 % ethanol with 90 % petrol (E10) in SI
engine vehicles. There has been significant interest by the private sector in the
biofuels industry as well.
Bio-ethanol is a promising alternative fuel for Fiji, with the availability of more than
one feedstock to consider and the availability of land to increase production, as well
as the potential for improvement in human capacity and interest by government and
private sector. It is clearly evident that with proper planning and development of the
biofuel industry, Fiji can improve its overall energy situation. The primary goal of
this study was to produce bio-ethanol from a renewable resource available in Fiji
which could be considered for blending with petrol for use in SI engines. An
important secondary goal was the testing of such blends in SI engines with a view to
ascertaining their viability for mitigating Fiji’s fuel supply and fuel import bill
situation.
1.2 Objectives
The main object of this project was to investigate the potential of using cassava as
feedstock for bio-ethanol production and the viability of using ethanol-petrol blends
as automotive fuels. The specific objectives were:
Chapter 1: Introduction
9
� To investigate the ethanol yield from selected cassava varieties obtained from
two different locations in Fiji.
� To determine the fuel characteristics of some ethanol-petrol blends and to
compare their properties with those of neat petrol.
� To compare the performance of an SI engine in terms of engine efficiency,
fuel consumption and exhaust emissions when using ethanol-petrol blends
with that of neat petrol
1.3 Structure of the Thesis
This thesis is organised as follows:
� Chapter 1 begins with an introduction which, amongst other things, gives an
overview of the research background, discusses the objectives and gives an
outline of the thesis.
� Chapter 2 provides an overview of the literature on the root crop cassava, the
breeding techniques, and effects of environmental factors on cassava. It also
provides details of the local cassava varieties in Fiji. This chapter briefly
outlines some techniques and results obtained by various authors that have
used cassava as feedstock for ethanol production. Finally, it describes the use
of ethanol as a fuel.
� Chapter 3 discusses the techniques and methods used in the data collection
for this work. The extraction of starch and determination of some of its
properties is described. Following this, the method for ethanol production
from the different varieties of starch and determining the ethanol content is
outlined. The technique used for blending ethanol-petrol together with the
determination of some fuel properties is presented. Also presented is the
method for the engine performance and emission tests.
� Chapter 4 presents the results and discusses their implications. This includes
tabulated results and discussion for starch yield, dry matter content and
various other properties of starch. The stability testing results and discussion
as well as variation of the density and gross calorific value with the varying
percentage of ethanol is shown. The engine performance in terms of fuel
Chapter 1: Introduction
10
consumption, specific fuel consumption and engine efficiency is analysed.
The emission characteristics of the ethanol-petrol bends are also presented
and discussed.
Chapter 5 summarizes the results of this work and provides suggestion for further
studies.
1.4 Relevance of the Thesis The work done in this research can contribute to developing knowledge on the bio-
ethanol market in Fiji, thus providing an important source of information to
policy/decision makers, academic researchers, businesses/industry and interested
groups. Some of the data presented in this research is completely new. This includes
the data on starch yield and the ethanol yield from the ten different cassava varieties
in Fiji that were studied. Therefore, this research is a start to obtaining important
information needed for the development of the bio-ethanol production industry in Fiji
For academic researchers this study can serve as a platform to provide basic
information on the bio-ethanol development using cassava available in Fiji as
feedstock. It enables potential areas to be identified for further study and research.
Similarly, for business society bio-ethanol development in the country is at an early
stage. Currently, there is no large scale ethanol production in Fiji. However, various
feedstock are being considered and this includes mainly molasses. With the
information contained in the study, important understanding can be obtained about
bio-ethanol in general and cassava as a potential feedstock.
Finally, for policy and decision makers some of the social and environmental issues
as well as barriers discussed in this work can provide important inputs for policy and
decision making to make interventions for sustainable domestic bio-ethanol
production.
11
Chapter 2 Literature Review
2.0 Overview
This chapter reviews relevant research done by various researchers in other countries
on cassava ethanol and the use of ethanol-petrol fuel blends. It discusses the use and
breeding of cassava globally and the various varieties of cassava present in Fiji, and
proceeds to consider various procedures used for producing ethanol from biomass
such as starch. Finally, it reviews the work done on ethanol blends as fuel for spark
ignition (SI) engines, and discusses the advantages as well as drawbacks associated
with the use of ethanol as blended fuels.
2.1 Cassava
Cassava or manioc (Manihot esculenta (Crantz)) which is a perennial shrub of the
New World is currently the sixth world food, in terms of global annual production
(Burns et al., 2010; El-Sharkawy, 2004). Cassava roots are an important staple food
for more than 800 million people in tropical and sub-tropical Africa, Asia and Latin
America (Burns et al., 2010). As Srinivas and Anantharuman (2000) have stated,
after cereals and grain legumes, root and tuber crops are the most important food
crops. Due to cassava’s potential for high matter production per day it stands out
among them.
Cassava is considered as one of the most important calorie-producing crops in the
tropics. It is adapted to a wide range of environments, and tolerant to drought and
acidic soils as well as being an efficient producer of carbohydrates (Jones, 1959;
Rogers and Appan, 1970; Kawano et al., 1978; Cock, 1982).
The importance of cassava is derived from its diverse use for human consumption,
animal feed and industrial application. According to Cock (1982) fresh roots of
cassava contain 30 to 40 % dry matter and approximately 85 % of the dry matter is
Chapter 2: Literature Review
12
starch. This percentage may vary according to cultivars, environment and plant age,
as pointed out by O’Hair et al. (1981), Rodriguez-Sosa et al. (1976) and Wholey and
Booth (1979). These researchers have stated that on fresh weight basis, root starch
concentration ranges from 5 to 40 %.
Starch, which consists 13-21 % amylose (Grace, 1977), is an important source of
carbohydrate for people who consume it. Young cassava leaves are also harvested
and used for human consumption as a vegetable or a constituent in the form of sauce
eaten along with staple meals (Lancaster and Brooks, 1983).
According to El-Sharkawy (2004) “About 70 % of the world cassava root production
(which is estimated to be 45 million metric tons of dry root annually) is used for
human consumption either directly after cooking or in processed forms; the
remaining 30 % is used for animal feed and other industrial products such as starch,
glucose and ethanol.”
2.1.1 Cassava Breeding
In the early 1970s a cassava breeding program was initiated by CIAT (Centro
Internacional de Agricultural Tropical) headquartered in Cali, Columbia. The main
objectives of CIAT were to improve yield potential and tolerance to diseases and
insect pests and adverse soil and environmental conditions (Kawano, 2003).
Cassava is one of the most efficient producers of carbohydrates under poor soil
conditions (Cook, 1982). According to this author, cassava crops are grown between
30° N and 30° S, in areas where mean temperature are greater than 18 °C and the
annual rainfall is greater than 750 ml. However, the growing conditions can differ for
different regions. Cassava can be grown in marginally, low fertility acidic soils under
variable rain-fed conditions ranging from less than 600 ml in semi-arid tropics (De
Tafut et al., 1997) to 1000 ml in sub-humid tropics (Pellet and El-Sharkawy, 1997).
Cassava generally grows in many soil types. However, cassava to some extent is
intolerant of saline or persistent water-logged conditions and it also does not tolerate
temperature at or below 10 °C (O’ Hair, 1990). According to Cock (1985) cassava
Chapter 2: Literature Review
13
tolerates soil with a pH of as low as 4.4 provided the aluminium level does not
exceed 80 % saturation and it also tolerates a pH as high as 8.0.
Cassava is propagated vegetatively from mature woody stem cuttings. Usually 15-30
cm long stem cuttings are planted horizontally, vertically, or inclined on flat or
ridged soils at densities ranging from 5000 to 20000 cuttings per hectare depending
on cropping system and purpose of production (Keating et al., 1988).
The harvesting time of roots differ and is dependent on cultivars, purpose of use and
growing conditions. However, generally it is 7-24 months after planting (El-
Sharkawy, 2004). According to El-Sharkawy, fresh roots have to be used
immediately after harvest for consumption, processed for starch extraction, dried for
flour production, roasted for food products and/or used for animals. This is because
roots tend to perish and deteriorate rapidly after harvest. However, pre-harvest
pruning in the weeks before harvest decreases root deterioration because of increases
in total sugar/starch ratio in roots (Van Oirschot et al., 2000).
Although, propagation by stem cuttings is the most common practice, it can also be
propagated from seeds (Ceballos et al., 2004). According to the authors seeds are
generated through crossing in breeding programs and this result in creating new
genetic variation. The use of seeds in commercial cassava production is a promising
option to obviate constraints, particularly diseases associated with vegetative
propagation (Iglesias et al., 1994).
2.1.2 Effect of Environmental Factors on Cassava
Like every other crop, cassava also needs certain favourable environmental
conditions for proper growth and development. According to Sriroth et al. (2001)
although cassava has the reputation of being a drought tolerant crop, when deprived
of water, plant and root development are affected. This eventually translates to an
altered starch synthesis expressed by variation in starch quality. According to these
authors, water stress plays an important role in the starch quality. Usually water
stress in early plant development retards growth and this only resumes after
immature plant receives sufficient water. In mature plants, environmental conditions
Chapter 2: Literature Review
14
affect the starch quality prior to root harvest. This is especially noticeable after the
onset of rain after a stress period as indicated by reduced starch paste.
Intensive production of cassava requires favourable climatic and soil conditions.
However, according to Silvestre (1989) in comparison with other plants, cassava
exhibits considerable tolerance to these factors. Silvestre has stated that the ideal
conditions for growing cassava are rain every two or three days, with large amounts
of sunshine in between, without a marked dry season or with a dry season lasting no
longer than two months.
The factors responsible for starch variation in roots are either influenced by genetic
or those influenced by environmental condition including the amount of rain
(Moorthy and Ramanujam, 1986; Asaoka et al., 1991; Asaoka et al., 1992; Defloor
et al., 1998; Sriroth et al., 1999; Santisopasri et al., 2001). Therefore, it becomes
extremely important to determine the suitable environmental condition for a
particular cultivar to be planted.
2.1.3 Cassava Varieties
When choosing cassava variety, the main criterion is of course productivity in terms
of dry matter or starch. But it can be the earliness of maturity as well, as some
varieties mature earlier than the others (Silvestre, 1989). According to Silvestre,
research centers and stations have programmes aimed at creating highly productive,
disease-resistant material and selecting varieties that are adapted to the ecological
situation with which they are concerned.
The classification of cultivars (varieties) is usually based on pigmentation and shape
of the leaves, stems and roots (Rogers and Appan, 1973). The cassava varieties in
Fiji are also identified using the above mentioned classifications.
According to Mason (1956), variety collection for Fiji cassava started in 1950,
resulting in the identification of fourteen Fijian varieties. However, Mason’s paper
has actually described sixteen varieties that were present at that time. These varieties
were; Vulatolu, Vulatolu 2, Merelesita, Merelesita 2, Yabia Damu, Yabia Vula,
Chapter 2: Literature Review
15
Niumea, Coci, Sokobale, Aikavitu, Kasaleka, Katafaga, Belesilika, Manioke, Yasawa
and Macuata.
Currently, Koronivia Research Station (KRS) is growing the following twenty-eight
varieties; Vulatolu, Vulatolu 2, Merelesita, Merelesita 2, Yabia Damu, Yabia Vula,
Niumea, Coci, Sokobale, Aikavitu, Kasaleka, Katafaga,, Belesilika, Manioke, Yasawa
Vulatolu, Malaya (Macuata), Ro Tubuanakoro, Coci (selection), Vulatolu (Dalip
Singh), H.165, H.97, Tilomuria No.3, Tavioka Falawa, Navolau, New Guinea,
Lomaivuna, Beqa, Hawaii and Kadavu (Nauluvula, 2009, pers. comm.).
Although, all of these cassava varieties can be grown together in the same ecological
conditions, their yield may differ indicating that different varieties may thrive better
if planted in those environmental conditions more suited. Hence, as Silvestre (1989)
has stated the best varieties for a given ecological situation are those that maintain a
good balance between the production of new leaves, stems and that of tuberous roots
in that particular environment.
2.2 Production of Ethanol
Ethanol (ethyl alcohol) is considered renewable when produced from sustainable
agricultural sources. It has the potential for reducing greenhouse gas emissions,
which is significantly dependent on the feedstock and the technology used in the
production process as well as distribution and blending procedures.
Several studies have been conducted on ethanol production from different feedstock
and production processes. Jamai et al. (2001) compared ethanol production using
glucose from calcium alginate-immobilized as well as free cells of Candida
tropicalis and Saccharomyces cerevisiae. The results indicate identical rate of
ethanol production in free and immobilized Saccharomyces cerevisiae YMES2.
However, immobilized Saccharomyces cerevisiae Σ1278 showed increased ethanol
production when compared to the free cells whereas for immobilized Candida
tropicalis YMECI4 and Y1552 ethanol production rate decreased by 25 % and 27 %
respectively. Ethanol concentration at the end of the fermentation cycle is similar for
Chapter 2: Literature Review
16
free and immobilized Candida tropicalis, but in order to reach this concentration
more time is required under immobilized condition. Free and immobilized cells of
Saccharomyces cerevisiae achieve complete fermentation at the same time but the
immobilized Candida tropicalis require 2-3 hours more than free Candida tropicalis
to complete the fermentation process.
Jamai et al. (2007) used a different feedstock, which was corn soluble starch, to
produce ethanol using Candida tropicalis. This is capable of fermenting starch at low
rates. Starch liquefaction was sufficient to drive the fermentation of starch to ethanol
by Candida tropicalis YMEC14, reaching ethanol yields comparable to those
obtained by other groups when using cell surface-engineered Saccharomyces
cerevisiae strains that display both α-amylase and glucoamylase. In order to display
the hydrolytic role of Candida tropicalis glucoamylase, ethanol production from
starch was compared between Candida tropicalis YMECI4, Saccharomyces
cerevisiae YMES2 and the amylolytic yeast Saccharomyces occidentalis ATCC
26077. The collective results are indicated in the table below.
Table 2.1: Kinetics parameters of ethanol production from starch following
growth of C. tropicalis, S. cerevisiae, and S. occidentalis in the
presence and absence of α-amylase treatment (Source: Jamai et al.,
2007)
C. tropicalis S. cerevisiae S. occidentalis
(+) (-) (+) (-) (+) (-)
YP/S
(g E/g S)
0.38 ±
0.02
0.19 ±
0.01
0.13 ±
0.01
0.025 ±
0.0005
0.26 ±
0.03
0.14 ±
0.01
YP/X
(g E/g B)
2.66 ±
0.12
1.42 ±
0.06
1.28 ±
0.04
0.26 ±
0.02
1.69 ±
0.04
0.89 ±
0.03
YX/S
(g B/g S)
0.14 ±
0.01
0.13 ±
0.01
0.10 ±
0.01
0.10 ±
0.01
0.15 ±
0.01
0.16 ±
0.02
QP
(g E/l h)
0.51 ±
0.03
0.23 ±
0.02
0.18 ±
0.02
0.03 ±
0.002
0.36 ±
0.03
0.16 ±
0.02
Notes: YP/S and YP/X: yield factor of ethanol on substrate and biomass respectively; YX/S: conversion rate of starch to biomass; QP: volumetric ethanol productivity; (E): ethanol, (S): substrate, (B): biomass; Mean ± SD (n=3)
Chapter 2: Literature Review
17
From this result it is evident that in order to get maximum ethanol yield from starch
fermentation. Starch first needs to undergo hydrolysis, that is, be liquefied as well
subjected to saccharification. Although, there are many organisms or yeast present
such as Candida tropicalis which have the ability to ferment starch directly, the
ethanol yield is low. Also evident is certain organisms have the ability to produce
more ethanol than others.
According to Verma et al. (2000) direct fermentation of starch to ethanol can be
carried out effectively by co-culture of Saccharomyces diastaticus and
Saccharomyces cerevisiae 21 with fermentation efficiency of 93 % and production of
24.8 g l-1 ethanol using raw unhydrolyzed starch in single-step fermentation. When
using only Saccharomyces diastaticus on α-amylase and glucoamylase treated starch
the efficiency was 78 % whereas using Saccharomyces cerevisiae 21 the efficiency
was 85 %. Starch is considered as a renewable agricultural substrate and can be
easily hydrolyzed to fermentable sugars using amylolytic enzymes. The most
commonly used distiller’s yeast Saccharomyces cerevisiae is unable to hydrolyze
starch directly and thus there is a need to use α-amylase and glucoamylase to convert
starch to fermentable sugar. Bioconversion of starch to ethanol can also be achieved
by using recombinant strain of Saccharomyces cerevisiae (Nakamura et al., 1997).
The results indicate a maximum ethanol production of 24.9 g l-1 from 100 g l-1 starch
medium using Saccharomyces cerevisiae SR 93.
The use of thermotolerant yeasts for ethanol production has also been described by
many researchers (Banat et al., 1996; Nigam et al., 1998 and Ryu et al., 1988).
Themotolerant yeast strains are of great advantage especially for tropical countries
and for summer months. These yeasts help reduce cost as well as save energy by
avoiding the need to cool reactors and in having faster fermentation rates which
makes the process economical. Sree et al. (1999) used various starchy substrates
such as sweet sorghum, sweet potato, wheat flour, rice starch, soluble starch and
potato starch to produce ethanol using thermotolerant yeast isolate (VS3) by
simultaneous saccharification and fermentation process. The fermentation process
employed was Solid Substrate Fermentation. The results obtained are indicated in the
table below.
Chapter 2: Literature Review
18
Table 2.2: Ethanol concentration and left over sugar in solid substrate
fermentation from various starchy substrates using thermotolerant
yeast (VS3) (Source: Sree et al., 1999)
Substrate Ethanol at
37 ˚C
(g/100 g
substrate)
LOS at 37˚C
(g/100 g
substrate)
Ethanol at
42˚C
(g/100 g
substrate)
LOS at 42˚C
(g/100 g
substrate)
Sweet
Sorghum
8.2 0.25 7.5 0.45
Sweet Potato 5.0 0.5 3.5 1.0
Rice Starch 10.0 1.0 3.5 5.0
Wheat Starch 6.0 0.5 3.2 1.4
Potato Starch 4.0 1.5 2.0 2.5
Soluble Starch 3.5 2.5 1.5 3.0
LOS = Left over sugar
There is tremendous scope for Solid Substrate Fermentation because of the following
potential advantages (Gibbons et al., 1986; Kargi et al., 1985 and Amin, 1992): (i)
less requirement of water, (ii) smaller volumes of fermentation mash, (iii) less
physical energy requirement, (iv) less capital investment, (v) less operating costs and
lower space requirement, (vi) reduced reactor volumes, easier product recovery, less
liquid waste to be disposed of hence less pollution problems. Pandey (1994),
Lonsane and Krishnaiah (1994) and Sree et al. (1999) also agree that Solid Substrate
Fermentation is more suitable and economical than conventional submerged
fermentation for producing a variety of fermentation products.
Ocloo and Ayernor (2008) investigated the physical and chemical changes besides
yeast growth in alcoholic fermentation of sugar syrup from cassava flour. Cassava
flour was hydrolyzed using rice malt to produce sugar syrup which was then
fermented at 28-30 ºC for 1, 2, 3, 4 and 5 days using Saccharomyces cerevisiae
(baker’s yeast). “Results showed that pH values decreased with increased total
acidity with concomitant increase in yeast growth (biomass) and alcohol contents of
the fermenting sugar syrup. There were deceases in soluble solid contents, refractive
Chapter 2: Literature Review
19
indices of the fermenting medium and increase in volatile acids (as acetic acid) with
increased alcoholic fermentation” (Ocloo and Ayernor , 2008).
The method for conversion of starch to alcohol is usually classified in three groups:
(i) combined saccharification and fermentation of soluble starch by genetically
engineered yeast, (ii) addition of amylolytic enzymes, mostly glucoamylase, to the
broth and (iii) use of mixed culture, either free or co-immobilized for starch
degradation and fermentation (Ülgen et al., 2002).
Ülgen et al. (2002) had used genetically engineered yeast to produce ethanol from
starch. Single step starch fermentation was investigated using a genetically
engineered recombinant Saccharomyces cerevisiae strain YPG/AB. Their findings
revealed a 34 % increase in ethanol production by YPG/AB in 40 g l-1 initial starch
containing medium supplemented with 4 g l-1 glucose.
Amutha and Gunasekaran (2001) used method (iii) description of conversion of
starch to ethanol. Ethanol was produced by batch fermentation using liquefied
cassava starch and co-immobilized cells of Saccharomyces diastaticus and
Zymomonas mobilis and compared to the ethanol concentration with immobilized
Saccharomyces diastaticus. The results showed that co-immobilized cells produced
46.7 g l-1 ethanol from 150 g l-1 liquefied cassava starch while the immobilized cells
of Saccharomyces distaticus produced 37.5 g l-1 ethanol. Ethanol concentration was
also higher when it was produced using immobilized cells rather than free cells of
Saccharomyces diastaticus and Zymomonas mobilis.
Looking at the above review, it can be well noted that the ethanol yield varies. These
variations are a result of experimental procedures employed, enzymes and catalysts
used, conditions such as temperature and pH at which fermentation has commenced.
