35


Biodiesel from moringa stenopetala seed oil

G. Y. Shage1* and A. Y. Ali2

1Forest Products Innovation Center, Ethiopian Forest Development, P.O. BOX: 2322, Addis Ababa, Ethiopia
2Process Engineering division, School of Chemical and Bioengineering, Addis Ababa institute of Technology, Addis Ababa 
University, P.O. BOX: 385, Addis Ababa, Ethiopia

Abstract

The aim of this paper is the production and characterization of biodiesel from Moringa stenopetala 
seed oil. Biodiesel is a renewable, biodegradable, and nontoxic biofuel. Moringa stenopetala seed 
oil is a potential feedstock that has not been discovered as an energy source. This study investigated 
the effects of process parameters: methanol to oil ratio, reaction temperature, and catalyst loading on 
the yield and quality of biodiesel. The experimental results showed that the maximum biodiesel yield 
was 94% and it was obtained at optimum process conditions: temperature 55°C, methanol to oil ratio 
6:1, and catalyst loading1.0. Biodiesel product was characterized based on international standards 
for testing fuels. According to the findings of the study, moringa stenopetala seed oil biodiesel has a 
specific gravity of 0.874 g/mole, a kinematic viscosity of 4.8 mm2/s, an acid value of  0.4 mg KOH/g, 
a saponification value of 196 mg KOH/g,  FFA 0.2%, iodine value 104.5 high heating value 10,287 
cal/g,  flash Point 184°C,  pour point 1°C, cloud point 10°C and cetane number 53. These results 
satisfy international standards for biodiesel.

Keywords: Biodiesel; Biomass; Characterization; Production; Moringa stenopetala

*Corresponding author e-mail: gemechyade@gmail.com

Available online at www.banglajol.info

Bangladesh J. Sci. Ind. Res. 58(1), 35-44, 2023

Introduction

Energy plays a crucial role in the socio-economic development 
of any country. The demand for energy sources has increased 
rapidly with the growing population in the world.  Nowadays, 
the world is highly dependent on non-renewable fuelsas an 
energy source. The current concerns such as high global 
warming, depletion of fossil fuels, and fluctuating price of 
conventional diesel fuels have pushed researchers toward 
finding new alternative, clean, renewable, and sustainable 
energy resourcessuch as solar, hydroelectric, wind, and 
biomass-derived fuels (Kafuku, G. and Mbarawa, 2010). 

Currently, fossil fuel is the dominant source of energy in the 
world though it is not renewable and has a high impact on 
global climate. The rapid increase in global energy demand, 
the depleting petroleum fuels, global climate change, the 
increasing price of fossil fuels, urbanization, and the 

increasing population has driven the search for renewable 
energy sources which are clean, sustainable, and environ-
mentally friendly (Atabani et al. 2013).

Biodiesel is a chain of mono-alkyl esters produced by the 
transesterification of vegetable oil and animal fats (Demsh-
emino et al. 2013). Biodiesel is a promising biofuel that is 
renewable, biodegradable, and non-toxic. Biodiesel is 
gaining importance as one of the most important substitutes 
for depleting fossil fuels. There are many advantages of using 
biodiesel as an alternative form of energy. It can be used as 
such in the diesel engine without any engine modification 
indicating that it has similar physical and chemical properties 
as conventional diesel fuel. The combustion properties of 
biodiesel are also very close to those of petroleum diesel 
(Sreepada and Vijayalaxmi, 2013).

The most common production technology of biodiesel is the 
transesterification process. Transesterification is a chemical 
reaction between one mole of triglyceride with three moles of 
alcohol to produce fatty acid methyl ester and glycerol in the 
presence of a catalyst or without a catalyst. Most transesteri-
fication reactions use ethanol or methanol alcohol. Many 
studies show that methanol is more practically used as 
alcohol than ethanol. Methanol is preferable due to its low 
cost and its physical and chemical advantages. Another 
advantage of using methanol is the ease of separation of 
glycerin which can be achieved by simple decantation 
(Marchetti and Yadessa, 2012).

Various catalysts can be used in the process. However, it was 
confirmed that the transesterification reaction was completed 
very fast when alkali catalysts are used. After the transesterifi-
cation reaction is completed, glycerol, catalyst, alcohol, and 
soap are separated from biodiesel. The factors affecting 
biodiesel yield and fuel quality are alcohol-to-oil ratios, 
temperature, catalyst loading, and reaction time (Raj and Bhan-
dari, 2017). Biodiesel is formed when triglyceride reacts with 
alcohol leaving glycerol as a byproduct as shown in Figure 1.

There are more than 300 vegetable oils identified as potential 
feedstocks for biodiesel production globally. The availability, 
characteristics, and variety of feedstocks make them promis-
ing ingredients for the sustainable production of biodiesel 
(Piyush et al. 2013). Researchers have proposed Moringa 
seed oil as an alternative potential feedstock to produce 
biodiesel. However, there is a research gap that promotes this 
feedstock for industrial processing. Moringa seed has an 
average of 35%-45% oil content with high oleic content of 
greater than 73% based on the type of the tree. Moringa oil 
has many various industrial and homemade benefits. One of 

oil by rotary evaporation at 80°C. Gum and wax were 
removed by a degumming method. Then, biodiesel was 
synthesized by transesterification reaction using a homoge-
nous catalyst (methanol) at different process parameters.

Experimental design

The experimental design used for this study was a Box 
Behnken design standard using design expert 11.0 software. 
The experimental design was done using three variables and 
tree levels for a response surface method. 17 experimental 
runswere selected by design expert 11.0 software using the 
Box Behnken design standard method, with five central 
points per block. The main factors that affect biodiesel 
production by transesterification reaction are reaction time, 
reaction temperature, and alcohol-to-oil ratio (Seema and 
Meena, 2017). As indicated in Table I, the overall production 
of biodiesel was carried out at optimum parameters of 
catalyst load of 0.5 to 1.5 wt.%, reaction temperature of 45 to 
65°C, and methanol to oil ratio of 3 to 9.  

The other parameters, reaction time and mixing intensity 
were kept constant at 1 hour and 500 rpm for all experimental 
runs. A combination of three factors and three levels of 
experimental runs was conducted. There are 17 experimental 
runs determined byBox Behnken’s design arrangement as 
shown in Table II.

Production and purification of the product

The method used to produce biodiesel was a one-steptranses-
terification reaction. Methanol was the alcohol selected for 
the transesterification reaction due to its availability, low 
cost, popularity, and ease of separation (Demirbas, 2005). 
The catalyst selected for this study was the base catalyst 
(KOH) since biodiesel can be produced at low temperatures 
and pressure reactions. Moreover, it is a homogeneous base 
catalyst that results in high conversion, minimum side 
reactions, short reaction time, and high yield (Marchetti and 

Yadessa, 2012). Though it has many advantages, the disad-
vantage of the catalyst used is it cannot be reused.

When the reaction is completed, biodiesel and glycerol were 
separated by a separatory funnel after it settles for 24 hours. 
Then, biodiesel was washed with hot distilled water to 
remove soap, remaining methanol, and wax.

Optimization of the process parameters using the Response 
Surface Method (RSM).

Optimization aims to determine the optimum value of the 
factors that affect the transesterification process to produce 
the maximum possible biodiesel yield at a minimum produc-
tion cost. This is done by minimizing the methanol to oil 
ratio, reaction temperature, and amount of catalyst used as 
indicated in Table III.

Characterization of biodiesel

Characterization of fuel is determining the physical and 
chemical properties (Atabani et al. 2013). The physical and 
chemical properties of biodiesel were determined according 
to the American Society for Testing Materials (ASTM D 
6751) and European standard (EN 14214) methods (Demir-
bas, 2005). Table IV showed the physical and chemical 
properties of biodiesel and the standard methods used to 
determine them.

Statistical analysis of experimental results

Data analysis of the experiment was done by design expert 
11.0 software using Box Behnken design standard. The 
significance of experimental variables was obtained from 
analysis of variance (ANOVA). 

Results and discussions

Yield

The maximum oil yield obtained at optimum conditions of 
temperature 80°C and extraction time 5 hours was 39.86 %. 
This result agreed with the average oil content of Moringa 
stenopetala seed oil which is 35% - 45% (Ayerza, 2012), and 
this result also agreed with the previous reportof 38% which 
was reported by Azad et al. (2015) and by Gemechu (2021).

The maximum yield of biodiesel was 94% and it was 
obtained at optimum process parameters of methanol to oil 
ratio 6:1, temperature 55°C, and catalyst loading 1.0%.  The 
yield of biodiesel obtained agrees with the previous report of 

Azad et al. (2015) which was 91%. The yield increased as 
transesterification parameters increased until the optimum 
value and decreased beyond the optimum value. At the lower 
value of parameters, the yield decreased due to the incom-
plete conversion of reactants to the product. Table V showed 
the yield response of all experimental runs.

Characterization of biodiesel

Physical and chemical properties of biodiesel were evaluated 
using standard methods and the results were compared with 
ASTM and EN standard methods and previous reports.

Density

The value of the density of biodiesel was 874 kg/m3. This 
result is within the standard range of density (860 – 900 
kg/m3) (Demirbas, 2005) and agrees with the previous report 
by Kafuku and Mbarawa (2010) which was 900 kg/m3. 
Higher density increases thesize of fuel droplets and causes 
higher emission of particulate matter and NOx emission ina 
diesel engine while the lower density of fuel expands the 
efficiency of atomization (Choi and Reitz, 1999).

Kinematic viscosity

The experimental result showed that the value of kinematic 
viscosity was 4.8 mm2/s. This result is within the range of the 
ASTM standard value of biodiesel which is 1.6-6 (Eman and 
Cadence, 2013; Demirbas, 2005). Highly viscous fuel is 
difficult to pump and operate in internal combustion engines 
while lower kinematic viscosity of fuels increases wear 
leakage due to insufficient lubrication (Rao, 2011).

Acid value

The value of an acid value obtained was 0.4 mm KOH/g.  
This result agrees with the previous report (Kafuku and 
Mbarawa, 2010), with a value of 1.2 mmKOH/g. Higher 
acid-value fuels need further acid treatment costs and it also 
lowers the quality of the fuels. In this study, the lower acid 
value of biodiesel indicates that it has higher fuel quality.

Calorific value

The experimental result showed that the value of biodiesel 
was 10287 Cal/ g or 43 MJ/kJ. This result agrees with the 
previous report of Mahamudul et al. (2017) which was 39 

MJ/kg, and the previous report of Agarwal and Das (2001) 
which was 43.2 kJ/kg. The result obtained is above the 
standard ASTM value which is 42-42.5 MJ/kg. This result 
indicates the higher fuel quality of biodiesel. The calorific 
value obtained is similar to that of conventional diesel fuels. 
This is the novel result of this study.

Flash point

The flash point obtained from the experimental result was 
184°C. This result agrees with the standard ASTM value of 
biodiesel flash point which is greater than 130°C. From this 
study, the higher flash point of biodiesel indicates that it is 
safer to handle, store and transport the fuel (Jayed et al. 
2011).

Cetane number

The value of the cetane number observed was 53. This result 
agrees with the standard ASTM value of the cetane number 
of biodiesel which is greater than 47 (Demirbas, 2005). Fuels 
with higher cetane number benefit the engine performance 
since the engine starts rapidly and run smoothly without 
causing much noise.

Cloud and Pour point

The experimental result showed that the cloud and pour 
points of biodiesel were 10°C and 1°C respectively. This 
result agrees with the previous report of Kafuku and Mbara-
wa (2010) which was 10°C and 3°C respectively. Cloud and 
pour point of fuel indicates the fuel performance at low ambi-
ent temperature (Agarwal and Das, 2001). Table VI showed 
the result of all main physicochemical properties of biodiesel 
synthesized.

Statistical analysis of experimental results 

Analysis of variance (ANOVA) for the quadratic model

Analysis of variance determines the significance of the 
experimental results using coded variables as indicated in 
Table VII. 

The Model F-value of 380.98 implies the model is signifi-
cant. There is only a 0.01% chance that an F-value this large 
could occur due to noise.

P-values less than 0.0500 indicate model terms are signifi-
cant. In this case, A, B, C, A², B², C² are significant model 
terms. Values greater than 0.1000 indicate the model terms 
are not significant. If there are many insignificant model 
terms (not counting those required to support hierarchy), 
model reduction may improve your model.

The Lack of Fit F-value of 5.69 implies there is a 6.31% 
chance that a Lack of Fit F-value this large could occur due to 
noise. Lack of fit is bad -- we want the model to fit. This 
relatively low probability (<10%) is troubling.

The coefficient estimate represents the expected change in 
response per unit change in factor value when all remaining 
factors are held constant. The intercept in an orthogonal 
design is the overall average response of all the runs. The 
coefficients are adjustments around that average based on the 

factor settings. When the factors are orthogonal the VIFs are 
1; VIFs greater than 1 indicate multi-collinearity, and the 
higher the VIF the more severe the correlation of factors. As 
a rough rule, VIFs less than 10 are tolerable.

The effect of process parameters on the yield of biodiesel

Effect of methanol to oil ratio

Figure. (2) Shows the effect of methanol to oil ratio on 
biodiesel yield at constant temperature and catalyst loading. 
It showed that the yield of biodiesel increases as the metha-
nol-to-oil ratio increases. Increasing the methanol-to-oil ratio 
beyond the optimum value results in excess methanol which 
decreases the yield of biodiesel. The maximum yield of 
biodiesel (94%) was obtained at a methanol-to-oil ratio of 6: 
1. Therefore, this ratio was taken as an optimum value of the 
methanol-to-oil ratio. Decreasing the methanol-to-oil ratio 

below the optimum value (3:1), decreased the conversion 
efficiency of the transesterification reaction and resulted in 
lower biodiesel yield.

Effect of reaction temperature

Figure (3) shows the effect of reaction temperature on the 
yield of biodiesel at a constant methanol-to-oil ratio and 
catalyst loading. The yield of biodiesel highly increased as 

temperature increased from 45°C to 55°C.  Maximum yield 
was obtained at 58°C and the yield started to decrease slight-
ly from 58°C to 65°C due to the vaporization of methanol 
resulting in soap formation. The boiling point of methanol is 
64.7°C. Increasing reaction temperature above this point 
leads to methanol loss by evaporation and decreases the 
conversion efficiency of the reaction. At 45°C, the yield is 
about 75°C.

Effect of catalyst loading

Figure (4) shows the effect of catalyst loading on the yield of 
biodiesel at a constant methanol-to-oil ratio and temperature.  
As the amount of catalyst increased from 0.5% to 1.0%, the 
yield of biodiesel increased from 89% to 94% and the yield 
starts to decrease slightly as the amount of catalyst increased 
from 1.0% to 1.5% due to the formation of soap and emul-
sion. At a lower amount of catalyst (0.5%), the yield of 
biodiesel decreased due to the incomplete conversion of 
triglycerides of oil to fatty acid methyl ester.

Optimization of transesterification process parameters using 
the Response Surface Method (RSM)

The Response Surface Method determined the optimum 
value of process variables that maximize the yield of the 
product and minimize production cost

Table VIII showed that Response Surface Method found 15 
solutions and selected the optimum values to minimize the 
economic cost of Temperature, Methanol, and Catalyst 
required for the reaction and to maximize the yield of 
biodiesel. The optimum yield of biodiesel (83.772%) was 
observed at a temperature of 51.537 and catalyst load of 
0.500 wt.%.

Conclusions

Biodiesel is a promising biofuel that is synthesized by the 
transesterification of vegetable oils and animal fats. In this 
study, biodiesel was synthesized from moringa stenopetala 
seed oil using an alkali catalyst. The effect of methanol to 
oil ratio, reaction temperature, and catalyst weight on the 
yield and quality of biodiesel have been studied. Biodiesel 
produced was characterized according to international fuel 
testing standards methods. The optimization of process 
parameters was carried out using Response Surface 
Method (RSM).

The experimental result showed that the highest yield of 
biodiesel was 94% and this result was obtained at an 
optimum value of temperature 55°C, methanol to oil ratio of 
6:1, and catalyst load of 1.0%. Increasing methanol to oil 
ratio, temperature, and catalyst load up to the optimum point 
increased the yield of biodiesel. However, further increase of 
the parameters above the optimum point decreased the yield 
of biodiesel. The temperature has the highest significant 
effect while the catalyst load has a lower effect. 

Besides to characterization of different basic fuel properties 
of it, biodiesel can be blended with petrol-diesel at different 
percentages and applied in compression ignition engine to 
evaluate the effect of using a blend of biodiesel using differ-

ent parameters such as engine power, brake thermal efficien-
cy, specific fuel consumption, exhaust gas temperature, and 
greenhouse gas temperature and gas emission. However, the 
performance analysis of the blend of biodiesel with petrol 
diesel in a compression ignition engine was not done due to a 
lack of laboratory setup and equipment required to measure 
these parameters. This study did not compare biodiesel with 
diesel fuels used in diesel engines. Moreover, it did not 
characterize the blend of biodiesel with petroleum fuels and 
did not compare biodiesel produced from other feedstocks 
other than moringa stenopetala. Thus, further research should 
be done on these areas. 

Generally, it can be concluded that moringa stenopetala is a 
promising alternative feedstock for biodiesel production for 
the reasons: it does not affect food security, has a good oil 
content, and can be harvested throughout the year.  The 
biodiesel produced meets the standard fuel quality and 
international standard specifications. 

Acknowledgment

The authors are thankful to Addis Ababa institute of Technol-
ogy, Addis Ababa University, Ethiopian Environment and 
Forest Research Institute, College of Natural and Computa-
tional Science, Addis Ababa University, and Ethiopian 
Geological Survey for their technical support.

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DOI: https://doi.org/10.3329/bjsir.v58i1.62772 

Received: 17 November 2022

Revised: 01 January 2023

Accepted: 15 January 2023

its advantages is it is considered a great natural cosmetic 
emollient and has high oxidative stability (Ayerza, 2012).

Moringa plant is a high-value tree of the Moringaceae family. 
It consists of 13 species highly distributed in Africa and Asia 
(Hamza and Azmach, 2017). Moringa is particularly suitable 
for dry regions since it can be grown using rainwater without 
expensive irrigation techniques.  Moringa has been given less 
attention and ignored tree by communities to utilize it in 
different ways (Gemeda and Desta, 2020). Flowering begins 
within the first six months. Moringa stenopetala seed is an 
available and underutilized resource. Ethiopia has a comfort-
able environment for mooring stenopetala plantations. Many 
parts of the country particularly southern parts such as Gamo 
Goffa, Sidama Wolayitta, Konso, and Darashe have planted 
moringa in their garden and farmland (Sreepada and Vijay-
alaxmi, 2013). Thus, this study investigated that moringa 
stenopetala seed oil is a potential industrial feedstock for 
biodiesel production as an alternative energy source.

Materials and methods

The sample of Moringa seed was collected from the Gamo 
Goffa Zone, Arba Minch area of Ethiopia. The seed sample 

was dried and milled to reduce the particle size. Then, 80 g of 
sample was measured and put into the soxhlet apparatus 
thimble. Then, it was placed in a 500 mL capacity soxhlet 
chamber. 400 mL solvent (Hexane) was used for the 
extraction at different temperatures for 3 hrs. to 5 hrs. The 
extraction was conducted at 70°C, 75°C, and 80°C by 
varying extraction time to get the maximum possible oil 
yield.  The soxhlet extraction method was selected since it 
results in high oil yield, is quick, the solvent can be reused, 
and is low cost (Sreepada and Vijayalaxmi, 2013). The 
unwanted substances were removed by evaporation and 
degumming. Evaporation was used to separate hexane from 



Biodiesel from moringa stenopetala seed oil 58(1) 202336

The most common production technology of biodiesel is the 
transesterification process. Transesterification is a chemical 
reaction between one mole of triglyceride with three moles of 
alcohol to produce fatty acid methyl ester and glycerol in the 
presence of a catalyst or without a catalyst. Most transesteri-
fication reactions use ethanol or methanol alcohol. Many 
studies show that methanol is more practically used as 
alcohol than ethanol. Methanol is preferable due to its low 
cost and its physical and chemical advantages. Another 
advantage of using methanol is the ease of separation of 
glycerin which can be achieved by simple decantation 
(Marchetti and Yadessa, 2012).

Various catalysts can be used in the process. However, it was 
confirmed that the transesterification reaction was completed 
very fast when alkali catalysts are used. After the transesterifi-
cation reaction is completed, glycerol, catalyst, alcohol, and 
soap are separated from biodiesel. The factors affecting 
biodiesel yield and fuel quality are alcohol-to-oil ratios, 
temperature, catalyst loading, and reaction time (Raj and Bhan-
dari, 2017). Biodiesel is formed when triglyceride reacts with 
alcohol leaving glycerol as a byproduct as shown in Figure 1.

There are more than 300 vegetable oils identified as potential 
feedstocks for biodiesel production globally. The availability, 
characteristics, and variety of feedstocks make them promis-
ing ingredients for the sustainable production of biodiesel 
(Piyush et al. 2013). Researchers have proposed Moringa 
seed oil as an alternative potential feedstock to produce 
biodiesel. However, there is a research gap that promotes this 
feedstock for industrial processing. Moringa seed has an 
average of 35%-45% oil content with high oleic content of 
greater than 73% based on the type of the tree. Moringa oil 
has many various industrial and homemade benefits. One of 

oil by rotary evaporation at 80°C. Gum and wax were 
removed by a degumming method. Then, biodiesel was 
synthesized by transesterification reaction using a homoge-
nous catalyst (methanol) at different process parameters.