All of these factors tend to affect ethanol yield.
Chapter 2: Literature Review
20
2.3 Ethanol as Fuel
Ethanol, together with biodiesel provides a suitable substitute for fossil fuels. Ethanol
made from biomass provides unique environmental, economic strategic benefits and
therefore can be considered as a safe and clean liquid fuel alternative to fossil fuels
(Chandel et al., 2007). The advantages and some of the drawbacks associated with
the use of ethanol as fuel as concluded by various researchers are discussed below.
An issue paper prepared by Environment Australia (2002) has provided a basis for
discussion of some of the issues associated with the use of ethanol as automotive
fuels. The first part discusses the background information on the use of ethanol as
automotive fuel and the other part raises issues for comments on vehicle operability
and the effect on engines, environmental performance and any health and safety
implications. Ethanol can be blended with petrol to form ethanol-petrol blends. These
are usually stated as volumetric ratio of ethanol to petrol. Some of the most common
of these blends are as follows:
1. 10 % ethanol blended with 90 % petrol (known as E10)
2. 85 % ethanol blended with 15 % petrol (known as E85); this blend is used in
some states of the US and requires a particular vehicle technology known as
‘Flexible Fuel Technology’ (FFT)
3. 20-24 % ethanol blended with 80-76 % petrol (known as E22); this blend is
used in Brazil and requires specific vehicle optimization (recalibration and
component changes) for 22 % ethanol.
4. 100 % ethanol (E100); this is used in Brazil and requires vehicle technology
dedicated to the fuel.
Ethanol is produced in two forms: hydrated and anhydrous. Hydrous ethanol which is
95 % ethanol with the rest being water is suitable for use as a straight spark ignition
(SI) fuel in warmer climates or for blending as a 15 % emulsion in diesel. Anhydrous
ethanol is 100 % ethanol that is used for blending with petrol. Ethanol blends tend to
result in reduced emissions of carbon monoxide (CO), hydrocarbons (HC),
particulate matter (PM) and certain known carcinogens. However, ethanol blends are
likely to increase emissions of aldehydes, particularly acetaldehyde.
Chapter 2: Literature Review
21
Within the Australian context, the use of E10 has been found to result in a decrease
of emissions of CO by 32 %, HC by 12 % and slight increase in nitrogen oxide
(NOx) by 1 %. There were increases in non-regulated toxics such as acetaldehyde
(180 %) and formaldehyde (25 %) and decrease in non-regulated toxics: 1-3
butadiene (19 %), benzene (27 %), toluene (30 %) and xylene (27 %).
An Australian life-cycle analysis work had revealed that E10 blends are greenhouse
neutral (Beer et al., 2001). The same study indicates that using E10 blends lead to
decreased tailpipe emission of hydrocarbons and NOx by 25 % and 15 %
respectively, but there was no change to the particulate matter. Studies by Beer et al.
(2002) have confirmed that renewable fuels such as biodiesel and ethanol emit larger
quantities of CO2 than conventional fuels. However, since most of this is from
renewable carbon stocks, that fraction does not count towards greenhouse gas
emission from the fuel.
Duncan (2002) stated that generally, modern vehicles operate satisfactorily on blends
up to 10 % ethanol in petrol and are designed to have fuel systems materials
compatible with the blends. This is because most modern vehicles are now designed
to use fuels containing some level of blended oxygenate including ethanol. Ethanol
will corrode mechanical components that are made of copper, brass and aluminium
due to the water solubility in ethanol (Wu et al., 2004).
Use of 10 % ethanol in petrol results in 3.6 % increase in volumetric fuel
consumption due to lower energy content of ethanol. The energy efficiency of
modern vehicles remains similar for blends as well as petrol. Also there was no
significant difference in exhaust emissions.
This is because modern vehicles are fitted with functional exhaust sensors (oxygen
sensors) and catalysts which help determine if the air fuel ratio of a combustion
engine is rich or lean. The oxygen sensors send information about the difference in
oxygen concentration in exhaust and the oxygen in air to the Electronic Control Unit
or ECU, which adjusts the amount of fuel injected into the engine to compensate for
excess air or excess fuel. The ECU tries to maintain the air-fuel ratio to
stoichiometric.
Chapter 2: Literature Review
22
However, in older vehicles without catalysts and in vehicles without fully functional
emission control systems, use of ethanol blends will likely result in reduced CO
emissions compared to petrol, slight reductions in HC and slight increases in NOx.
This is mostly due to the fact that engine would be running on lean conditions.
According to Duncan’s (2002) result an E10 blend will produce 0.1 % less CO2 from
vehicle tailpipes than petrol when used at an equivalent efficiency. CO2 emitted
during manufacture of ethanol ranges between 30 to 90 % of CO2 generated as
tailpipe emission after combustion depending on process technologies and
accounting protocols used. On this basis and with an increase in energy efficiency of
vehicles by 1 %, net CO2 emissions using an E10 blend will be 1.5 to 5.5 % lower
than that of petrol. Although, these reductions seem low, lowering the ethanol
manufacturing emission levels could result in higher reduction in CO2 emissions.
This could depend considerably on (Duncan, 2002):
� Type of feedstock used for ethanol production, location and yields
� Treatment of ethanol production as a by-product of the crop or the objective
of growing the crop
� The procedures used for greenhouse gas accounting
� CO2 sequestration assumed for process by-products, for example, fertilizers
and stock feed
� Energy products used in processing: renewable fuels from process by-
products or non-renewables such as coal, oil or natural gas
Hence, a 10 % ethanol concentration by volume is appropriate because of vehicle
performance and compatibility and consistency with international experience.
Hsieh et al (2002) used a commercial SI engine running on various ethanol-petrol
blends (0 %, 5 %, 10 %, 20 %, and 30 %) to investigate the engine performance and
pollutant emissions resulting from these various blends. The collective results
showed a 10-90 % reduction in CO and 20-80 % in HC as a result of leaning effect.
There was an increase in CO2 tailpipe emissions by 5-25 %. As expected the fuel
consumption increased with increasing amount of ethanol in the blends.
Chapter 2: Literature Review
23
A four stroke, four cylinder SI engine (type TOYOTA, TERCEL-3A) was used by
Al-Hasan (2003) in order to study the effect of using unleaded gasoline-ethanol
blends on SI exhaust emission and engine performance. The results obtained by Al-
Hasan showed increase in fuel consumptions by 5.7 % whereas the CO and HC
emissions decreased by 46.5 % and 24.3 % respectively. The CO2 emissions
resulting from the engine increased by 7.5 %. This is due to the fact that blended
fuels enable the fuel to burn more efficiently. Of the ten test blends ranging from 0 %
to 25 % ethanol in increments of 2.5 %, it was found that 20 % ethanol fuel blend
gave best results for the various parameters that were measured. Ethanol addition
also leads to the increase in brake power, brake thermal efficiency and volumetric
efficiency by about 8.3 %, 9 % and 7 %, respectively.
Pikūnas et al. (2003) studied the engine performance and pollution emission of a SI
engine using ethanol-petrol blended fuel (E10) and pure gasoline. The results for
engine test indicated that when ethanol-petrol blended fuel is used, the engine power
and specific fuel consumption of engine slightly increases; CO emission decrease
dramatically; HC emission decreased in some engine working conditions but
increase at maximum load; and CO2 emissions increases because of the improved
combustion and the amount of incomplete combustion products decreases. The
reduction in CO emission is due to the leaning effect. Addition of ethanol to blended
fuels provides more oxygen for the combustion process and this leads to the so called
“leaning effect”. Quantitatively the emission levels indicate a decrease in CO by 15
% at lower engine output and revolutions in comparison with petrol. However,
increase in engine output and revolutions indicate the difference of CO emission
increased by 30 %. The results have shown slight increases of approximately 1-2 %
in specific fuel consumption of E10 over petrol. This is attributed to the fact that
ethanol’s heating value is 1.6 times less than that of petrol.
Similarly, Butkus and Pukalskas (2004) used engine test facilities to investigate the
effect of 3.5 % and 7 % ethanol in the fuel blends and special additives in the engine
performance and pollution emissions of SI engine. The results indicated a general
trend of reduction in the emissions as well as increase in the octane rating. However,
from the results, conclusions were drawn that the maximum CO emissions results
Chapter 2: Literature Review
24
due to the use of pure petrol. They concluded that ethanol used in fuel blend with
petrol had a positive influence on the engine performance and exhaust emission.
Theoretical as well as experimental investigation into the effects ethanol blends on
the performance and exhaust emissions have also been carried out by Bayraktar
(2005). Experimental application was performed on blends containing 1.5 %, 3 %,
4.5 %, 6 %, 7.5 %, 9 %, 10.5 % and 12 % by volume ethanol with petrol. Theoretical
investigation was carried out on a quasi-dimensional SI engine cycle model
developed by the author on blends up to 21 %. Experimental results indicated that
among the various blends, blend of 7.5 % ethanol was the most suitable in terms of
engine performance as well as reduction in CO emissions. However, in comparison
with the theoretical results blend containing 16.5 % ethanol was found to be more
viable. This difference experimental and theoretical can be “attributed to the water
content of ethanol: as known, in actual conditions, water may cause phase
separation, therefore, power loss and this can be observed experimentally, however,
this negative effect of water cannot be considered in theoretical model” (Bayraktar,
2005). Therefore, if purity of ethanol is increased and phase separation prevented, the
ethanol content can be increased towards 16.5 % to yield the best results.
It is well known that addition of ethanol to ethanol-petrol blends tends to reduce the
heating value and as a result the fuel consumption of ethanol-petrol blends tend to
increase. Bayraktar (2005) results showed that the specific fuel consumption
measured at compression ratio 7.75 and 8.25 were lower when operating on ethanol-
petrol blends than on petrol. The specific fuel consumption decreased by 5.59 % and
4.94 % at ε=7.75 and 8.25, respectively, when operating on 7.5 % ethanol blended
with petrol. The CO mole ratio showed a reduction of 44.26 % (at ε=7.75) and 41.67
% (at ε=8.25) whereas theoretical reductions were 61.82 % (at ε=7.75) and 68.16 %
(at ε=8.25). The obvious reasons suggested by the author were that increase in
ethanol content leads to more complete combustion and rise and flame temperature
due to stoichiometric combustion. The fact that the carbon content of ethanol is less
than petrol is another reason for such drastic reduction in CO.
Topgül et al. (2006) in their research studied the engine performance and exhaust
emissions when using unleaded petrol (E0) and ethanol-petrol blends (E10, E20, E40
Chapter 2: Literature Review
25
and E60). The experiment was performed on a Hydra single-cylinder, four stroke, SI
engine by varying its compression ratio (8:1, 9:1, 10:1) and ignition timing at a
constant speed of 2000 rpm at wide open throttle (WOT).
The collective results indicated a decrease in CO emissions when using different
ethanol-unleaded petrol blends over the test range 8:1 to 10:1 compression ratio. E40
gave the best results for reduction of CO emissions by 31.8 % at 9.1 compression
ratio. Whereas, E60 showed a decrease in CO emission by 19.8 % and 22.3 % mean
average values at 8:1 and 9:1 compression ratio respectively.
The authors also noted that increasing ignition temperature results combustion
process to occur earlier in the cycle that leads to decrease in exhaust temperature. As
a result of this the HC emission increased. However, retarding the ignition timing
leads to reduced HC emissions. This was seen when E60 caused a 31.45 % reduction
in HC emission at compression ratio 10:1.
Celik’s (2008) work included determination of the suitable ethanol-petrol blend rate
in terms of performance and emissions for small engines. The other aim was to
investigate experimentally the performance as well as the emissions resulting from
the engine with suitable ethanol-petrol blended fuel at high compression ratio
without any knock.
In the initial stage of the test the engine was tested with E0, E25, E50, E75 and E100
fuels with its original compression ratio (6:1), 2000 rpm, full throttle opening and air
excess ratio of 1.0. The results obtained for this test indicated slight power increases
in E25, E50 and E75 when compared to E0. However, the power increase starts to
decrease when ethanol content was raised to more than 50 %. When looking at the
emissions, CO and CO2 emission deceased. CO emission was 3.76 %, 2.65 %, 2.06
%, 1.24 % and 0.73 % for E0, E25, E50, E75 and E100 fuels, respectively. In
addition the CO2 emission were 13.25 %, 12.14 %, 11.62 %, 10.25 % and 9.51 % for
E0, E25, E50, E75 and E100 fuels, respectively. There was decrease in the HC
emission for E0, E25 and E50 but for E75 and E100 the HC emission increased. The
NOx emission decreased as the ethanol content in the fuel was increased.
Chapter 2: Literature Review
26
In the second stage the testing was performed with E0 and E50 at compression ratios
6:1, 8:1 and 10:1 with full load in the range of 1500-4000 rpm at intervals of 500
rpm. E0 fuel could only be tested at compression ratio of 6:1 since it caused knock at
a compression ratio 8:1, full throttle opening and low engine speeds. However, E50
enabled the engine to run without knock at high compression ratio (10:1) at full
throttle load and all speeds. E50 fuel lead to the increase in engine power by 29 %
when compared to E0 fuel whereas the specific fuel consumption, CO, CO2, HC and
NOx emissions reduced by 3 %, 53 %, 10 %, 12 % and 19 %, respectively.
Abdel-Rahman and Osman (1997) also used blended fuels in the ratio of 10 %, 20 %,
30 % and 40 % in variable compression ratio engine. Their results showed that under
various compression ratios of engine, the optimum blend rate was found to be 10 %
ethanol with 90 % petrol.
A conventional engine under various air-fuel equivalence ratios (λ) was used by Wu
et al. (2004) to study its performance as well as pollution emissions using ethanol-
gasoline blends (E0, E5, E10, E20 and E30). The result of engine performance tests
showed that torque output improves when using ethanol-gasoline blends. However,
there are no noticeable changes with the brake specific heat consumption. HC and
CO emissions reduced with the increase of ethanol content in the blended fuel. The
maximum CO2 emission was obtained at λ~1 but the smallest amount of CO2
emission was obtained with E30. The study indicated that using 10 % ethanol fuel
could reduce pollution emission efficiently.
Moreover, according to Yüksel and Yüksel (2004) ethanol-petrol mixtures
containing up to 20 % ethanol by volume, can be used safely without causing any
damage to the motor. It is observed that phase separation tends to occur in ethanol-
petrol mixtures if the amount of water present in the mixture is over a certain limit.
Water in blended fuels results in corrosion problems on mechanical components
especially those components made from copper, brass or aluminium. Usually
gasoline containing less than 20 % ethanol by volume and is aromatic in character
and said to be more stable. According, to the authors phase separation depends on the
ethanol and water content of the blends, environmental temperature and composition
of gasoline. However, phase separation temperature can be reduced if higher
Chapter 2: Literature Review
27
aliphatic alcohols such as tertiary butyl alcohol, benzyl alcohol, cyclohexanol or
toluene are added to gasoline-alcohol blends (Ferfecki and Sorenson, 1983 and
Karaosmanoglu et al., 1992).
From the above literature review, it is understood, that ethanol-petrol blends can be
used to effectively reduce pollutant emissions in both engines with modification and
without modification depending on the percentage of ethanol blended with petrol.
However, it is seen that with increasing percentage of ethanol there is decrease in
heating value and as a result an increase in fuel consumption.
28
Chapter 3 Methodology
3.0 Overview
This chapter gives the details of the procedure that was employed in order to produce
ethanol from some cassava varieties available in Fiji and the ethanol yield from these
different varieties. It also outlines the methodology for the determination of the fuel
properties of ethanol-petrol blends as compared to neat petrol and the fuel economy
and the emissions resulting from the use of certain ethanol-petrol blends.
3.1 Cassava Varieties in Fiji
The cassava varieties that were used for ethanol production were obtained from two
different research stations of the Ministry of Primary Industries in Fiji. One was
Koronivia Research Station (KRS) situated 18˚ 32’811” S and 178˚ 32’133” E and
the other was Dobuilevu Research Station (DRS) situated 17˚ 33’620” S and 178˚
14’736” E. These two locations are indicated in the map of Fiji in Figure 3.1.
Figure 3.1: Map of Fiji showing the collection points of cassava varieties
Chapter 3: Methodology
29
The ten cassava varieties obtained were; Niumea, Sokobale, Beqa, New Guinea,
Coci, Vula Tolu, Yabia Damu, Merelesita, Nadelei and Navolau. The variety
Sokobale was not available at DRS therefore; only nine varieties were used for
ethanol production from this location. The cassava varieties obtained from KRS and
DRS were approximately 12 months old. Cassava from these two sites were obtained
in order to determine whether, apart from varieties or genetic constituent of plants,
location also played a part in starch yield which will then influence the ethanol yield.
3.1.1 Dry Matter Content of Cassava Roots
Dry matter content (DMC), retention of leaf and starch accumulation in roots has an
important impact on dry matter yield (Pérez et al., 2002). The percentage of starch
and starch yield are closely related to dry matter percentage. Therefore, this is one of
the factors that need to be determined in order to identify the best cassava variety for
starch and ethanol yield.
DMC was determined according to the procedure described by Benesi (2005). The
roots of different cassava varieties were analyzed for DMC within 12 hours of
harvesting. The roots were peeled, cleaned and then shredded into fine slice before
100 g of these were weighed in a Petri dish ( 1w ). The Petri dish was then placed in
an oven at a temperature of 65 ˚C for 72 hours. The samples were removed after 72
hours and weighed immediately ( 2w ). DMC was calculated using the equation 3.1:
DMC (%) = %1001
2 �ww (3.1)
3.1.2 Starch Extraction from Cassava Roots
The extraction of starch from cassava was done according to the method described
by Birse and Cecil (1980) however, some parts of the method was modified. A
flowchart of starch extraction is shown in Figure 3.2. Cassava roots were washed,
peeled then washed again before the roots were chopped into approximately 1 cm
cubes. The weight of the chopped cassava ( 3w ) was taken before pulverizing it in a
Chapter 3: Methodology
30
high speed blender for 5-10 mins. The pulp was then suspended in ten times its
volume of water, stirred for about 5 mins before filtering using a double fold cheese
cloth. The filtrate was left to stand for about 6 hours before the starch settled and the
liquid potion discarded. Water was then added to the sediment and the whole process
was repeated. The starch was then dried at 50 ˚C for 24 hours and its weight
measured ( 4w ).
Cassava Root ↓
Peeling ↓
Washing ↓
Chopping/Blending ↓
Mixing with Water ↓
Filtering ↓
Settling ↓
Starch Washing ↓
Settling/Dewatering ↓
Drying ↓
Cassava Starch Figure 3.2: Flowchart for cassava starch production
The starch yield was determined using the equation 3.2:
Starch Yield (%) = 1003
4 �ww
% (3.2)
Chapter 3: Methodology
31
3.1.2.1 Moisture Content of Starch
Moisture content of the extracted starch was determined according to the method
described by Benesi (2005) however the quantity of cassava starch to be analyzed
was increased.
Approximately 10 g of cassava starch ( 5w ) was dried in an oven at 105 ˚C for 24
hours. After 24 hours the samples were cooled in a desiccator and weighed
immediately ( 6w ). The moisture content was determined using equation 3.3:
Moisture content (%) = 1005
65 ��w
ww% (3.3)
3.1.2.2 Ash Content of Starch
Ash content was determined according to the method described by International
Starch Institute (1999 a). Clean ashing crucibles were heated in the furnace for
approximately half an hour at 900 ˚C. The crucibles were cooled in a dessicator to
room temperature and weighed ( 0w ). Approximately 5 g of the starch sample was
uniformly distributed in the ashing crucible and weighed ( 7w ). The samples were
then incinerated on a bunsen burner until it completely carbonised before placing the
ashing crucibles in the furnace for 5 hours at 900 ˚C. After incineration, the samples
were cooled to room temperature in a dessicator and weighed ( 8w ). Ash content of
starch was determined using equation 3.4:
Ash content (%) = 10007
08 ���
wwww
% (3.4)
3.1.2.3 pH Determination of Starch
The pH of starch was determined according to the method described by International
Starch Institute (1999 b). Approximately 5 g of starch was mixed with 20 ml of
Chapter 3: Methodology
32
distilled water. The starch was then allowed to settle for 15 mins before the pH of the
water phase was measured using a calibrated pH meter. The calibration of the pH
meter was done by turning on the meter at least 30 minutes before use, allowing it to
warm up. The pH electrode was removed from the storage solution of 3.5 M KCl
(potassium chloride) solution and rinsed with distilled water. The pH 4 and 7 buffer
were prepared by dissolving the buffer 4 and buffer 7 standard tablets in 100ml of
distilled water. The electrode was submerged into the pH 7 buffer and
“CALIBRATE” button was pressed. When the pH icon had stopped flashing,
CALIBRATE button was again pressed. The electrode was rinsed with distilled
water. Calibrating steps were repeated with pH 4 buffer. The electrode was removed
and rinsed with distilled water again to remove buffer solution preventing it from
contaminating the sample. The electrode was then submerged into the sample and
MEASURE button was pressed to get the pH of the sample.
3.2 Ethanol Production from Cassava Starch
The cassava starch that was extracted from Niumea, Sokobale, Beqa, New Guinea,
Coci, Vula Tolu, Yabia Damu, Merelesita, Nadelei and Navolau from the two
locations were used as feedstock for ethanol production. This was done to determine
the best ethanol yielding cassava variety from the ten varieties of cassava used.
3.2.1 List of Equipment and Reagents A PerkinElmer’s Lambda 25 UV/VIS spectrophotometer was used for determination
of reducing sugars and a PerkinElmer’s Clarus 500 Gas Chromatography (GC) for
determination of ethanol concentration. The reagents that were used for ethanol
production are given in Table 3.1.
Chapter 3: Methodology
33
Table 3.1: Reagents used for ethanol production
Reagents Source α-amylase Type XII-A From Bacillus
Licheniformis (830 U/mg)
Sigma Aldrich, Australia
Amyloglucosidase from Aspergillus Niger (66.6
U/mg)
Sigma Aldrich, Australia
Yeast (Saccharomyces cerevisiae) Sigma Aldrich, Australia
3, 5-Dinitrosalicylic Acid Sigma Aldrich, Australia
Sodium Hydroxide Anhydrous Pellets Sigma Aldrich, Australia
Sodium Potassium Tartrate Tetrahydrate Sigma Aldrich, Australia
Hydrocloric Acid (HCL) Sigma Aldrich, Australia
Absolute Ethanol Unilab, Ajax Finechem, Australia
95 % Ethanol Unilab, Ajax Finechem, Australia
Glucose Sigma Aldrich, Australia
3.2.2 Preparation of Cassava Starch Solution
The extracted starch from the ten different varieties of Fijian cassava was made into
200 g l-1 concentration. Exactly 100 g of the starch was mixed in 100 ml of cold
water. While stirring the slurry was added to approximately 400 ml of gently boiled
water in a conical flask so that the final volume was 500 ml. This resulted in the
formation of gelatinized starch solution.
Gelatinized starch forms from the weakening of the inter and intra hydrogen bonds
which results from the rise in temperature of the starch solution (Wang, n.d). Starch
granules form hydrogen bonds within the same molecule and with the other
neighbouring molecules and these tend to be quite resistant to penetration of water
and hydrolytic enzymes (Wang, n.d). However, raising the temperature tends to
weaken these hydrogen bonds which results in water being absorbed and swelling of
starch granules. The resulting gelatinized starch is shown in Figure 3.3.
Chapter 3: Methodology
34
Figure 3.3: Gelatinized cassava starch solution
3.2.3 Treatment of Cassava Starch Solution to Simple Sugars
Starch substance comprises the major part of human diet and is synthesized naturally
in plants. Some of these plants are corn, potato, rice, sorghum, wheat and cassava.
Starch molecules are glucose polymers linked together by α-1, 4 and α-1, 6
glucosidic bonds (Kearsley and Dziedzic, 1995). Starch must first be hydrolyzed into
glucose units prior to alcohol fermentation by ethanologenic micro-organisms such
as yeast (Lee et al., 1992).
Starch hydrolysis can be achieved by using two enzymes: α-amylase and
amyloglucosidase or glucoamylase. Starch hydrolysis is achieved in two stages-
liquefaction and saccharification. During the starch liquefaction the α-amylase
enzymes work on the gelatinized starch slurry to partially hydrolyze the starch to
dextrin. Dextrin solutions are less viscous hence, the starch gel is liquefied. Dextrin
is short glucose chains, and small amounts of glucose and maltose (Kearsley and
Dziedzic, 1995). Dextrin can be further hydrolyzed to glucose by adding
amyloglucosidase and this stage is called saccharification.
α-amylase reacts endogenously with α-1, 4 glucosidic linkages of polysaccharides to
produce oligosaccharides whereas amyloglucosidase hydrolyzes exogenously the
Chapter 3: Methodology
35
non-reducing end α-1, 4, α-1, 6 and α-1, 3 glucosidic linkages of oligosaccharides to
produce glucose (Pazur and Ando, 1960).
3.2.3.1 Pre-treatment of Gelatinized Starch with α-amylase
The liquefaction of gelatinized starch was conducted at 65 ºC and the level of α-
amylase used was 200 U g-1 starch. In order for complete liquefaction to occur the
experiment was conducted for 2 hours. Montesinos and Navarro (2000) reported that
2 hours of liquefaction was absolutely necessary for complete starch hydrolysis using
raw wheat flour as substrate. Using this literature the current author also assumed the
same time would be required for the complete liquefaction of cassava starch.
Liquefaction of gelatinized cassava starch was conducted by adding α-amylase from
Bacillus licheniformis (830 U mg-1). One unit (1 U) liberates 1.0 mg of maltose from
starch in 3 mins at pH 6.9 at 20 ºC. The sample was then hydrolyzed at 65 ºC with
mild agitation for 2 hours as shown in Figure 3.4. Starch gel was liquefied to produce
dextrin which consists of shorter glucose chains containing glucose and maltose.
Usually hydrolysis of starch consists of two stages- liquefaction and saccharification.
However, in order to save time and make the process cost effective the
saccharification stage has been incorporated with the ethanol fermentation, a
technique known as simultaneous saccharification and fermentation (SSF).
Chapter 3: Methodology
36
Figure 3.4: Starch hydrolysis using α-amylase
3.2.4 Simultaneous Saccharification and Fermentation
SSF reaction mixtures contained liquefied cassava starch, yeast inoculum of 15 %
concentration and amyloglucosidase at 200 U g-1 starch. The amyloglucosidase used
was obtained from Aspergillus niger and has an activity of 66.6 U mg-1. Here 1 U
corresponds to the amount of enzyme that liberates 1 µmol glucose per min at pH 4.8
and 60°C. The 15 % yeast inoculum was prepared by hydrating 15 g of dry baker’s
yeast (Saccharomyces cerevisiae) in 100 ml of distilled water at 37 ºC for 10 mins.
Ocloo and Ayernor (2008) used a ratio of 1:30 yeast inoculum to cassava sugar syrup
while conducting fermentation. The current author used the same ratio for the
fermentation reaction.
Fermentation reaction mixtures were placed in one litre three necked round bottom
flasks. The flasks were topped with special air locks which allowed carbon dioxide to
escape. A syringe and needle was inserted on one of the other necks to draw out
samples and the last neck of the flask was fully blocked. The flask was then placed in
a water bath at 37 ºC as shown in Figure 3.5 and fermentation was allowed to
continue for five days.
Chapter 3: Methodology
37
Figure 3.5: Setup for Simultaneous Saccharification and Fermentation
3.2.5 Analytical Analysis
The samples obtained from the SSF were centrifuged within one hour of sampling.
This was accomplished by spinning the samples in a centrifuge at 6000 rpm for 5
mins. The liquid portion of the sample was then passed through a 0.45 µm filter
before the samples were analysed for reducing sugars and ethanol concentration.
3.2.5.1 Reducing Sugar Analysis Reducing sugars are classified as sugars that contain aldehyde groups and can be
oxidised to carboxylic acids or carbonyl group (Campbell and Farrell, 2009). All
common monosaccharide such as glucose and disaccharides such as maltose and
lactose are examples of reducing sugars (AUS-e-TUTE, n.d). The reducing sugar
concentration was determined using 3, 5–dinitrosalicylic acid (DNS) method as
described by Miller (1959).
Chapter 3: Methodology
38
3.2.5.1.1 Preparation of Dinitrosalicylic Acid Solution (DNS)
The DNS was prepared by dissolving 10 g of 3, 5-dinitrosalicylic acid in 2 M sodium
hydroxide solution. In a separate beaker, 300 g of sodium potassium tartrate was
dissolved in 300 ml of distilled water. To ensure that all the 3, 5-dinitrosalicylic acid
dissolved in 2 M sodium hydroxide solution the mixture was heated and stirred until
no particles were seen at the bottom of the beaker. The mixture of 3, 5-
dinitrosalicylic acid and 2 M sodium hydroxide solution was then added to potassium
sodium tartrate solution and thoroughly mixed. The final volume of this solution was
made up to 1 litre with distilled water in a volumetric flask. The DNS solution was
stored in a refrigerator at 4 ºC in a brown bottle.
3.2.5.1.2 Standard Curve
The calibration curve was prepared with 1 g l-1 of glucose solution. The dilution of
different concentration of 0.1 g l-1, 0.2 g l-1, 0.4 g l-1, 0.6 g l-1 and 0.8 g l-1 was made
by pipetting 1 ml, 2 ml, 4 ml, 6 ml, and 8 ml of the respective volume of stock
solutions into five different volumetric flasks and making the final volume to 10 ml
by adding distilled water. One volumetric flask contained only distilled water that
acted as the control.
To 1 ml of each of the dilution of the glucose solution 1 ml of DNS was added in a
test tube and capped. The test tube was then placed in a boiling water bath for 15
mins and then cooled in an ice bath. The 1 ml of the cooled sample was taken and 5
ml of distilled water was added. This was done to ensure that when the absorbance
was recorded at 540 nm it ranged from 0 to 1. The respective absorbance recorded
was plotted against the different glucose concentrations to make the standard curve
for glucose.
3.2.5.1.3 Determination of Reducing Sugar
The amount of reducing sugar (as glucose content) was determined by adding 1 ml of
the centrifuged and filtered sample from SSF to 1 ml of DNS reagent in a test tube.
The centrifuged and filtered sample from SSF needed to be diluted by adding
Chapter 3: Methodology
39
distilled water to it before adding DNS reagent to this. This was done to ensure that
the absorbance of the samples was within that of the standard curve. The capped test
tubes containing the sample and the DNS reagent was then placed in a boiling water
bath for 15 mins and then cooled in an ice bath. The 1 ml of the cooled sample was
taken and 5 ml of distilled water was added before absorbance was recorded at 540
nm. The absorbance was then converted to glucose concentration using the standard
curve.
3.2.5.2 Determination of Ethanol Concentration
The ethanol produced from the SSF process was determined using Gas
Chromatography (GC). The GC method utilized propan-1-ol as the internal standard
and was used to determine the ethanol concentration in g l-1 from the fermentation
supernatant.
3.2.5.2.1 Preparation of Internal Standard Spiking Solution, Analytical
Standards and Samples
The internal standard spiking solution used was reagent grade propan-1-ol. The
internal standard spiking solution was prepared by diluting propan-1-ol to 0.9 g l-1
with distilled water. The internal standard spiking solution was added in equal
proportion to the standards and the samples that were analyzed.
Five ethanol standards were prepared by diluting absolute ethanol with distilled
water to cover the range of 0.1 g l-1 to 5 g l-1 ethanol. Pure ethanol and distilled water
were chosen to minimize the possibility of non ethanol components interfering in the
determination of the ethanol content of the standards. To each of the standards 0.9 g
l-1 propan-1-ol (internal standard spiking solution) was added in the same ratio.
The fermentation sample that was obtained from SSF was appropriately filtered so
that liquid portion of the sample was obtained. The samples were then diluted by
adding distilled water. A tenfold dilution was suitable for samples obtained at 24, 28,
32, 48 and 72 hours whereas twenty-five fold dilutions brought the 96 and 120 hours
Chapter 3: Methodology
40
sample within range of the calibration curve. The internal standard spiking solution
was then added to each of the samples in the same proportion as the standards.
3.2.5.2.2 Procedure and Conditions of the Gas chromatography
The chromatograph consisted of a Clarus 500 Gas Chromatography (GC) with flame
ionization detector, and a 15 m X 0.53 mm stainless-steel column packed with 100 %
dimethylpolysiloxane. The column temperature was 175 °C and the detector
temperature was 275 °C. The oven was kept at 30 °C. Nitrogen carrier flow was 2.5
ml min-1. A sample size of 1 µl was injected, and peak area counts were printed out
on a chromatogram by the Agilent 3395 digital integrator.
It was ensured that all the standards and samples were at room temperatures before
any injections were carried out. Before injection with the standards and samples,
several injections were made using deionized water. The standards were then
injected from low concentration to high. Following this, again several injections were
made using deionized water before the batch of samples was injected. The GC was
recalibrated after every 6 hours of analysis.
The chromatograms obtained for the standards were used to plot the ratio of peak
area of ethanol to propan-1-ol against the different concentrations of ethanol.
Knowing the ratio of peak area of ethanol to propan-1-ol for the various samples
enabled the determination of the concentration of ethanol from the calibration curve.
3.3 Preparation of Ethanol-Petrol Blends
The blends that were tested were 10 % ethanol and 90 % unleaded petrol (E10), 15 %
ethanol and 85 % unleaded petrol (E15) and 20 % ethanol and 80 % unleaded petrol
(E20). These blends were prepared by mixing together the required proportion of 96
% ethanol and unleaded petrol.
Chapter 3: Methodology
41
3.3.1 Stability Testing of Ethanol-Petrol Blends
Ethanol and petrol blends tend undergo phase separation at low temperatures
especially if there is water present in the mixture. The level of phase separation that
can occur is determined by a number of variables, including the amount of ethanol,
the composition of the fuel, temperature of the environment and the presence of
contaminants. If phase separation of ethanol-petrol blends occur, this can have
detrimental effect on engines. Therefore, it is of extreme importance to test whether
the ethanol-petrol blends are stable before using in engines
To test the blend stability, 93 %, 95 %, 97 % and absolute ethanol was used to make
E10, E15 and E20 blends by mixing with unleaded petrol. These blends were placed
into 50 ml vials at a temperature of 25 °C. They were then thoroughly shaken and let
to stand for a period of 6 months at room temperature, which varied between 14 °C
and 28 °C.
3.4 Physical Properties
The physical properties of the ethanol-petrol blends determined were the density and
gross calorific value.
The gross calorific value (GCV) is the property that influences the fuel consumption.
In order to produce a specific amount of power output, a definite amount of fuel is
required. Fuels with higher GCV are desired as they have the tendency to produce
more power in the engine. Therefore, the determination of the GCV is of
significance.
The density is a parameter used extensively in the calculations and conversions of
other relevant parameters. A density measurement is needed to convert mass results
to volumetric results and vice-versa. Additionally, density is required in correcting
the volume for different temperatures.
These properties are of importance and these are needed in the determination of the
efficiency and fuel consumption of the test engine and the effect.
Chapter 3: Methodology
42
3.4.1 Gross Calorific Value
The GCV measures the energy content of a material. This property is also referred to
as heat of combustion or heating value. The unit used for measurement of the GCV
was kJ g-1. A conversion to a volume basis of kJ ml-1 was also made for calculation
purposes.
The determination of the GCV is necessary since fuels having high gross calorific
values are desired for better fuel economy. It is generally expected fuel with a high
GCV is likely to produce more power during combustion as a result decrease the fuel
consumption. The GCV was determined using the Gallenkamp Ballistic Bomb
Calorimeter shown in Figure 3.6.
In order to determine the GCV of different fuel samples, a known weight of sample
is ignited electrically and burnt in excess of oxygen in the combustion chamber. The
maximum rise in temperature of the sample is measured with the thermocouple and
galvanometer system. Therefore, by comparing the temperature rise of the weighed
sample of unknown GCV with that obtained when a sample of known calorific value
(standard) is burnt, the calorific value of the sample material can be determined.
Figure 3.6: Set up for Ballistic Bomb Calorimeter
Thermocouple
Combustion Chamber
Galvanometer
Oxygen Supply Pipe
Oxygen Pressure Gauge
Chapter 3: Methodology
43
3.4.1.1 Calibrating the Bomb Calorimeter
The bomb calorimeter needs to be calibrated before any measurements can be taken.
This is to ensure that accurate results are obtained. Calibration of the bomb
calorimeter was done by determining the correction for constant heat gain test and
calibration with standard sample. A correction of 0.2 divisions was made for heat
released due to firing current and a 5 cm length of firing cotton string. This amount
was subtracted from the total deflection of the galvanometer. The standard substance
used for calibrating the bomb calorimeter was benzoic acid. The calorific value of
benzoic acid is 26.44 kJ g-1. Samples of benzoic acid were burnt in the calorimeter
and the maximum deflection on the galvanometer was noted. The results obtained
were used to determine the calibration factor which indicated the relationship
between the galvanometer deflection and the amount of heat released by the
combustion of the sample. The calibration factor was determined using equation 3.5:
CF = 12
1144.26�� ��� mkJg (3.5)
where,
CF = Calibration Factor (kJ/div)
1m = mass of benzoic acid (g)
1� = correction factor of 0.2 (div)
2� = deflection of benzoic acid (div)
3.4.1.2 Determination of Gross Calorific Value
In order to determine the calorific value of the fuel samples, the bomb calorimeter
was set as follows. Samples were weighed into the crucible and placed on the support
pillar in the base of the calorimeter. A 5 cm length of cotton thread was positioned
between the coils of the firing wire with the other end dipped in the centre of sample
in the crucible. The system was then enclosed and oxygen was let into the chamber at
a pressure of 30 atmospheres (atm) to ensure that complete combustion took place.
Chapter 3: Methodology
44
The bomb was then fired and the maximum deflection of the galvanometer was
noted.
The temperature rise of the bomb calorimeter was measured with the calibrated
galvanometer-thermocouple assembly. The GCV of the sample was determined
using the calibration factor as calculated using benzoic acid in kJ per division, the
mass of sample burnt and the deflection of the sample. Equation 3.6 was used to
calculate the energy content orGCV of the sample fuels.
GCV = 2
13 )(m
CF �� �� (3.6)
where,
GCV = Gross Calorific Value (kJ g-1)
CF = Calibration Factor (kJ/div)
1� = correction factor of 0.2 (div)
3� = deflection of sample (div)
2m = mass of fuel sample (g)
3.4.2 Density
Density is defined as the mass per unit volume of any liquid at a given temperature.
The density of the fuel sample was determined using a picnometer as shown in
Figure 3.7. Picnometer is a special glass flask which is used for determining a
relative density of liquids using the weight of a known volume.
Chapter 3: Methodology
45
Figure 3.7: Picnometer with Fuel Sample
3.4.2.1 Determine the Volume of the Picnometer
The mass of a dry picnometer with stopper was measured on an analytical balance (
1m ). The room temperature was also noted. The picnometer was then filled with
distilled water that was at room temperature, excess water (above the mark) was
removed from the picnometer using a strip of filtering paper. The mass of the
picnometer plus the water was then determined ( 2m ).The temperature of the distilled
water was measured and the density at this temperature was found from Aylward and
Findlay (2003) text book. Therefore, the volume of the picnometer ( pv ) was
determined as shown in equation 3.7:
wp
mmv�
)( 12 �� (3.7)
where,
pv = volume of picnometer (m-3)
1m = mass of dry picnometer (kg)
2m = mass of picnometer and distilled water (kg)
w� = Density of water (kg m-3)
Chapter 3: Methodology
46
3.4.2.2 Determine the Density of Fuel Sample
The picnometer was filled with the fuel sample and the picnometer and fuel sample
was weighed ( 3m ). Since the mass of the dry picnometer was known, the mass of the
sample was calculated. Having calculated the exact volume of the picnometer and the
knowing mass of the sample, the density of the sample was determined by using the
equation 3.8.
pFS v
mm 13 ��� (3.8)
where, FS� = Density of fuel sample (kg m-3)
1m = mass of dry picnometer (kg)
3m = mass of picnometer and fuel sample (kg)
pv = volume of picnometer (m-3)
3.5 Engine Efficiency, Fuel Consumption and Emission
Testing
A Yamaha petrol genset was used to test the performance of the engine using petrol
and different blends of ethanol and petrol. The specifications of the petrol engine and
the generator are provided in Tables 3.2 and 3.3 respectively.
Chapter 3: Methodology
47
Table 3.2: Specification of the petrol engine (Source: Instruction manual of
Yamaha EF2600 Petrol Generator)
Engine Specifications
Model Yamaha EF2600FW
Type MZ175: Air cooled 4-stroke gasoline
OHV
Cylinder Arrangement Inclined, 1 cylinder
Operation Hours 10.6 h
Fuel Tank Capacity 12 L
Engine Oil Quantity 0.6 L
Spark Plug Type BPR4ES (NGK)
Spark Plug Gap 0.7-0.8 mm
Ignition System Transistor Controlled Ignition (TCI)
Maximum Output Power 4.1 hp (3.1 kW)
Continuous Output Power 3.8 hp (2.8 kW)
Bore 66 mm
Stroke 50 mm
Displacement 171 cm3
Lubrication System Splash type
Chapter 3: Methodology
48
Table 3.3: Specification of the generator (Source: Instruction manual of Yamaha
EF2600 Petrol Generator)
Generator Specifications
Generator Type Single Phase AC generator
Type Bi-polar revolving field / with damper
winding
Frequency 50 Hz
Rated Power Output 2 kVA
Maximum Power Output 2.3 kVA
Voltage (AC) 220 V
Current (AC) 9.1 A
Voltage (DC) 12 V
Current (DC) 8.3 A
Speed 3000 rpm
Power Factor 1
Phase Number Single phase
The fuel samples that were tested on the Yamaha petrol genset were neat (100 %)
petrol, E10, E15 and E20. The details of the testing done are outlined in the
following sections.
3.5.1 The Testing Equipment
Engine performance testing requires the measurement of engine torque and power,
which is measured using a dynamometer. The generator supplied with a resistive
load-bank, was used as an electric dynamometer to determine engine performance
The engine performance together with fuel consumption and the resulting emission
when using petrol and different blends of ethanol and petrol blends was determined
using the genset load assembly as shown in Figure 3.8.