Experimental design

The experimental design used for this study was a Box 
Behnken design standard using design expert 11.0 software. 
The experimental design was done using three variables and 
tree levels for a response surface method. 17 experimental 
runswere selected by design expert 11.0 software using the 
Box Behnken design standard method, with five central 
points per block. The main factors that affect biodiesel 
production by transesterification reaction are reaction time, 
reaction temperature, and alcohol-to-oil ratio (Seema and 
Meena, 2017). As indicated in Table I, the overall production 
of biodiesel was carried out at optimum parameters of 
catalyst load of 0.5 to 1.5 wt.%, reaction temperature of 45 to 
65°C, and methanol to oil ratio of 3 to 9.  

The other parameters, reaction time and mixing intensity 
were kept constant at 1 hour and 500 rpm for all experimental 
runs. A combination of three factors and three levels of 
experimental runs was conducted. There are 17 experimental 
runs determined byBox Behnken’s design arrangement as 
shown in Table II.

Production and purification of the product

The method used to produce biodiesel was a one-steptranses-
terification reaction. Methanol was the alcohol selected for 
the transesterification reaction due to its availability, low 
cost, popularity, and ease of separation (Demirbas, 2005). 
The catalyst selected for this study was the base catalyst 
(KOH) since biodiesel can be produced at low temperatures 
and pressure reactions. Moreover, it is a homogeneous base 
catalyst that results in high conversion, minimum side 
reactions, short reaction time, and high yield (Marchetti and 

Yadessa, 2012). Though it has many advantages, the disad-
vantage of the catalyst used is it cannot be reused.

When the reaction is completed, biodiesel and glycerol were 
separated by a separatory funnel after it settles for 24 hours. 
Then, biodiesel was washed with hot distilled water to 
remove soap, remaining methanol, and wax.

Optimization of the process parameters using the Response 
Surface Method (RSM).

Optimization aims to determine the optimum value of the 
factors that affect the transesterification process to produce 
the maximum possible biodiesel yield at a minimum produc-
tion cost. This is done by minimizing the methanol to oil 
ratio, reaction temperature, and amount of catalyst used as 
indicated in Table III.

Characterization of biodiesel

Characterization of fuel is determining the physical and 
chemical properties (Atabani et al. 2013). The physical and 
chemical properties of biodiesel were determined according 
to the American Society for Testing Materials (ASTM D 
6751) and European standard (EN 14214) methods (Demir-
bas, 2005). Table IV showed the physical and chemical 
properties of biodiesel and the standard methods used to 
determine them.

Statistical analysis of experimental results

Data analysis of the experiment was done by design expert 
11.0 software using Box Behnken design standard. The 
significance of experimental variables was obtained from 
analysis of variance (ANOVA). 

Results and discussions

Yield

The maximum oil yield obtained at optimum conditions of 
temperature 80°C and extraction time 5 hours was 39.86 %. 
This result agreed with the average oil content of Moringa 
stenopetala seed oil which is 35% - 45% (Ayerza, 2012), and 
this result also agreed with the previous reportof 38% which 
was reported by Azad et al. (2015) and by Gemechu (2021).

The maximum yield of biodiesel was 94% and it was 
obtained at optimum process parameters of methanol to oil 
ratio 6:1, temperature 55°C, and catalyst loading 1.0%.  The 
yield of biodiesel obtained agrees with the previous report of 

Azad et al. (2015) which was 91%. The yield increased as 
transesterification parameters increased until the optimum 
value and decreased beyond the optimum value. At the lower 
value of parameters, the yield decreased due to the incom-
plete conversion of reactants to the product. Table V showed 
the yield response of all experimental runs.

Characterization of biodiesel

Physical and chemical properties of biodiesel were evaluated 
using standard methods and the results were compared with 
ASTM and EN standard methods and previous reports.

Density

The value of the density of biodiesel was 874 kg/m3. This 
result is within the standard range of density (860 – 900 
kg/m3) (Demirbas, 2005) and agrees with the previous report 
by Kafuku and Mbarawa (2010) which was 900 kg/m3. 
Higher density increases thesize of fuel droplets and causes 
higher emission of particulate matter and NOx emission ina 
diesel engine while the lower density of fuel expands the 
efficiency of atomization (Choi and Reitz, 1999).

Kinematic viscosity

The experimental result showed that the value of kinematic 
viscosity was 4.8 mm2/s. This result is within the range of the 
ASTM standard value of biodiesel which is 1.6-6 (Eman and 
Cadence, 2013; Demirbas, 2005). Highly viscous fuel is 
difficult to pump and operate in internal combustion engines 
while lower kinematic viscosity of fuels increases wear 
leakage due to insufficient lubrication (Rao, 2011).

Acid value

The value of an acid value obtained was 0.4 mm KOH/g.  
This result agrees with the previous report (Kafuku and 
Mbarawa, 2010), with a value of 1.2 mmKOH/g. Higher 
acid-value fuels need further acid treatment costs and it also 
lowers the quality of the fuels. In this study, the lower acid 
value of biodiesel indicates that it has higher fuel quality.

Calorific value

The experimental result showed that the value of biodiesel 
was 10287 Cal/ g or 43 MJ/kJ. This result agrees with the 
previous report of Mahamudul et al. (2017) which was 39 

MJ/kg, and the previous report of Agarwal and Das (2001) 
which was 43.2 kJ/kg. The result obtained is above the 
standard ASTM value which is 42-42.5 MJ/kg. This result 
indicates the higher fuel quality of biodiesel. The calorific 
value obtained is similar to that of conventional diesel fuels. 
This is the novel result of this study.

Flash point

The flash point obtained from the experimental result was 
184°C. This result agrees with the standard ASTM value of 
biodiesel flash point which is greater than 130°C. From this 
study, the higher flash point of biodiesel indicates that it is 
safer to handle, store and transport the fuel (Jayed et al. 
2011).

Cetane number

The value of the cetane number observed was 53. This result 
agrees with the standard ASTM value of the cetane number 
of biodiesel which is greater than 47 (Demirbas, 2005). Fuels 
with higher cetane number benefit the engine performance 
since the engine starts rapidly and run smoothly without 
causing much noise.

Cloud and Pour point

The experimental result showed that the cloud and pour 
points of biodiesel were 10°C and 1°C respectively. This 
result agrees with the previous report of Kafuku and Mbara-
wa (2010) which was 10°C and 3°C respectively. Cloud and 
pour point of fuel indicates the fuel performance at low ambi-
ent temperature (Agarwal and Das, 2001). Table VI showed 
the result of all main physicochemical properties of biodiesel 
synthesized.

Statistical analysis of experimental results 

Analysis of variance (ANOVA) for the quadratic model

Analysis of variance determines the significance of the 
experimental results using coded variables as indicated in 
Table VII. 

The Model F-value of 380.98 implies the model is signifi-
cant. There is only a 0.01% chance that an F-value this large 
could occur due to noise.

P-values less than 0.0500 indicate model terms are signifi-
cant. In this case, A, B, C, A², B², C² are significant model 
terms. Values greater than 0.1000 indicate the model terms 
are not significant. If there are many insignificant model 
terms (not counting those required to support hierarchy), 
model reduction may improve your model.

The Lack of Fit F-value of 5.69 implies there is a 6.31% 
chance that a Lack of Fit F-value this large could occur due to 
noise. Lack of fit is bad -- we want the model to fit. This 
relatively low probability (<10%) is troubling.

The coefficient estimate represents the expected change in 
response per unit change in factor value when all remaining 
factors are held constant. The intercept in an orthogonal 
design is the overall average response of all the runs. The 
coefficients are adjustments around that average based on the 

factor settings. When the factors are orthogonal the VIFs are 
1; VIFs greater than 1 indicate multi-collinearity, and the 
higher the VIF the more severe the correlation of factors. As 
a rough rule, VIFs less than 10 are tolerable.

The effect of process parameters on the yield of biodiesel

Effect of methanol to oil ratio

Figure. (2) Shows the effect of methanol to oil ratio on 
biodiesel yield at constant temperature and catalyst loading. 
It showed that the yield of biodiesel increases as the metha-
nol-to-oil ratio increases. Increasing the methanol-to-oil ratio 
beyond the optimum value results in excess methanol which 
decreases the yield of biodiesel. The maximum yield of 
biodiesel (94%) was obtained at a methanol-to-oil ratio of 6: 
1. Therefore, this ratio was taken as an optimum value of the 
methanol-to-oil ratio. Decreasing the methanol-to-oil ratio 

below the optimum value (3:1), decreased the conversion 
efficiency of the transesterification reaction and resulted in 
lower biodiesel yield.

Effect of reaction temperature

Figure (3) shows the effect of reaction temperature on the 
yield of biodiesel at a constant methanol-to-oil ratio and 
catalyst loading. The yield of biodiesel highly increased as 

temperature increased from 45°C to 55°C.  Maximum yield 
was obtained at 58°C and the yield started to decrease slight-
ly from 58°C to 65°C due to the vaporization of methanol 
resulting in soap formation. The boiling point of methanol is 
64.7°C. Increasing reaction temperature above this point 
leads to methanol loss by evaporation and decreases the 
conversion efficiency of the reaction. At 45°C, the yield is 
about 75°C.

Effect of catalyst loading

Figure (4) shows the effect of catalyst loading on the yield of 
biodiesel at a constant methanol-to-oil ratio and temperature.  
As the amount of catalyst increased from 0.5% to 1.0%, the 
yield of biodiesel increased from 89% to 94% and the yield 
starts to decrease slightly as the amount of catalyst increased 
from 1.0% to 1.5% due to the formation of soap and emul-
sion. At a lower amount of catalyst (0.5%), the yield of 
biodiesel decreased due to the incomplete conversion of 
triglycerides of oil to fatty acid methyl ester.

Optimization of transesterification process parameters using 
the Response Surface Method (RSM)

The Response Surface Method determined the optimum 
value of process variables that maximize the yield of the 
product and minimize production cost

Table VIII showed that Response Surface Method found 15 
solutions and selected the optimum values to minimize the 
economic cost of Temperature, Methanol, and Catalyst 
required for the reaction and to maximize the yield of 
biodiesel. The optimum yield of biodiesel (83.772%) was 
observed at a temperature of 51.537 and catalyst load of 
0.500 wt.%.

Conclusions

Biodiesel is a promising biofuel that is synthesized by the 
transesterification of vegetable oils and animal fats. In this 
study, biodiesel was synthesized from moringa stenopetala 
seed oil using an alkali catalyst. The effect of methanol to 
oil ratio, reaction temperature, and catalyst weight on the 
yield and quality of biodiesel have been studied. Biodiesel 
produced was characterized according to international fuel 
testing standards methods. The optimization of process 
parameters was carried out using Response Surface 
Method (RSM).

The experimental result showed that the highest yield of 
biodiesel was 94% and this result was obtained at an 
optimum value of temperature 55°C, methanol to oil ratio of 
6:1, and catalyst load of 1.0%. Increasing methanol to oil 
ratio, temperature, and catalyst load up to the optimum point 
increased the yield of biodiesel. However, further increase of 
the parameters above the optimum point decreased the yield 
of biodiesel. The temperature has the highest significant 
effect while the catalyst load has a lower effect. 

Besides to characterization of different basic fuel properties 
of it, biodiesel can be blended with petrol-diesel at different 
percentages and applied in compression ignition engine to 
evaluate the effect of using a blend of biodiesel using differ-

ent parameters such as engine power, brake thermal efficien-
cy, specific fuel consumption, exhaust gas temperature, and 
greenhouse gas temperature and gas emission. However, the 
performance analysis of the blend of biodiesel with petrol 
diesel in a compression ignition engine was not done due to a 
lack of laboratory setup and equipment required to measure 
these parameters. This study did not compare biodiesel with 
diesel fuels used in diesel engines. Moreover, it did not 
characterize the blend of biodiesel with petroleum fuels and 
did not compare biodiesel produced from other feedstocks 
other than moringa stenopetala. Thus, further research should 
be done on these areas. 

Generally, it can be concluded that moringa stenopetala is a 
promising alternative feedstock for biodiesel production for 
the reasons: it does not affect food security, has a good oil 
content, and can be harvested throughout the year.  The 
biodiesel produced meets the standard fuel quality and 
international standard specifications. 

Acknowledgment

The authors are thankful to Addis Ababa institute of Technol-
ogy, Addis Ababa University, Ethiopian Environment and 
Forest Research Institute, College of Natural and Computa-
tional Science, Addis Ababa University, and Ethiopian 
Geological Survey for their technical support.

References

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Biodiesel from Moringa Stenopetala Seed Oil via 
Catalytic Transesterification Process, Thesis work at 
Addis Ababa University Institute of Technology, Addis 
Ababa, Ethiopia.

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trees: from a nutritionaland medicinal point of view in 
tropical regions, Journal of medicinal plants studies 5 
(4): 151-162.

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M and Liaquat AM (2011), Prospects of dedicated 
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its advantages is it is considered a great natural cosmetic 
emollient and has high oxidative stability (Ayerza, 2012).

Moringa plant is a high-value tree of the Moringaceae family. 
It consists of 13 species highly distributed in Africa and Asia 
(Hamza and Azmach, 2017). Moringa is particularly suitable 
for dry regions since it can be grown using rainwater without 
expensive irrigation techniques.  Moringa has been given less 
attention and ignored tree by communities to utilize it in 
different ways (Gemeda and Desta, 2020). Flowering begins 
within the first six months. Moringa stenopetala seed is an 
available and underutilized resource. Ethiopia has a comfort-
able environment for mooring stenopetala plantations. Many 
parts of the country particularly southern parts such as Gamo 
Goffa, Sidama Wolayitta, Konso, and Darashe have planted 
moringa in their garden and farmland (Sreepada and Vijay-
alaxmi, 2013). Thus, this study investigated that moringa 
stenopetala seed oil is a potential industrial feedstock for 
biodiesel production as an alternative energy source.

Materials and methods

The sample of Moringa seed was collected from the Gamo 
Goffa Zone, Arba Minch area of Ethiopia. The seed sample 

was dried and milled to reduce the particle size. Then, 80 g of 
sample was measured and put into the soxhlet apparatus 
thimble. Then, it was placed in a 500 mL capacity soxhlet 
chamber. 400 mL solvent (Hexane) was used for the 
extraction at different temperatures for 3 hrs. to 5 hrs. The 
extraction was conducted at 70°C, 75°C, and 80°C by 
varying extraction time to get the maximum possible oil 
yield.  The soxhlet extraction method was selected since it 
results in high oil yield, is quick, the solvent can be reused, 
and is low cost (Sreepada and Vijayalaxmi, 2013). The 
unwanted substances were removed by evaporation and 
degumming. Evaporation was used to separate hexane from 

Fig. 1. Transesterification reaction

Biodiesel               +           Glycerol  Triglyceride                    +           Alcohol                           



Shage and Ali 37

The most common production technology of biodiesel is the 
transesterification process. Transesterification is a chemical 
reaction between one mole of triglyceride with three moles of 
alcohol to produce fatty acid methyl ester and glycerol in the 
presence of a catalyst or without a catalyst. Most transesteri-
fication reactions use ethanol or methanol alcohol. Many 
studies show that methanol is more practically used as 
alcohol than ethanol. Methanol is preferable due to its low 
cost and its physical and chemical advantages. Another 
advantage of using methanol is the ease of separation of 
glycerin which can be achieved by simple decantation 
(Marchetti and Yadessa, 2012).

Various catalysts can be used in the process. However, it was 
confirmed that the transesterification reaction was completed 
very fast when alkali catalysts are used. After the transesterifi-
cation reaction is completed, glycerol, catalyst, alcohol, and 
soap are separated from biodiesel. The factors affecting 
biodiesel yield and fuel quality are alcohol-to-oil ratios, 
temperature, catalyst loading, and reaction time (Raj and Bhan-
dari, 2017). Biodiesel is formed when triglyceride reacts with 
alcohol leaving glycerol as a byproduct as shown in Figure 1.

There are more than 300 vegetable oils identified as potential 
feedstocks for biodiesel production globally. The availability, 
characteristics, and variety of feedstocks make them promis-
ing ingredients for the sustainable production of biodiesel 
(Piyush et al. 2013). Researchers have proposed Moringa 
seed oil as an alternative potential feedstock to produce 
biodiesel. However, there is a research gap that promotes this 
feedstock for industrial processing. Moringa seed has an 
average of 35%-45% oil content with high oleic content of 
greater than 73% based on the type of the tree. Moringa oil 
has many various industrial and homemade benefits. One of 

oil by rotary evaporation at 80°C. Gum and wax were 
removed by a degumming method. Then, biodiesel was 
synthesized by transesterification reaction using a homoge-
nous catalyst (methanol) at different process parameters.

Experimental design

The experimental design used for this study was a Box 
Behnken design standard using design expert 11.0 software. 
The experimental design was done using three variables and 
tree levels for a response surface method. 17 experimental 
runswere selected by design expert 11.0 software using the 
Box Behnken design standard method, with five central 
points per block. The main factors that affect biodiesel 
production by transesterification reaction are reaction time, 
reaction temperature, and alcohol-to-oil ratio (Seema and 
Meena, 2017). As indicated in Table I, the overall production 
of biodiesel was carried out at optimum parameters of 
catalyst load of 0.5 to 1.5 wt.%, reaction temperature of 45 to 
65°C, and methanol to oil ratio of 3 to 9.  

The other parameters, reaction time and mixing intensity 
were kept constant at 1 hour and 500 rpm for all experimental 
runs. A combination of three factors and three levels of 
experimental runs was conducted. There are 17 experimental 
runs determined byBox Behnken’s design arrangement as 
shown in Table II.

Production and purification of the product

The method used to produce biodiesel was a one-steptranses-
terification reaction. Methanol was the alcohol selected for 
the transesterification reaction due to its availability, low 
cost, popularity, and ease of separation (Demirbas, 2005). 
The catalyst selected for this study was the base catalyst 
(KOH) since biodiesel can be produced at low temperatures 
and pressure reactions. Moreover, it is a homogeneous base 
catalyst that results in high conversion, minimum side 
reactions, short reaction time, and high yield (Marchetti and 

Yadessa, 2012). Though it has many advantages, the disad-
vantage of the catalyst used is it cannot be reused.

When the reaction is completed, biodiesel and glycerol were 
separated by a separatory funnel after it settles for 24 hours. 
Then, biodiesel was washed with hot distilled water to 
remove soap, remaining methanol, and wax.

Optimization of the process parameters using the Response 
Surface Method (RSM).

Optimization aims to determine the optimum value of the 
factors that affect the transesterification process to produce 
the maximum possible biodiesel yield at a minimum produc-
tion cost. This is done by minimizing the methanol to oil 
ratio, reaction temperature, and amount of catalyst used as 
indicated in Table III.

Characterization of biodiesel

Characterization of fuel is determining the physical and 
chemical properties (Atabani et al. 2013). The physical and 
chemical properties of biodiesel were determined according 
to the American Society for Testing Materials (ASTM D 
6751) and European standard (EN 14214) methods (Demir-
bas, 2005). Table IV showed the physical and chemical 
properties of biodiesel and the standard methods used to 
determine them.

Statistical analysis of experimental results

Data analysis of the experiment was done by design expert 
11.0 software using Box Behnken design standard. The 
significance of experimental variables was obtained from 
analysis of variance (ANOVA). 

Results and discussions

Yield

The maximum oil yield obtained at optimum conditions of 
temperature 80°C and extraction time 5 hours was 39.86 %. 
This result agreed with the average oil content of Moringa 
stenopetala seed oil which is 35% - 45% (Ayerza, 2012), and 
this result also agreed with the previous reportof 38% which 
was reported by Azad et al. (2015) and by Gemechu (2021).

The maximum yield of biodiesel was 94% and it was 
obtained at optimum process parameters of methanol to oil 
ratio 6:1, temperature 55°C, and catalyst loading 1.0%.  The 
yield of biodiesel obtained agrees with the previous report of 

Azad et al. (2015) which was 91%. The yield increased as 
transesterification parameters increased until the optimum 
value and decreased beyond the optimum value. At the lower 
value of parameters, the yield decreased due to the incom-
plete conversion of reactants to the product. Table V showed 
the yield response of all experimental runs.

Characterization of biodiesel

Physical and chemical properties of biodiesel were evaluated 
using standard methods and the results were compared with 
ASTM and EN standard methods and previous reports.

Density

The value of the density of biodiesel was 874 kg/m3. This 
result is within the standard range of density (860 – 900 
kg/m3) (Demirbas, 2005) and agrees with the previous report 
by Kafuku and Mbarawa (2010) which was 900 kg/m3. 
Higher density increases thesize of fuel droplets and causes 
higher emission of particulate matter and NOx emission ina 
diesel engine while the lower density of fuel expands the 
efficiency of atomization (Choi and Reitz, 1999).

Kinematic viscosity

The experimental result showed that the value of kinematic 
viscosity was 4.8 mm2/s. This result is within the range of the 
ASTM standard value of biodiesel which is 1.6-6 (Eman and 
Cadence, 2013; Demirbas, 2005). Highly viscous fuel is 
difficult to pump and operate in internal combustion engines 
while lower kinematic viscosity of fuels increases wear 
leakage due to insufficient lubrication (Rao, 2011).

Acid value

The value of an acid value obtained was 0.4 mm KOH/g.  
This result agrees with the previous report (Kafuku and 
Mbarawa, 2010), with a value of 1.2 mmKOH/g. Higher 
acid-value fuels need further acid treatment costs and it also 
lowers the quality of the fuels. In this study, the lower acid 
value of biodiesel indicates that it has higher fuel quality.

Calorific value

The experimental result showed that the value of biodiesel 
was 10287 Cal/ g or 43 MJ/kJ. This result agrees with the 
previous report of Mahamudul et al. (2017) which was 39 

MJ/kg, and the previous report of Agarwal and Das (2001) 
which was 43.2 kJ/kg. The result obtained is above the 
standard ASTM value which is 42-42.5 MJ/kg. This result 
indicates the higher fuel quality of biodiesel. The calorific 
value obtained is similar to that of conventional diesel fuels. 
This is the novel result of this study.