Chapter 3: Methodology
49
Figure 3.8: Equipment for testing engine efficiency, fuel consumption and
emission
As seen from Figure 3.8 the testing equipment consisted of a petrol generator, load-
bank, power meter, Horiba automotive emission gas analyzer and the two fuel tanks.
The fuel tank consisted of two 2000 ml graduated measuring cylinder which had two
fuel lines connected by a 3 way valve. One of the measuring cylinder contained
petrol and the other ethanol-petrol blend. The valve was used to select the
appropriate fuel. The emissions that resulted from different test fuels were measured
using the Horiba emission gas analyzer. A power meter was connected to the system
between the generator and the load-bank and this was used to determine the actual
power output. The load bank consisted of light bulbs
Fuel Tank
Horiba Automotive Emission Gas Analyser
Petrol Generator
Load Bank
Power Meter
Chapter 3: Methodology
50
3.5.2 The Testing Procedure
The testing began by setting up the equipment as shown in Figure 3.8. The generator
was started on petrol and let to run on this fuel for 5 min so that the engine warmed
up. The fuel was then switched to the test fuel and the system was flushed with this
fuel by letting it run on 200 ml of the fuel before any measurements were taken.
In the initial stages the engine loss from the system was determined. This was
achieved by running the system without any load and recording the time taken for
120 ml of the test fuel to be consumed.
The loads were then varied and the time taken for 120 ml of the test fuel to be
consumed was recorded. Loads were added gradually by switching the appropriate
light bulbs. This procedure was repeated twice in order to determine the average time
taken for 120 ml of test fuel to be consumed. At each change of load, the system was
run until 40 ml of the fuel was used. This was done to ensure that the system
stabilized before data could be recorded.
The actual electrical power output was measured using the power meter and the
emissions resulting from the test fuels were measured using the Horibar Automotive
Gas Emission Analyser. The data for these were recorded after 40 ml, 80 ml and 120
ml of the fuel had been consumed. The results were then averaged. The power input
to the system was calculated by knowing the GCV of the test fuel and the fuel
consumption over the time period.
3.6 Engine Efficiency
The efficiency ( S� ) of the whole system (gen-set) that is the engine and alternator is
given by total power output per unit power input. This can also be expressed in terms
of energy that is energy output per unit energy input. Equation 3.9 shows the
efficiency of the whole system in terms of energy.
Chapter 3: Methodology
51
S� = 100�in
out
EE = 100�
��
VGCVtPout (3.9)
where,
S� = System Efficiency (%)
outE = energy output of the generator (J)
inE = energy input to the generator (J)
outP = power output of the generator (W)
t = time for specified volume of fuel to be consumed (s)
GCV = gross calorific value of the fuel (J L-1)
V = volume of fuel consumed per test run (L)
The energy input of the system is determined by the GCV of the fuel multiplied by
the volume of fuel used. The volume of fuel used was kept constant for all runs,
therefore as the GCV of the fuels increased the energy input of the system increased.
As mentioned above the system (genset), which consists of the engine and the
alternator. Therefore, to determine the efficiency of the engine only, the efficiency of
each component of the system needs to be determined.
A dynamometer is usually used to determine the efficiency of engines. However, as
this was not available, the method outlined below which was also used by Singh
(2009) was considered as an alternative. The efficiency of the alternator was
determined knowing the alternator input ( 1P ) and the alternator output ( outP ). The
alternator input ( 1P ) is the same as the engine output, while the alternator output
( outP ) is the same as the generator output. A flowchart illustrating the system is
shown in Figure. 3.9 where 1L represents the power loss from the engine and 2L the
power loss from the alternator:
Chapter 3: Methodology
52
1L 2L Figure 3.9: Generalised flowchart of the systems input, output and losses (Source:
Adapted from Singh, 2009)
The alternator efficiency was assumed to be constant at the rated speed of the engine.
This is due to the fact that the engine has a governor coupled to it. The purpose of the
governor is to maintain the speed of an engine during varying load conditions
(Phakatkar, 2008). When there is a change in load, the governor comes into
operation. During increase in load on the engine, the speed decreases making it
necessary to increase fuel supply by opening throttle valve. Similarly, when the there
is a decrease in load, the engine speed increases and the fuel supply needs to be
reduced. The governor maintains the fuel supply by means of the throttle valve thus
keeping the speed of the engine within the required limits of the load (Phakatkar,
2008). Although fluctuations in the rpm do occur, the governor stabilises it.
During the experiment, data was taken after 40 ml of the fuel had been used, so that
the fluctuations in the rpm could be stabilised. Therefore, to determine the alternator
efficiency equation 3.10 can be used:
A� = %1001
�P
Pout (3.10)
1P inP
%1001
��P
PoutA�
Engine
Alternator
Load bank
outP
�E� %1001 �inP
P
Chapter 3: Methodology
53
where,
A� = Alternator Efficiency (%)
outP = power output of the alternator (kW)
1P = power input of alternator (kW)
Substituting these values as specified by the manufacturer at 3000 rpm, the efficiency
of the alternator becomes:
%1008.20.2��A�
= 71 %
The efficiency of the alternator is 71% based on manufacturers specifications. The
data used in equation 3.10 was obtained from the manufacturers stated values at the
rated speed, which was 3000 rpm. The engine output was 2.8 kW which as stated
earlier is the input of the alternator, while the alternator output was 2.0 kW at the
same speed.
Therefore, knowing the system efficiency and the alternator efficiency the engine
efficiency can be determined. This is shown in equation 3.11:
E� = %100�A
s
��
(3.11)
where,
A� = Alternator Efficiency (%)
S� = System Efficiency (%)
E� = Engine Efficiency (%)
3.6.1 Power Loss from the System
Any system or engine is not a hundred percent efficient. There are often power losses
from the system. When the system contains a heat engine, the Second Law of
Chapter 3: Methodology
54
Thermodynamics states that its efficiency will never be equal to 100 %. This may be
re-stated in terms of Carnot’s Theorem, which states that no real heat engine
operating between two energy reservoirs can be more efficient than a Carnot engine
operating between the same two reservoirs. That is all real engines are less efficient
than the Carnot engine (Carter, 2003). A typical internal combustion engine remains
only about 20-25 % efficient (Carter, 2003).
The method of analysing the energy flow in the whole system comprising of the
engine and the alternator has been given by Singh (2009). This considers the power
inputs and losses at each stage of the system. The following equations, 3.12, 3.13 and
3.14 represent the system energy budget:
inP = 1P + 1L (3.12)
1P = outP + 2L (3.13)
inP = outP + L2 + L1 (3.14)
Therefore, if the input power of the engine is to be calculated, then equation 3.15 can
be used:
inP =AE
outP��
(3.15)
where,
inP = power input of the engine, which is supplied by the GCV of
the fuel
outP = power output of the alternator, supplied to the load bank
E� = Engine Efficiency
A� = Alternator Efficiency
Chapter 3: Methodology
55
3.7 Emission Testing
The Horiba Automotive Emission Gas Analyzer MEXA-554J was used to analyse
the CO, HC, and CO2 components resulting from various fuel samples used to run
the petrol generator. The specifications of the analyser are given in Table 3.4. This is
a portable analyser used for analysing the exhaust gases from automotives as well as
some non-automotives such as a generator.
Table 3.4: Specifications of the Horiba Automotive Emission Gas Analyser
(Source: Instruction manual of Horiba Automotive Emission Gas
Analyser MEXA-554J series)
Model MEXA-554JA
Gases Measured CO, HC, CO2 and O2
Measurement Range CO: 0-10 % vol
HC: 0-20, 000 ppm vol
CO2: 0-20 % vol
O2: 0-25 % vol
Repeatability within one third of [larger one of ± 0.06 % vol
CO, ± 12 ppm vol HC, ± 0.5 % vol CO2 of
readout] 13 times or more in 20 measurement
times
Response speed TD + T90: Within 10 seconds
TD + T95: Within 15 seconds
Output Analog: 0 to 1 V DC
Ambient Temperature Range 0 °C to 40 °C
Ambient Humidity Range 90 % or less
3.7.1 Instrument Start-up
Horiba automotive emission gas analyser was warmed-up and certain tests were
performed before it was ready to be used. This was done so that measurements made
would be stable and have a greater degree of accuracy.
Chapter 3: Methodology
56
The power supply on the rear of the instrument was turned on. The warm-up screen
was displayed and the instrument automatically began the warm-up procedures. The
warm-up time for the instrument was 5 mins.
After the warm-up HC Hang-up test was performed. This test was made to check
how much hydrocarbon (HC) is absorbed by the sampling unit. During this test clean
air continues to be purged in until the reading becomes 20 ppm or less. The screen
will show a passed sign when the test is complete.
Leak test was performed to check if any filter, probe or the sampling unit needed to
be replaced. This is done to ensure that there is no gas leakage. A seal cap is fitted
over the leading end of the probe to block the gas absorption holes on the probe. The
test is then started and a seal retention time of 5 seconds is counted down. A passed
sign is displayed if the test is successful.
Having completed the warm-up and the other tests the instrument was ready for
measurement. The “M” key located on the front panel is pressed and the “MEAS”
mark blinks on the display for 10 seconds before the instrument entered the
measurement mode.
3.7.2 Measurement of Emission
The Horiba automotive emission gas analyser was ready for measurement after the
warm-up, calibration and the two tests; HC hang-up and leak test were completed.
The instrument was pre-calibrated by the manufacturers. The probe was inserted into
the exhaust pipe of the generator. Measurements were carried out after 40 ml of the
sample had been used. This ensured that the system had stabilised and also that any
residual gas components of the previous fuel sample had been removed. Initially,
when the probe was inserted in the exhaust pipe of the generator, fluctuations in the
reading where observed however, the readings stabilised after 20 s, after which data
was taken. Data was again taken after 80 ml and 120 ml of the fuel had been used.
This was to ensure the emission levels of the sample were consistent throughout the
run-time of the fuel. The averages of the readings were taken and it was noted that
the differences between the data were minimal. The results were within an accuracy
Chapter 3: Methodology
57
of ± 0.06 % vol CO, ± 12 ppm vol HC and ± 0.5 % vol CO2. After the completion of
the testing the instrument was left in the measurement mode for 30 mins so the
sample lines were purged with clean air before switching the instrument off.
58
Chapter 4 Results and Discussions
4.0 Overview
This chapter has five main sections. The first section discusses the viability of
producing ethanol from locally available cassava varieties in Fiji. The second section
presents and discusses the results of ethanol production from cassava starch. The
third and fourth section deals with the preparation and identification of physical
properties of ethanol-petrol blends respectively. The final section presents and
discusses the results of the investigations of engine performance, which include the
efficiency, fuel consumption and emission data.
4.1 Cassava Varieties in Fiji
The starch yield from different cassava varieties obtained from two different
locations in Fiji is shown in Table 4.1 below. The starch yields for cassava varieties
obtained from both the stations ranges from 17 to 23 %.
Chapter 4: Results and Discussions
59
Table 4.1: Starch Yield from Cassava Varieties
Cassava
Variety Koronivia Dobuilevu
Starch Yield
(%)
Starch Yield
(%)
Niumea 18.3 19.9
Sokobale 17.7 *
Beqa 21.9 17.0
New Guinea 20.9 19.5
Coci 20.5 23.3
Vula Tolu 17.3 18.1
Yabia Damu 19.6 17.9
Merelesita 18.6 18.8
Nadelei 23.1 22.1
Navolau 17.0 19.8 * means the variety was not available at this location
The results show that the yields are dependent on the sites of the plantations. They
show that Beqa, New Guinea, Yabia Damu, and Nadelei are more suited to the
Koronivia site with regard to their starch yields. On the other hand Niumea, Coci,
Vula Tolu and Navolau performed better at the Dobuilevu site for their starch yields.
The Merelesita starch yield did not show much variation with site. Therefore, it is
seen that location is one of the factors that influence starch yield.
Benesi’s (2005) result indicated that the genetic constitution of the plant is the most
influential factor. However, sites, rounds of starch extraction and their interaction
also have appreciable influence. Similar observations were also made by
Ngendahayo and Dixion (2001) who found that after six months, the starch content
in plants are influenced by genotype, harvesting time and rainfall pattern.
The annual rainfall for KRS was 3626 mm in 2008/2009, during the growing seasons
and for DRS it was 3069.6 mm in 2008/2009. Both research stations received highest
rainfall in January. When cassava was planted at KRS for the first four months of
planting there was decrease in rainfall as seen in Figure 4.1. After September there
Chapter 4: Results and Discussions
60
was increase in rainfall until January.1. Then from February to harvest there were
monthly fluctuations observed in rainfall.
Figure 4.1: Rainfall and Temperature data at KRS
On the other hand at DRS, a slight increase was observed in rainfall for the first
month of planting as seen in Figure 4.2. Then there was a gradual decrease in rainfall
in September until October. From October to January there was eventual increase in
rainfall. Then after January until harvest again there was a decrease in rainfall.
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34
0
100
200
300
400
500
600
700
Tem
pera
ture
(°C
)
Rai
nfal
l (m
m)
Rainfall and Temperature Data for KRS
Rainfall
Max Temperature Min Temperature
Chapter 4: Results and Discussions
61
Figure 4.2: Rainfall and Temperature data at DRS
Monthly mean maximum temperatures ranged between 26.9 and 31.2 °C for
Koronivia and 31.2 and 34.3 °C for Dobuilevu. Monthly mean minimum
temperatures ranged between 19.6 and 23.3 °C for Koronivia, 25.2 and 29 °C for
Dobuilevu. It is seen that Dobuilevu generally had higher temperatures than
Koronivia.
The dry matter content obtained from two different locations is shown in Table 4.2.
The cassava from Koronivia had a dry matter content as high as 41 % (New Guinea
and Beqa) whereas the ones from Dobuilevu had a maximum of 38 % (Nadelei).
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38
0 100 200 300 400 500 600 700 800 900
1000 1100 1200 1300 1400
Tem
pera
ture
(°C
)
Rai
nfal
l (m
m)
Rainfall and Temperature Data for DRS
Rainfall
Max Temperature Min Temperature
Chapter 4: Results and Discussions
62
Table 4.2: Dry Matter Content of Cassava Varieties
Cassava
Variety Koronivia Dobuilevu
Dry Matter
Content (%)
Dry Matter
Content (%)
Niumea 37.9 36.2
Sokobale 36.3 *
Beqa 41.2 32.2
New Guinea 41.5 32.3
Coci 37.0 36.8
Vula Tolu 31.1 35.6
Yabia Damu 35.7 36.0
Merelesita 40.9 35.6
Nadelei 40.8 38.0
Navolau 33.7 33.8
* indicates the variety was not available at this location
Dry matter content is very much related to rainfall during six to eighteen months of
plant growth (Ngendahayo and Dixion, 2001). This suggests that the difference in
dry matter content between the sites could be contributed to the rainfall received
during plant growth. However, Benesi et al. (2004) have reported that the root dry
matter content of cassava in Malawi is in the range 38.24 to 46.48 % and that dry
matter content was not as much influenced by the environment as by the genetic
differences.
Most researchers agree that the optimum time for harvest of cassava roots depend on
varieties and ecological factors (Ashoka et al. 1984, Ngendahayo and Dixion, 2001).
Hence, there is a need to identify optimum harvest time for different cassava
varieties and also identify the most suitable environment for these varieties.
Optimum economic returns in terms of dry matter content and starch yield can be
ensured if suitable varieties and ecological factors are identified.
Chapter 4: Results and Discussions
63
The mineral elements and inorganic salts present in starch are referred to as ash.
Table 4.3 shows that the ash content for cassava varieties obtained from Koronivia is
0.10 to 0.17 % and for Dobuilevu it was 0.1 to 0.21 %.
Table 4.3: Ash Content of Cassava Starch from Various Varieties
Cassava
Variety Koronivia Dobuilevu
Ash Content
(%)
Ash Content
(%)
Niumea 0.17±0.01 0.19±0.03
Beqa 0.17±0.03 0.21±0.02
Sokobale 0.11±0.02 *
New Guinea 0.09±0.01 0.15±0.04
Coci 0.14±0.02 0.13±0.01
Vula Tolu 0.10±0.02 0.12±0.02
Yabia Damu 0.10±0.02 0.17±0.03
Merelesita 0.12±0.02 0.13±0.01
Nadelei 0.10±0.02 0.10±0.02
Navolau 0.14±0.02 0.16±0.04
Notes: Means of three replicates (± SD) * indicates the variety was not available at this location
According to Thomas and Atwell (1999) ash content is typically less than 0.5 % of
dry mass and this agrees with the results obtained for all the cassava varieties
obtained from Koronivia and Dobuilevu. Variations in ash content depend upon
source of raw material, agronomic practices, extraction and milling procedures and
types of chemical modifications (Benesi, 2005).
The pH of cassava starch as reported in Table 4.4 ranged from 4.07 to 5.23 for the
varieties obtained from Koronivia and 5.03 to 6.20 for those varieties obtained from
Dobuilevu. Benesi (2005) indicated a pH range of 5.0 to 5.5 for the native starch
obtained from ten elite Malawian cassava genotype. The recommended pH range
stated by the National Starch and Chemical Company (2002) is between 4.5 and 7.0.
Therefore, as the obtained starch pH of the different cassava varieties in Fiji are
Chapter 4: Results and Discussions
64
within the recommended range, they are favourably disposed for industrial and food
applications.
Table 4.4: pH of Cassava Starch from Various Varieties
Cassava
Variety Koronivia Dobuilevu
pH pH
Niumea 4.07±0.02 5.98±0.05
Sokobale 4.18±0.02 *
Beqa 4.89±0.01 5.81±0.04
New Guinea 5.23±0.02 5.03±0.02
Coci 4.47±0.01 5.04±0.03
Vula Tolu 4.63±0.03 5.17±0.01
Yabia Damu 4.44±0.01 6.20±0.02
Merelesita 4.53±0.03 5.21±0.03
Nadelei 4.53±0.02 5.48±0.03
Navolau 4.37±0.01 5.34±0.02
Notes: Means of three replicates (± SD) * indicates the variety was not available at this location
The moisture content of starch from cassava varieties obtained at Koronivia as
shown in Table 4.5, ranged from 12.4 to 14.7 %, whereas, for Dobuilevu it was from
12.0 to 14.5 %. The results obtained are consistent with the results reported by
Nuwamanya et al. (2008) and Benesi (2005). Nuwamanya et al. (2008) reported
moisture content ranged from 14.09 and 16.49 % for the parental lines and 14.80 to
16.11 % in the progenies. The native cassava starch moisture content that Benesi
(2005) found for the ten varieties investigated ranged from 10.47 to 12.83 %. High
moisture content in cassava starch is not a desired property. It leads to growth of
micro-organisms that are capable of degrading starch (Nanda, n. d). Moorthy (2001)
reported that high moisture content affects the pasting properties of cassava starch
and Willet and Doane (2002) stated that the tensile properties and overall granular
structure of starch are also affected by high moisture content.
Chapter 4: Results and Discussions
65
Table 4.5: Moisture Content of Cassava Starch from Various Varieties
Cassava
Variety Koronivia Dobuilevu
Moisture
Content (%)
Moisture
Content (%)
Niumea 12.6±0.5 12.9±0.9
Sokobale 14.7±0.6 *
Beqa 14.1±0.8 14.5±0.4
New Guinea 13.9±0.6 13.6±0.9
Coci 13.1±0.5 12.5±1.0
Vula Tolu 13.9±0.6 13.7±1.2
Yabia Damu 12.9±0.3 12.8±0.5
Merelesita 12.4±1.0 13.0±0.4
Nadelei 13.7±0.4 13.6±0.9
Navolau 12.5±1.0 12.0±1.2
Notes: Means of three replicates (± SD) * means the variety was not available at this location
In Fiji, cassava is predominantly grown for human consumption. There is almost no
processing of cassava into dried form for human or animal use. However, apart from
food, cassava is exported to Australia and New Zealand as frozen tubers. Cassava is
grown in most parts of Fiji. As it is tolerant to a range of climatic conditions as well
as growing in marginal land, limited effort is currently being placed in improving
conditions for planting. There is minimum land preparation, weeding is hardly done
and limited fertilizer applied. In 2007, the cassava yield was 13.80 t ha-1 (SOPAC,
2009). This yield can be increased with sustainable cultivation practices and also by
identifying high yielding varieties. Cassava research in Fiji is mostly done by KRS
and other stations of the Ministry of Agriculture, Fisheries and Forest.
Bio-ethanol is produced by fermenting sugars or substances that can be converted to
sugars, such as starch and cellulose. Cassava roots contain starch that can be
converted to sugar. As seen in the starch yield results obtained (Table 4.1), cassava in
Fiji can be used for bio-ethanol production. The Fiji Government has plans to
Chapter 4: Results and Discussions
66
produce bio-ethanol from agricultural sources available in Fiji namely sugarcane,
molasses and cassava. It has been pointed out (Rao, 1997), cassava is one of the best
crops to be used for bio-ethanol production. The ethanol yield of cassava per unit
land area is higher than any other known energy crop as seen in Table 4.6. In
addition, it is much cheaper to set up a cassava ethanol factory because of lower
investment and the processing technology is much simpler due to the special
characteristics of starch (Wang, 2002). The cost of cassava ethanol can be lowered
due to production of useful by-products from different parts of cassava plant (Wang,
2002).
Table 4.6: Comparison of ethanol yield made from various energy crops
Crop Yield
(t ha-1 year-1)
Conversion rate
to sugar or
starch (%)
Conversion rate
to ethanol
(L t-1)
Ethanol Yield
(kg ha-1 year-1)
Sugarcane 70 12.5 70 4,900
Cassava 40 25 150 6,000
Carrot 45 16 100 4,500
Sweet sorghum 35 14 80 2,800
Maize 5 69 410 2,050
Wheat 4 66 390 1,560
Rice 5 75 450 2,250
Source: (Rao, 1997)
However, since cassava is primarily produced in Fiji for food by the people, an
approach needs to be found that would balance out the use of agricultural land for
food and fuel. The use of food crops for fuel usually drives the prices of these crops.
For this reason governments in many countries are now ensuring that biofuels do not
increase the price of staple foods. The Fiji Government has dismissed the threat to
food security on the grounds that more than enough land is idle in Fiji according to
Food and Agriculture Organization (FAO) 2006 figures (SOPAC, 2009). As stated in
the FAO report (SOPAC, 2009), promoting diversification and setting aside land for
food production is one strategy. However, governments need to make a national-
level decision as to what extent staple crops should be used for biofuel production.
Chapter 4: Results and Discussions
67
4.2 Ethanol Production from Cassava Starch
Ethanol can be produced from cassava starch by fermentation using yeast such as
Saccharomyces cerevisiae. However, cassava starch first needs to be hydrolyzed to
sugar before bioconversion to ethanol by Saccharomyces cerevisiae.
The results of the ethanol produced and the amount of reducing sugars remaining as
a function of time from each variety of cassava starch obtained from KRS and DRS
in this study are shown in Figures 4.3 and 4.4 respectively.
As seen in both the figures, from 0 hours to 24 hours there is a rise in amount of
reducing sugars from an approximate average of 70 g l-1 peaking at 24 hours and then
declining after 24 hours with a simultaneous rise in the value of ethanol
concentration. This is explained by observing that during the liquefaction stage small
amounts of reducing sugars were produced by the action of α-amylase. The action of
the amyloglucosidase produced further amount of reducing sugars through the
additional breakdown of the dextrin which was obtained from liquefaction.
From all the figures it is revealed that yeast (Saccharomyces cerevisiae) began
producing ethanol after 24 hours with decline in reducing sugars concentration and a
simultaneous increase in ethanol concentration. These results support published
reports that both α-amylase and amyloglucosidase activities are needed for starch
fermentation by Saccharomyces cerevisiae (Eksteen et al., 2003; Shigenchi et al.,
2004; Jamai et al., 2007).
Chapter 4: Results and Discussions
68
(a)
(b)
0 10 20 30 40 50 60 70
0 20 40 60 80
100 120 140
0 24 48 72 96 120 Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration for Niumea (Koronivia)
Reducing Sugars
Ethanol Concentration
0 10 20 30 40 50 60 70
0 20 40 60 80
100 120 140 160
0 24 48 72 96 120 Eth
anol
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs) Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Reducing Sugars and Ethanol Concentration Sokobale (Koronivia)
Reducing Sugars
Ethanol Concentration
Chapter 4: Results and Discussions
69
(c)
(d)
0 10 20 30 40 50 60 70
0 20 40 60 80
100 120 140 160
0 24 48 72 96 120 Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration Beqa (Koronivia)
Reducing Sugars Ethanol Concentration
0
10
20
30
40
50
60
0
20
40
60
80
100
120
0 24 48 72 96 120 Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
artio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentartion New Guinea (Koronivia)
Reducing Sugars Ethanol Concentration
Chapter 4: Results and Discussions
70
(e)
(f)
0 10 20 30 40 50 60 70
0 20 40 60 80
100 120 140 160
0 24 48 72 96 120 Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration Coci (Koronivia)
Reducing Sugars Ethanol Concentration
0
10
20
30
40
50
60
70
0
20
40
60
80
100
120
0 24 48 72 96 120
Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration Vula Tolu (Koronivia)
Reducing Sugars Ethanol Concentration
Chapter 4: Results and Discussions
71
(g)
(h)
0
10
20
30
40
50
60
70
0
20
40
60
80
100
120
140
0 24 48 72 96 120
Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration Yabia Damu (Koronivia)
Reducing Sugars Ethanol Concentration
0
10
20
30
40
50
60
70
0 20 40 60 80
100 120 140 160 180
0 24 48 72 96 120
Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration Merelesita (Koronivia)
Reducing Sugars Ethanol Concentration
Chapter 4: Results and Discussions
72
(i)
(j) Figure 4.3: Ethanol Concentration and remnant reducing sugars concentration from
(a) Niumea, (b) Sokobale, (c) Beqa, (d) New Guinea, (e) Coci, (f) Vula
Tolu, (g) Yabia Damu, (h) Merelesita, (i) Nadelei, (j) Navolau cassava
variety starch obtained at KRS
0 10 20 30 40 50 60 70
0 20 40 60 80
100 120 140 160
0 24 48 72 96 120 Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration Nadelei (Koronivia)
Reducing Sugars Ethanol Concentration
0 10 20 30 40 50 60 70
0
20
40
60
80
100
120
0 24 48 72 96 120 Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration Navolau (Koronivia)
Reducing Sugars Ethanol Concentration
Chapter 4: Results and Discussions
73
(a)
(b)
0
10
20
30
40
50
60
0 20 40 60 80
100 120 140
0 24 48 72 96 120 Eth
anol
Con
cent
ratio
n (g
l-1
)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration for Niumea (Dobuilevu)
Reducing Sugars Ethanol Concentration
0 10 20 30 40 50 60 70
0 20 40 60 80
100 120 140 160
0 24 48 72 96 120 Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration Beqa (Dobuilevu)
Reducing Sugars Ethanol Concentration
Chapter 4: Results and Discussions
74
(c)
(d)
0 10 20 30 40 50 60 70
0
20
40
60
80
100
120
0 24 48 72 96 120 Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
artio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentartion New Guinea (Dobuilevu)
Reducing Sugars
Ethanol Concentration
0 10 20 30 40 50 60 70
0 20 40 60 80
100 120 140 160 180
0 24 48 72 96 120 Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration Coci (Dobuilevu)
Reducing Sugars Ethanol Concentration
Chapter 4: Results and Discussions
75
(e)
(f)
0 10 20 30 40 50 60 70
0 20 40 60 80
100 120 140 160 180
0 24 48 72 96 120 Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration Vula Tolu (Dobuilevu)
Reducing Sugars Ethanol Concentration
0 10 20 30 40 50 60 70
0 20 40 60 80
100 120 140 160
0 24 48 72 96 120 Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration Yabia Damu (Dobuilevu)
Reducing Sugars Ethanol Concentration
Chapter 4: Results and Discussions
76
(g)
(h)
0
10
20
30
40
50
60
70
0 20 40 60 80
100 120 140 160 180 200
0 24 48 72 96 120 Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration Merelesita (Dobuilevu)
Reducing Sugars Ethanol Concentration
0
10
20
30
40
50
60
70
0 20 40 60 80
100 120 140 160 180 200
0 24 48 72 96 120
Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration Nadelei (Dobuilevu)
Reducing Sugars Ethanol Concentration
Chapter 4: Results and Discussions
77
(i)
Figure 4.4: Ethanol Concentration and remnant reducing sugars concentration from
(a) Niumea, (b) Beqa, (c) New Guinea, (d) Coci, (e) Vula Tolu, (f) Yabia
Damu, (g) Merelesita, (h) Nadelei, (i) Navolau cassava variety starch
obtained at DRS
The ethanol concentration obtained after 120 hours of fermentation was in the range
of 55-63 g l-1 for cassava obtained from KRS and 55-65 g l-1 for cassava obtained
from DRS as seen in Table 4.7. Statistical analysis performed on the results showed
that there is no significant difference among the ethanol concentration obtained from
starch of different cassava varieties (p < 0.05). Similarly, there was no significance
found in ethanol concentration obtained from starch at the two locations and
interaction between cassava variety and location at (p < 0.05).
The ethanol yield, which was expressed as litres of ethanol produced per kilogram of
starch used, was in the range of 0.35-0.40 L of ethanol per kg of starch and 0.35-0.41
L of ethanol per kg of starch for KRS and DRS respectively. The details of this are
indicated in Table 4.7. There was no significant difference among the ethanol yield
obtained from starch of different cassava varieties (p < 0.05). Similarly, there was no
significant difference found in ethanol concentration obtained from starch at the two
locations and between cassava varieties from the two locations (p < 0.05).
0
10
20
30
40
50
60
70
0 20 40 60 80
100 120 140 160 180 200
0 24 48 72 96 120
Eth
anol
Con
cent
ratio
n (g
l-1)
Red
ucin
g Su
gars
Con
cent
ratio
n (g
l-1)
Fermentation Time (hrs)
Reducing Sugars and Ethanol Concentration Navolau (Dobuilevu)
Reducing Sugars Ethanol Concentration
Chapter 4: Results and Discussions
78
Cassava has been shown to be a good source of ethanol production because it has a
high amylose/amylopectin ratio (Dubey, 2001). Starch is a polymer of glucose. It is
made up of two related but structurally different polymers, amylose and amylopectin.
The basic building block of both amylose and amylopectin is glucose monomer
through the α–1, 4 glucosidic bonds (Kearsley and Dziedzic, 1995). As the there is
no significant difference in the ethanol concentration and ethanol yield resulting from
using starch from the different cassava varieties and obtained from the two locations,
it can be assumed that the starch from these cassava are almost similar in structure.
This indicates that the enzymatic activity and also fermentation by Saccharomyces
cerevisiae on the starch from different cassava varieties were the same.
Table 4.7: Final ethanol concentration and ethanol yield from cassava varieties
from two different locations
KRS DRS
Cassava
Variety
Final Ethanol
Concentration
(g l-1)
Ethanol Yield
(L Ethanol kg-
1 Starch)
Final Ethanol
Concentration
(g l-1)
Ethanol Yield
(L Ethanol kg-
1 Starch)
Niumea 61 ± 7 0.39 ± 0.04 55 ± 7 0.35 ± 0.04
Sokobale 62 ± 7 0.39 ± 0.04 * *
Beqa 59 ± 4 0.38 ± 0.03 61 ± 4 0.39 ± 0.03
New Guinea 55 ± 5 0.35 ± 0.03 59 ± 4 0.38 ± 0.02
Coci 63 ± 5 0.40 ± 0.03 59 ± 5 0.37 ± 0.03
Vula Tolu 60 ± 6 0.38 ± 0.04 63 ± 7 0.40 ± 0.04
Yabia Damu 61 ± 9 0.39 ± 0.06 62 ± 4 0.39 ± 0.02
Merelesita 60 ± 7 0.38 ± 0.05 65 ± 6 0.41 ± 0.04
Nadelei 59 ± 8 0.38 ± 0.05 59 ± 6 0.38 ± 0.04
Navolau 58 ± 6 0.37 ± 0.04 60 ± 4 0.38 ± 0.02
Notes: Means of three replicates (± SD) * means the variety was not available at this location
Chapter 4: Results and Discussions
79
Analysis of ethanol production from different cassava varieties as seen in Table 4.8
shows that approximately 11.47-15.85 kg of cassava is required by different varieties
to produce 1 L ethanol. As seen in Table 4.8 the least amount of cassava is required
by the variety Nadelei (11.47 kg) which also has the highest starch yield from
cassava roots. On the other hand, it is noted that variety Navolau and Beqa both have
the lowest starch yield (17 %) but since the ethanol yield when using Beqa (0.39 L
Ethanol kg-1 Starch) variety is slightly more than Navolau (0.37 L Ethanol kg-1
Starch), more cassava is required by the variety Navolau (15.85 kg) to produce 1 L of
ethanol.
Chapter 4: Results and Discussions
80
Table 4.8: Cassava required for producing 1 L ethanol from each cassava variety
studied
KRS
DRS
Cassava
Variety
Starch
Yield
(%)
Ethanol
Yield (L
Ethanol kg-1
Starch)
Starch
require
d to
produce
1 L
ethanol
(kg)
Cassava
require
d to
produce
1 L
ethanol
(kg)
Starch
Yield
(%)
Ethanol
Yield (L
Ethanol
kg-1
Starch)
Starch
require
d to
produce
1 L
Ethanol
(kg)
Cassava
required
to
produce
1 L
ethanol
(kg)
Niumea 18.3 0.39 ±
0.04
2.58 13.71 19.9 0.35 ±
0.04
2.84 14.28
Sokobale 17.7 0.39 ±
0.04
2.55 14.40 * * * *
Beqa 21.9 0.38 ±
0.03
2.65 12.10 17 0.39 ±
0.03
2.56 15.08
New
Guinea 20.9 0.35 ±
0.03
2.84 13.59 19.5 0.38 ±
0.02
2.66 13.66
Coci 20.5 0.40 ±
0.03
2.48 12.11 23.3 0.37 ±
0.03
2.68 11.50
Vula
Tolu 17.3 0.38 ±
0.04
2.62 15.14 18.1 0.40 ±
0.04
2.51 13.86
Yabia
Damu 19.6 0.39 ±
0.06
2.56 13.08 17.9 0.39 ±
0.02
2.55 14.24
Merelesit
a 18.6 0.38 ±
0.05
2.62 14.09 18.8 0.41 ±
0.04
2.42 12.86
Nadelei 23.1 0.38 ±
0.05
2.65 11.47 22.1 0.38 ±
0.04
2.66 12.06
Navolau 17 0.37 ±
0.04
2.69 15.85 19.8 0.38 ±
0.02
2.63 13.31
Notes: Means of three replicates (± SD) * means the variety was not available at this location
Chapter 4: Results and Discussions
81
The ethanol yield obtained from the Fiji cassava varieties shows a lot of variation
from literature obtained from cassava at other places. According to Li and Halbrendt
(2009), in China 7.2 t of fresh cassava can yield 1 t of ethanol. This is almost same as
producing 1 L ethanol from approximately 5.7 kg of cassava. The high ethanol yield
from cassava available in China can be attributed to the fact that starch content in
cassava from China is higher than 30 %. Researchers Sriroth et al. (2006) have
indicated that for Thailand cassava at 25 % starch content about 6 kg of fresh cassava
can yield 1 L ethanol. Similarly, Sorapipatana and Yoosin (2011) have reported that
approximately 1 t cassava can yield 160 L ethanol, which is same as 6.25 kg cassava
for 1 L ethanol. Table 4.9 summarizes theses results.
Table 4.9: Comparison of Obtained Ethanol yield with Literature Results Country Cassava needed for producing 1 L
ethanol (kg)
Fiji 11.47-15.85
China 5.7
Thailand 6-6.25
Looking at the literature values it is clear that the ethanol yield obtained from Fiji
cassava is low. The reason for this could be due to the cassava varieties and the
agronomic practice in Fiji. The cassava that was used for experimental purposes were
obtained from the research stations. The varieties obtained were considered to be
high yielding and to have good starch content but no data on this was obtained by the
research stations themselves as the stations were still doing trials. According to them
very little scientific input had been put into growing the different varieties. The
following are some factors that need to be considered in order to ensure high yield of
cassava (ICS-Nigeria, n. d):
� Choice of land
� Choosing cassava variety
� Recommended varieties
� Acquisition of planting materials
� Stem storage
� Stem quality
Chapter 4: Results and Discussions
82
� Preparation of planting materials
� Handling of stakes
� Time of planting
� Method of planting
� Plant population
� Weed control
� Fertilizer rate and time of application
� Harvesting
For high ethanol yield, high starch content in cassava roots is the most important
criterion. Therefore, varieties with the highest starch content should be used for
ethanol production and the development of high starch content varieties through
breeding should be considered. There are other factors that affect the results of
ethanol yield such as fermentation temperature, removal of inhibiting substances,
agitation of fermentation tube and the yeast species (Liu and Liang, 1983).
Nevertheless, feedstock selection and conversion of feedstock to ethanol are very
important consideration that needs to be made when production of bio-ethanol is
considered especially for mass production and sustainable use.
4.3 Preparation of Ethanol-Petrol Blends
Ethanol is a hydrophilic compound, which means it absorbs water from the
atmosphere. Due to ethanol’s high affinity for water, storage of ethanol-petrol blends
needs to be done with due care. Also blends should be made when they are
absolutely required rather than storing for long periods of time.
Ethanol-petrol blends were observed for stability at different temperatures that are
expected in Fiji. The composition of ethanol-petrol blends prepared for testing is
shown in Table 4.10.
Chapter 4: Results and Discussions
83
Table 4.10: Composition of ethanol-petrol blended samples used for analysis
Sample code % Ethanol % Petrol
E10 10 90
E15 15 85
E20 20 80
The preparation of the E10, E15 and the E20 samples were done using 93 %, 95 %,
97 % and absolute ethanol respectively. This was done to see whether apart from
absolute ethanol if any other purity of ethanol could be used for blending without
showing signs of phase separation. Table 4.11 to 4.14 summarizes the observations
of the ethanol-petrol blends.
Table 4.11: Stability testing using absolute ethanol in ethanol-petrol blends
Temperature
(ºC)
28 26 24 22 18 14
Phase Separation (Yes/No)
E10 No No No No No No
E15 No No No No No No
E20 No No No No No No
Table 4.12: Stability testing using 97 % ethanol in ethanol-petrol blends
Temperature
(ºC)
28 26 24 22 18 14
Phase Separation (Yes/No)
E10 No No No No No No
E15 No No No No No No
E20 No No No No No No
Chapter 4: Results and Discussions
84
Table 4.13: Stability testing using 95 % ethanol in ethanol-petrol blends
Temperature
(ºC)
28 26 24 22 18 14
Phase Separation (Yes/No)
E10 No No No No No Yes
E15 No No No No No Yes
E20 No No No No No Yes
Table 4.14: Stability testing using 93 % ethanol in ethanol-petrol blends
Temperature
(ºC)
28 26 24 22 18 14
Phase Separation (Yes/No)
E10 No No No No Yes Yes
E15 No No No No Yes Yes
E20 No No No Yes Yes Yes
As seen in the tables there is no phase separation when using absolute ethanol in
blends. This is consistent with the absence of water in these samples. With the 97 %,
95 % and 93 % ethanol blends it was observed that, with the exception of the 93%
ethanol, there is no phase separation above 18 °C. Generally, the temperature at
which phase separation occurs increases with the water content. In Fiji the average
ambient temperature is usually between 26 and 29 ºC. The results above show that it
is possible to blend ethanol and petrol with even 93 % pure ethanol in Fiji without
phase separation occurring.
Since ethanol has an affinity for water, phase separation is likely to occur as the
water content of ethanol-petrol blend increases. For this reason, ethanol-petrol blends
should be stored in a secure place where the possibility of water entering the blends
is absolutely minimum.
The results of this study are consistent with those reported in the literature, which
show that phase separation in ethanol-petrol blends is temperature dependent, and
Chapter 4: Results and Discussions
85
that it occurs more readily at lower temperatures with lower ethanol content and at
higher temperatures with higher ethanol content (Guibet, 1999). Together with
temperature, phase separation is also dependent on aromatics and ethanol content
(Environment Australia, 2002).
The blends studied in this work were prepared using 96 % ethanol. This was
considered suitable for blending without phase separation. A lower percentage could
also have been used as well but just to avoid too much water being in the blend 96 %
ethanol was considered suitable. Also absolute ethanol requires additional distillation
to produce which can be quite costly to produce and also require extra energy.
Saving on this additional energy expenditure may help ensure that energy returned
on energy invested on bio-ethanol is positive thus indicating that using bio-ethanol
should be pursued.
4.4 Physical Properties of Ethanol-Petrol Blends
The three different ethanol-petrol blends that were prepared were tested for density
and gross calorific value (GCV) before they were used in engine and emission
testing.
4.4.1 Density
The density of the petrol and ethanol-petrol blends at 25 °C as a function of the
ethanol content in the blends has been plotted in Figure 4.5. It is observed that the
density of blends increase with increasing ethanol content in blends. This is expected
considering the density of ethanol is more than that of petrol.
Chapter 4: Results and Discussions
86
Figure 4.5: Density of Petrol, E10, E15 and E20
There is an increase in density by 0.7 % upon addition of 10 % ethanol in petrol. This
change is bought about due to the fact that petrol has a density of 0.741 g cm-3
whereas 96 % ethanol that used for blending had a density of 0.793 g cm-3. Similarly,
E15 had an increase in density by 1.10 % and E20 by 1.52 % when compared to
petrol.
Density is a fundamental physical property that can be used in conjunction with other
properties. It also gives an indication of the purity of the fuel. Whenever fuel gets
contaminated with another liquid, density will either increase or decrease depending
on the density of the contaminant liquid. Density is also an indicator of how much
fuel is supplied to the engine, because the fuel pump delivers fuel on a volumetric
basis (Puhan and Nagarajan, 2008). As seen from Figure 4.5 the density of the blends
is higher when compared to petrol, this means more of the fuel is supplied to the
engine when compared to petrol. Therefore, E10, E15 and E20 supply more fuel to
the engine when compared to petrol which can result in increased power output.