Flash point

The flash point obtained from the experimental result was 
184°C. This result agrees with the standard ASTM value of 
biodiesel flash point which is greater than 130°C. From this 
study, the higher flash point of biodiesel indicates that it is 
safer to handle, store and transport the fuel (Jayed et al. 
2011).

Cetane number

The value of the cetane number observed was 53. This result 
agrees with the standard ASTM value of the cetane number 
of biodiesel which is greater than 47 (Demirbas, 2005). Fuels 
with higher cetane number benefit the engine performance 
since the engine starts rapidly and run smoothly without 
causing much noise.

Cloud and Pour point

The experimental result showed that the cloud and pour 
points of biodiesel were 10°C and 1°C respectively. This 
result agrees with the previous report of Kafuku and Mbara-
wa (2010) which was 10°C and 3°C respectively. Cloud and 
pour point of fuel indicates the fuel performance at low ambi-
ent temperature (Agarwal and Das, 2001). Table VI showed 
the result of all main physicochemical properties of biodiesel 
synthesized.

Statistical analysis of experimental results 

Analysis of variance (ANOVA) for the quadratic model

Analysis of variance determines the significance of the 
experimental results using coded variables as indicated in 
Table VII. 

The Model F-value of 380.98 implies the model is signifi-
cant. There is only a 0.01% chance that an F-value this large 
could occur due to noise.

P-values less than 0.0500 indicate model terms are signifi-
cant. In this case, A, B, C, A², B², C² are significant model 
terms. Values greater than 0.1000 indicate the model terms 
are not significant. If there are many insignificant model 
terms (not counting those required to support hierarchy), 
model reduction may improve your model.

The Lack of Fit F-value of 5.69 implies there is a 6.31% 
chance that a Lack of Fit F-value this large could occur due to 
noise. Lack of fit is bad -- we want the model to fit. This 
relatively low probability (<10%) is troubling.

The coefficient estimate represents the expected change in 
response per unit change in factor value when all remaining 
factors are held constant. The intercept in an orthogonal 
design is the overall average response of all the runs. The 
coefficients are adjustments around that average based on the 

factor settings. When the factors are orthogonal the VIFs are 
1; VIFs greater than 1 indicate multi-collinearity, and the 
higher the VIF the more severe the correlation of factors. As 
a rough rule, VIFs less than 10 are tolerable.

The effect of process parameters on the yield of biodiesel

Effect of methanol to oil ratio

Figure. (2) Shows the effect of methanol to oil ratio on 
biodiesel yield at constant temperature and catalyst loading. 
It showed that the yield of biodiesel increases as the metha-
nol-to-oil ratio increases. Increasing the methanol-to-oil ratio 
beyond the optimum value results in excess methanol which 
decreases the yield of biodiesel. The maximum yield of 
biodiesel (94%) was obtained at a methanol-to-oil ratio of 6: 
1. Therefore, this ratio was taken as an optimum value of the 
methanol-to-oil ratio. Decreasing the methanol-to-oil ratio 

below the optimum value (3:1), decreased the conversion 
efficiency of the transesterification reaction and resulted in 
lower biodiesel yield.

Effect of reaction temperature

Figure (3) shows the effect of reaction temperature on the 
yield of biodiesel at a constant methanol-to-oil ratio and 
catalyst loading. The yield of biodiesel highly increased as 

temperature increased from 45°C to 55°C.  Maximum yield 
was obtained at 58°C and the yield started to decrease slight-
ly from 58°C to 65°C due to the vaporization of methanol 
resulting in soap formation. The boiling point of methanol is 
64.7°C. Increasing reaction temperature above this point 
leads to methanol loss by evaporation and decreases the 
conversion efficiency of the reaction. At 45°C, the yield is 
about 75°C.

Effect of catalyst loading

Figure (4) shows the effect of catalyst loading on the yield of 
biodiesel at a constant methanol-to-oil ratio and temperature.  
As the amount of catalyst increased from 0.5% to 1.0%, the 
yield of biodiesel increased from 89% to 94% and the yield 
starts to decrease slightly as the amount of catalyst increased 
from 1.0% to 1.5% due to the formation of soap and emul-
sion. At a lower amount of catalyst (0.5%), the yield of 
biodiesel decreased due to the incomplete conversion of 
triglycerides of oil to fatty acid methyl ester.

Optimization of transesterification process parameters using 
the Response Surface Method (RSM)

The Response Surface Method determined the optimum 
value of process variables that maximize the yield of the 
product and minimize production cost

Table VIII showed that Response Surface Method found 15 
solutions and selected the optimum values to minimize the 
economic cost of Temperature, Methanol, and Catalyst 
required for the reaction and to maximize the yield of 
biodiesel. The optimum yield of biodiesel (83.772%) was 
observed at a temperature of 51.537 and catalyst load of 
0.500 wt.%.

Conclusions

Biodiesel is a promising biofuel that is synthesized by the 
transesterification of vegetable oils and animal fats. In this 
study, biodiesel was synthesized from moringa stenopetala 
seed oil using an alkali catalyst. The effect of methanol to 
oil ratio, reaction temperature, and catalyst weight on the 
yield and quality of biodiesel have been studied. Biodiesel 
produced was characterized according to international fuel 
testing standards methods. The optimization of process 
parameters was carried out using Response Surface 
Method (RSM).

The experimental result showed that the highest yield of 
biodiesel was 94% and this result was obtained at an 
optimum value of temperature 55°C, methanol to oil ratio of 
6:1, and catalyst load of 1.0%. Increasing methanol to oil 
ratio, temperature, and catalyst load up to the optimum point 
increased the yield of biodiesel. However, further increase of 
the parameters above the optimum point decreased the yield 
of biodiesel. The temperature has the highest significant 
effect while the catalyst load has a lower effect. 

Besides to characterization of different basic fuel properties 
of it, biodiesel can be blended with petrol-diesel at different 
percentages and applied in compression ignition engine to 
evaluate the effect of using a blend of biodiesel using differ-

ent parameters such as engine power, brake thermal efficien-
cy, specific fuel consumption, exhaust gas temperature, and 
greenhouse gas temperature and gas emission. However, the 
performance analysis of the blend of biodiesel with petrol 
diesel in a compression ignition engine was not done due to a 
lack of laboratory setup and equipment required to measure 
these parameters. This study did not compare biodiesel with 
diesel fuels used in diesel engines. Moreover, it did not 
characterize the blend of biodiesel with petroleum fuels and 
did not compare biodiesel produced from other feedstocks 
other than moringa stenopetala. Thus, further research should 
be done on these areas. 

Generally, it can be concluded that moringa stenopetala is a 
promising alternative feedstock for biodiesel production for 
the reasons: it does not affect food security, has a good oil 
content, and can be harvested throughout the year.  The 
biodiesel produced meets the standard fuel quality and 
international standard specifications. 

Acknowledgment

The authors are thankful to Addis Ababa institute of Technol-
ogy, Addis Ababa University, Ethiopian Environment and 
Forest Research Institute, College of Natural and Computa-
tional Science, Addis Ababa University, and Ethiopian 
Geological Survey for their technical support.

References

Agarwal AK and Das LM (2001), Biodiesel development and 
characterization for use as a fuel in compression in 
ignition engines, J Eng Gas Turbines Power. 123(2): 
440-447. DOI: 10.1115/1.1364522

Atabani AE, Silitonga AS,  Ong HC, Mahila TM, Masjuki 
HH,  Irfan A and Fayaz H (2013), Non-edible 
vegetable oils: evaluation of oil extraction, fatty acid 
compositions, biodiesel production, characteristics, 
engine performance and emissions production, Ren. 
Sus. Energy Rev. 18: 211-245. DOI: 10.1016/ 
j.rser.2012.10.013

Atabani AE, Mahlia TM, Ifran A, Masjuki HH, Chong WT 
and Keat TL (2013), Investigation of physical and 
chemical properties of potential edible and non-edible 
feedstocks for biodiesel production, a comparative 
analysis, Ren. Sus. Energy Rev. 21: 749-55. DOI: 
10.1016/j.rser.2013.01.027

Ayerza HR (2012), Seed and oil yields of moringa oleifera 
variety periyakalum-1 introduced for oil production in 
four ecosystems of South America, Ind. Crops Prod. 
36: 70-73. DOI: 10.1016/j.indcrop.2011.08.008

Azad A, Rasul M, Khan K, Subhash CS and Rubayat I 
(2015), Prospect of Moringa Seed oil is a 
sustainable biodiesel fuel in Australia, Procedia 
Engineering. 105: 601-606, DOI: 10.1016/j.proeng. 
2015.05.037

Choi C and Reitz R (1999), A numerical analysis of emission 
characteristics of biodiesel blended fuels, J Eng Gas 
Turbines Power 121(1): 31-37. DOI: 10.1115/1. 
2816309 

Demirbas A (2005), Potential applications of renewable 
energy sources, biomasscombustion problems in boiler 
power systems, and combustion-related 
environmentalissues, Progress in Energy and 
combustion sci. 31: 171-192. DOI: 10.1016/j.pecs. 
2005.02.002 

Demshemino SI, Donnel PS, Muhamma FY, Niwadike and 
Okoro LN (2013), Comparative analysis of biodiesel 
and petroleum diesel, International journal of 
education and research 1(8): 2-5.

Eman NA and Cadence IT (2013), Characterization of 
Biodiesel produced from palm oilvia base-catalyzed 
transesterification, Procedia Engineering. 53: 7-12. 
DOI: 10.1016/j.proeng.2013.02.002  

Gemeda T and Desta N (2020), Pre-extension demonstration 
of Moringa preparation and utilization methods in east 
Shoa zones of Oromia, Ethiopia, Journal of 
Biomaterials. 4(1): 17-22. DOI: 10.11648/j.jb. 
20200401.12 

Gemechu YS (2021), Production and Characterization of 
Biodiesel from Moringa Stenopetala Seed Oil via 
Catalytic Transesterification Process, Thesis work at 
Addis Ababa University Institute of Technology, Addis 
Ababa, Ethiopia.

Hamza TA and Azmach NN (2017), The miraculous Moringa 
trees: from a nutritionaland medicinal point of view in 
tropical regions, Journal of medicinal plants studies 5 
(4): 151-162.

Jayed MH, Masjuki HH, Kalam MA, Mahlia TM, Husnawan 
M and Liaquat AM (2011), Prospects of dedicated 
biodiesel engine vehicles in Malaysia and Indonesia, 
Ren. Sus. Ener. Rev. 15: 220-235. DOI: 
10.1016/j.rser.2010.09.002 

Kafuku G and Mbarawa M (2010), Alkaline-catalyzed 
biodiesel production from moringa oleifera oil with 
optimized production parameters, Applied Energy. 
87 (8): 2561-2565. DOI:10.1016/j. apenergy. 
2010.02.026 

Marchetti JM and Yadessa GK (2012), A review of oil 
extraction from plant seeds for biodiesel production, 
IMS Energy. 5(4): 316-340. DOI: 10.3934/energy. 
2017.2.316 

Mahmudul H, Hagos R, Mamat A, Abdul A and Ishak RA 
(2017), Production, characterization and performance 
of Biodiesel as an alternative fuel in diesel engines, 
Renewable and Sustainable Energy Reviews 72(c): 
497-509. DOI: 10.1016/j.rser.2017.01.001 

Piyush N, Subramanian KA and Dastidar MG (2013), 
Production and characterization of Biodieselfrom 
algae, Fuel processing technology. 120: 79-88. DOI: 
10.1016/j.fuproc.2013.12.003 

Raj S and Bhandari M (2017), Comparison of methods of 
production of biodiesel from Jatropha curcas, Journal 
of Biofuel. 8(2): 58-80.

Rao PV (2011), Experimental investigations on the 
influence of properties of jatropha biodiesel on 
performance, combustion, and emission 
characteristics of DI–CI engines, World Acad. Sci. 
Eng. Technol. 5(3): 855-868.

Sreepada H and Vijayalaxmi H (2013), An overview of 
moringa production in Ethiopia, International Journal 
of Science and Research 4(4): 2319-7064. DOI: 
10.36106/ijsr

Seema R and Meena B (2017), Comparison of methods of 
biodiesel productionfrom Jatropha Curcas, Journal of 
Biofuels. 8(2): 58-80.

its advantages is it is considered a great natural cosmetic 
emollient and has high oxidative stability (Ayerza, 2012).

Moringa plant is a high-value tree of the Moringaceae family. 
It consists of 13 species highly distributed in Africa and Asia 
(Hamza and Azmach, 2017). Moringa is particularly suitable 
for dry regions since it can be grown using rainwater without 
expensive irrigation techniques.  Moringa has been given less 
attention and ignored tree by communities to utilize it in 
different ways (Gemeda and Desta, 2020). Flowering begins 
within the first six months. Moringa stenopetala seed is an 
available and underutilized resource. Ethiopia has a comfort-
able environment for mooring stenopetala plantations. Many 
parts of the country particularly southern parts such as Gamo 
Goffa, Sidama Wolayitta, Konso, and Darashe have planted 
moringa in their garden and farmland (Sreepada and Vijay-
alaxmi, 2013). Thus, this study investigated that moringa 
stenopetala seed oil is a potential industrial feedstock for 
biodiesel production as an alternative energy source.

Materials and methods

The sample of Moringa seed was collected from the Gamo 
Goffa Zone, Arba Minch area of Ethiopia. The seed sample 

was dried and milled to reduce the particle size. Then, 80 g of 
sample was measured and put into the soxhlet apparatus 
thimble. Then, it was placed in a 500 mL capacity soxhlet 
chamber. 400 mL solvent (Hexane) was used for the 
extraction at different temperatures for 3 hrs. to 5 hrs. The 
extraction was conducted at 70°C, 75°C, and 80°C by 
varying extraction time to get the maximum possible oil 
yield.  The soxhlet extraction method was selected since it 
results in high oil yield, is quick, the solvent can be reused, 
and is low cost (Sreepada and Vijayalaxmi, 2013). The 
unwanted substances were removed by evaporation and 
degumming. Evaporation was used to separate hexane from 

Variable Unit 
Level 

-1 +1 

Methanol to oil ratio - 3 9 

Catalyst loading Wt.% 0.5 1.5 

Reaction temperature °C  45 65 

Table I. Independent variables and level of main factors 
that affect transesterification reaction

Volume of pure biodiesel produced

 a volume of oil used
Yield (%) = *100



Biodiesel from moringa stenopetala seed oil 58(1) 202338

The most common production technology of biodiesel is the 
transesterification process. Transesterification is a chemical 
reaction between one mole of triglyceride with three moles of 
alcohol to produce fatty acid methyl ester and glycerol in the 
presence of a catalyst or without a catalyst. Most transesteri-
fication reactions use ethanol or methanol alcohol. Many 
studies show that methanol is more practically used as 
alcohol than ethanol. Methanol is preferable due to its low 
cost and its physical and chemical advantages. Another 
advantage of using methanol is the ease of separation of 
glycerin which can be achieved by simple decantation 
(Marchetti and Yadessa, 2012).

Various catalysts can be used in the process. However, it was 
confirmed that the transesterification reaction was completed 
very fast when alkali catalysts are used. After the transesterifi-
cation reaction is completed, glycerol, catalyst, alcohol, and 
soap are separated from biodiesel. The factors affecting 
biodiesel yield and fuel quality are alcohol-to-oil ratios, 
temperature, catalyst loading, and reaction time (Raj and Bhan-
dari, 2017). Biodiesel is formed when triglyceride reacts with 
alcohol leaving glycerol as a byproduct as shown in Figure 1.

There are more than 300 vegetable oils identified as potential 
feedstocks for biodiesel production globally. The availability, 
characteristics, and variety of feedstocks make them promis-
ing ingredients for the sustainable production of biodiesel 
(Piyush et al. 2013). Researchers have proposed Moringa 
seed oil as an alternative potential feedstock to produce 
biodiesel. However, there is a research gap that promotes this 
feedstock for industrial processing. Moringa seed has an 
average of 35%-45% oil content with high oleic content of 
greater than 73% based on the type of the tree. Moringa oil 
has many various industrial and homemade benefits. One of 

oil by rotary evaporation at 80°C. Gum and wax were 
removed by a degumming method. Then, biodiesel was 
synthesized by transesterification reaction using a homoge-
nous catalyst (methanol) at different process parameters.

Experimental design

The experimental design used for this study was a Box 
Behnken design standard using design expert 11.0 software. 
The experimental design was done using three variables and 
tree levels for a response surface method. 17 experimental 
runswere selected by design expert 11.0 software using the 
Box Behnken design standard method, with five central 
points per block. The main factors that affect biodiesel 
production by transesterification reaction are reaction time, 
reaction temperature, and alcohol-to-oil ratio (Seema and 
Meena, 2017). As indicated in Table I, the overall production 
of biodiesel was carried out at optimum parameters of 
catalyst load of 0.5 to 1.5 wt.%, reaction temperature of 45 to 
65°C, and methanol to oil ratio of 3 to 9.  

The other parameters, reaction time and mixing intensity 
were kept constant at 1 hour and 500 rpm for all experimental 
runs. A combination of three factors and three levels of 
experimental runs was conducted. There are 17 experimental 
runs determined byBox Behnken’s design arrangement as 
shown in Table II.

Production and purification of the product

The method used to produce biodiesel was a one-steptranses-
terification reaction. Methanol was the alcohol selected for 
the transesterification reaction due to its availability, low 
cost, popularity, and ease of separation (Demirbas, 2005). 
The catalyst selected for this study was the base catalyst 
(KOH) since biodiesel can be produced at low temperatures 
and pressure reactions. Moreover, it is a homogeneous base 
catalyst that results in high conversion, minimum side 
reactions, short reaction time, and high yield (Marchetti and 

Yadessa, 2012). Though it has many advantages, the disad-
vantage of the catalyst used is it cannot be reused.

When the reaction is completed, biodiesel and glycerol were 
separated by a separatory funnel after it settles for 24 hours. 
Then, biodiesel was washed with hot distilled water to 
remove soap, remaining methanol, and wax.

Optimization of the process parameters using the Response 
Surface Method (RSM).

Optimization aims to determine the optimum value of the 
factors that affect the transesterification process to produce 
the maximum possible biodiesel yield at a minimum produc-
tion cost. This is done by minimizing the methanol to oil 
ratio, reaction temperature, and amount of catalyst used as 
indicated in Table III.

Characterization of biodiesel

Characterization of fuel is determining the physical and 
chemical properties (Atabani et al. 2013). The physical and 
chemical properties of biodiesel were determined according 
to the American Society for Testing Materials (ASTM D 
6751) and European standard (EN 14214) methods (Demir-
bas, 2005). Table IV showed the physical and chemical 
properties of biodiesel and the standard methods used to 
determine them.

Statistical analysis of experimental results

Data analysis of the experiment was done by design expert 
11.0 software using Box Behnken design standard. The 
significance of experimental variables was obtained from 
analysis of variance (ANOVA). 

Results and discussions

Yield

The maximum oil yield obtained at optimum conditions of 
temperature 80°C and extraction time 5 hours was 39.86 %. 
This result agreed with the average oil content of Moringa 
stenopetala seed oil which is 35% - 45% (Ayerza, 2012), and 
this result also agreed with the previous reportof 38% which 
was reported by Azad et al. (2015) and by Gemechu (2021).

The maximum yield of biodiesel was 94% and it was 
obtained at optimum process parameters of methanol to oil 
ratio 6:1, temperature 55°C, and catalyst loading 1.0%.  The 
yield of biodiesel obtained agrees with the previous report of 

Azad et al. (2015) which was 91%. The yield increased as 
transesterification parameters increased until the optimum 
value and decreased beyond the optimum value. At the lower 
value of parameters, the yield decreased due to the incom-
plete conversion of reactants to the product. Table V showed 
the yield response of all experimental runs.

Characterization of biodiesel

Physical and chemical properties of biodiesel were evaluated 
using standard methods and the results were compared with 
ASTM and EN standard methods and previous reports.

Density

The value of the density of biodiesel was 874 kg/m3. This 
result is within the standard range of density (860 – 900 
kg/m3) (Demirbas, 2005) and agrees with the previous report 
by Kafuku and Mbarawa (2010) which was 900 kg/m3. 
Higher density increases thesize of fuel droplets and causes 
higher emission of particulate matter and NOx emission ina 
diesel engine while the lower density of fuel expands the 
efficiency of atomization (Choi and Reitz, 1999).

Kinematic viscosity

The experimental result showed that the value of kinematic 
viscosity was 4.8 mm2/s. This result is within the range of the 
ASTM standard value of biodiesel which is 1.6-6 (Eman and 
Cadence, 2013; Demirbas, 2005). Highly viscous fuel is 
difficult to pump and operate in internal combustion engines 
while lower kinematic viscosity of fuels increases wear 
leakage due to insufficient lubrication (Rao, 2011).

Acid value

The value of an acid value obtained was 0.4 mm KOH/g.  
This result agrees with the previous report (Kafuku and 
Mbarawa, 2010), with a value of 1.2 mmKOH/g. Higher 
acid-value fuels need further acid treatment costs and it also 
lowers the quality of the fuels. In this study, the lower acid 
value of biodiesel indicates that it has higher fuel quality.

Calorific value

The experimental result showed that the value of biodiesel 
was 10287 Cal/ g or 43 MJ/kJ. This result agrees with the 
previous report of Mahamudul et al. (2017) which was 39 

MJ/kg, and the previous report of Agarwal and Das (2001) 
which was 43.2 kJ/kg. The result obtained is above the 
standard ASTM value which is 42-42.5 MJ/kg. This result 
indicates the higher fuel quality of biodiesel. The calorific 
value obtained is similar to that of conventional diesel fuels. 
This is the novel result of this study.

Flash point

The flash point obtained from the experimental result was 
184°C. This result agrees with the standard ASTM value of 
biodiesel flash point which is greater than 130°C. From this 
study, the higher flash point of biodiesel indicates that it is 
safer to handle, store and transport the fuel (Jayed et al. 
2011).

Cetane number

The value of the cetane number observed was 53. This result 
agrees with the standard ASTM value of the cetane number 
of biodiesel which is greater than 47 (Demirbas, 2005). Fuels 
with higher cetane number benefit the engine performance 
since the engine starts rapidly and run smoothly without 
causing much noise.

Cloud and Pour point

The experimental result showed that the cloud and pour 
points of biodiesel were 10°C and 1°C respectively. This 
result agrees with the previous report of Kafuku and Mbara-
wa (2010) which was 10°C and 3°C respectively. Cloud and 
pour point of fuel indicates the fuel performance at low ambi-
ent temperature (Agarwal and Das, 2001). Table VI showed 
the result of all main physicochemical properties of biodiesel 
synthesized.

Statistical analysis of experimental results 

Analysis of variance (ANOVA) for the quadratic model

Analysis of variance determines the significance of the 
experimental results using coded variables as indicated in 
Table VII. 

The Model F-value of 380.98 implies the model is signifi-
cant. There is only a 0.01% chance that an F-value this large 
could occur due to noise.

P-values less than 0.0500 indicate model terms are signifi-
cant. In this case, A, B, C, A², B², C² are significant model 
terms. Values greater than 0.1000 indicate the model terms 
are not significant. If there are many insignificant model 
terms (not counting those required to support hierarchy), 
model reduction may improve your model.

The Lack of Fit F-value of 5.69 implies there is a 6.31% 
chance that a Lack of Fit F-value this large could occur due to 
noise. Lack of fit is bad -- we want the model to fit. This 
relatively low probability (<10%) is troubling.

The coefficient estimate represents the expected change in 
response per unit change in factor value when all remaining 
factors are held constant. The intercept in an orthogonal 
design is the overall average response of all the runs. The 
coefficients are adjustments around that average based on the 

factor settings. When the factors are orthogonal the VIFs are 
1; VIFs greater than 1 indicate multi-collinearity, and the 
higher the VIF the more severe the correlation of factors. As 
a rough rule, VIFs less than 10 are tolerable.

The effect of process parameters on the yield of biodiesel

Effect of methanol to oil ratio

Figure. (2) Shows the effect of methanol to oil ratio on 
biodiesel yield at constant temperature and catalyst loading. 
It showed that the yield of biodiesel increases as the metha-
nol-to-oil ratio increases. Increasing the methanol-to-oil ratio 
beyond the optimum value results in excess methanol which 
decreases the yield of biodiesel. The maximum yield of 
biodiesel (94%) was obtained at a methanol-to-oil ratio of 6: 
1. Therefore, this ratio was taken as an optimum value of the 
methanol-to-oil ratio. Decreasing the methanol-to-oil ratio 

below the optimum value (3:1), decreased the conversion 
efficiency of the transesterification reaction and resulted in 
lower biodiesel yield.

Effect of reaction temperature

Figure (3) shows the effect of reaction temperature on the 
yield of biodiesel at a constant methanol-to-oil ratio and 
catalyst loading. The yield of biodiesel highly increased as 

temperature increased from 45°C to 55°C.  Maximum yield 
was obtained at 58°C and the yield started to decrease slight-
ly from 58°C to 65°C due to the vaporization of methanol 
resulting in soap formation. The boiling point of methanol is 
64.7°C. Increasing reaction temperature above this point 
leads to methanol loss by evaporation and decreases the 
conversion efficiency of the reaction. At 45°C, the yield is 
about 75°C.

Effect of catalyst loading

Figure (4) shows the effect of catalyst loading on the yield of 
biodiesel at a constant methanol-to-oil ratio and temperature.  
As the amount of catalyst increased from 0.5% to 1.0%, the 
yield of biodiesel increased from 89% to 94% and the yield 
starts to decrease slightly as the amount of catalyst increased 
from 1.0% to 1.5% due to the formation of soap and emul-
sion. At a lower amount of catalyst (0.5%), the yield of 
biodiesel decreased due to the incomplete conversion of 
triglycerides of oil to fatty acid methyl ester.

Optimization of transesterification process parameters using 
the Response Surface Method (RSM)

The Response Surface Method determined the optimum 
value of process variables that maximize the yield of the 
product and minimize production cost

Table VIII showed that Response Surface Method found 15 
solutions and selected the optimum values to minimize the 
economic cost of Temperature, Methanol, and Catalyst 
required for the reaction and to maximize the yield of 
biodiesel. The optimum yield of biodiesel (83.772%) was 
observed at a temperature of 51.537 and catalyst load of 
0.500 wt.%.

Conclusions

Biodiesel is a promising biofuel that is synthesized by the 
transesterification of vegetable oils and animal fats. In this 
study, biodiesel was synthesized from moringa stenopetala 
seed oil using an alkali catalyst. The effect of methanol to 
oil ratio, reaction temperature, and catalyst weight on the 
yield and quality of biodiesel have been studied. Biodiesel 
produced was characterized according to international fuel 
testing standards methods. The optimization of process 
parameters was carried out using Response Surface 
Method (RSM).

The experimental result showed that the highest yield of 
biodiesel was 94% and this result was obtained at an 
optimum value of temperature 55°C, methanol to oil ratio of 
6:1, and catalyst load of 1.0%. Increasing methanol to oil 
ratio, temperature, and catalyst load up to the optimum point 
increased the yield of biodiesel. However, further increase of 
the parameters above the optimum point decreased the yield 
of biodiesel. The temperature has the highest significant 
effect while the catalyst load has a lower effect. 

Besides to characterization of different basic fuel properties 
of it, biodiesel can be blended with petrol-diesel at different 
percentages and applied in compression ignition engine to 
evaluate the effect of using a blend of biodiesel using differ-

ent parameters such as engine power, brake thermal efficien-
cy, specific fuel consumption, exhaust gas temperature, and 
greenhouse gas temperature and gas emission. However, the 
performance analysis of the blend of biodiesel with petrol 
diesel in a compression ignition engine was not done due to a 
lack of laboratory setup and equipment required to measure 
these parameters. This study did not compare biodiesel with 
diesel fuels used in diesel engines. Moreover, it did not 
characterize the blend of biodiesel with petroleum fuels and 
did not compare biodiesel produced from other feedstocks 
other than moringa stenopetala. Thus, further research should 
be done on these areas. 

Generally, it can be concluded that moringa stenopetala is a 
promising alternative feedstock for biodiesel production for 
the reasons: it does not affect food security, has a good oil 
content, and can be harvested throughout the year.  The 
biodiesel produced meets the standard fuel quality and 
international standard specifications. 

Acknowledgment

The authors are thankful to Addis Ababa institute of Technol-
ogy, Addis Ababa University, Ethiopian Environment and 
Forest Research Institute, College of Natural and Computa-
tional Science, Addis Ababa University, and Ethiopian 
Geological Survey for their technical support.

References

Agarwal AK and Das LM (2001), Biodiesel development and 
characterization for use as a fuel in compression in 
ignition engines, J Eng Gas Turbines Power. 123(2): 
440-447. DOI: 10.1115/1.1364522

Atabani AE, Silitonga AS,  Ong HC, Mahila TM, Masjuki 
HH,  Irfan A and Fayaz H (2013), Non-edible 
vegetable oils: evaluation of oil extraction, fatty acid 
compositions, biodiesel production, characteristics, 
engine performance and emissions production, Ren. 
Sus. Energy Rev. 18: 211-245. DOI: 10.1016/ 
j.rser.2012.10.013

Atabani AE, Mahlia TM, Ifran A, Masjuki HH, Chong WT 
and Keat TL (2013), Investigation of physical and 
chemical properties of potential edible and non-edible 
feedstocks for biodiesel production, a comparative 
analysis, Ren. Sus. Energy Rev. 21: 749-55. DOI: 
10.1016/j.rser.2013.01.027

Ayerza HR (2012), Seed and oil yields of moringa oleifera 
variety periyakalum-1 introduced for oil production in 
four ecosystems of South America, Ind. Crops Prod. 
36: 70-73. DOI: 10.1016/j.indcrop.2011.08.008

Azad A, Rasul M, Khan K, Subhash CS and Rubayat I 
(2015), Prospect of Moringa Seed oil is a 
sustainable biodiesel fuel in Australia, Procedia 
Engineering. 105: 601-606, DOI: 10.1016/j.proeng. 
2015.05.037

Choi C and Reitz R (1999), A numerical analysis of emission 
characteristics of biodiesel blended fuels, J Eng Gas 
Turbines Power 121(1): 31-37. DOI: 10.1115/1. 
2816309 

Demirbas A (2005), Potential applications of renewable 
energy sources, biomasscombustion problems in boiler 
power systems, and combustion-related 
environmentalissues, Progress in Energy and 
combustion sci. 31: 171-192. DOI: 10.1016/j.pecs. 
2005.02.002 

Demshemino SI, Donnel PS, Muhamma FY, Niwadike and 
Okoro LN (2013), Comparative analysis of biodiesel 
and petroleum diesel, International journal of 
education and research 1(8): 2-5.

Eman NA and Cadence IT (2013), Characterization of 
Biodiesel produced from palm oilvia base-catalyzed 
transesterification, Procedia Engineering. 53: 7-12. 
DOI: 10.1016/j.proeng.2013.02.002  

Gemeda T and Desta N (2020), Pre-extension demonstration 
of Moringa preparation and utilization methods in east 
Shoa zones of Oromia, Ethiopia, Journal of 
Biomaterials. 4(1): 17-22. DOI: 10.11648/j.jb. 
20200401.12 

Gemechu YS (2021), Production and Characterization of 
Biodiesel from Moringa Stenopetala Seed Oil via 
Catalytic Transesterification Process, Thesis work at 
Addis Ababa University Institute of Technology, Addis 
Ababa, Ethiopia.

Hamza TA and Azmach NN (2017), The miraculous Moringa 
trees: from a nutritionaland medicinal point of view in 
tropical regions, Journal of medicinal plants studies 5 
(4): 151-162.

Jayed MH, Masjuki HH, Kalam MA, Mahlia TM, Husnawan 
M and Liaquat AM (2011), Prospects of dedicated 
biodiesel engine vehicles in Malaysia and Indonesia, 
Ren. Sus. Ener. Rev. 15: 220-235. DOI: 
10.1016/j.rser.2010.09.002 

Kafuku G and Mbarawa M (2010), Alkaline-catalyzed 
biodiesel production from moringa oleifera oil with 
optimized production parameters, Applied Energy. 
87 (8): 2561-2565. DOI:10.1016/j. apenergy. 
2010.02.026 

Marchetti JM and Yadessa GK (2012), A review of oil 
extraction from plant seeds for biodiesel production, 
IMS Energy. 5(4): 316-340. DOI: 10.3934/energy. 
2017.2.316 

Mahmudul H, Hagos R, Mamat A, Abdul A and Ishak RA 
(2017), Production, characterization and performance 
of Biodiesel as an alternative fuel in diesel engines, 
Renewable and Sustainable Energy Reviews 72(c): 
497-509. DOI: 10.1016/j.rser.2017.01.001 

Piyush N, Subramanian KA and Dastidar MG (2013), 
Production and characterization of Biodieselfrom 
algae, Fuel processing technology. 120: 79-88. DOI: 
10.1016/j.fuproc.2013.12.003 

Raj S and Bhandari M (2017), Comparison of methods of 
production of biodiesel from Jatropha curcas, Journal 
of Biofuel. 8(2): 58-80.

Rao PV (2011), Experimental investigations on the 
influence of properties of jatropha biodiesel on 
performance, combustion, and emission 
characteristics of DI–CI engines, World Acad. Sci. 
Eng. Technol. 5(3): 855-868.

Sreepada H and Vijayalaxmi H (2013), An overview of 
moringa production in Ethiopia, International Journal 
of Science and Research 4(4): 2319-7064. DOI: 
10.36106/ijsr

Seema R and Meena B (2017), Comparison of methods of 
biodiesel productionfrom Jatropha Curcas, Journal of 
Biofuels. 8(2): 58-80.

its advantages is it is considered a great natural cosmetic 
emollient and has high oxidative stability (Ayerza, 2012).

Moringa plant is a high-value tree of the Moringaceae family. 
It consists of 13 species highly distributed in Africa and Asia 
(Hamza and Azmach, 2017). Moringa is particularly suitable 
for dry regions since it can be grown using rainwater without 
expensive irrigation techniques.  Moringa has been given less 
attention and ignored tree by communities to utilize it in 
different ways (Gemeda and Desta, 2020). Flowering begins 
within the first six months. Moringa stenopetala seed is an 
available and underutilized resource. Ethiopia has a comfort-
able environment for mooring stenopetala plantations. Many 
parts of the country particularly southern parts such as Gamo 
Goffa, Sidama Wolayitta, Konso, and Darashe have planted 
moringa in their garden and farmland (Sreepada and Vijay-
alaxmi, 2013). Thus, this study investigated that moringa 
stenopetala seed oil is a potential industrial feedstock for 
biodiesel production as an alternative energy source.

Materials and methods

The sample of Moringa seed was collected from the Gamo 
Goffa Zone, Arba Minch area of Ethiopia. The seed sample 

was dried and milled to reduce the particle size. Then, 80 g of 
sample was measured and put into the soxhlet apparatus 
thimble. Then, it was placed in a 500 mL capacity soxhlet 
chamber. 400 mL solvent (Hexane) was used for the 
extraction at different temperatures for 3 hrs. to 5 hrs. The 
extraction was conducted at 70°C, 75°C, and 80°C by 
varying extraction time to get the maximum possible oil 
yield.  The soxhlet extraction method was selected since it 
results in high oil yield, is quick, the solvent can be reused, 
and is low cost (Sreepada and Vijayalaxmi, 2013). The 
unwanted substances were removed by evaporation and 
degumming. Evaporation was used to separate hexane from 

Table II. Box Behnken design arrangement (experimental design matrix)

Run  

 

Factor 1  

A: Methanol to oil ratio  

Factor 2  

B: Temperature  

Factor 3  

C: Catalyst     
loading  

Yield 
response   
(%)  

1  6  55  1.0  

2  6  65  0.5  

3  6  45  0.5  

4  3  55  1.5  

5  9  45  1.0  

6  9  65  1.0  

7  3  65  1.0  

8  6  55  1.0  

9  6  55  1.0  

10  9  55  0.5  

11  3  55  0.5  

12  6  55  1.0  

13  3  45  1.0  

14  9  55  1.5  

15  6  45  1.5  

16  6  65  1.5  

17  6  55  1.0  

Table III. The goal of optimization and limitation of process parameters

Name 

Goal 

Lower 

limit 

Upper 

limit 

Lower 

weight 

Upper 

weight 

Importance 

A: Methanol to oil 

ratio 

minimize 3 9 1 3 3 

B: Temperature minimize 45 65 1 3 3 

C: Catalyst loading minimize 0.5 1.5 1 3 3 

Yield maximize 65.67 94.0 1 3 3 



Shage and Ali 39

The most common production technology of biodiesel is the 
transesterification process. Transesterification is a chemical 
reaction between one mole of triglyceride with three moles of 
alcohol to produce fatty acid methyl ester and glycerol in the 
presence of a catalyst or without a catalyst. Most transesteri-
fication reactions use ethanol or methanol alcohol. Many 
studies show that methanol is more practically used as 
alcohol than ethanol. Methanol is preferable due to its low 
cost and its physical and chemical advantages. Another 
advantage of using methanol is the ease of separation of 
glycerin which can be achieved by simple decantation 
(Marchetti and Yadessa, 2012).

Various catalysts can be used in the process. However, it was 
confirmed that the transesterification reaction was completed 
very fast when alkali catalysts are used. After the transesterifi-
cation reaction is completed, glycerol, catalyst, alcohol, and 
soap are separated from biodiesel. The factors affecting 
biodiesel yield and fuel quality are alcohol-to-oil ratios, 
temperature, catalyst loading, and reaction time (Raj and Bhan-
dari, 2017). Biodiesel is formed when triglyceride reacts with 
alcohol leaving glycerol as a byproduct as shown in Figure 1.

There are more than 300 vegetable oils identified as potential 
feedstocks for biodiesel production globally. The availability, 
characteristics, and variety of feedstocks make them promis-
ing ingredients for the sustainable production of biodiesel 
(Piyush et al. 2013). Researchers have proposed Moringa 
seed oil as an alternative potential feedstock to produce 
biodiesel. However, there is a research gap that promotes this 
feedstock for industrial processing. Moringa seed has an 
average of 35%-45% oil content with high oleic content of 
greater than 73% based on the type of the tree. Moringa oil 
has many various industrial and homemade benefits. One of 

oil by rotary evaporation at 80°C. Gum and wax were 
removed by a degumming method. Then, biodiesel was 
synthesized by transesterification reaction using a homoge-
nous catalyst (methanol) at different process parameters.

Experimental design

The experimental design used for this study was a Box 
Behnken design standard using design expert 11.0 software. 
The experimental design was done using three variables and 
tree levels for a response surface method. 17 experimental 
runswere selected by design expert 11.0 software using the 
Box Behnken design standard method, with five central 
points per block. The main factors that affect biodiesel 
production by transesterification reaction are reaction time, 
reaction temperature, and alcohol-to-oil ratio (Seema and 
Meena, 2017). As indicated in Table I, the overall production 
of biodiesel was carried out at optimum parameters of 
catalyst load of 0.5 to 1.5 wt.%, reaction temperature of 45 to 
65°C, and methanol to oil ratio of 3 to 9.  

The other parameters, reaction time and mixing intensity 
were kept constant at 1 hour and 500 rpm for all experimental 
runs. A combination of three factors and three levels of 
experimental runs was conducted. There are 17 experimental 
runs determined byBox Behnken’s design arrangement as 
shown in Table II.

Production and purification of the product

The method used to produce biodiesel was a one-steptranses-
terification reaction. Methanol was the alcohol selected for 
the transesterification reaction due to its availability, low 
cost, popularity, and ease of separation (Demirbas, 2005). 
The catalyst selected for this study was the base catalyst 
(KOH) since biodiesel can be produced at low temperatures 
and pressure reactions. Moreover, it is a homogeneous base 
catalyst that results in high conversion, minimum side 
reactions, short reaction time, and high yield (Marchetti and 

Yadessa, 2012). Though it has many advantages, the disad-
vantage of the catalyst used is it cannot be reused.

When the reaction is completed, biodiesel and glycerol were 
separated by a separatory funnel after it settles for 24 hours. 
Then, biodiesel was washed with hot distilled water to 
remove soap, remaining methanol, and wax.

Optimization of the process parameters using the Response 
Surface Method (RSM).

Optimization aims to determine the optimum value of the 
factors that affect the transesterification process to produce 
the maximum possible biodiesel yield at a minimum produc-
tion cost. This is done by minimizing the methanol to oil 
ratio, reaction temperature, and amount of catalyst used as 
indicated in Table III.

Characterization of biodiesel

Characterization of fuel is determining the physical and 
chemical properties (Atabani et al. 2013). The physical and 
chemical properties of biodiesel were determined according 
to the American Society for Testing Materials (ASTM D 
6751) and European standard (EN 14214) methods (Demir-
bas, 2005). Table IV showed the physical and chemical 
properties of biodiesel and the standard methods used to 
determine them.

Statistical analysis of experimental results

Data analysis of the experiment was done by design expert 
11.0 software using Box Behnken design standard. The 
significance of experimental variables was obtained from 
analysis of variance (ANOVA). 

Results and discussions

Yield

The maximum oil yield obtained at optimum conditions of 
temperature 80°C and extraction time 5 hours was 39.86 %. 
This result agreed with the average oil content of Moringa 
stenopetala seed oil which is 35% - 45% (Ayerza, 2012), and 
this result also agreed with the previous reportof 38% which 
was reported by Azad et al. (2015) and by Gemechu (2021).

The maximum yield of biodiesel was 94% and it was 
obtained at optimum process parameters of methanol to oil 
ratio 6:1, temperature 55°C, and catalyst loading 1.0%.  The 
yield of biodiesel obtained agrees with the previous report of 

Azad et al. (2015) which was 91%. The yield increased as 
transesterification parameters increased until the optimum 
value and decreased beyond the optimum value. At the lower 
value of parameters, the yield decreased due to the incom-
plete conversion of reactants to the product. Table V showed 
the yield response of all experimental runs.

Characterization of biodiesel

Physical and chemical properties of biodiesel were evaluated 
using standard methods and the results were compared with 
ASTM and EN standard methods and previous reports.

Density

The value of the density of biodiesel was 874 kg/m3. This 
result is within the standard range of density (860 – 900 
kg/m3) (Demirbas, 2005) and agrees with the previous report 
by Kafuku and Mbarawa (2010) which was 900 kg/m3. 
Higher density increases thesize of fuel droplets and causes 
higher emission of particulate matter and NOx emission ina 
diesel engine while the lower density of fuel expands the 
efficiency of atomization (Choi and Reitz, 1999).

Kinematic viscosity

The experimental result showed that the value of kinematic 
viscosity was 4.8 mm2/s. This result is within the range of the 
ASTM standard value of biodiesel which is 1.6-6 (Eman and 
Cadence, 2013; Demirbas, 2005). Highly viscous fuel is 
difficult to pump and operate in internal combustion engines 
while lower kinematic viscosity of fuels increases wear 
leakage due to insufficient lubrication (Rao, 2011).