0.74 0.742 0.744 0.746 0.748
0.75 0.752 0.754
0 5 10 15 20 25
Den
sity
(g c
m-3
)
Ethanol Fraction in Blends (%)
Density of Petrol and Ethanol/Petrol Blends
Chapter 4: Results and Discussions
87
4.4.2 Gross Calorific Value
The gross calorific value (GCV) of petrol, E10, E15 and E20 are shown in Figure
4.6.
Figure 4.6: GCV of Petrol, E10, E15 and E20 on mass and volume basis
It is observed that blends containing ethanol have a lower GCV, i.e. the GCV
decreases as the ethanol content in blends increases. This can be attributed to the fact
that ethanol has a lower GCV than petrol.
The GCV of petrol was found to be 45.4 kJ g-1 whereas for ethanol it was 29.2 kJ g-1.
The ethanol GCV is almost 35.7 % lower than petrol GCV. E10 GCV is
approximately 4.6 % lower than petrol. For E15 and E20 a decrease of 8.4 % and 9.9
% respectively is observed in GCV when compared with petrol.
Lower GCV in the ethanol-petrol blends means that more fuel should be consumed
by vehicles and in non automotive engines as the ethanol content in blends increases.
The increase in fuel consumption as a result of using ethanol-petrol blends is
discussed in later sections.
GCV on mass basis (kJ g-1) GCV on volume basis (kJ ml-1)
Chapter 4: Results and Discussions
88
4.5 Engine Performance and Emission Characteristics of
Ethanol-Petrol Blends
Ethanol contains an oxygen atom hence; it can be treated as a partially oxidized
hydrocarbon. When ethanol is added to petrol to make the blended fuel, it provides
more oxygen for the combustion process and leads to the so-called ‘‘leaning effect’’
(Hsieh et al., 2002). The leaning effect leads to reduction in carbon monoxide (CO)
and the hydrocarbon (HC) emissions will also decrease under some operating
conditions. The carbon dioxide (CO2) increases when using ethanol-petrol blends due
to more complete combustion. In this section, the effects of the ethanol-petrol
blended fuels on the engine performance and pollutant emission are the main issues
and will be discussed in detail. These results and discussions are based in terms of
engine efficiency, fuel consumption and specific fuel consumption. The emission
characteristics of ethanol-petrol blends are represented in terms of CO, HC and CO2
emissions.
4.5.1 Engine Efficiency
Three different ethanol-petrol blends (E10, E15 and E20) were prepared and tested
for engine performance in a spark ignition (SI) engine. The engine efficiency using
the ethanol-petrol blends and petrol under varying load conditions is given in Figure
4.7 (For tabulated data refer to Appendix A).
Chapter 4: Results and Discussions
89
Figure 4.7: Engine efficiency using Petrol and Ethanol-Petrol blends under
varying loads
There is a steady increase in the efficiency as the load increases in all the blends and
petrol. When the load on engines increase more fuel is supplied for burning to cater
for the increased load resulting in more energy input. Therefore, this results in high
efficiency with increased energy output. It is observed that the efficiency is quite
insensitive to the variation of the blend rate of ethanol-petrol blends and petrol
especially at lower loading up to 800 W. This indicates that other fuel properties such
as the laminar flame speed and heat of vaporization can counteract the energy
content in a fuel, as indicated by the heating value, to produce the same fuel
conversion efficiency (Curtis et al., 2008).
However, at high load the efficiency of petrol is slightly lower when compared to
E10, E15 and E20, this was also observed by Pikūnas et al. (2003). This can be
explained by the fact that the addition of ethanol in petrol results in leaning effect
which then increases the air-fuel equivalence ratio to a higher value, making the
burning closer to be stoichiometric (Hsieh et al., 2002). In other words addition of
ethanol results in better combustion which then makes it possible to have high
efficiency. Another observation to be noted is that at high load condition E10 has a
better efficiency followed by E15 and E20. This is probably because the heating
0
5
10
15
20
25
30
0 400 800 1200 1600 2000
Eng
ine
Eff
icie
ncy
(%)
Load (W)
Engine Efficiency Under Varying Load
Petrol E10 E15 E20
Chapter 4: Results and Discussions
90
value or GCV of E10 more than E15 and E20. Similarly, E15 has a higher heating
value then E20.
Finally, it can be stated that apart from some differences obvious in the figures which
are not so radical, the load-efficiency curves for all ethanol-petrol blends generally
lie very close to that for petrol. This clearly indicates that the ethanol-petrol blends
studied under the various load conditions are not very different from petrol in their
power production capacity.
4.5.1.2 Engine Losses
The efficiency of engines that transform energy is never greater than the Carnot
efficiency. The Carnot efficiency depends on the temperature of the reservoirs
between which the engine is operating. A hundred percent efficiency can only be
obtained if the temperature of the cold reservoir is 0 K which is practically not
possible with heat engines (Jewett, 2004). In most cases, the cold reservoir
temperatures are around room temperatures of 300 K. These effects lead to Carnot
losses.
There are other energy losses that also decrease the engine efficiency as some of the
energy used does not perform useful work. This may be wasted in moving the engine
parts in order to overcome friction inherent in all engines.
Friction forces in engines are a consequence of hydrodynamic stress in oil films and
metal to metal contact. Frictional losses are significant to power produced in engines;
therefore minimizing the friction is a major consideration in engine design and
operation. In order to reduce friction, engines are usually lubricated. Frictional
energy is eventually removed as waste heat by the engine cooling system.
The frictional processes in engines are classified into three main components:
(1) the mechanical friction
(2) the pumping work
(3) the accessory work
The mechanical work includes the friction of the internal moving parts like the
crankshaft, piston, rings and the valve train. The accessory work is the work required
Chapter 4: Results and Discussions
91
for the operation of the accessories such as the oil pump, fuel pump, alternator and
fan.
The pumping work is the net work done during the intake and exhaust strokes.
Pumping losses are caused by the way power output from an engine is regulated. It is
regulated by constricting airflow to the engine. This constriction of airflow creates
partial vacuum resulting in low pressure in the inlet manifold. Energy gets wasted
when maintaining this low pressure in the inlet manifold.
Some of the other losses associated in engines include; heat being carried away by
the exhaust gases, and also passing through the cylinder walls or cylinder head into
the engine cooling system, eventually passing to the atmosphere via the cooling
system.
4.5.2 Fuel Consumption
The relationship between the fuel consumption of the engine at different load
conditions for petrol and the ethanol-petrol blends is shown in Figure 4.8 (For
tabulated data refer to Appendix B).
Figure 4.8: Fuel consumption of Petrol, E10, E15, E20 under varying loads
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 400 800 1200 1600 2000
Fuel
Con
sum
ptio
n (L
hr-1
)
Load (W)
Fuel consumption under varying load
Petrol E10 E15 E20
Chapter 4: Results and Discussions
92
There is an increase in fuel consumption of the engine as the load increases and was
found to be maximum at the maximum load for petrol as well as the blended fuels.
Similar observations were made by Hsieh et al (2002), Al-Hasan (2003), Bayraktar
(2005). When the load increases the engine has to do more work to meet the higher
load conditions as a result more fuel is consumed to meet the power demand.
As seen in the graph the fuel consumption is highest for E20 followed by E15 and
then E10. The reason being that ethanol has a lower GCV than petrol, hence; as the
ethanol fraction in ethanol-petrol blend increases the GCV decreases. Therefore,
more fuel is consumed by increasing ethanol fractions in ethanol-petrol blends to
meet the increasing load demands.
An interesting observation that is made from Figure 4.8 is that the fuel consumption
for petrol at lower loads is almost similar to E10 and then at higher loads (above
1200 W) the fuel consumption is slightly more than E10. This can be explained by
the fact that ethanol addition to petrol makes the engine operation leaner and
improves combustion in the engine as well as performance and efficiency. The high
octane rating of ethanol can also to a certain degree compensate the inevitable drop
in the energy content of the fuel (Wallin et al., 2005).
4.5.3 Specific Fuel Consumption
The specific fuel consumption (SFC) is the amount of fuel consumed against the
work done by the engine over time at a constant load. The relationship between the
SFC under varying loads for petrol, E10, E15 and E20 is depicted in Figure 4.9 (For
tabulated data refer to Appendix B).
.
Chapter 4: Results and Discussions
93
Figure 4.9: Specific Fuel Consumption of Petrol, E10, E15, E20 under varying load
Owing to the fact that the GCV of ethanol is lower than petrol, the SFC increases as
the ethanol content in blends increases. The mass ratio of air to fuel present in an
internal combustion engine is defined as Air Fuel Ratio (AFR). The theoretical AFR
of petrol is 1.6 times more than ethanol (Wu et al., 2004). For this reason the SFC
should increase with increase in ethanol content. However, the fuel injection strategy
tends to operate the engine at fuel-rich condition; as a result the ethanol addition
produces leaning effect to enhance the combustion of fuel (Hsieh et al., 2002). Also
usually at a fixed throttle opening and fixed engine speed, the intake of air is
constant. Therefore, to obtain the same AFR more volume flow rate of ethanol-petrol
blends is needed then petrol as a result compensating for the 1.6 times lower heating
value of ethanol than petrol (Wu et al., 2004). Due to these factors there is almost no
difference in the SFC of petrol and the ethanol-petrol blends.
4.5.4 Engine Exhausts Emission Analysis
An exhaust analyzer was used to measure the exhaust emissions resulting from the
influence of different ethanol-petrol blends at different load conditions. The
following sections will discuss the emissions: CO, HC and CO2.
0.4 0.5 0.6 0.7 0.8 0.9
1 1.1 1.2 1.3 1.4
0 400 800 1200 1600 2000 Spec
ific
fuel
con
sum
ptio
n (k
g kW
-1 h
r-1)
Load (W)
Specific Fuel Consumption under varying load
Petrol E10 E15 E20
Chapter 4: Results and Discussions
94
4.5.4.1 CO Emission
Figure 4.10 shows the effect CO emission on of various blends of ethanol and petrol
under different loads.
Figure 4.10: Effect of varying loads on CO emissions for Petrol, E10, E15 and E20
It was observed that while using E20 to run the engine, the CO emission is less than
other fuels (Petrol, E10 and E15) for each engine loading. At idling, the CO decreses
by 26, 45 and 57 % with E10, E15 and E20, respectively, when compared to petrol.
At maximum load, there is a decrese in CO emission by 34, 61 and 78 % with E10,
E15 and E20, respectively, when compared to petrol. The trend that is observed is
reduction in CO emissions with incresing load and increasing ethanol concentration.
Similar results has also been observed by other researchers.
According to Zervas et al. (2003) the decrease in CO emission is due not only to
dilution of the the fuel but it is also because addition of oxygenated compounds
promotes combustion of CO in the cylinder or during postcombustion processes.
Ethanol is an oygenated compound as it contains an oxygen in its compound. When
ethanol containig the oxygen is mixed with petrol the combustion in the engine
becomes better resulting in reduction of CO.
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
0 400 800 1200 1600 2000
CO
(% v
ol)
Load (W)
CO Emission Under Varying Loads
ULP E10 E15 E20
Chapter 4: Results and Discussions
95
It was noted that as the engine loading incresed the CO emissions decreased. This
can be explained by the fact that increasing loads on engine generation leads to an
increase in the combustion temperature, which when combines with high level of
excess oxygen at these loads results in lower CO emission when compared to low
engine loads (Saiyasitpanich et al., 2005).
In addition, when ethanol is added to petrol it creates the leaning effect which
increases the AFR to a higher value and thus causes the burning closer to
stoichiometric conditions. This results in achieving better combusion and also
increase in combustion temperature (Yücesu et al., 2006).
4.5.4.2 HC Emission
The HC emission characteristics as a function of load for ethanol-petrol blends and
petrol is given in Figure. 4.11.
Figure 4.11: Effect of varying loads on HC emissions for Petrol, E10, E15 and E20
Unburt HCs in exhaust is usually caused by three mechanisms: misfiring or
incomplete combustion , flame quenching effect and deposits or oil membranes (Wu
et al., 2004). As seen from Figure 4.11 HCs decrease as the ethanol content in petrol
increases. E20 has the minimum HC emission followed by E15, E10 and petrol,
0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
80.00
0 400 800 1200 1600 2000
HC
(ppm
)
Load (W)
HC Emission Under Varying Loads
ULP E10 E15 E20
Chapter 4: Results and Discussions
96
respectively. The decrease in HCs can be attributted to the fact that addition of
ethanol which is an oxygenated compound improves the combustion of HCs. Ethanol
can be treated as an partially oxidized HC when it is added to blended fuels, hence
HC emissions decrease (Yüksel and Yüksel, 2004). Addition of ethanol in fuel
enhances the increase in engine volumetric efficiency (Bayraktar, 2005). Reduction
in HC emission with incremental increase in ethanol content in blended fuel can also
be related to increase in volumetric efficiency (Zervas and Tazerout, 2000).
From Figure 4.11 it can be noted that initially there is are slight increases in HC
emission at low engine loads followed by decrease in HC emission. This trend is
observed for all the blended fuels that were tested. The reason why HC emissions
increase at lower engine loads is that high latent heat of vaporization of ethanol tends
to produce slow vaporization and mixing of fuel and air (He et al., 2003). However,
the reduction in HC emission for high engine load for blended fuels can be explained
by two factors (Cheung et al., 2008): (1) the high combustion temperature at high
engine loads enhances vaporization of ethanol-petrol blends and mixing with air,
leading to better combustion, (2) higher oxygen concentration due to addition of
ethanol in blended fuels promotes HC oxidation.
4.5.4.3 CO2 Emission
CO2 is one of the major greenhouse gases that contributes to greenhouse effect.
Figure 4.12 shows the effect of varying engine load on CO2 emissions for different
blends of ethanol-petrol.
Chapter 4: Results and Discussions
97
Figure 4.12: Effect of varying loads on CO2 emissions for Petrol, E10, E15 and E20
It is observed from Figure 4.12 that CO2 emission increases with increasing load,
with petrol having the highest CO2 emission at all engine load, followed by E10, E15
and E20, respectively. The reason for CO2 reduction with increasing ethanol content
is low carbon/hydrogen ratio and high oxygen content in blends (He et al., 2003).
High oygen content in ethanol-petrol blends ensures that the combustion is complete
as a result of this CO2 is produced. The reduction in CO2 at maximum engine load in
E10 is 7 %, 17 % for E15 and 20 % for E20 when compared to petrol. Similar trend
is also observed at other engine loading, the reason being that ethanol contains less
carbon atoms than petrol, therefore, as ethanol content in blended fuels increase, it
gives off lower CO2 (Celik, 2008).
Another important relationship to note is that CO and CO2 have a complementary
relationship. When comparing Figure 4.10 and 4.12 it can be noted that as CO
decreses for all engine loads the CO2 increases. According to Wu et al. (2004) CO2
emission is dependent on the AFR and the CO emission concentration.
0
1
2
3
4
5
6
7
8
0 400 800 1200 1600 2000
CO
2 (%
vol
)
Load (W)
CO2 Emission Under Varying Loads
ULP E10 E15 E20
Chapter 4: Results and Discussions
98
4.5.4.4 The Effects of Various Fuels on Exhaust Emissions at Constant
Load
It is more enlightening to compare the emissions under a constant load for different
fuels. Figures 4.13-4.15 show the CO, HC and CO2 emissions for the various fuels
when the engine is operated at maximum load (1863.5 W). In all the graph it is
observed that there is a decrease in emissions when the proportion of ethanol in
petrol is increased. E20 gives the highest reduction in CO, HC and CO2 emissions.
Figure 4.13: CO emissions for various fuels at maximum load
0
0.5
1
1.5
2
2.5
Petrol E10 E15 E20
CO
(% v
ol)
CO emission at maximum load for Petrol, E10, E15 and E20
0
10
20
30
40
50
60
70
Petrol E10 E15 E20
HC
(ppm
)
HC emission at maximum load for Petrol, E10, E15 and E20
Chapter 4: Results and Discussions
99
Figure 4.14: HC emissions for various fuels at maximum load
Figure 4.15: CO2 emissions for various fuels at maximum load
In this study, it was found that using ethanol-petrol blended fuels resulted in
reduction of CO and HC emissions by 21-78 % and 6-67 %, respectively. Also
reductions in CO2 emission were by 6-20 % with respect to petrol depending on
engine loading. This is comparable to results obtained by Hsieh (2002) which
showed a 10-90 % reduction in CO and 20-80 % in HC as a result of leaning effect.
In terms of reduction of emissions E20 was found to be the best blend. Al-Hasan
(2003) used a range of blends from 0 % to 25 % in increments of 2.5 % and found
E20 to give the best results. The tabulated data for emissions is given in Appendix C.
4.5.5 Prospects and Challenges for Bio-ethanol Use in Vehicles
Worldwide liquid biofuels make a small but increasing contribution to fuel usage
(REN21, 2012). In 2011 biofuels provided about 3 % of global road transport fuels
and is expected to rise to 27 % by 2050 (IEA, 2011). Therefore, it is timely for
developing countries like Fiji to consider developing their biofuel industry.
0
1
2
3
4
5
6
7
8
Petrol E10 E15 E20
CO
2 (%
vol
)
CO2 emission at maximum load for Petrol, E10, E15 and E20
Chapter 4: Results and Discussions
100
With the policy for use of biofuels namely bio-diesel and bio-ethanol already in place
by the Fiji Department of Energy (FDOE), it should start looking towards sustainable
production and use of biofuels for transportation. SI engine cars later than the 1990
model in Fiji can use a blend of up to 10 % ethanol in petrol without modification of
engines. For models older than 1990 modification to the carburetor will be required
before ethanol-petrol blends with 5 to 10 % ethanol can be used (ANFAVEA, 2005).
This mainly includes the material of the body and cover of the carburettor which
cannot be aluminium or Zamak and also any component of Nylon, which will have to
be replaced if unprotected. As most fleets in Fiji are currently 1990 models and later,
therefore, compatibility issue should not arise when using blends containing up to a
maximum of 10 % ethanol.
Generally, compatibility issues when using blends of ethanol-petrol are due to
metallic materials of the vehicle (giving rise to corrosion), plastic and rubber
materials of vehicle (which are susceptible to chemical attack), high fuel
consumption (due to low energy content of ethanol), losses in drivability (due to
different AFR for combustion) and cold start difficulties (due to lower vapour
pressure) (Coelho et al., 2005). However, the extent of these compatibility issues
depend on the blends of ethanol-petrol used, quality and specification of ethanol and
the vehicle technology. Many countries such as the United States (US), Bolivia,
China, Colombia, Jamaica, Kenya, Nigeria, Venezuela, Argentina, Canada, Chile,
India, Philippines, and Costa Rica are already using petrol blended with 5-10 %
ethanol (IEA, 2011).
In order to use higher blends of ethanol-petrol in Fiji, certain modifications to
engines will have to be made so that the benefits associated with the higher oxygen
content could be utilized which include improved fuel efficiency and reduced
emissions. The modifications required for using higher blends include engines with
higher compression ratios so that ethanol’s higher octane rating can be used to
achieve higher efficiencies, and modifications to the fuel feed system and ignition in
order to compensate for differences in the AFR. In addition, modification of some
materials that come in contact with the fuel, such as anticorrosive treatment of the
metal surfaces of fuel tanks, fuel filters and pumps, substitution of fuel lines, and use
Chapter 4: Results and Discussions
101
of materials which are more compatible with ethanol are necessary (BNDES and
CGEE, 2008).
Flex-fuel, or flexible fuel, vehicles (FFVs) are a solution to using higher blends of
ethanol-petrol. These have engines that can alternate between two sources of fuel,
including petrol and bio-ethanol or petrol and natural gas (The Royal Society, 2008).
FFVs for petrol and bio-ethanol have been used extensively in Brazil and to some
extent in USA and Sweden and offer many advantages (Joseph 2007). FFVs in Brazil
can operate with up to 100 % hydrated ethanol but in the US flex-fuel models can
use a maximum of 85 % ethanol, due to problems at cold start. FFV vehicles are
equipped with electronic sensors which enable the on-board computer to recognize
the fuel type and adjust the engine combustion parameters, with no interference from
the driver (Joseph, 2007). FFVs may become a solution for greater bio-ethanol usage.
With the development of appropriate market incentives to encourage the
development and supply of FFVs, these vehicles could offer more flexibility to
increase bio-ethanol usage (The Royal Society, 2008).
Currently, Volkswagen, General Motors, Fiat, Ford, Peugeot, and Renault are some
of manufacturers producing FFVs in Brazil (Coelho et al., 2005). In Fiji, currently
there has been no move to introduce FFVs. Therefore, the focus is mostly on
introducing blends up to 10 % ethanol with 90 % petrol in the existing vehicle fleets.
However, this might change should the bio-ethanol industry develop and the
production of bio-ethanol increases. In order to ensure sustainability, with increasing
bio-ethanol use there needs to be parallel and compatible development of engine
technologies, bio-ethanol feedstock and feedstock conversion technology.