Acid value

The value of an acid value obtained was 0.4 mm KOH/g.  
This result agrees with the previous report (Kafuku and 
Mbarawa, 2010), with a value of 1.2 mmKOH/g. Higher 
acid-value fuels need further acid treatment costs and it also 
lowers the quality of the fuels. In this study, the lower acid 
value of biodiesel indicates that it has higher fuel quality.

Calorific value

The experimental result showed that the value of biodiesel 
was 10287 Cal/ g or 43 MJ/kJ. This result agrees with the 
previous report of Mahamudul et al. (2017) which was 39 

MJ/kg, and the previous report of Agarwal and Das (2001) 
which was 43.2 kJ/kg. The result obtained is above the 
standard ASTM value which is 42-42.5 MJ/kg. This result 
indicates the higher fuel quality of biodiesel. The calorific 
value obtained is similar to that of conventional diesel fuels. 
This is the novel result of this study.

Flash point

The flash point obtained from the experimental result was 
184°C. This result agrees with the standard ASTM value of 
biodiesel flash point which is greater than 130°C. From this 
study, the higher flash point of biodiesel indicates that it is 
safer to handle, store and transport the fuel (Jayed et al. 
2011).

Cetane number

The value of the cetane number observed was 53. This result 
agrees with the standard ASTM value of the cetane number 
of biodiesel which is greater than 47 (Demirbas, 2005). Fuels 
with higher cetane number benefit the engine performance 
since the engine starts rapidly and run smoothly without 
causing much noise.

Cloud and Pour point

The experimental result showed that the cloud and pour 
points of biodiesel were 10°C and 1°C respectively. This 
result agrees with the previous report of Kafuku and Mbara-
wa (2010) which was 10°C and 3°C respectively. Cloud and 
pour point of fuel indicates the fuel performance at low ambi-
ent temperature (Agarwal and Das, 2001). Table VI showed 
the result of all main physicochemical properties of biodiesel 
synthesized.

Statistical analysis of experimental results 

Analysis of variance (ANOVA) for the quadratic model

Analysis of variance determines the significance of the 
experimental results using coded variables as indicated in 
Table VII. 

The Model F-value of 380.98 implies the model is signifi-
cant. There is only a 0.01% chance that an F-value this large 
could occur due to noise.

P-values less than 0.0500 indicate model terms are signifi-
cant. In this case, A, B, C, A², B², C² are significant model 
terms. Values greater than 0.1000 indicate the model terms 
are not significant. If there are many insignificant model 
terms (not counting those required to support hierarchy), 
model reduction may improve your model.

The Lack of Fit F-value of 5.69 implies there is a 6.31% 
chance that a Lack of Fit F-value this large could occur due to 
noise. Lack of fit is bad -- we want the model to fit. This 
relatively low probability (<10%) is troubling.

The coefficient estimate represents the expected change in 
response per unit change in factor value when all remaining 
factors are held constant. The intercept in an orthogonal 
design is the overall average response of all the runs. The 
coefficients are adjustments around that average based on the 

factor settings. When the factors are orthogonal the VIFs are 
1; VIFs greater than 1 indicate multi-collinearity, and the 
higher the VIF the more severe the correlation of factors. As 
a rough rule, VIFs less than 10 are tolerable.

The effect of process parameters on the yield of biodiesel

Effect of methanol to oil ratio

Figure. (2) Shows the effect of methanol to oil ratio on 
biodiesel yield at constant temperature and catalyst loading. 
It showed that the yield of biodiesel increases as the metha-
nol-to-oil ratio increases. Increasing the methanol-to-oil ratio 
beyond the optimum value results in excess methanol which 
decreases the yield of biodiesel. The maximum yield of 
biodiesel (94%) was obtained at a methanol-to-oil ratio of 6: 
1. Therefore, this ratio was taken as an optimum value of the 
methanol-to-oil ratio. Decreasing the methanol-to-oil ratio 

below the optimum value (3:1), decreased the conversion 
efficiency of the transesterification reaction and resulted in 
lower biodiesel yield.

Effect of reaction temperature

Figure (3) shows the effect of reaction temperature on the 
yield of biodiesel at a constant methanol-to-oil ratio and 
catalyst loading. The yield of biodiesel highly increased as 

temperature increased from 45°C to 55°C.  Maximum yield 
was obtained at 58°C and the yield started to decrease slight-
ly from 58°C to 65°C due to the vaporization of methanol 
resulting in soap formation. The boiling point of methanol is 
64.7°C. Increasing reaction temperature above this point 
leads to methanol loss by evaporation and decreases the 
conversion efficiency of the reaction. At 45°C, the yield is 
about 75°C.

Effect of catalyst loading

Figure (4) shows the effect of catalyst loading on the yield of 
biodiesel at a constant methanol-to-oil ratio and temperature.  
As the amount of catalyst increased from 0.5% to 1.0%, the 
yield of biodiesel increased from 89% to 94% and the yield 
starts to decrease slightly as the amount of catalyst increased 
from 1.0% to 1.5% due to the formation of soap and emul-
sion. At a lower amount of catalyst (0.5%), the yield of 
biodiesel decreased due to the incomplete conversion of 
triglycerides of oil to fatty acid methyl ester.

Optimization of transesterification process parameters using 
the Response Surface Method (RSM)

The Response Surface Method determined the optimum 
value of process variables that maximize the yield of the 
product and minimize production cost

Table VIII showed that Response Surface Method found 15 
solutions and selected the optimum values to minimize the 
economic cost of Temperature, Methanol, and Catalyst 
required for the reaction and to maximize the yield of 
biodiesel. The optimum yield of biodiesel (83.772%) was 
observed at a temperature of 51.537 and catalyst load of 
0.500 wt.%.

Conclusions

Biodiesel is a promising biofuel that is synthesized by the 
transesterification of vegetable oils and animal fats. In this 
study, biodiesel was synthesized from moringa stenopetala 
seed oil using an alkali catalyst. The effect of methanol to 
oil ratio, reaction temperature, and catalyst weight on the 
yield and quality of biodiesel have been studied. Biodiesel 
produced was characterized according to international fuel 
testing standards methods. The optimization of process 
parameters was carried out using Response Surface 
Method (RSM).

The experimental result showed that the highest yield of 
biodiesel was 94% and this result was obtained at an 
optimum value of temperature 55°C, methanol to oil ratio of 
6:1, and catalyst load of 1.0%. Increasing methanol to oil 
ratio, temperature, and catalyst load up to the optimum point 
increased the yield of biodiesel. However, further increase of 
the parameters above the optimum point decreased the yield 
of biodiesel. The temperature has the highest significant 
effect while the catalyst load has a lower effect. 

Besides to characterization of different basic fuel properties 
of it, biodiesel can be blended with petrol-diesel at different 
percentages and applied in compression ignition engine to 
evaluate the effect of using a blend of biodiesel using differ-

ent parameters such as engine power, brake thermal efficien-
cy, specific fuel consumption, exhaust gas temperature, and 
greenhouse gas temperature and gas emission. However, the 
performance analysis of the blend of biodiesel with petrol 
diesel in a compression ignition engine was not done due to a 
lack of laboratory setup and equipment required to measure 
these parameters. This study did not compare biodiesel with 
diesel fuels used in diesel engines. Moreover, it did not 
characterize the blend of biodiesel with petroleum fuels and 
did not compare biodiesel produced from other feedstocks 
other than moringa stenopetala. Thus, further research should 
be done on these areas. 

Generally, it can be concluded that moringa stenopetala is a 
promising alternative feedstock for biodiesel production for 
the reasons: it does not affect food security, has a good oil 
content, and can be harvested throughout the year.  The 
biodiesel produced meets the standard fuel quality and 
international standard specifications. 

Acknowledgment

The authors are thankful to Addis Ababa institute of Technol-
ogy, Addis Ababa University, Ethiopian Environment and 
Forest Research Institute, College of Natural and Computa-
tional Science, Addis Ababa University, and Ethiopian 
Geological Survey for their technical support.

References

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characterization for use as a fuel in compression in 
ignition engines, J Eng Gas Turbines Power. 123(2): 
440-447. DOI: 10.1115/1.1364522

Atabani AE, Silitonga AS,  Ong HC, Mahila TM, Masjuki 
HH,  Irfan A and Fayaz H (2013), Non-edible 
vegetable oils: evaluation of oil extraction, fatty acid 
compositions, biodiesel production, characteristics, 
engine performance and emissions production, Ren. 
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Atabani AE, Mahlia TM, Ifran A, Masjuki HH, Chong WT 
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Ayerza HR (2012), Seed and oil yields of moringa oleifera 
variety periyakalum-1 introduced for oil production in 
four ecosystems of South America, Ind. Crops Prod. 
36: 70-73. DOI: 10.1016/j.indcrop.2011.08.008

Azad A, Rasul M, Khan K, Subhash CS and Rubayat I 
(2015), Prospect of Moringa Seed oil is a 
sustainable biodiesel fuel in Australia, Procedia 
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energy sources, biomasscombustion problems in boiler 
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transesterification, Procedia Engineering. 53: 7-12. 
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Gemechu YS (2021), Production and Characterization of 
Biodiesel from Moringa Stenopetala Seed Oil via 
Catalytic Transesterification Process, Thesis work at 
Addis Ababa University Institute of Technology, Addis 
Ababa, Ethiopia.

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trees: from a nutritionaland medicinal point of view in 
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M and Liaquat AM (2011), Prospects of dedicated 
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(2017), Production, characterization and performance 
of Biodiesel as an alternative fuel in diesel engines, 
Renewable and Sustainable Energy Reviews 72(c): 
497-509. DOI: 10.1016/j.rser.2017.01.001 

Piyush N, Subramanian KA and Dastidar MG (2013), 
Production and characterization of Biodieselfrom 
algae, Fuel processing technology. 120: 79-88. DOI: 
10.1016/j.fuproc.2013.12.003 

Raj S and Bhandari M (2017), Comparison of methods of 
production of biodiesel from Jatropha curcas, Journal 
of Biofuel. 8(2): 58-80.

Rao PV (2011), Experimental investigations on the 
influence of properties of jatropha biodiesel on 
performance, combustion, and emission 
characteristics of DI–CI engines, World Acad. Sci. 
Eng. Technol. 5(3): 855-868.

Sreepada H and Vijayalaxmi H (2013), An overview of 
moringa production in Ethiopia, International Journal 
of Science and Research 4(4): 2319-7064. DOI: 
10.36106/ijsr

Seema R and Meena B (2017), Comparison of methods of 
biodiesel productionfrom Jatropha Curcas, Journal of 
Biofuels. 8(2): 58-80.

its advantages is it is considered a great natural cosmetic 
emollient and has high oxidative stability (Ayerza, 2012).

Moringa plant is a high-value tree of the Moringaceae family. 
It consists of 13 species highly distributed in Africa and Asia 
(Hamza and Azmach, 2017). Moringa is particularly suitable 
for dry regions since it can be grown using rainwater without 
expensive irrigation techniques.  Moringa has been given less 
attention and ignored tree by communities to utilize it in 
different ways (Gemeda and Desta, 2020). Flowering begins 
within the first six months. Moringa stenopetala seed is an 
available and underutilized resource. Ethiopia has a comfort-
able environment for mooring stenopetala plantations. Many 
parts of the country particularly southern parts such as Gamo 
Goffa, Sidama Wolayitta, Konso, and Darashe have planted 
moringa in their garden and farmland (Sreepada and Vijay-
alaxmi, 2013). Thus, this study investigated that moringa 
stenopetala seed oil is a potential industrial feedstock for 
biodiesel production as an alternative energy source.

Materials and methods

The sample of Moringa seed was collected from the Gamo 
Goffa Zone, Arba Minch area of Ethiopia. The seed sample 

was dried and milled to reduce the particle size. Then, 80 g of 
sample was measured and put into the soxhlet apparatus 
thimble. Then, it was placed in a 500 mL capacity soxhlet 
chamber. 400 mL solvent (Hexane) was used for the 
extraction at different temperatures for 3 hrs. to 5 hrs. The 
extraction was conducted at 70°C, 75°C, and 80°C by 
varying extraction time to get the maximum possible oil 
yield.  The soxhlet extraction method was selected since it 
results in high oil yield, is quick, the solvent can be reused, 
and is low cost (Sreepada and Vijayalaxmi, 2013). The 
unwanted substances were removed by evaporation and 
degumming. Evaporation was used to separate hexane from 

Table IV. Standard methods (ASTM D 6751 and EN 
14214)  for physical and chemical properties of 
biodiesel 

Property Standard Methods 

Specific gravity EN 14214 

Kinematic viscosity ASTM D445 

Saponification value ASTM D5558  

Acid value EN 14104 

Calorific value ASTM D240 

Flash and fire point ASTM D93 

Moisture content EN 14774 -1 

Iodine value EN 14111 

Pour point ASTM D5771 

Cloud point ASTM D6950 

Factor 1 Factor 2 Factor 3 Response 1
Std 

Run oil ratio 
A: Methanol to         B: C: Catalyst

Temperature loading 
Yield 

- °C wt.% % 
10 1 6 65 0.5 86.67 
3 2 3 65 1 78.18 

13 3 6 55 1 93.81 
2 4 9 45 1 78.18 
9 5 6 45 0.5 76.36 
4 6 9 65 1 81.82 

12 7 6 65 1.5 88.34 
8 8 9 55 1.5 85.45 

15 9 6 55 1 93.84 
7 10 3 55 1.5 80 
5 11 3 55 0.5 72.71 

11 12 6 45 1.5 76.67 
14 13 6 55 1 94 
17 14 6 55 1 93.27 
16 15 6 55 1 93.92 
6 16 9 55 0.5 83.63 
1 17 3 45 1 76.67 

Table V. Biodiesel Yield response of experimental runs



Biodiesel from moringa stenopetala seed oil 58(1) 202340

The most common production technology of biodiesel is the 
transesterification process. Transesterification is a chemical 
reaction between one mole of triglyceride with three moles of 
alcohol to produce fatty acid methyl ester and glycerol in the 
presence of a catalyst or without a catalyst. Most transesteri-
fication reactions use ethanol or methanol alcohol. Many 
studies show that methanol is more practically used as 
alcohol than ethanol. Methanol is preferable due to its low 
cost and its physical and chemical advantages. Another 
advantage of using methanol is the ease of separation of 
glycerin which can be achieved by simple decantation 
(Marchetti and Yadessa, 2012).

Various catalysts can be used in the process. However, it was 
confirmed that the transesterification reaction was completed 
very fast when alkali catalysts are used. After the transesterifi-
cation reaction is completed, glycerol, catalyst, alcohol, and 
soap are separated from biodiesel. The factors affecting 
biodiesel yield and fuel quality are alcohol-to-oil ratios, 
temperature, catalyst loading, and reaction time (Raj and Bhan-
dari, 2017). Biodiesel is formed when triglyceride reacts with 
alcohol leaving glycerol as a byproduct as shown in Figure 1.

There are more than 300 vegetable oils identified as potential 
feedstocks for biodiesel production globally. The availability, 
characteristics, and variety of feedstocks make them promis-
ing ingredients for the sustainable production of biodiesel 
(Piyush et al. 2013). Researchers have proposed Moringa 
seed oil as an alternative potential feedstock to produce 
biodiesel. However, there is a research gap that promotes this 
feedstock for industrial processing. Moringa seed has an 
average of 35%-45% oil content with high oleic content of 
greater than 73% based on the type of the tree. Moringa oil 
has many various industrial and homemade benefits. One of 

oil by rotary evaporation at 80°C. Gum and wax were 
removed by a degumming method. Then, biodiesel was 
synthesized by transesterification reaction using a homoge-
nous catalyst (methanol) at different process parameters.

Experimental design

The experimental design used for this study was a Box 
Behnken design standard using design expert 11.0 software. 
The experimental design was done using three variables and 
tree levels for a response surface method. 17 experimental 
runswere selected by design expert 11.0 software using the 
Box Behnken design standard method, with five central 
points per block. The main factors that affect biodiesel 
production by transesterification reaction are reaction time, 
reaction temperature, and alcohol-to-oil ratio (Seema and 
Meena, 2017). As indicated in Table I, the overall production 
of biodiesel was carried out at optimum parameters of 
catalyst load of 0.5 to 1.5 wt.%, reaction temperature of 45 to 
65°C, and methanol to oil ratio of 3 to 9.  

The other parameters, reaction time and mixing intensity 
were kept constant at 1 hour and 500 rpm for all experimental 
runs. A combination of three factors and three levels of 
experimental runs was conducted. There are 17 experimental 
runs determined byBox Behnken’s design arrangement as 
shown in Table II.

Production and purification of the product

The method used to produce biodiesel was a one-steptranses-
terification reaction. Methanol was the alcohol selected for 
the transesterification reaction due to its availability, low 
cost, popularity, and ease of separation (Demirbas, 2005). 
The catalyst selected for this study was the base catalyst 
(KOH) since biodiesel can be produced at low temperatures 
and pressure reactions. Moreover, it is a homogeneous base 
catalyst that results in high conversion, minimum side 
reactions, short reaction time, and high yield (Marchetti and 

Yadessa, 2012). Though it has many advantages, the disad-
vantage of the catalyst used is it cannot be reused.

When the reaction is completed, biodiesel and glycerol were 
separated by a separatory funnel after it settles for 24 hours. 
Then, biodiesel was washed with hot distilled water to 
remove soap, remaining methanol, and wax.

Optimization of the process parameters using the Response 
Surface Method (RSM).

Optimization aims to determine the optimum value of the 
factors that affect the transesterification process to produce 
the maximum possible biodiesel yield at a minimum produc-
tion cost. This is done by minimizing the methanol to oil 
ratio, reaction temperature, and amount of catalyst used as 
indicated in Table III.

Characterization of biodiesel

Characterization of fuel is determining the physical and 
chemical properties (Atabani et al. 2013). The physical and 
chemical properties of biodiesel were determined according 
to the American Society for Testing Materials (ASTM D 
6751) and European standard (EN 14214) methods (Demir-
bas, 2005). Table IV showed the physical and chemical 
properties of biodiesel and the standard methods used to 
determine them.

Statistical analysis of experimental results

Data analysis of the experiment was done by design expert 
11.0 software using Box Behnken design standard. The 
significance of experimental variables was obtained from 
analysis of variance (ANOVA). 

Results and discussions

Yield

The maximum oil yield obtained at optimum conditions of 
temperature 80°C and extraction time 5 hours was 39.86 %. 
This result agreed with the average oil content of Moringa 
stenopetala seed oil which is 35% - 45% (Ayerza, 2012), and 
this result also agreed with the previous reportof 38% which 
was reported by Azad et al. (2015) and by Gemechu (2021).

The maximum yield of biodiesel was 94% and it was 
obtained at optimum process parameters of methanol to oil 
ratio 6:1, temperature 55°C, and catalyst loading 1.0%.  The 
yield of biodiesel obtained agrees with the previous report of 

Azad et al. (2015) which was 91%. The yield increased as 
transesterification parameters increased until the optimum 
value and decreased beyond the optimum value. At the lower 
value of parameters, the yield decreased due to the incom-
plete conversion of reactants to the product. Table V showed 
the yield response of all experimental runs.

Characterization of biodiesel

Physical and chemical properties of biodiesel were evaluated 
using standard methods and the results were compared with 
ASTM and EN standard methods and previous reports.

Density

The value of the density of biodiesel was 874 kg/m3. This 
result is within the standard range of density (860 – 900 
kg/m3) (Demirbas, 2005) and agrees with the previous report 
by Kafuku and Mbarawa (2010) which was 900 kg/m3. 
Higher density increases thesize of fuel droplets and causes 
higher emission of particulate matter and NOx emission ina 
diesel engine while the lower density of fuel expands the 
efficiency of atomization (Choi and Reitz, 1999).

Kinematic viscosity

The experimental result showed that the value of kinematic 
viscosity was 4.8 mm2/s. This result is within the range of the 
ASTM standard value of biodiesel which is 1.6-6 (Eman and 
Cadence, 2013; Demirbas, 2005). Highly viscous fuel is 
difficult to pump and operate in internal combustion engines 
while lower kinematic viscosity of fuels increases wear 
leakage due to insufficient lubrication (Rao, 2011).

Acid value

The value of an acid value obtained was 0.4 mm KOH/g.  
This result agrees with the previous report (Kafuku and 
Mbarawa, 2010), with a value of 1.2 mmKOH/g. Higher 
acid-value fuels need further acid treatment costs and it also 
lowers the quality of the fuels. In this study, the lower acid 
value of biodiesel indicates that it has higher fuel quality.

Calorific value

The experimental result showed that the value of biodiesel 
was 10287 Cal/ g or 43 MJ/kJ. This result agrees with the 
previous report of Mahamudul et al. (2017) which was 39 

MJ/kg, and the previous report of Agarwal and Das (2001) 
which was 43.2 kJ/kg. The result obtained is above the 
standard ASTM value which is 42-42.5 MJ/kg. This result 
indicates the higher fuel quality of biodiesel. The calorific 
value obtained is similar to that of conventional diesel fuels. 
This is the novel result of this study.

Flash point

The flash point obtained from the experimental result was 
184°C. This result agrees with the standard ASTM value of 
biodiesel flash point which is greater than 130°C. From this 
study, the higher flash point of biodiesel indicates that it is 
safer to handle, store and transport the fuel (Jayed et al. 
2011).

Cetane number

The value of the cetane number observed was 53. This result 
agrees with the standard ASTM value of the cetane number 
of biodiesel which is greater than 47 (Demirbas, 2005). Fuels 
with higher cetane number benefit the engine performance 
since the engine starts rapidly and run smoothly without 
causing much noise.