102
Chapter 5 Conclusions
The aim of this study was to produce ethanol from a renewable resource available in
Fiji which could be considered for blending with petrol for use in spark ignition (SI)
engines. This was accomplished by producing ethanol from ten selected cassava
varieties available in Fiji at two different locations and determining the ethanol yield
from different varieties. Ethanol-petrol blend testing using E10, E15 and E20 were
also conducted on an SI engine and their performance in terms of engine efficiency,
fuel consumption and exhaust emissions were compared.
Cassava roots have a number of end-uses, such as food and feed processing, the
starch industry, bio-ethanol production and as well as contributing to the food export
industry. The ten varieties of Fiji cassava possessed a range of starch yields and dry
matter content. . Cassava can be grown in poor soil and other marginal conditions,
making it a resilient crop. While the Fijian varieties studied had lower starch yields
than those reported for other countries, with suitable farming practices cassava root
yields as well as starch yields can be increased. Ethanol concentration obtained after
120 hours of fermentation was in the range of 55-63 g l-1 for cassava obtained from
Koronivia Research Station (KRS) and 55-65 g l-1 for cassava obtained from
Dobuilevu Research Station (DRS) with an ethanol yield of 0.35-0.40 L of ethanol
per kg of starch and 0.35-0.41 L of ethanol per kg of starch for KRS and DRS
respectively. For high ethanol yield, high starch content in cassava roots is the most
important criterion. Therefore the development of high starch content varieties
through breeding should be considered.
Furthermore, experimental results indicated that using ethanol-petrol blended fuels,
the engine efficiency at lower loading of up to 800 W was quite insensitive to the
ethanol content in the blends but at high load the efficiency of petrol is slightly lower
when compared to the ethanol blends E10, E15 and E20. Fuel consumption of the
engine increased slightly with increasing ethanol content in the blends. Whereas, CO
and HC emissions decrease dramatically as a result of the leaning effect caused by
Chapter 5: Conclusions
103
the ethanol addition, the CO2 emission increases because of the improved
combustion. In this study, it was found that using ethanol–petrol blended fuels
resulted in the reduction of CO and HC emissions by 21-78 % and 6-67 %,
respectively, while CO2 emission decreases by 6-20 % depending on engine
conditions.
Although, the current research was conducted on a laboratory scale, the results
obtained provide valuable insight into the commercial viability of ethanol-petrol
blends. They suggest that the blends are viable candidates as alternative fuels for SI
engines. The study also reveals that for tropical conditions, it is possible to use 96 %
ethanol for blending, without any deleterious effects on the engine. The results of this
study also show that as far as the engine efficiency is concerned, ethanol-petrol fuels
will produce very similar engine performance as petrol.
As cassava is primarily produced for food in Fiji, a suitable compromise needs to be
established that would balance out the use of agricultural land for food and fuel. The
use of food crops for fuel usually drives up the prices of these crops. Although, the
Fiji Government has dismissed this threat, indicating that there is sufficient unused
land, there is still a need to take necessary precautions to avoid a food versus fuel
crisis in Fiji. Setting aside land for food production is one strategy. However,
governments need to make a national-level decision as to what extent staple crops
should be used for biofuel production. Clearly, there are several measures that need
to be taken in order to develop bio-ethanol production on a sustainable basis. These
should include the proper coordination and integration of national policies and the
conduct of feasibility studies which evaluate the opportunities for bio-ethanol
production from different feedstocks.
The most common reason for biofuels development would be to reduce the
greenhouse gas emissions. However, Pacific Island Countries (PICs) are amongst the
lowest carbon emitters in the world. Fiji has a carbon footprint of 1.7 t and is ranked
131 emitter of the world (Singh, 2012). Therefore, considering such low overall
emission of PICs, it becomes clear that the main reason to replace fosil fuels with
biofuels should be to improve the country’s economy and to reduce the import bills.
It may not be feasible to replace all fossil fuel imports in Fiji with biofuels for
Chapter 5: Conclusions
104
transportation. However, reduction in fossil fuel imports would be possible by
incorporating the use of biofuel blends in the energy mix of Fiji (Singh, 2012). In
order for Fiji to reduce its petroleum import, drastic measures may be required.
Having a large agro-based economy, Fiji’s bio-ethanol advantage is very much due
to the rich endowment of natural resources. Ethanol can also be an option for other
larger Pacific Island Countries that can support sufficient amounts of sugary or
starchy crops.
5.1 Recommendations and Suggestions for Future Work
The present research has only looked at ten cassava varieties for starch yield and dry
matter content. Research needs to be carried out on the other varieties of cassava that
are available in Fiji and from various other locations. The Ministry of Agriculture in
Fiji should do research on new and better varieties of cassava that are more suitable
to the climatic condition and are high yielding. They should also monitor the new
varieties released for large scale farming and promote the use of superior varieties of
cassava to farmers. Also other possible root crops such as yams should be considered
for starch and bio-ethanol production. Similarly, ethanol yield from other varieties of
starch should also be considered. As the other varieties might have high starch
content and more efficient in ethanol conversion.
The ethanol-petrol blends in this study were only tested for a short duration of time
on the SI engine. Long term research, such as a 2000 hours material compatibility
testing, needs to be carried out in order to determine effect of blends on various
engine components.
Some more fuel properties could have been tested such as flash point and vapor
pressure. However, due to lack of availability of instruments this could not be done.
Therefore, in future research should consider having these properties to be tested by
sending samples abroad.
Fiji already has a policy in place for the use of 10 % ethanol blended with petrol in
vehicles. However, this has not been made mandatory yet due to lack of production
capacity. Therefore, in order to promote the use of bio-ethanol successfully, it should
Chapter 5: Conclusions
105
start considering production of ethanol from improved technology so that production
costs are lowered.
Government research investment in the development of crop technology should
focus on interventions that would lower the high labour and input requirements of
cassava production. Higher budget allocation for research on farm mechanization and
varietal development should be provided by government to increase yield, increase
starch content and consequently increase ethanol productivity of cassava as
feedstock. Also tax exemptions for fertilizers and agro-chemicals as well as fuel for
farm machineries would significantly help reduce farm production costs. This will
ensure the total production cost of bio-ethanol is lower than the price of petrol.
106
References
Abdel-Rahman, A. A. and M. M. Osman, 1997. Experimental investigation on
varying compression ratio of SI engine working under different ethanol-gasoline fuel
blends. International Journal of Energy Research 21: 31-40.
Al-Hasan, M., 2003. Effect of ethanol-unleaded gasoline blends on engine
performance and exhaust emission. Energy Conversion and Management 44: 1547-
1561.
Amin, G., 1992. Conversion of sugar beet particles to ethanol by the bacterium
Zymomonas mobilis in solid state fermentation. Biotechnology Letter 14 (6): 499-504.
Amutha, R. and P. Gunasekaran, 2001. Production of ethanol from liquefied cassava
starch using co-immobilized cells of Zymomonas mobilis and Saccharomyces
diastaticus. Journal of Bioscience and Bioengineering 92 (6): 560-564.
ANFAVEA, 2005. Ethanol Fuel Vehicular Application Technology. Presentation of
Henry Joseph Jr. (Brazilian Automotive Industry Associations Energy & Environment
Commission [email protected]) at CEPAL/CENBIO/USP Seminar São Paulo,
17th August, 2005.
Asaoka, M., J. M. V. Blanshard, and J. E. Rickard, 1991. Seasonal effects on the
physico-chemical properties of starch from four cultivars of cassava. Starch/Starke
43: 455-459.
Asaoka, M., J. M. V. Blanshard, and J. E. Rickard, 1992. Effects of cultivar and
growth season on the gelatinization properties of cassava (Manihot esculenta) starch.
Journal of the Science of Food and Agriculture 59: 53-58.
Ashoka, P. V., S. V. Nair, T. M. Kurian, 1984. Influence of stages of harvest on yield
and quality of cassava, Manihot esculenta Crantz. Madras Agricultural Journal
71:447-449.
References
107
AUS-e-TUTE, n. d., Chemistry Tutorial: Reducing and Non-reducing Sugars.
Available online <http://www.ausetute.com.au/redsugar.html> (date accessed 5th
July, 2012).
Aylward, G. and T. Findlay, 2003. SI Chemical Data, 5th Ed. John Wiley and Sons,
Sussex, UK.
Banat, I. M., P. Singh, and R. Marchant, 1996. The use of thermotolerant fermentative
Kluyveromyces marxianus IMB3 yeast strain for ethanol production. Acta
Biotechnology 16: 215-223.
Bayraktar, H., 2005. Experimental and theoretical investigation of using gasoline–
ethanol blends in spark ignition engines. Renewable Energy 30:1733–1747.
Beer, T., T. Grant, G. Morgan, J. Lapszewicz, P. Anyon, J. Edwards, P. Nelson, H.
Watson and D. Williams, 2001. Comparison of Transport Fuels. Final Report
(EV45A/2/F3C), Australian Greenhouse Office, Victoria, Australia.
Beer, T., T. Grant, D. Williams and H. Watson, 2002. Fuel-cycle greenhouse gas
emissions from alternative fuels in Australian heavy vehicles. Atmospheric
Environment 36: 753-763.
Benesi, I. R. M., M. T. Labuschagne, A. G. O. Dixon, and N. M. Mahungu, 2004.
Stability of native starch quality parameters, starch extraction and root dry matter of
cassava genotypes in different environments. Journal of the Science of Food and
Agriculture 84: 1381-1388.
Benesi, M., 2005, Characterization of Malawian Cassava Germplasm for diversity,
starch extraction and its native and modified properties, PhD thesis, Free State
University, South Africa.
Biofuels Digest, 2012. Brazil sets up $38 billion ethanol subsidy program to stimulate
expansion, Biofuels Digest, 27 February 2012. Available
References
108
<http://www.biofuelsdigest.com/bdigest/2012/02/27/brazil-sets-up-38-billion-ethanol-
subsidy-program-to-stimulate-expansion/> (date accessed 10th December, 2012).
Birse, D. G. and J. E. Cecil, 1980. Starch Extraction: a checklist of commercially
available machinery. Tropical Products Institute, London, England.
BNDES and CGEE, 2008. Sugarcane-based bioethanol : energy for sustainable
Development. Rio de Janeiro. Available online <www.sugarcanebioethanol.org> (date
accessed 9th January 2011).
Bureau of Statistics, 2011. Key Statistics 2010. Bureau of Statistics, Suva, Fiji.
Burns, A., R. Gleadow, J. Cliff, A. Zacarias and T. Cavagnaro, 2010. Cassava: The
drought, war and femine crop in the changing world. Sustainability 2: 3572-3607.
Butkus, A. and S. Pukalskas, 2004. The research into the influence of ecological
petrol additives in the automobile laboratory. Transport X1X (1): 24-27.
Campbell, M. K. and S. O. Farrell, 2009. Biochemistry, 6th Ed. Brooks/Cole Cengage
Learning. Kentucky, USA.
Carter, S., 2003. Engine Efficiency: Good or Bad? Available < http://ffden-
2.phys.uaf.edu/212_fall2003.web.dir/Sarah_Carter/index.html> (date accessed 12th
December, 2012).
Ceballos, H., C. A. Iglesias, J. C. Pèrez, and A. G. O. Dixon, 2004. Cassava breeding
opportunities and challenges. Plant Molecular Biology 56: 503-516.
Celik, M. B., 2008. Experimental determination of suitable ethanol-gasoline blend
rate at high compression ratio for gasoline engine. Applied Thermal Engineering 28:
396-404.
References
109
Chandel, A. K., E. S. Chan, R. Rudravaram, M. L. Narasu, L. V. Rao, and P.
Ravindra, 2007. Economics and environmental impact of bioethanol production
technologies: An appraisal. Biotechnology and Molecular Biology 2 (1): 14-32.
Cheung, C. S., Y. Di and Z. Huang, 2008. Experimental investigation of regulated and
unregulated emissions from a diesel engine fueled with ultralow-sulphur diesel fuel
blended with ethanol and dodecanol. Atmospheric Environment 42: 8843-8851.
Cloin, J., A. Woodruff and D. Furstenwerth, 2007. Liquid Biofuels in Pacific Island
Countries. SOPAC Miscellaneous Report 628.
Colitt, R. and S. Nielsen, 2012. Brazil Ethanol Drive Falters on Domestic Supply
Shortage. Bloomberg Businessweek, 13 March 2012. Available
<http://www.businessweek.com/news/2012-03-13/brazil-ethanol-slows> (date
accessed: 16th December, 2012).
Cock, J., 1985. Cassava- New Potential for a Neglected Crop. Westview Press.
Boulder, Colorado, USA.
Cock, J. H., 1982. Cassava: A Basic Energy Source in the Tropics. Science 218: 755-
762.
Coelho, S. T., J. Goldemberg, O. Lucon and P. Guardabassi, 2005. Brazilian
sugarcane ethanol: lessons learned. Paper prepared for STAP workshop on Liquid
Biofuels, Delhi, 29th August to 2nd September, 2005.
Curtis, S., M. Owen, T. Hess and S. Egan, 2008. Effect of Ethanol Blends on a Spark
Ignition, 4-Stroke, Internal Combustion Engine. Brigham Young University Provo,
Utah. Available online <http://www.et.byu.edu/~curtis5/Ethanol%20Paper.pdf> (date
accessed: 16th August, 2011).
Defloor, I., R. Swennen, M. Bokanga and J. A. Delcour, 1998. Moisture stress during
growth affects the breadmaking and gelatinization properties of cassava (Manihot
esculenta Crantz) flour. Journal of the Science of Food and Agriculture 76: 233-238.
References
110
De Taful, S. M., M. A. El-Sharkawy and F. Calle, 1997. Photosynthesis and yield
performance of cassava in seasonally dry and semiarid environments. Photosynthetica
33: 229-257.
Dubey, R. C., 2001. Textbook of Biotechnology, 1st Ed. S. Chand and Company
Limited, New Delhi, India.
Duncan, J., 2002. Blending ethanol into petrol: An Overview. Report Prepared for
Energy Efficiency and Conservation Authority, Wellington, New Zealand.
Eksteen, J. M., P. van Rensburg, R. R. Cordero Otero, I. S. Pretorius, 2003. Starch
fermentation by recombinant Saccharomyces cerevisiae strains expressing the α-
amylase and glucoamylase from Lipomyces kononenkoae and Saccharomycopsis
fibruligera. Biotechnology and Bioengineering 84: 639-646.
El-Sharkawy, M. A., 2004. Cassava biology and physiology. Plant Molecular Biology
56: 481-501.
Environment Australia, 2002. Setting the Limit of Ethanol in Petrol. Available online
<http://www.environment.gov.au/atmosphere/fuelquality/publications/ethanol-
limit/index.html> (date accessed 25th January 2010).
Ethanol in Petrol. Available online <http://www.raa.com.au/page.asp?TerID=146>
(date accessed: 14th November, 2010).
Ferfecki, F. J. and S. C. Sorenson, 1983. Performance of ethanol blends in gasoline
engines. American Society of Agricultural Engineers 26 (1): 0038-0043.
Ferguson, C. R. and A. T. Kirkpatrick, 2001. Internal Combusion Engines Applied
Thermosciences, 2nd Ed. John Wiley and Sons New Jersey, USA.
Fuel Phase Separation in Ethanol Blended Gasoline? Available online
<http://www.enertechlabs.com/fuel_phase_separation_in_ethanol.php> (date
accessed: 2nd January, 2010).
References
111
Gibbons, W. R., C. A. Westby, and T. L. Dobbs, 1986. Intermediate scale,
semicontinuous solid phase fermentation process for production of fuel ethanol from
Sweet Sorghum. Applied Environment Microbiology 51 (1): 115-122.
Grace, M. R., 1977. Cassava production. Food and Agriculture Organization, United
Nations, Rome, Italy.
Gravalos, I., D. Moshou, T. Gialamas, P. Xyradakis, K. Kateris, and Z. Tsiropoulos,
2011. Performance and emission characteristics of spark ignition engine fuelled with
ethanol and methanol gasoline blended fuels. In: Manzanera, M. (Ed.) Alternative
Fuel, ISBN: 978-953-307-372-9, InTech. Available online
<http://www.intechopen.com/articles/show/title/performance-and-emission
characteristics-of-spark-ignition-engine-fuelled-with-ethanol-and-methanol> (date
accessed 2nd February, 2012).
Guibet, J. C., 1999. Fuels and Engines: Technology, Energy, Environment, Vol. 2.
Enfield Pub & Distribution Co, New Hampshire, USA.
He, B-H., S-J. Shuai, J-X. Wang and H. He, 2003. The effect of ethanol blended
diesel fuels on emissions from a diesel engine. Atmospheric Environment 37: 4965-
4971.
Hofstrand, D., 2009. Brazil’s Ethanol Industry. AgDM Newsletter, January, 2009.
Hsieh, W-D., R-H Chen, T-L Wu, and T-H Lin, 2002. Engine performance and
pollutant emission of an SI engine using ethanol–gasoline blended fuels. Atmospheric
Environment 36: 403–410.
ICS-Nigeria, n. d. Growing Cassava in Nigeria. Available
<http://www.cassavabiz.org/agroenterprise/ent%20images/cassava_02.pdf> (date
accessed 10th December, 2012).
IEA, 2004. Biofuels for transport: an international perspective. International Energy
Agency, Paris, France.
References
112
IEA, 2011. Technology Roadmap:Biofuels for transport. International Energy
Agency, Paris, France.
Iglesias, C., C. Hershey, F. Calle, and A. Bolaños, 1994. Propagating cassava
(Manihot esculenta) by sexual seed. Experimental Agriculture 30: 283-290.
International Starch Institute, 1999 (a). Determination of ash in Starch at 900 ˚C: ISI
02-1e. Available online <http://www.starch.dk/isi/methods/02ash.htm> (date
accesses: 13th May, 2009).
International Starch Institute, 1999 (b). Determination of pH in Starch and Syrup: ISI
26-5e. Available online <http://www.starch.dk/isi/methods/26ph.htm> (date accessed:
13th May 2009).
Jamai, L., K. Ettayebi, J. E. Yamani, and M. Ettayebi, 2007. Production of ethanol
from starch by free and immobilized Candida tropicalis in presence of α-amylase.
Bioresource Technology 98: 2765-2770.
Jamai, L., K. Sendide, K. Ettayebi, F. Errachidi, O. Hamdouni-Alami, M. A. Tahri-
Jouti, T. McDermont and M. Ettayebi, 2001. Physiological difference during ethanol
fermentation between calcium alginate-immobilized Candida tropicalis and
Saccharomyces cerevisiae. FEMS Microbiology Letters 204: 375-379.
Jewett, S., 2004. Physics for Scientists and Engineers with Modern Physics, 6th
Edition. Brooks/Cole-Thomson Learning, Califonia, USA. Jones, W. O., 1959.
Manioc in Africa. Stanford University Press, California, USA.
Joseph H., 2007. The vehicle adaptation to ethanol fuel. Presentation to the Royal
Society International Biofuels Meeting held in London, April 2007. Available online
at< www.royalsoc.ac.uk/downloaddoc.asp?id=4248> (date accessed: 13th May 2012).
Karaosmanoglu, F., A. Isigigur and H. A. Aksoy, 1992. The effects of methanol-
gasoline blends on exhaust emissions. Presentation at the International Conference
References
113
Next Generation Technologies for Efficient Energy, End Uses and Fuel Switching.
Dortmund, Germany.
Kargi, F., J. A. Curme and J. Sheehan, 1985. Solid state fermentation of sweet
sorghum to ethanol. Biotechnology Bioengineering 27 (1): 34-40.
Kawano, K. 2003. Thirty years of cassava breeding for productivity-biological and
social factors for success. Crop Science 43: 1325-1335.
Kawano, K., P. Daza, A. Amaya, M. Rios and W. M. F. Goncalves, 1978. Evaluation
of cassava germplasm for productivity. Crop Science 18: 377-380.
Kearsley, M. W. and S. Z. Dziedzic (Eds.), 1995. Handbook of starch hydrolysis
products and their derivatives. Blackie Academic & Professional, New York, USA.
Keating, B. A., G. L. Wilson and J. P. Evenson, 1988. Effects of length, thickness,
orientation and planting density of cassava (Manihot esculenta Crantz) planting
material on subsequent establishment, growth and yield. East African Agricultural
and Forestry Journal 53: 145-149.
Koç, M., Y. Sekme, T. Topgül and H. S. Yücesu, 2009. The effects of ethanol–
unleaded gasoline blends on engine performance and exhaust emissions in a spark-
ignition engine. Renewable Energy 34: 2101-2106.
Lancaster, P. A. and J. E. Brooks, 1983. Cassava leaves as human food. Economic
Botany 37: 331-348.
Lee, C. G., C. H. Kim and S. K. Rhee, 1992. A kinetic model and simulation of starch
saccharification and simultaneous ethanol fermentation by amyloglucosidase and
Zymomonas mobilis. Bioprocess Engineering 7: 335-341.
Li, S-Z and C. C. Halbrendt, 2009. Ethanol production in (the) People’s Republic of
China: Potential and technologies. Applied Energy 86: S162–S169.
References
114
Lin, W., Y. Chang and Y. Hsieh, 2010. Effect of ethanol-gasoline blends on small
engine generator energy efficiency and exhaust emission. Journal of Air and Waste
Management Association 60: 142-148.
Liu, S-Y. and C-L. Liang, 1983. Studies on the efficiency of alcohol production in
sweet potato, cassava and potato. Journal of Agricultural Resources China 32 (2):
111-121.
Lonsane, B. K. and M. M. Krishnaiah, 1994. Solid state fermentation foods of Indian
origin. In: Pandey, A. (Ed.) Solid-state fermentation: An overview, Wiley Eastern
Publishers, New Delhi, India.
Mason, R. R., 1956. Cassava varieties in Fiji. Fiji Agricultural Journal 27 (3/4): 88-
93.
Miller, G. L., 1959. Use of Dinitrosalicylic Acid Reagent for determination of
reducing sugar. Analytical Chemistry 31 (3): 426-428.
Montesinos, T. and J. Navarro, 2000. Production of alcohol from raw wheat flour by
amyloglucosidase and Saccharomyces cerevisiae. Enzyme and Microbial Technology
27 (6): 362-370.
Moorthy, S., 2001. Tuber crop starches. Technical Bulletin No. 18, Central Tuber
Crops Research Institute, Kerala, India.
Moorthy, S. N. and T. Ramanujam, 1986. Variation in properties of starch in cassava
varieties in relation to age of the crop. Starch/Starke 38: 8-61.
Nakamura, Y., F. Kobayashi, M. Ohnaga and T. Swada, 1997. Alcoholic fermentation
of starch by a genetic recombinant yeast having glucoamylase activity. Biotechnology
Bioengineering 53: 21-25.
Nakavulevu, P, 2011. Promoting Renewable Energy Policies in Fiji. Presentation at
workshop organized by IRENA “Accelerated Renewable Energy Deployment on
References
115
Islands with Emphasis on Pacific Islands”, 26-28th October, Sydney, Australia.
Nanda, S. K., C. Balagopalan, G. Padmaja, S. N. Moorthy and M. S. Sanjeev, n. d.
Post-Harvest Management of Cassava for Industrial Utilization in India, Central
Tuber Crops Research Institute (CTCRI), India. Available online
<http://webapp.ciat.cgiar.org/> (date accessed 8th January 2010).
National Starch and Chemical Company, 2002. 100 Years of Food Starch History.
Available online <http://www.foodstarch.com/about/abo_fhistory.asp> (date accessed
2nd September, 2009).
Ngendahayo, M. and A. G. O. Dixon, 2001. Effect of harvest on tuber yield, dry
matter, starch and harvest index of cassava in two ecological zones in Nigeria. In:
Akoroda, M. O., and J. M. Ngeve (Eds.) Root Crops in the Twenty-first Century,
Proceedings of the seventh Triannual Symposium of the International society for
Tropical Root Crops- Africa Branch (ISTRC-AB), Centre International des
Conférences, Cotonou, Benin.
Nigam, P., I. M. Banat, D. Singh, A. P. McHale and R. Marchant, 1998. Continuous
ethanol production by thermotolerant Kluyveromyces marxianus IMB3 immobilized
on mineral kissiris at 45 ºC. World Journal of Microbiology Biotechnology 13: 283-
288.
Nuwamanya, E., Y. Baguma, R. S. Kawuki and P. R. Rubaihayo, 2008.
Quantification of starch physicochemical characteristics in a cassava segregating
population. African Crop Science Journal 16: 191-202.
OECD, 2011. Brazil’s biofuel sector: What future? OECD Observer, No. 287.
Available
<http://www.oecdobserver.org/m/fullstory.php/aid/3748/Brazil_92s_biofuel_sector:_
What_future_.html> (date accessed 13th December, 2012).
References
116
Ocloo, F. C. K. and G. S. Ayernor, 2008. Physical, chemical and microbiological
changes in alcoholic fermentation of sugar syrup from cassava flour. African Journal
of Biotechnology 7 (2): 164-168.
O’Hair, S. K., 1990. Tropical Root and Tuber Crops. In: Janick, J. (Ed.) Horticultural
Reviews, Vol. 12. Timber Press, Oregon, USA.
O’Hair, S. K., J. M. Dangler, P. H. Everett, R. B. Forbes, L. H. Halsey, S. J. Locascio,
H. Y. Ozaki, J. R. Rich, R. L. Stanley, H. J. Trafford and J. M. White, 1981. Location,
growing season and soil type effects on Florida cassava yields. HortScience 16: 262-
267.
Pandey, A., 1994. Solid-state fermentation: An overview. Wiley Eastern Publishers,
New Delhi, India.
Pazur, J. H. and T. Ando, 1960. The hydrolysis of glucosyl oligosaccharides with α-
D-(1→4) and α-D-(1→6) bonds by fungal amyloglucosidase. Journal of Biological
Chemistry 235: 297-302.Pellet, D. M. and M. A. El-Sharkawy, 1997. Cassava varietal
response to fertilization: growth dynamics and implications for cropping
sustainability. Experimental Agriculture 33: 353-365.
Pèrez J. C., N. Morante, J. López, J. I. Lenis, G. Jaramillo, H. Ceballos, F. Calle,
2002. Advantages of the New Cassava breeding scheme at CIAT. In: Taylor N. J., F.
Ogbe, C. M. Fauquet (Eds.) Cassava, an ancient crop for modern times food, health,
culture. A paper presented at 5th international scientific meeting of the cassava
biotechnology network, Danforth Plant Science Center St. Louis, Missouri, USA.
Phakatkar, H. G., 2005. Theory of Machines and Mechanisms-II, 4th Ed. Nirali
Prakashan, Pune, India.
Pikūnas, A., S. Pukalskas and J. Grabys, 2003. Influence of composition of gasoline
ethanol blends on parameter of internal combustion engines. Journal of Kones
Internal Combustion Engines 10: 205-211.
References
117
Puhan, S. and G. Nagarajan, 2008. NOx reduction in a DI diesel engine using
biodiesel as a renewable fuel. International Journal of Sustainable Energy 27 (3):
143-154.Rao, P. J. M., 1997. Industrial utilization of sugarcane and its co-product,
Indian Commission of Sugar Industry Development, ISPCK Publishers, New Delhi,
India.
REN21, 2012. Renewables 2012 Global Status Report, REN21 Secretariat, Paris,
France.
Rodriguez-Sosa, E. J., O. Parsi-Ros and M. A. Gonzalez, 1976. Composition of
cassava (Manihot esculenta Crantz) and the rheological characteristics of its starch.
Journal of Agriculture of the University of Puerto Rico 61: 32-40.
Rogers, D. J. and S. G. Appan, 1970. Untapped genetic resources for cassava
improvement. In Proceedings of the 2nd International Symposium on Tropical Root
and Tuber Crops, University Hawaii Press, Honolulu. Hawaii.
Rogers, D. J. and S. G. Appan, 1973. Manihot and Manihotoides (Euphorbiaceae), a
computer assisted study. In: Rogerson, C. T. (Ed.) Flora Neotropica, Monograph 13.
Hafner Press, New York, USA.
Ryu, B. H., K. D. Nam, H. S. Kim, D. S. Kim, Y. A. Ji and S. J. Jung, 1988.
Screening of thermotolerant yeast strain for ethanol production. Korean Journal of
Applied Microbiology Bioengineering 16. 265-269.
Saiyasitpanich, P., T. C. Keener, S-J. Khang, M. Lu, F. Linag, 2005. The effect of
diesel fuel sulfur content on particulate matter emissions for a nonroad diesel
generator. Journal of Air & Waste Management. Association 55: 993-998.
Santisopasri, V., K. Kurotjanawong, S. Chotineeranat, K. Piyachomkwan, K. Sriroth
and C. G. Oates, 2001. Impact of water stress on yield and quality of cassava starch.
Industrial Crops and Products 13 (2): 115-129.
References
118
Shigechi, H., K. Uyama, Y. Fujita, T. Matsumoto, M. Ueda, A. Tanaka, H. Fukuda,
A. Kondo, 2002. Efficient ethanol production from starch through development of
novel flocculent yeast strains displaying glucoamylase and co-displaying or secreting
α-amylase. Journal of Molecular Catalysis B: Enzymatic 17: 179-187.
Silvestre, P., 1989. Cassava. The Tropical Agricultural Series. Macmillan with the
Technical Centre for Agriculture and Rural Cooperation (CTA), London, England.
Singh, A., 2012. Biofuels and Fiji’s roadmap to energy self-sufficiency. Biofuels 3:
269-284.
Singh, P. J., 2009. Preparation, characterisation and engine performance of coconut
oil based hybrid fuels. MSc thesis, School of Engineering and Physics, The University
of the South Pacific, Suva, Fiji.
SOPAC, 2009. Potential for liquid Biofuels in Fiji. SOPAC Miscellaneous Report
677.
Sorapipatana, C. and S. Yoosin, 2011. Life cycle cost of ethanol production from
cassava in Thailand. Renewable and Sustainable Energy Reviews 15: 1343–1349.
Sree, N. K., M. Sridhar, K. Suresh and L. V. Rao, 1999. High alcohol production by
solid substrate fermentation from starchy substrates using thermotolerant
Saccharomyces cerevisiae. Bioprocess Engineering 20: 561-563.
Srinivas, T. and M. Anantharuman, 2000. Status of cassava production, processing
and marketing in Andra Pradesh. Central Tuber Crops Research Institute, Kerada,
India.
Sriroth, K., B. Lamchaiyaphum, K. Piyachomkwan, 2006. Present situation and
future potential of cassava in Thailand. Cassava and Starch Technology Research
Unit, Available online <www.cassava.org/doc/presentsituation2.pdf> (date accessed
8th January 2011).
References
119
Sriroth, K., K. Piyachomkwan, V. Santisopasri and C. G. Oates, 2001. Environmental
conditions during root development: Drought constraint on cassava starch quality.
Euphytica 120: 95-101.
Sriroth, K., V. Santisopasri, C. Petchalnuwat, K. Kurotjanawong, K. Piyachomkwan
and C. G. Oates, 1999. Cassava Starch granule structure-function properties: influence
of time and conditions at harvest on four cultivars of cassava starch. Carbohydrate
Polymers 38: 161-170.
Stephenson, G., 1973. Small Gasoline Engines. Delmar Publishers, New York, USA.
Stone, R., 1999. Introduction to Internal Combustion Engines, 3rd Ed. Palgrave, New
York, USA.
Thomas, D. J. and W. A. Atwell, 1999. Starches: Practical guides for the food
industry, Eagan Press, Minnesota, USA.
The Royal Society, 2008. Sustainable Biofuels: Prospects and Challenges. Policy
document 01/08. Available online <royalsociety.org> (date accessed: 9th July, 2012).
Topgül, T., H. S. Yücesu, C. Çinar and A. Koca, 2006. The effects of ethanol-gasoline
blends and ignition timing on engine performance and exhaust emissions. Renewable
Energy 31: 2534-2542.
Ülgen, K. Ö., B. Saygili, Z. Önsan and B. Kirdar, 2002. Bioconversion of starch into
ethanol by a recombinant Saccharomyces cerevisiae strain YPG-AB. Process
Biochemistry 37: 1157-1168.
Van Oirschot, Q. E. A., G. M. O’Brian, D. Dufour, M. A. El-Sharkawy and E. Mesa,
2000. The effect of pre-harvest pruning of cassava upon root deterioration and quality
characteristics. Journal of the Science of Food and Agriculture 80: 1866-1873.
References
120
Verma, G., P. Nigam, D. Singh and K. Chaudhary, 2000. Bioconversion of starch to
ethanol in a single-step process by coculture of amylolytic yeasts and Saccharomyces
cerevisiae 21. Bioresource Technology 72: 261-266.
Wallin, M., R. Westerholm, K. E. Egebäck, B. Rehnlund and M. Henke, 2005.
Blending of ethanol in gasoline for spark ignition engines-Problem Inventory and
Evaporative Measurements. Report No. MTC 5407, AVL MTC Tech Centre,
Haninge, Sweden.
Wang, N. S., nd. Starch Hydrolysis by Amylase. Available online
<http://www.eng.umd.edu/~nsw/ench485/lab5.htm> (date accessed: 2nd October,
2010).
Wang, W., 2002. Cassava production for industrial utilization in China-Present and
future perspectives. In: Howeler, R. H. (Ed.) Cassava Research and Development in
Asia: Exploring new opportunities for an ancient crop, Proceedings of Seventh
Regional Workshop held in Bangkok, Thailand, 28th October-1st November, 2002.
Wholey, D. W. and R. H. Booth, 1979. Influence of variety and planting density of
starch accumulation in cassava roots. Journal of the Science of Food and Agriculture
30: 165-170.
Willett, J. and M. Doane, 2002. Effect of moisture content on tensile properties of
starch/poly(hydroxyester ether) composite materials. Polymer 43: 4413-4420.
World Watch Institute (WWI), 2007. Biofuels for transportation: Global potential
and implications for sustainable agriculture and energy in the 21st century. Available
online <www.worldwatch.org/node/4078> (date accesses 26th November, 2011).
Wu, C-W., R-H. Chen, J-Y. Pu and T-H. Lin, 2004. The influence of air-fuel ratio on
engine performance and pollutant emission of an SI engine using ethanol-gasoline-
blended fuels. Atmospheric Environment 38: 7093-7100.
References
121
Yücesu, H. S., T. Topgül, C. Çinar and M. Okur, 2006. Effects of ethanol-gasoline
blends on engine performance and exhaust emissions in different compression ratios.
Applied Thermal Engineering 26: 2272-2278.
Yüksel, F. and B. Yüksel, 2004. The use of ethanol-gasoline blends as a fuel in an SI
engine. Renewable. Energy 29: 1181-1191.
Zervas, E. and M. Tazerout, 2000. Organic acids emissions from natural-gas-fed
engines. Atmospheric Environment 34: 3921-3929.
Zervas, E., X. Montagne and J. Lahaye, 2003. Emissions of regulated pollutants from
a spark ignition engine. Influence of fuel and air/fuel equivalence ratio.
Environmental science technology 37: 3232-3238.
2005. The Internal Combustion Engine. Available online <http://www.hybrid-
vehicle.org/hybrid-vehicle-ice.html> (date accessed 8th April, 2012)
<http://www.enertechlabs.com/fuel_phase_separation_in_ethanol.php> (date accessed
16th November, 2011)
<http://www.hybrid-vehicle.org date accessed> (date accessed 6th June, 2011)
122
Appendix A Engine Efficiency Data
Table A: Engine Efficiency Data for Petrol, E10, E15 and E20
Fuel
Sample
Power
Output
(W)
Vol. Fuel
Used (ml)
Time
(s)
Calorific
Value
(kJ ml-1)
Power
Input
(W)
Overall
Efficiency
(%)
Engine
Efficiency
(%)
Petrol
0.0 120.0 905.0 33.6 4457.9 0.0 0.0
365.5 120.0 682.5 5911.2 6.2 8.7
714.0 120.0 551.5 7315.3 9.8 13.7
1217.5 120.0 449.0 8985.3 13.5 19.0
1567.0 120.0 401.0 10060.8 15.6 21.8
1863.5 120.0 364.0 11083.5 16.8 23.5
E10
0.0 120.0 845.5 32.3 4582.9 0.0 0.0
365.5 120.0 709.0 5465.2 6.7 9.4
714.0 120.0 568.5 6815.8 10.5 14.7
1217.5 120.0 462.5 8377.9 14.5 20.3
1567.0 120.0 427.5 9063.9 17.3 24.2
1863.5 120.0 392.0 9884.7 18.9 26.4
E15
0.0 120.0 832.5 31.2 4493.0 0.0 0.0
365.5 120.0 687.5 5440.6 6.7 9.4
714.0 120.0 547.0 6838.0 10.4 14.6
1217.5 120.0 431.0 8678.4 14.0 19.6
1567.0 120.0 406.0 9212.8 17.0 23.8
1863.5 120.0 376.5 9934.7 18.8 26.3
E20
0.0 120.0 806.0 30.8 4578.2 0.0 0.0
365.5 120.0 665.5 5544.7 6.6 9.2
714.0 120.0 534.0 6910.1 10.3 14.5
1217.5 120.0 415.5 8880.9 13.7 19.2
1567.0 120.0 382.0 9659.7 16.2 22.7
1863.5 120.0 357.0 10336.1 18.0 25.2
123
Appendix B Fuel and Specific Fuel Consumption Data
Table B: Fuel Consumption and Specific Fuel Consumption Data for Petrol, E10,
E15, E20
Fuel
Sample
Power
Output
(kW)
Vol.
Fuel
Used
(ml)
Fuel
Consumption
(L hr-1)
Density
(g cm-3)
Time
(hr)
Mass of
fuel
consumed
(kg)
Fuel rate
(kg hr-1)
Specific fuel
consumption
(kg kW-1 hr-1)
Petrol 0 120 0.477 0.741 0.251 0.089 0.354
0.371 120 0.633 0.190 0.089 0.469 1.264
0.723 120 0.783 0.153 0.089 0.580 0.803
1.232 120 0.962 0.125 0.089 0.713 0.579
1.593 120 1.077 0.111 0.089 0.798 0.501
1.904 120 1.187 0.101 0.089 0.879 0.462
E10 0 120 0.511 0.746 0.235 0.090 0.381
0.366 120 0.609 0.197 0.090 0.455 1.242
0.714 120 0.760 0.158 0.090 0.567 0.794
1.222 120 0.934 0.128 0.090 0.697 0.570
1.576 120 1.011 0.119 0.090 0.754 0.478
1.859 120 1.111 0.108 0.090 0.828 0.446
E15 0 120 0.519 0.749 0.231 0.090 0.389
0.363 120 0.628 0.191 0.090 0.471 1.297
0.709 120 0.790 0.152 0.090 0.592 0.834
1.209 120 1.002 0.120 0.090 0.751 0.621
1.55 120 1.064 0.113 0.090 0.797 0.514
1.85 120 1.147 0.105 0.090 0.859 0.465
E20
0 120 0.536 0.752 0.224 0.090 0.403
0.362 120 0.649 0.185 0.090 0.488 1.348
0.71 120 0.809 0.148 0.090 0.608 0.857
1.207 120 1.040 0.115 0.090 0.782 0.648
1.549 120 1.131 0.106 0.090 0.850 0.549
1.841 120 1.210 0.099 0.090 0.910 0.494
124
Appendix C Emission Data
Table C: Emission Data for Petrol, E10, E15, E20
Fuel Sample Load (W) CO (% vol) HC (ppm) CO2 (% vol)
Petrol
0 2.97 70.67 3.7
365.5 2.65 66 3.85
714 2.56 64 4.06
1217.5 2.4 62.67 4.86
1567 2.35 60.67 5.71
1863.5 2.1 58 6.88
E10
0 2.19 43.33 3.31
365.5 2.09 51 3.58
714 1.98 60 3.73
1217.5 1.82 56 4.56
1567 1.78 54 5.32
1863.5 1.38 52 6.39
E15
0 1.63 34 3.16
365.5 1.32 38.67 3.55
714 1.29 43.33 3.64
1217.5 1.2 42.67 4.45
1567 1.06 42.67 5.05
1863.5 0.82 40.67 5.72
E20
0 1.29 23.33 3
365.5 1.16 28 3.47
714 1.03 40.67 3.61
1217.5 1.02 40.67 4.28
1567 0.74 40.67 4.85
1863.5 0.47 38 5.53
125
Appendix D
One paper has been presented in conjunction with the above work at the International
Conference on Technology Transfer and Renewable Energy, which was held on 21st
to 22nd June, 2012 in Mauritius. The proceedings will be published in a book
“Technological Approaches in Renewable Energy- An Overview in Small Island
States and Beyond”.
� Bijay, P. and Singh, A. 2012. Viability of using cassava as feedstock for
bioethanol production in Fiji. In: Technological Approaches in Renewable
Energy- An Overview in Small Island States and Beyond, Proceedings of the
International Conference on Technology Transfer and Renewable Energy,
Mauritius, 21st-22nd June, 2012. (Accepted for Publication).
Abstract: Ethanol production from renewable resources has received attention
due to increasing petroleum shortage. One such renewable resource that has
been identified is cassava starch. Cassava starch is extracted from root crop,
cassava (Manihot esculenta (Crantz)) and is readily available in Fiji. Many
countries such as China, Thailand and Philippines are already having success
in producing high starch yielding cassava varieties that can be used for ethanol
production.
The current paper investigates the viability of producing ethanol from locally
available cassava varieties in Fiji. Starch was extracted from the roots of ten
different cassava varieties available at two different research stations in Fiji.
The sedimentation technique was used to extract starch from cassava roots and
some properties of the extracted starch were also determined. In the case of
Koronivia Research Station (KRS) the variety Nadelei had the highest starch
yield (23.1 %) whereas Coci had the highest starch yield (23.3 %) for
Dobuilevu Research Station (DRS). The paper discusses and compares starch
yield obtained from Fiji cassava varieties with some other countries and make
recommendations on how starch yield from Fiji cassava varieties can be
increased.
Appendix D
126
Finally, the paper provides recommendations on enhancing the viability of
cassava as a source for bioethanol production in Fiji. It also assesses the
resources available in Fiji currently to make cassava bioethanol in Fiji a viable
proposition.
Top Related