Cloud and Pour point

The experimental result showed that the cloud and pour 
points of biodiesel were 10°C and 1°C respectively. This 
result agrees with the previous report of Kafuku and Mbara-
wa (2010) which was 10°C and 3°C respectively. Cloud and 
pour point of fuel indicates the fuel performance at low ambi-
ent temperature (Agarwal and Das, 2001). Table VI showed 
the result of all main physicochemical properties of biodiesel 
synthesized.

Statistical analysis of experimental results 

Analysis of variance (ANOVA) for the quadratic model

Analysis of variance determines the significance of the 
experimental results using coded variables as indicated in 
Table VII. 

The Model F-value of 380.98 implies the model is signifi-
cant. There is only a 0.01% chance that an F-value this large 
could occur due to noise.

P-values less than 0.0500 indicate model terms are signifi-
cant. In this case, A, B, C, A², B², C² are significant model 
terms. Values greater than 0.1000 indicate the model terms 
are not significant. If there are many insignificant model 
terms (not counting those required to support hierarchy), 
model reduction may improve your model.

The Lack of Fit F-value of 5.69 implies there is a 6.31% 
chance that a Lack of Fit F-value this large could occur due to 
noise. Lack of fit is bad -- we want the model to fit. This 
relatively low probability (<10%) is troubling.

The coefficient estimate represents the expected change in 
response per unit change in factor value when all remaining 
factors are held constant. The intercept in an orthogonal 
design is the overall average response of all the runs. The 
coefficients are adjustments around that average based on the 

factor settings. When the factors are orthogonal the VIFs are 
1; VIFs greater than 1 indicate multi-collinearity, and the 
higher the VIF the more severe the correlation of factors. As 
a rough rule, VIFs less than 10 are tolerable.

The effect of process parameters on the yield of biodiesel

Effect of methanol to oil ratio

Figure. (2) Shows the effect of methanol to oil ratio on 
biodiesel yield at constant temperature and catalyst loading. 
It showed that the yield of biodiesel increases as the metha-
nol-to-oil ratio increases. Increasing the methanol-to-oil ratio 
beyond the optimum value results in excess methanol which 
decreases the yield of biodiesel. The maximum yield of 
biodiesel (94%) was obtained at a methanol-to-oil ratio of 6: 
1. Therefore, this ratio was taken as an optimum value of the 
methanol-to-oil ratio. Decreasing the methanol-to-oil ratio 

below the optimum value (3:1), decreased the conversion 
efficiency of the transesterification reaction and resulted in 
lower biodiesel yield.

Effect of reaction temperature

Figure (3) shows the effect of reaction temperature on the 
yield of biodiesel at a constant methanol-to-oil ratio and 
catalyst loading. The yield of biodiesel highly increased as 

temperature increased from 45°C to 55°C.  Maximum yield 
was obtained at 58°C and the yield started to decrease slight-
ly from 58°C to 65°C due to the vaporization of methanol 
resulting in soap formation. The boiling point of methanol is 
64.7°C. Increasing reaction temperature above this point 
leads to methanol loss by evaporation and decreases the 
conversion efficiency of the reaction. At 45°C, the yield is 
about 75°C.

Effect of catalyst loading

Figure (4) shows the effect of catalyst loading on the yield of 
biodiesel at a constant methanol-to-oil ratio and temperature.  
As the amount of catalyst increased from 0.5% to 1.0%, the 
yield of biodiesel increased from 89% to 94% and the yield 
starts to decrease slightly as the amount of catalyst increased 
from 1.0% to 1.5% due to the formation of soap and emul-
sion. At a lower amount of catalyst (0.5%), the yield of 
biodiesel decreased due to the incomplete conversion of 
triglycerides of oil to fatty acid methyl ester.

Optimization of transesterification process parameters using 
the Response Surface Method (RSM)

The Response Surface Method determined the optimum 
value of process variables that maximize the yield of the 
product and minimize production cost

Table VIII showed that Response Surface Method found 15 
solutions and selected the optimum values to minimize the 
economic cost of Temperature, Methanol, and Catalyst 
required for the reaction and to maximize the yield of 
biodiesel. The optimum yield of biodiesel (83.772%) was 
observed at a temperature of 51.537 and catalyst load of 
0.500 wt.%.

Conclusions

Biodiesel is a promising biofuel that is synthesized by the 
transesterification of vegetable oils and animal fats. In this 
study, biodiesel was synthesized from moringa stenopetala 
seed oil using an alkali catalyst. The effect of methanol to 
oil ratio, reaction temperature, and catalyst weight on the 
yield and quality of biodiesel have been studied. Biodiesel 
produced was characterized according to international fuel 
testing standards methods. The optimization of process 
parameters was carried out using Response Surface 
Method (RSM).

The experimental result showed that the highest yield of 
biodiesel was 94% and this result was obtained at an 
optimum value of temperature 55°C, methanol to oil ratio of 
6:1, and catalyst load of 1.0%. Increasing methanol to oil 
ratio, temperature, and catalyst load up to the optimum point 
increased the yield of biodiesel. However, further increase of 
the parameters above the optimum point decreased the yield 
of biodiesel. The temperature has the highest significant 
effect while the catalyst load has a lower effect. 

Besides to characterization of different basic fuel properties 
of it, biodiesel can be blended with petrol-diesel at different 
percentages and applied in compression ignition engine to 
evaluate the effect of using a blend of biodiesel using differ-

ent parameters such as engine power, brake thermal efficien-
cy, specific fuel consumption, exhaust gas temperature, and 
greenhouse gas temperature and gas emission. However, the 
performance analysis of the blend of biodiesel with petrol 
diesel in a compression ignition engine was not done due to a 
lack of laboratory setup and equipment required to measure 
these parameters. This study did not compare biodiesel with 
diesel fuels used in diesel engines. Moreover, it did not 
characterize the blend of biodiesel with petroleum fuels and 
did not compare biodiesel produced from other feedstocks 
other than moringa stenopetala. Thus, further research should 
be done on these areas. 

Generally, it can be concluded that moringa stenopetala is a 
promising alternative feedstock for biodiesel production for 
the reasons: it does not affect food security, has a good oil 
content, and can be harvested throughout the year.  The 
biodiesel produced meets the standard fuel quality and 
international standard specifications. 

Acknowledgment

The authors are thankful to Addis Ababa institute of Technol-
ogy, Addis Ababa University, Ethiopian Environment and 
Forest Research Institute, College of Natural and Computa-
tional Science, Addis Ababa University, and Ethiopian 
Geological Survey for their technical support.

References

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Biodiesel from Moringa Stenopetala Seed Oil via 
Catalytic Transesterification Process, Thesis work at 
Addis Ababa University Institute of Technology, Addis 
Ababa, Ethiopia.

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trees: from a nutritionaland medicinal point of view in 
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M and Liaquat AM (2011), Prospects of dedicated 
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its advantages is it is considered a great natural cosmetic 
emollient and has high oxidative stability (Ayerza, 2012).

Moringa plant is a high-value tree of the Moringaceae family. 
It consists of 13 species highly distributed in Africa and Asia 
(Hamza and Azmach, 2017). Moringa is particularly suitable 
for dry regions since it can be grown using rainwater without 
expensive irrigation techniques.  Moringa has been given less 
attention and ignored tree by communities to utilize it in 
different ways (Gemeda and Desta, 2020). Flowering begins 
within the first six months. Moringa stenopetala seed is an 
available and underutilized resource. Ethiopia has a comfort-
able environment for mooring stenopetala plantations. Many 
parts of the country particularly southern parts such as Gamo 
Goffa, Sidama Wolayitta, Konso, and Darashe have planted 
moringa in their garden and farmland (Sreepada and Vijay-
alaxmi, 2013). Thus, this study investigated that moringa 
stenopetala seed oil is a potential industrial feedstock for 
biodiesel production as an alternative energy source.

Materials and methods

The sample of Moringa seed was collected from the Gamo 
Goffa Zone, Arba Minch area of Ethiopia. The seed sample 

was dried and milled to reduce the particle size. Then, 80 g of 
sample was measured and put into the soxhlet apparatus 
thimble. Then, it was placed in a 500 mL capacity soxhlet 
chamber. 400 mL solvent (Hexane) was used for the 
extraction at different temperatures for 3 hrs. to 5 hrs. The 
extraction was conducted at 70°C, 75°C, and 80°C by 
varying extraction time to get the maximum possible oil 
yield.  The soxhlet extraction method was selected since it 
results in high oil yield, is quick, the solvent can be reused, 
and is low cost (Sreepada and Vijayalaxmi, 2013). The 
unwanted substances were removed by evaporation and 
degumming. Evaporation was used to separate hexane from 

Table VI. Summary of physicochemical properties of moringa stenopetala seed biodiesel

Property  Result  Unit Standard method 
used 

Moisture  1.4 % ASTM D4442-07 

Ph 7.9 -  

Density at 15°C  874 Kg/m3 EN 3675 

Kinematic viscosity at 22°C 4.8 mm2/s ASTM D445 

Acid value 0.4 mg KOH/g  ASTM D664 

Saponification value 196 mg KOH/g   

Free fatty acid 0.2  %  

Iodine value 104.5 g I2 /100 g EN 14111 

Calorific value 10,287 Cal/g ASTM D240 

Flash point 184  °C  ASTM D93 

Cetane number 53 - ASTM D 6751 

Fire point 190 °C  ASTM D93 

Specific gravity 0.874 g/mole EN 14214  

Cloud point 10 °c ASTM D6950 

Pour point 1 °c ASTM D5771 



Shage and Ali 41

The most common production technology of biodiesel is the 
transesterification process. Transesterification is a chemical 
reaction between one mole of triglyceride with three moles of 
alcohol to produce fatty acid methyl ester and glycerol in the 
presence of a catalyst or without a catalyst. Most transesteri-
fication reactions use ethanol or methanol alcohol. Many 
studies show that methanol is more practically used as 
alcohol than ethanol. Methanol is preferable due to its low 
cost and its physical and chemical advantages. Another 
advantage of using methanol is the ease of separation of 
glycerin which can be achieved by simple decantation 
(Marchetti and Yadessa, 2012).

Various catalysts can be used in the process. However, it was 
confirmed that the transesterification reaction was completed 
very fast when alkali catalysts are used. After the transesterifi-
cation reaction is completed, glycerol, catalyst, alcohol, and 
soap are separated from biodiesel. The factors affecting 
biodiesel yield and fuel quality are alcohol-to-oil ratios, 
temperature, catalyst loading, and reaction time (Raj and Bhan-
dari, 2017). Biodiesel is formed when triglyceride reacts with 
alcohol leaving glycerol as a byproduct as shown in Figure 1.

There are more than 300 vegetable oils identified as potential 
feedstocks for biodiesel production globally. The availability, 
characteristics, and variety of feedstocks make them promis-
ing ingredients for the sustainable production of biodiesel 
(Piyush et al. 2013). Researchers have proposed Moringa 
seed oil as an alternative potential feedstock to produce 
biodiesel. However, there is a research gap that promotes this 
feedstock for industrial processing. Moringa seed has an 
average of 35%-45% oil content with high oleic content of 
greater than 73% based on the type of the tree. Moringa oil 
has many various industrial and homemade benefits. One of 

oil by rotary evaporation at 80°C. Gum and wax were 
removed by a degumming method. Then, biodiesel was 
synthesized by transesterification reaction using a homoge-
nous catalyst (methanol) at different process parameters.

Experimental design

The experimental design used for this study was a Box 
Behnken design standard using design expert 11.0 software. 
The experimental design was done using three variables and 
tree levels for a response surface method. 17 experimental 
runswere selected by design expert 11.0 software using the 
Box Behnken design standard method, with five central 
points per block. The main factors that affect biodiesel 
production by transesterification reaction are reaction time, 
reaction temperature, and alcohol-to-oil ratio (Seema and 
Meena, 2017). As indicated in Table I, the overall production 
of biodiesel was carried out at optimum parameters of 
catalyst load of 0.5 to 1.5 wt.%, reaction temperature of 45 to 
65°C, and methanol to oil ratio of 3 to 9.  

The other parameters, reaction time and mixing intensity 
were kept constant at 1 hour and 500 rpm for all experimental 
runs. A combination of three factors and three levels of 
experimental runs was conducted. There are 17 experimental 
runs determined byBox Behnken’s design arrangement as 
shown in Table II.

Production and purification of the product

The method used to produce biodiesel was a one-steptranses-
terification reaction. Methanol was the alcohol selected for 
the transesterification reaction due to its availability, low 
cost, popularity, and ease of separation (Demirbas, 2005). 
The catalyst selected for this study was the base catalyst 
(KOH) since biodiesel can be produced at low temperatures 
and pressure reactions. Moreover, it is a homogeneous base 
catalyst that results in high conversion, minimum side 
reactions, short reaction time, and high yield (Marchetti and 

Yadessa, 2012). Though it has many advantages, the disad-
vantage of the catalyst used is it cannot be reused.

When the reaction is completed, biodiesel and glycerol were 
separated by a separatory funnel after it settles for 24 hours. 
Then, biodiesel was washed with hot distilled water to 
remove soap, remaining methanol, and wax.

Optimization of the process parameters using the Response 
Surface Method (RSM).

Optimization aims to determine the optimum value of the 
factors that affect the transesterification process to produce 
the maximum possible biodiesel yield at a minimum produc-
tion cost. This is done by minimizing the methanol to oil 
ratio, reaction temperature, and amount of catalyst used as 
indicated in Table III.

Characterization of biodiesel

Characterization of fuel is determining the physical and 
chemical properties (Atabani et al. 2013). The physical and 
chemical properties of biodiesel were determined according 
to the American Society for Testing Materials (ASTM D 
6751) and European standard (EN 14214) methods (Demir-
bas, 2005). Table IV showed the physical and chemical 
properties of biodiesel and the standard methods used to 
determine them.

Statistical analysis of experimental results

Data analysis of the experiment was done by design expert 
11.0 software using Box Behnken design standard. The 
significance of experimental variables was obtained from 
analysis of variance (ANOVA). 

Results and discussions

Yield

The maximum oil yield obtained at optimum conditions of 
temperature 80°C and extraction time 5 hours was 39.86 %. 
This result agreed with the average oil content of Moringa 
stenopetala seed oil which is 35% - 45% (Ayerza, 2012), and 
this result also agreed with the previous reportof 38% which 
was reported by Azad et al. (2015) and by Gemechu (2021).

The maximum yield of biodiesel was 94% and it was 
obtained at optimum process parameters of methanol to oil 
ratio 6:1, temperature 55°C, and catalyst loading 1.0%.  The 
yield of biodiesel obtained agrees with the previous report of 

Azad et al. (2015) which was 91%. The yield increased as 
transesterification parameters increased until the optimum 
value and decreased beyond the optimum value. At the lower 
value of parameters, the yield decreased due to the incom-
plete conversion of reactants to the product. Table V showed 
the yield response of all experimental runs.

Characterization of biodiesel

Physical and chemical properties of biodiesel were evaluated 
using standard methods and the results were compared with 
ASTM and EN standard methods and previous reports.

Density

The value of the density of biodiesel was 874 kg/m3. This 
result is within the standard range of density (860 – 900 
kg/m3) (Demirbas, 2005) and agrees with the previous report 
by Kafuku and Mbarawa (2010) which was 900 kg/m3. 
Higher density increases thesize of fuel droplets and causes 
higher emission of particulate matter and NOx emission ina 
diesel engine while the lower density of fuel expands the 
efficiency of atomization (Choi and Reitz, 1999).

Kinematic viscosity

The experimental result showed that the value of kinematic 
viscosity was 4.8 mm2/s. This result is within the range of the 
ASTM standard value of biodiesel which is 1.6-6 (Eman and 
Cadence, 2013; Demirbas, 2005). Highly viscous fuel is 
difficult to pump and operate in internal combustion engines 
while lower kinematic viscosity of fuels increases wear 
leakage due to insufficient lubrication (Rao, 2011).

Acid value

The value of an acid value obtained was 0.4 mm KOH/g.  
This result agrees with the previous report (Kafuku and 
Mbarawa, 2010), with a value of 1.2 mmKOH/g. Higher 
acid-value fuels need further acid treatment costs and it also 
lowers the quality of the fuels. In this study, the lower acid 
value of biodiesel indicates that it has higher fuel quality.

Calorific value

The experimental result showed that the value of biodiesel 
was 10287 Cal/ g or 43 MJ/kJ. This result agrees with the 
previous report of Mahamudul et al. (2017) which was 39 

MJ/kg, and the previous report of Agarwal and Das (2001) 
which was 43.2 kJ/kg. The result obtained is above the 
standard ASTM value which is 42-42.5 MJ/kg. This result 
indicates the higher fuel quality of biodiesel. The calorific 
value obtained is similar to that of conventional diesel fuels. 
This is the novel result of this study.

Flash point

The flash point obtained from the experimental result was 
184°C. This result agrees with the standard ASTM value of 
biodiesel flash point which is greater than 130°C. From this 
study, the higher flash point of biodiesel indicates that it is 
safer to handle, store and transport the fuel (Jayed et al. 
2011).

Cetane number

The value of the cetane number observed was 53. This result 
agrees with the standard ASTM value of the cetane number 
of biodiesel which is greater than 47 (Demirbas, 2005). Fuels 
with higher cetane number benefit the engine performance 
since the engine starts rapidly and run smoothly without 
causing much noise.

Cloud and Pour point

The experimental result showed that the cloud and pour 
points of biodiesel were 10°C and 1°C respectively. This 
result agrees with the previous report of Kafuku and Mbara-
wa (2010) which was 10°C and 3°C respectively. Cloud and 
pour point of fuel indicates the fuel performance at low ambi-
ent temperature (Agarwal and Das, 2001). Table VI showed 
the result of all main physicochemical properties of biodiesel 
synthesized.

Statistical analysis of experimental results 

Analysis of variance (ANOVA) for the quadratic model

Analysis of variance determines the significance of the 
experimental results using coded variables as indicated in 
Table VII. 

The Model F-value of 380.98 implies the model is signifi-
cant. There is only a 0.01% chance that an F-value this large 
could occur due to noise.

P-values less than 0.0500 indicate model terms are signifi-
cant. In this case, A, B, C, A², B², C² are significant model 
terms. Values greater than 0.1000 indicate the model terms 
are not significant. If there are many insignificant model 
terms (not counting those required to support hierarchy), 
model reduction may improve your model.

The Lack of Fit F-value of 5.69 implies there is a 6.31% 
chance that a Lack of Fit F-value this large could occur due to 
noise. Lack of fit is bad -- we want the model to fit. This 
relatively low probability (<10%) is troubling.

The coefficient estimate represents the expected change in 
response per unit change in factor value when all remaining 
factors are held constant. The intercept in an orthogonal 
design is the overall average response of all the runs. The 
coefficients are adjustments around that average based on the 

factor settings. When the factors are orthogonal the VIFs are 
1; VIFs greater than 1 indicate multi-collinearity, and the 
higher the VIF the more severe the correlation of factors. As 
a rough rule, VIFs less than 10 are tolerable.

The effect of process parameters on the yield of biodiesel

Effect of methanol to oil ratio

Figure. (2) Shows the effect of methanol to oil ratio on 
biodiesel yield at constant temperature and catalyst loading. 
It showed that the yield of biodiesel increases as the metha-
nol-to-oil ratio increases. Increasing the methanol-to-oil ratio 
beyond the optimum value results in excess methanol which 
decreases the yield of biodiesel. The maximum yield of 
biodiesel (94%) was obtained at a methanol-to-oil ratio of 6: 
1. Therefore, this ratio was taken as an optimum value of the 
methanol-to-oil ratio. Decreasing the methanol-to-oil ratio 

below the optimum value (3:1), decreased the conversion 
efficiency of the transesterification reaction and resulted in 
lower biodiesel yield.

Effect of reaction temperature

Figure (3) shows the effect of reaction temperature on the 
yield of biodiesel at a constant methanol-to-oil ratio and 
catalyst loading. The yield of biodiesel highly increased as 

temperature increased from 45°C to 55°C.  Maximum yield 
was obtained at 58°C and the yield started to decrease slight-
ly from 58°C to 65°C due to the vaporization of methanol 
resulting in soap formation. The boiling point of methanol is 
64.7°C. Increasing reaction temperature above this point 
leads to methanol loss by evaporation and decreases the 
conversion efficiency of the reaction. At 45°C, the yield is 
about 75°C.

Effect of catalyst loading

Figure (4) shows the effect of catalyst loading on the yield of 
biodiesel at a constant methanol-to-oil ratio and temperature.  
As the amount of catalyst increased from 0.5% to 1.0%, the 
yield of biodiesel increased from 89% to 94% and the yield 
starts to decrease slightly as the amount of catalyst increased 
from 1.0% to 1.5% due to the formation of soap and emul-
sion. At a lower amount of catalyst (0.5%), the yield of 
biodiesel decreased due to the incomplete conversion of 
triglycerides of oil to fatty acid methyl ester.

Optimization of transesterification process parameters using 
the Response Surface Method (RSM)

The Response Surface Method determined the optimum 
value of process variables that maximize the yield of the 
product and minimize production cost

Table VIII showed that Response Surface Method found 15 
solutions and selected the optimum values to minimize the 
economic cost of Temperature, Methanol, and Catalyst 
required for the reaction and to maximize the yield of 
biodiesel. The optimum yield of biodiesel (83.772%) was 
observed at a temperature of 51.537 and catalyst load of 
0.500 wt.%.

Conclusions

Biodiesel is a promising biofuel that is synthesized by the 
transesterification of vegetable oils and animal fats. In this 
study, biodiesel was synthesized from moringa stenopetala 
seed oil using an alkali catalyst. The effect of methanol to 
oil ratio, reaction temperature, and catalyst weight on the 
yield and quality of biodiesel have been studied. Biodiesel 
produced was characterized according to international fuel 
testing standards methods. The optimization of process 
parameters was carried out using Response Surface 
Method (RSM).

The experimental result showed that the highest yield of 
biodiesel was 94% and this result was obtained at an 
optimum value of temperature 55°C, methanol to oil ratio of 
6:1, and catalyst load of 1.0%. Increasing methanol to oil 
ratio, temperature, and catalyst load up to the optimum point 
increased the yield of biodiesel. However, further increase of 
the parameters above the optimum point decreased the yield 
of biodiesel. The temperature has the highest significant 
effect while the catalyst load has a lower effect. 

Besides to characterization of different basic fuel properties 
of it, biodiesel can be blended with petrol-diesel at different 
percentages and applied in compression ignition engine to 
evaluate the effect of using a blend of biodiesel using differ-

ent parameters such as engine power, brake thermal efficien-
cy, specific fuel consumption, exhaust gas temperature, and 
greenhouse gas temperature and gas emission. However, the 
performance analysis of the blend of biodiesel with petrol 
diesel in a compression ignition engine was not done due to a 
lack of laboratory setup and equipment required to measure 
these parameters. This study did not compare biodiesel with 
diesel fuels used in diesel engines. Moreover, it did not 
characterize the blend of biodiesel with petroleum fuels and 
did not compare biodiesel produced from other feedstocks 
other than moringa stenopetala. Thus, further research should 
be done on these areas. 

Generally, it can be concluded that moringa stenopetala is a 
promising alternative feedstock for biodiesel production for 
the reasons: it does not affect food security, has a good oil 
content, and can be harvested throughout the year.  The 
biodiesel produced meets the standard fuel quality and 
international standard specifications. 

Acknowledgment

The authors are thankful to Addis Ababa institute of Technol-
ogy, Addis Ababa University, Ethiopian Environment and 
Forest Research Institute, College of Natural and Computa-
tional Science, Addis Ababa University, and Ethiopian 
Geological Survey for their technical support.

References

Agarwal AK and Das LM (2001), Biodiesel development and 
characterization for use as a fuel in compression in 
ignition engines, J Eng Gas Turbines Power. 123(2): 
440-447. DOI: 10.1115/1.1364522

Atabani AE, Silitonga AS,  Ong HC, Mahila TM, Masjuki 
HH,  Irfan A and Fayaz H (2013), Non-edible 
vegetable oils: evaluation of oil extraction, fatty acid 
compositions, biodiesel production, characteristics, 
engine performance and emissions production, Ren. 
Sus. Energy Rev. 18: 211-245. DOI: 10.1016/ 
j.rser.2012.10.013

Atabani AE, Mahlia TM, Ifran A, Masjuki HH, Chong WT 
and Keat TL (2013), Investigation of physical and 
chemical properties of potential edible and non-edible 
feedstocks for biodiesel production, a comparative 
analysis, Ren. Sus. Energy Rev. 21: 749-55. DOI: 
10.1016/j.rser.2013.01.027

Ayerza HR (2012), Seed and oil yields of moringa oleifera 
variety periyakalum-1 introduced for oil production in 
four ecosystems of South America, Ind. Crops Prod. 
36: 70-73. DOI: 10.1016/j.indcrop.2011.08.008

Azad A, Rasul M, Khan K, Subhash CS and Rubayat I 
(2015), Prospect of Moringa Seed oil is a 
sustainable biodiesel fuel in Australia, Procedia 
Engineering. 105: 601-606, DOI: 10.1016/j.proeng. 
2015.05.037

Choi C and Reitz R (1999), A numerical analysis of emission 
characteristics of biodiesel blended fuels, J Eng Gas 
Turbines Power 121(1): 31-37. DOI: 10.1115/1. 
2816309 

Demirbas A (2005), Potential applications of renewable 
energy sources, biomasscombustion problems in boiler 
power systems, and combustion-related 
environmentalissues, Progress in Energy and 
combustion sci. 31: 171-192. DOI: 10.1016/j.pecs. 
2005.02.002 

Demshemino SI, Donnel PS, Muhamma FY, Niwadike and 
Okoro LN (2013), Comparative analysis of biodiesel 
and petroleum diesel, International journal of 
education and research 1(8): 2-5.

Eman NA and Cadence IT (2013), Characterization of 
Biodiesel produced from palm oilvia base-catalyzed 
transesterification, Procedia Engineering. 53: 7-12. 
DOI: 10.1016/j.proeng.2013.02.002  

Gemeda T and Desta N (2020), Pre-extension demonstration 
of Moringa preparation and utilization methods in east 
Shoa zones of Oromia, Ethiopia, Journal of 
Biomaterials. 4(1): 17-22. DOI: 10.11648/j.jb. 
20200401.12 

Gemechu YS (2021), Production and Characterization of 
Biodiesel from Moringa Stenopetala Seed Oil via 
Catalytic Transesterification Process, Thesis work at 
Addis Ababa University Institute of Technology, Addis 
Ababa, Ethiopia.

Hamza TA and Azmach NN (2017), The miraculous Moringa 
trees: from a nutritionaland medicinal point of view in 
tropical regions, Journal of medicinal plants studies 5 
(4): 151-162.

Jayed MH, Masjuki HH, Kalam MA, Mahlia TM, Husnawan 
M and Liaquat AM (2011), Prospects of dedicated 
biodiesel engine vehicles in Malaysia and Indonesia, 
Ren. Sus. Ener. Rev. 15: 220-235. DOI: 
10.1016/j.rser.2010.09.002 

Kafuku G and Mbarawa M (2010), Alkaline-catalyzed 
biodiesel production from moringa oleifera oil with 
optimized production parameters, Applied Energy. 
87 (8): 2561-2565. DOI:10.1016/j. apenergy. 
2010.02.026 

Marchetti JM and Yadessa GK (2012), A review of oil 
extraction from plant seeds for biodiesel production, 
IMS Energy. 5(4): 316-340. DOI: 10.3934/energy. 
2017.2.316 

Mahmudul H, Hagos R, Mamat A, Abdul A and Ishak RA 
(2017), Production, characterization and performance 
of Biodiesel as an alternative fuel in diesel engines, 
Renewable and Sustainable Energy Reviews 72(c): 
497-509. DOI: 10.1016/j.rser.2017.01.001 

Piyush N, Subramanian KA and Dastidar MG (2013), 
Production and characterization of Biodieselfrom 
algae, Fuel processing technology. 120: 79-88. DOI: 
10.1016/j.fuproc.2013.12.003 

Raj S and Bhandari M (2017), Comparison of methods of 
production of biodiesel from Jatropha curcas, Journal 
of Biofuel. 8(2): 58-80.

Rao PV (2011), Experimental investigations on the 
influence of properties of jatropha biodiesel on 
performance, combustion, and emission 
characteristics of DI–CI engines, World Acad. Sci. 
Eng. Technol. 5(3): 855-868.

Sreepada H and Vijayalaxmi H (2013), An overview of 
moringa production in Ethiopia, International Journal 
of Science and Research 4(4): 2319-7064. DOI: 
10.36106/ijsr

Seema R and Meena B (2017), Comparison of methods of 
biodiesel productionfrom Jatropha Curcas, Journal of 
Biofuels. 8(2): 58-80.

its advantages is it is considered a great natural cosmetic 
emollient and has high oxidative stability (Ayerza, 2012).

Moringa plant is a high-value tree of the Moringaceae family. 
It consists of 13 species highly distributed in Africa and Asia 
(Hamza and Azmach, 2017). Moringa is particularly suitable 
for dry regions since it can be grown using rainwater without 
expensive irrigation techniques.  Moringa has been given less 
attention and ignored tree by communities to utilize it in 
different ways (Gemeda and Desta, 2020). Flowering begins 
within the first six months. Moringa stenopetala seed is an 
available and underutilized resource. Ethiopia has a comfort-
able environment for mooring stenopetala plantations. Many 
parts of the country particularly southern parts such as Gamo 
Goffa, Sidama Wolayitta, Konso, and Darashe have planted 
moringa in their garden and farmland (Sreepada and Vijay-
alaxmi, 2013). Thus, this study investigated that moringa 
stenopetala seed oil is a potential industrial feedstock for 
biodiesel production as an alternative energy source.

Materials and methods

The sample of Moringa seed was collected from the Gamo 
Goffa Zone, Arba Minch area of Ethiopia. The seed sample 

was dried and milled to reduce the particle size. Then, 80 g of 
sample was measured and put into the soxhlet apparatus 
thimble. Then, it was placed in a 500 mL capacity soxhlet 
chamber. 400 mL solvent (Hexane) was used for the 
extraction at different temperatures for 3 hrs. to 5 hrs. The 
extraction was conducted at 70°C, 75°C, and 80°C by 
varying extraction time to get the maximum possible oil 
yield.  The soxhlet extraction method was selected since it 
results in high oil yield, is quick, the solvent can be reused, 
and is low cost (Sreepada and Vijayalaxmi, 2013). The 
unwanted substances were removed by evaporation and 
degumming. Evaporation was used to separate hexane from 

Table VII. Analysis of variance (ANOVA)

Source Sum of 
Squares 

Df Mean 
Square 

F-value p-value  

Model 1316.65 9 146.29 380.98 < 0.0001 significant
A-Methanol to oil ratio 35.15 1 35.15 91.55 < 0.0001 
B-Temperature 332.56 1 332.56 866.06 < 0.0001 
C-Catalyst loading 7.55 1 7.55 19.65 0.0030 
AB 0.6972 1 0.6972 1.82 0.2198 
AC 0.3481 1 0.3481 0.9065 0.3727 
BC 0.0380 1 0.0380 0.0990 0.7622 
A² 393.68 1 393.68 1025.23 < 0.0001 
B² 458.66 1 458.66 1194.44 < 0.0001 
C² 16.58 1 16.58 43.18 0.0003 
Residual 2.69 7 0.3840 
Lack of Fit 2.18 3 0.7259 5.69 0.0631 not significant

 

Pure Error 0.5101 4 0.1275 
Cor Total 1319.33 16 
 



Biodiesel from moringa stenopetala seed oil42 58(1) 2023

The most common production technology of biodiesel is the 
transesterification process. Transesterification is a chemical 
reaction between one mole of triglyceride with three moles of 
alcohol to produce fatty acid methyl ester and glycerol in the 
presence of a catalyst or without a catalyst. Most transesteri-
fication reactions use ethanol or methanol alcohol. Many 
studies show that methanol is more practically used as 
alcohol than ethanol. Methanol is preferable due to its low 
cost and its physical and chemical advantages. Another 
advantage of using methanol is the ease of separation of 
glycerin which can be achieved by simple decantation 
(Marchetti and Yadessa, 2012).

Various catalysts can be used in the process. However, it was 
confirmed that the transesterification reaction was completed 
very fast when alkali catalysts are used. After the transesterifi-
cation reaction is completed, glycerol, catalyst, alcohol, and 
soap are separated from biodiesel. The factors affecting 
biodiesel yield and fuel quality are alcohol-to-oil ratios, 
temperature, catalyst loading, and reaction time (Raj and Bhan-
dari, 2017). Biodiesel is formed when triglyceride reacts with 
alcohol leaving glycerol as a byproduct as shown in Figure 1.

There are more than 300 vegetable oils identified as potential 
feedstocks for biodiesel production globally. The availability, 
characteristics, and variety of feedstocks make them promis-
ing ingredients for the sustainable production of biodiesel 
(Piyush et al. 2013). Researchers have proposed Moringa 
seed oil as an alternative potential feedstock to produce 
biodiesel. However, there is a research gap that promotes this 
feedstock for industrial processing. Moringa seed has an 
average of 35%-45% oil content with high oleic content of 
greater than 73% based on the type of the tree. Moringa oil 
has many various industrial and homemade benefits. One of 

oil by rotary evaporation at 80°C. Gum and wax were 
removed by a degumming method. Then, biodiesel was 
synthesized by transesterification reaction using a homoge-
nous catalyst (methanol) at different process parameters.

Experimental design

The experimental design used for this study was a Box 
Behnken design standard using design expert 11.0 software. 
The experimental design was done using three variables and 
tree levels for a response surface method. 17 experimental 
runswere selected by design expert 11.0 software using the 
Box Behnken design standard method, with five central 
points per block. The main factors that affect biodiesel 
production by transesterification reaction are reaction time, 
reaction temperature, and alcohol-to-oil ratio (Seema and 
Meena, 2017). As indicated in Table I, the overall production 
of biodiesel was carried out at optimum parameters of 
catalyst load of 0.5 to 1.5 wt.%, reaction temperature of 45 to 
65°C, and methanol to oil ratio of 3 to 9.  

The other parameters, reaction time and mixing intensity 
were kept constant at 1 hour and 500 rpm for all experimental 
runs. A combination of three factors and three levels of 
experimental runs was conducted. There are 17 experimental 
runs determined byBox Behnken’s design arrangement as 
shown in Table II.

Production and purification of the product

The method used to produce biodiesel was a one-steptranses-
terification reaction. Methanol was the alcohol selected for 
the transesterification reaction due to its availability, low 
cost, popularity, and ease of separation (Demirbas, 2005). 
The catalyst selected for this study was the base catalyst 
(KOH) since biodiesel can be produced at low temperatures 
and pressure reactions. Moreover, it is a homogeneous base 
catalyst that results in high conversion, minimum side 
reactions, short reaction time, and high yield (Marchetti and 

Yadessa, 2012). Though it has many advantages, the disad-
vantage of the catalyst used is it cannot be reused.

When the reaction is completed, biodiesel and glycerol were 
separated by a separatory funnel after it settles for 24 hours. 
Then, biodiesel was washed with hot distilled water to 
remove soap, remaining methanol, and wax.

Optimization of the process parameters using the Response 
Surface Method (RSM).

Optimization aims to determine the optimum value of the 
factors that affect the transesterification process to produce 
the maximum possible biodiesel yield at a minimum produc-
tion cost. This is done by minimizing the methanol to oil 
ratio, reaction temperature, and amount of catalyst used as 
indicated in Table III.

Characterization of biodiesel

Characterization of fuel is determining the physical and 
chemical properties (Atabani et al. 2013). The physical and 
chemical properties of biodiesel were determined according 
to the American Society for Testing Materials (ASTM D 
6751) and European standard (EN 14214) methods (Demir-
bas, 2005). Table IV showed the physical and chemical 
properties of biodiesel and the standard methods used to 
determine them.

Statistical analysis of experimental results

Data analysis of the experiment was done by design expert 
11.0 software using Box Behnken design standard. The 
significance of experimental variables was obtained from 
analysis of variance (ANOVA). 

Results and discussions

Yield

The maximum oil yield obtained at optimum conditions of 
temperature 80°C and extraction time 5 hours was 39.86 %. 
This result agreed with the average oil content of Moringa 
stenopetala seed oil which is 35% - 45% (Ayerza, 2012), and 
this result also agreed with the previous reportof 38% which 
was reported by Azad et al. (2015) and by Gemechu (2021).

The maximum yield of biodiesel was 94% and it was 
obtained at optimum process parameters of methanol to oil 
ratio 6:1, temperature 55°C, and catalyst loading 1.0%.  The 
yield of biodiesel obtained agrees with the previous report of 

Azad et al. (2015) which was 91%. The yield increased as 
transesterification parameters increased until the optimum 
value and decreased beyond the optimum value. At the lower 
value of parameters, the yield decreased due to the incom-
plete conversion of reactants to the product. Table V showed 
the yield response of all experimental runs.

Characterization of biodiesel

Physical and chemical properties of biodiesel were evaluated 
using standard methods and the results were compared with 
ASTM and EN standard methods and previous reports.

Density

The value of the density of biodiesel was 874 kg/m3. This 
result is within the standard range of density (860 – 900 
kg/m3) (Demirbas, 2005) and agrees with the previous report 
by Kafuku and Mbarawa (2010) which was 900 kg/m3. 
Higher density increases thesize of fuel droplets and causes 
higher emission of particulate matter and NOx emission ina 
diesel engine while the lower density of fuel expands the 
efficiency of atomization (Choi and Reitz, 1999).

Kinematic viscosity

The experimental result showed that the value of kinematic 
viscosity was 4.8 mm2/s. This result is within the range of the 
ASTM standard value of biodiesel which is 1.6-6 (Eman and 
Cadence, 2013; Demirbas, 2005). Highly viscous fuel is 
difficult to pump and operate in internal combustion engines 
while lower kinematic viscosity of fuels increases wear 
leakage due to insufficient lubrication (Rao, 2011).

Acid value

The value of an acid value obtained was 0.4 mm KOH/g.  
This result agrees with the previous report (Kafuku and 
Mbarawa, 2010), with a value of 1.2 mmKOH/g. Higher 
acid-value fuels need further acid treatment costs and it also 
lowers the quality of the fuels. In this study, the lower acid 
value of biodiesel indicates that it has higher fuel quality.

Calorific value

The experimental result showed that the value of biodiesel 
was 10287 Cal/ g or 43 MJ/kJ. This result agrees with the 
previous report of Mahamudul et al. (2017) which was 39 

MJ/kg, and the previous report of Agarwal and Das (2001) 
which was 43.2 kJ/kg. The result obtained is above the 
standard ASTM value which is 42-42.5 MJ/kg. This result 
indicates the higher fuel quality of biodiesel. The calorific 
value obtained is similar to that of conventional diesel fuels. 
This is the novel result of this study.

Flash point

The flash point obtained from the experimental result was 
184°C. This result agrees with the standard ASTM value of 
biodiesel flash point which is greater than 130°C. From this 
study, the higher flash point of biodiesel indicates that it is 
safer to handle, store and transport the fuel (Jayed et al. 
2011).

Cetane number

The value of the cetane number observed was 53. This result 
agrees with the standard ASTM value of the cetane number 
of biodiesel which is greater than 47 (Demirbas, 2005). Fuels 
with higher cetane number benefit the engine performance 
since the engine starts rapidly and run smoothly without 
causing much noise.

Cloud and Pour point

The experimental result showed that the cloud and pour 
points of biodiesel were 10°C and 1°C respectively. This 
result agrees with the previous report of Kafuku and Mbara-
wa (2010) which was 10°C and 3°C respectively. Cloud and 
pour point of fuel indicates the fuel performance at low ambi-
ent temperature (Agarwal and Das, 2001). Table VI showed 
the result of all main physicochemical properties of biodiesel 
synthesized.

Statistical analysis of experimental results 

Analysis of variance (ANOVA) for the quadratic model

Analysis of variance determines the significance of the 
experimental results using coded variables as indicated in 
Table VII. 

The Model F-value of 380.98 implies the model is signifi-
cant. There is only a 0.01% chance that an F-value this large 
could occur due to noise.

P-values less than 0.0500 indicate model terms are signifi-
cant. In this case, A, B, C, A², B², C² are significant model 
terms. Values greater than 0.1000 indicate the model terms 
are not significant. If there are many insignificant model 
terms (not counting those required to support hierarchy), 
model reduction may improve your model.

The Lack of Fit F-value of 5.69 implies there is a 6.31% 
chance that a Lack of Fit F-value this large could occur due to 
noise. Lack of fit is bad -- we want the model to fit. This 
relatively low probability (<10%) is troubling.

The coefficient estimate represents the expected change in 
response per unit change in factor value when all remaining 
factors are held constant. The intercept in an orthogonal 
design is the overall average response of all the runs. The 
coefficients are adjustments around that average based on the 

factor settings. When the factors are orthogonal the VIFs are 
1; VIFs greater than 1 indicate multi-collinearity, and the 
higher the VIF the more severe the correlation of factors. As 
a rough rule, VIFs less than 10 are tolerable.

The effect of process parameters on the yield of biodiesel

Effect of methanol to oil ratio

Figure. (2) Shows the effect of methanol to oil ratio on 
biodiesel yield at constant temperature and catalyst loading. 
It showed that the yield of biodiesel increases as the metha-
nol-to-oil ratio increases. Increasing the methanol-to-oil ratio 
beyond the optimum value results in excess methanol which 
decreases the yield of biodiesel. The maximum yield of 
biodiesel (94%) was obtained at a methanol-to-oil ratio of 6: 
1. Therefore, this ratio was taken as an optimum value of the 
methanol-to-oil ratio. Decreasing the methanol-to-oil ratio 

below the optimum value (3:1), decreased the conversion 
efficiency of the transesterification reaction and resulted in 
lower biodiesel yield.

Effect of reaction temperature

Figure (3) shows the effect of reaction temperature on the 
yield of biodiesel at a constant methanol-to-oil ratio and 
catalyst loading. The yield of biodiesel highly increased as 

temperature increased from 45°C to 55°C.  Maximum yield 
was obtained at 58°C and the yield started to decrease slight-
ly from 58°C to 65°C due to the vaporization of methanol 
resulting in soap formation. The boiling point of methanol is 
64.7°C. Increasing reaction temperature above this point 
leads to methanol loss by evaporation and decreases the 
conversion efficiency of the reaction. At 45°C, the yield is 
about 75°C.

Effect of catalyst loading

Figure (4) shows the effect of catalyst loading on the yield of 
biodiesel at a constant methanol-to-oil ratio and temperature.  
As the amount of catalyst increased from 0.5% to 1.0%, the 
yield of biodiesel increased from 89% to 94% and the yield 
starts to decrease slightly as the amount of catalyst increased 
from 1.0% to 1.5% due to the formation of soap and emul-
sion. At a lower amount of catalyst (0.5%), the yield of 
biodiesel decreased due to the incomplete conversion of 
triglycerides of oil to fatty acid methyl ester.

Optimization of transesterification process parameters using 
the Response Surface Method (RSM)

The Response Surface Method determined the optimum 
value of process variables that maximize the yield of the 
product and minimize production cost

Table VIII showed that Response Surface Method found 15 
solutions and selected the optimum values to minimize the 
economic cost of Temperature, Methanol, and Catalyst 
required for the reaction and to maximize the yield of 
biodiesel. The optimum yield of biodiesel (83.772%) was 
observed at a temperature of 51.537 and catalyst load of 
0.500 wt.%.

Conclusions

Biodiesel is a promising biofuel that is synthesized by the 
transesterification of vegetable oils and animal fats. In this 
study, biodiesel was synthesized from moringa stenopetala 
seed oil using an alkali catalyst. The effect of methanol to 
oil ratio, reaction temperature, and catalyst weight on the 
yield and quality of biodiesel have been studied. Biodiesel 
produced was characterized according to international fuel 
testing standards methods. The optimization of process 
parameters was carried out using Response Surface 
Method (RSM).

The experimental result showed that the highest yield of 
biodiesel was 94% and this result was obtained at an 
optimum value of temperature 55°C, methanol to oil ratio of 
6:1, and catalyst load of 1.0%. Increasing methanol to oil 
ratio, temperature, and catalyst load up to the optimum point 
increased the yield of biodiesel. However, further increase of 
the parameters above the optimum point decreased the yield 
of biodiesel. The temperature has the highest significant 
effect while the catalyst load has a lower effect. 

Besides to characterization of different basic fuel properties 
of it, biodiesel can be blended with petrol-diesel at different 
percentages and applied in compression ignition engine to 
evaluate the effect of using a blend of biodiesel using differ-

ent parameters such as engine power, brake thermal efficien-
cy, specific fuel consumption, exhaust gas temperature, and 
greenhouse gas temperature and gas emission. However, the 
performance analysis of the blend of biodiesel with petrol 
diesel in a compression ignition engine was not done due to a 
lack of laboratory setup and equipment required to measure 
these parameters. This study did not compare biodiesel with 
diesel fuels used in diesel engines. Moreover, it did not 
characterize the blend of biodiesel with petroleum fuels and 
did not compare biodiesel produced from other feedstocks 
other than moringa stenopetala. Thus, further research should 
be done on these areas. 

Generally, it can be concluded that moringa stenopetala is a 
promising alternative feedstock for biodiesel production for 
the reasons: it does not affect food security, has a good oil 
content, and can be harvested throughout the year.  The 
biodiesel produced meets the standard fuel quality and 
international standard specifications. 

Acknowledgment

The authors are thankful to Addis Ababa institute of Technol-
ogy, Addis Ababa University, Ethiopian Environment and 
Forest Research Institute, College of Natural and Computa-
tional Science, Addis Ababa University, and Ethiopian 
Geological Survey for their technical support.

References

Agarwal AK and Das LM (2001), Biodiesel development and 
characterization for use as a fuel in compression in 
ignition engines, J Eng Gas Turbines Power. 123(2): 
440-447. DOI: 10.1115/1.1364522

Atabani AE, Silitonga AS,  Ong HC, Mahila TM, Masjuki 
HH,  Irfan A and Fayaz H (2013), Non-edible 
vegetable oils: evaluation of oil extraction, fatty acid 
compositions, biodiesel production, characteristics, 
engine performance and emissions production, Ren. 
Sus. Energy Rev. 18: 211-245. DOI: 10.1016/ 
j.rser.2012.10.013

Atabani AE, Mahlia TM, Ifran A, Masjuki HH, Chong WT 
and Keat TL (2013), Investigation of physical and 
chemical properties of potential edible and non-edible 
feedstocks for biodiesel production, a comparative 
analysis, Ren. Sus. Energy Rev. 21: 749-55. DOI: 
10.1016/j.rser.2013.01.027

Ayerza HR (2012), Seed and oil yields of moringa oleifera 
variety periyakalum-1 introduced for oil production in 
four ecosystems of South America, Ind. Crops Prod. 
36: 70-73. DOI: 10.1016/j.indcrop.2011.08.008

Azad A, Rasul M, Khan K, Subhash CS and Rubayat I 
(2015), Prospect of Moringa Seed oil is a 
sustainable biodiesel fuel in Australia, Procedia 
Engineering. 105: 601-606, DOI: 10.1016/j.proeng. 
2015.05.037

Choi C and Reitz R (1999), A numerical analysis of emission 
characteristics of biodiesel blended fuels, J Eng Gas 
Turbines Power 121(1): 31-37. DOI: 10.1115/1. 
2816309 

Demirbas A (2005), Potential applications of renewable 
energy sources, biomasscombustion problems in boiler 
power systems, and combustion-related 
environmentalissues, Progress in Energy and 
combustion sci. 31: 171-192. DOI: 10.1016/j.pecs. 
2005.02.002 

Demshemino SI, Donnel PS, Muhamma FY, Niwadike and 
Okoro LN (2013), Comparative analysis of biodiesel 
and petroleum diesel, International journal of 
education and research 1(8): 2-5.

Eman NA and Cadence IT (2013), Characterization of 
Biodiesel produced from palm oilvia base-catalyzed 
transesterification, Procedia Engineering. 53: 7-12. 
DOI: 10.1016/j.proeng.2013.02.002  

Gemeda T and Desta N (2020), Pre-extension demonstration 
of Moringa preparation and utilization methods in east 
Shoa zones of Oromia, Ethiopia, Journal of 
Biomaterials. 4(1): 17-22. DOI: 10.11648/j.jb. 
20200401.12 

Gemechu YS (2021), Production and Characterization of 
Biodiesel from Moringa Stenopetala Seed Oil via 
Catalytic Transesterification Process, Thesis work at 
Addis Ababa University Institute of Technology, Addis 
Ababa, Ethiopia.

Hamza TA and Azmach NN (2017), The miraculous Moringa 
trees: from a nutritionaland medicinal point of view in 
tropical regions, Journal of medicinal plants studies 5 
(4): 151-162.

Jayed MH, Masjuki HH, Kalam MA, Mahlia TM, Husnawan 
M and Liaquat AM (2011), Prospects of dedicated 
biodiesel engine vehicles in Malaysia and Indonesia, 
Ren. Sus. Ener. Rev. 15: 220-235. DOI: 
10.1016/j.rser.2010.09.002 

Kafuku G and Mbarawa M (2010), Alkaline-catalyzed 
biodiesel production from moringa oleifera oil with 
optimized production parameters, Applied Energy. 
87 (8): 2561-2565. DOI:10.1016/j. apenergy. 
2010.02.026 

Marchetti JM and Yadessa GK (2012), A review of oil 
extraction from plant seeds for biodiesel production, 
IMS Energy. 5(4): 316-340. DOI: 10.3934/energy. 
2017.2.316 

Mahmudul H, Hagos R, Mamat A, Abdul A and Ishak RA 
(2017), Production, characterization and performance 
of Biodiesel as an alternative fuel in diesel engines, 
Renewable and Sustainable Energy Reviews 72(c): 
497-509. DOI: 10.1016/j.rser.2017.01.001 

Piyush N, Subramanian KA and Dastidar MG (2013), 
Production and characterization of Biodieselfrom 
algae, Fuel processing technology. 120: 79-88. DOI: 
10.1016/j.fuproc.2013.12.003 

Raj S and Bhandari M (2017), Comparison of methods of 
production of biodiesel from Jatropha curcas, Journal 
of Biofuel. 8(2): 58-80.

Rao PV (2011), Experimental investigations on the 
influence of properties of jatropha biodiesel on 
performance, combustion, and emission 
characteristics of DI–CI engines, World Acad. Sci. 
Eng. Technol. 5(3): 855-868.

Sreepada H and Vijayalaxmi H (2013), An overview of 
moringa production in Ethiopia, International Journal 
of Science and Research 4(4): 2319-7064. DOI: 
10.36106/ijsr

Seema R and Meena B (2017), Comparison of methods of 
biodiesel productionfrom Jatropha Curcas, Journal of 
Biofuels. 8(2): 58-80.

its advantages is it is considered a great natural cosmetic 
emollient and has high oxidative stability (Ayerza, 2012).

Moringa plant is a high-value tree of the Moringaceae family. 
It consists of 13 species highly distributed in Africa and Asia 
(Hamza and Azmach, 2017). Moringa is particularly suitable 
for dry regions since it can be grown using rainwater without 
expensive irrigation techniques.  Moringa has been given less 
attention and ignored tree by communities to utilize it in 
different ways (Gemeda and Desta, 2020). Flowering begins 
within the first six months. Moringa stenopetala seed is an 
available and underutilized resource. Ethiopia has a comfort-
able environment for mooring stenopetala plantations. Many 
parts of the country particularly southern parts such as Gamo 
Goffa, Sidama Wolayitta, Konso, and Darashe have planted 
moringa in their garden and farmland (Sreepada and Vijay-
alaxmi, 2013). Thus, this study investigated that moringa 
stenopetala seed oil is a potential industrial feedstock for 
biodiesel production as an alternative energy source.

Materials and methods

The sample of Moringa seed was collected from the Gamo 
Goffa Zone, Arba Minch area of Ethiopia. The seed sample 

was dried and milled to reduce the particle size. Then, 80 g of 
sample was measured and put into the soxhlet apparatus 
thimble. Then, it was placed in a 500 mL capacity soxhlet 
chamber. 400 mL solvent (Hexane) was used for the 
extraction at different temperatures for 3 hrs. to 5 hrs. The 
extraction was conducted at 70°C, 75°C, and 80°C by 
varying extraction time to get the maximum possible oil 
yield.  The soxhlet extraction method was selected since it 
results in high oil yield, is quick, the solvent can be reused, 
and is low cost (Sreepada and Vijayalaxmi, 2013). The 
unwanted substances were removed by evaporation and 
degumming. Evaporation was used to separate hexane from 

Table VIII. Optimum numerical solution by RSM

Number  Methanol
to oil ratio  

Temperature  Catalyst 
loading  

Yield Desirability

1 4.489 51.537 0.500  83.683 0.753 Selected
2 4.511 51.501 0.500  83.722 0.753
3 4.513 51.518 0.500  83.753 0.753
4 4.487 51.430 0.500  83.529 0.753
5 4.500 51.630 0.500  83.850 0.753
6 4.444 51.617 0.500  83.610 0.753
7 4.521 51.382 0.500  83.599 0.753
8 4.450 51.419 0.500  83.369 0.753
9 4.419 51.558 0.500  83.428 0.753

10 4.512 51.729 0.500  84.028 0.753
11 4.422 51.412 0.500  83.243 0.753
12 4.472 51.818 0.500  83.981 0.753
13 4.421 51.813 0.500  83.769 0.753
14 4.773 50.864 0.500  83.781 0.751
15 5.068 53.527 0.500  87.898 0.737

Fig. 2. Effect of methanol to oil ratio on yield of biodiesel
 

Design-Expert® Software
Factor Coding: Actual

Yield (%)
Design Points
95% CI Bands

X1 = A: Methanol to oil ratio

Actual Factors
B: Temperature = 55
C: Catalyst loading = 1

A: Methanol to oil ratio (-)
3 4 5 6 7 8 9

Y
ie

ld
 (

%
)

65

72.25

79.5

86.75

94 3
22
22

One Factor

Fig. 3. Effect of temperature on yield of biodiesel

Design-Expert® Software
Factor Coding: Actual

Yield (%)
Design Points
95% CI Bands

X1 = B: Temperature

Actual Factors
A: Methanol to oil ratio = 6
C: Catalyst loading = 1

B: Temperature

45 50 55 60 65

Y
ie

ld
 (

%
)

65

72.25

79.5

86.75

94 3
22
22

One Factor

Design-Expert® Software
Factor Coding: Actual

Yield (%)
Design Points
95% CI Bands

X1 = C: Catalyst loading

Actual Factors
A: Methanol to oil ratio = 6
B: Temperature = 55

C: Catalyst loading (Wt.%)
0.5 0.7 0.9 1.1 1.3 1.5

Y
ie

ld
 (

%
)

65

72.25

79.5

86.75

94 3
22
22

One Factor

Fig. 4. Effect of catalyst loading on yield of biodiesel



The most common production technology of biodiesel is the 
transesterification process. Transesterification is a chemical 
reaction between one mole of triglyceride with three moles of 
alcohol to produce fatty acid methyl ester and glycerol in the 
presence of a catalyst or without a catalyst. Most transesteri-
fication reactions use ethanol or methanol alcohol. Many 
studies show that methanol is more practically used as 
alcohol than ethanol. Methanol is preferable due to its low 
cost and its physical and chemical advantages. Another 
advantage of using methanol is the ease of separation of 
glycerin which can be achieved by simple decantation 
(Marchetti and Yadessa, 2012).

Various catalysts can be used in the process. However, it was 
confirmed that the transesterification reaction was completed 
very fast when alkali catalysts are used. After the transesterifi-
cation reaction is completed, glycerol, catalyst, alcohol, and 
soap are separated from biodiesel. The factors affecting 
biodiesel yield and fuel quality are alcohol-to-oil ratios, 
temperature, catalyst loading, and reaction time (Raj and Bhan-
dari, 2017). Biodiesel is formed when triglyceride reacts with 
alcohol leaving glycerol as a byproduct as shown in Figure 1.

There are more than 300 vegetable oils identified as potential 
feedstocks for biodiesel production globally. The availability, 
characteristics, and variety of feedstocks make them promis-
ing ingredients for the sustainable production of biodiesel 
(Piyush et al. 2013). Researchers have proposed Moringa 
seed oil as an alternative potential feedstock to produce 
biodiesel. However, there is a research gap that promotes this 
feedstock for industrial processing. Moringa seed has an 
average of 35%-45% oil content with high oleic content of 
greater than 73% based on the type of the tree. Moringa oil 
has many various industrial and homemade benefits. One of 

oil by rotary evaporation at 80°C. Gum and wax were 
removed by a degumming method. Then, biodiesel was 
synthesized by transesterification reaction using a homoge-
nous catalyst (methanol) at different process parameters.

Experimental design

The experimental design used for this study was a Box 
Behnken design standard using design expert 11.0 software. 
The experimental design was done using three variables and 
tree levels for a response surface method. 17 experimental 
runswere selected by design expert 11.0 software using the 
Box Behnken design standard method, with five central 
points per block. The main factors that affect biodiesel 
production by transesterification reaction are reaction time, 
reaction temperature, and alcohol-to-oil ratio (Seema and 
Meena, 2017). As indicated in Table I, the overall production 
of biodiesel was carried out at optimum parameters of 
catalyst load of 0.5 to 1.5 wt.%, reaction temperature of 45 to 
65°C, and methanol to oil ratio of 3 to 9.  

The other parameters, reaction time and mixing intensity 
were kept constant at 1 hour and 500 rpm for all experimental 
runs. A combination of three factors and three levels of 
experimental runs was conducted. There are 17 experimental 
runs determined byBox Behnken’s design arrangement as 
shown in Table II.

Production and purification of the product

The method used to produce biodiesel was a one-steptranses-
terification reaction. Methanol was the alcohol selected for 
the transesterification reaction due to its availability, low 
cost, popularity, and ease of separation (Demirbas, 2005). 
The catalyst selected for this study was the base catalyst 
(KOH) since biodiesel can be produced at low temperatures 
and pressure reactions. Moreover, it is a homogeneous base 
catalyst that results in high conversion, minimum side 
reactions, short reaction time, and high yield (Marchetti and 

Yadessa, 2012). Though it has many advantages, the disad-
vantage of the catalyst used is it cannot be reused.

When the reaction is completed, biodiesel and glycerol were 
separated by a separatory funnel after it settles for 24 hours. 
Then, biodiesel was washed with hot distilled water to 
remove soap, remaining methanol, and wax.

Optimization of the process parameters using the Response 
Surface Method (RSM).

Optimization aims to determine the optimum value of the 
factors that affect the transesterification process to produce 
the maximum possible biodiesel yield at a minimum produc-
tion cost. This is done by minimizing the methanol to oil 
ratio, reaction temperature, and amount of catalyst used as 
indicated in Table III.

Characterization of biodiesel

Characterization of fuel is determining the physical and 
chemical properties (Atabani et al. 2013). The physical and 
chemical properties of biodiesel were determined according 
to the American Society for Testing Materials (ASTM D 
6751) and European standard (EN 14214) methods (Demir-
bas, 2005). Table IV showed the physical and chemical 
properties of biodiesel and the standard methods used to 
determine them.

Statistical analysis of experimental results

Data analysis of the experiment was done by design expert 
11.0 software using Box Behnken design standard. The 
significance of experimental variables was obtained from 
analysis of variance (ANOVA). 

Results and discussions

Yield

The maximum oil yield obtained at optimum conditions of 
temperature 80°C and extraction time 5 hours was 39.86 %. 
This result agreed with the average oil content of Moringa 
stenopetala seed oil which is 35% - 45% (Ayerza, 2012), and 
this result also agreed with the previous reportof 38% which 
was reported by Azad et al. (2015) and by Gemechu (2021).

The maximum yield of biodiesel was 94% and it was 
obtained at optimum process parameters of methanol to oil 
ratio 6:1, temperature 55°C, and catalyst loading 1.0%.  The 
yield of biodiesel obtained agrees with the previous report of 

Azad et al. (2015) which was 91%. The yield increased as 
transesterification parameters increased until the optimum 
value and decreased beyond the optimum value. At the lower 
value of parameters, the yield decreased due to the incom-
plete conversion of reactants to the product. Table V showed 
the yield response of all experimental runs.

Characterization of biodiesel

Physical and chemical properties of biodiesel were evaluated 
using standard methods and the results were compared with 
ASTM and EN standard methods and previous reports.

Density

The value of the density of biodiesel was 874 kg/m3. This 
result is within the standard range of density (860 – 900 
kg/m3) (Demirbas, 2005) and agrees with the previous report 
by Kafuku and Mbarawa (2010) which was 900 kg/m3. 
Higher density increases thesize of fuel droplets and causes 
higher emission of particulate matter and NOx emission ina 
diesel engine while the lower density of fuel expands the 
efficiency of atomization (Choi and Reitz, 1999).

Kinematic viscosity

The experimental result showed that the value of kinematic 
viscosity was 4.8 mm2/s. This result is within the range of the 
ASTM standard value of biodiesel which is 1.6-6 (Eman and 
Cadence, 2013; Demirbas, 2005). Highly viscous fuel is 
difficult to pump and operate in internal combustion engines 
while lower kinematic viscosity of fuels increases wear 
leakage due to insufficient lubrication (Rao, 2011).

Acid value

The value of an acid value obtained was 0.4 mm KOH/g.  
This result agrees with the previous report (Kafuku and 
Mbarawa, 2010), with a value of 1.2 mmKOH/g. Higher 
acid-value fuels need further acid treatment costs and it also 
lowers the quality of the fuels. In this study, the lower acid 
value of biodiesel indicates that it has higher fuel quality.

Calorific value

The experimental result showed that the value of biodiesel 
was 10287 Cal/ g or 43 MJ/kJ. This result agrees with the 
previous report of Mahamudul et al. (2017) which was 39 

MJ/kg, and the previous report of Agarwal and Das (2001) 
which was 43.2 kJ/kg. The result obtained is above the 
standard ASTM value which is 42-42.5 MJ/kg. This result 
indicates the higher fuel quality of biodiesel. The calorific 
value obtained is similar to that of conventional diesel fuels. 
This is the novel result of this study.

Flash point

The flash point obtained from the experimental result was 
184°C. This result agrees with the standard ASTM value of 
biodiesel flash point which is greater than 130°C. From this 
study, the higher flash point of biodiesel indicates that it is 
safer to handle, store and transport the fuel (Jayed et al. 
2011).

Cetane number

The value of the cetane number observed was 53. This result 
agrees with the standard ASTM value of the cetane number 
of biodiesel which is greater than 47 (Demirbas, 2005). Fuels 
with higher cetane number benefit the engine performance 
since the engine starts rapidly and run smoothly without 
causing much noise.

Cloud and Pour point

The experimental result showed that the cloud and pour 
points of biodiesel were 10°C and 1°C respectively. This 
result agrees with the previous report of Kafuku and Mbara-
wa (2010) which was 10°C and 3°C respectively. Cloud and 
pour point of fuel indicates the fuel performance at low ambi-
ent temperature (Agarwal and Das, 2001). Table VI showed 
the result of all main physicochemical properties of biodiesel 
synthesized.

Statistical analysis of experimental results 

Analysis of variance (ANOVA) for the quadratic model

Analysis of variance determines the significance of the 
experimental results using coded variables as indicated in 
Table VII. 

The Model F-value of 380.98 implies the model is signifi-
cant. There is only a 0.01% chance that an F-value this large 
could occur due to noise.

P-values less than 0.0500 indicate model terms are signifi-
cant. In this case, A, B, C, A², B², C² are significant model 
terms. Values greater than 0.1000 indicate the model terms 
are not significant. If there are many insignificant model 
terms (not counting those required to support hierarchy), 
model reduction may improve your model.

The Lack of Fit F-value of 5.69 implies there is a 6.31% 
chance that a Lack of Fit F-value this large could occur due to 
noise. Lack of fit is bad -- we want the model to fit. This 
relatively low probability (<10%) is troubling.

The coefficient estimate represents the expected change in 
response per unit change in factor value when all remaining 
factors are held constant. The intercept in an orthogonal 
design is the overall average response of all the runs. The 
coefficients are adjustments around that average based on the 

factor settings. When the factors are orthogonal the VIFs are 
1; VIFs greater than 1 indicate multi-collinearity, and the 
higher the VIF the more severe the correlation of factors. As 
a rough rule, VIFs less than 10 are tolerable.

The effect of process parameters on the yield of biodiesel

Effect of methanol to oil ratio

Figure. (2) Shows the effect of methanol to oil ratio on 
biodiesel yield at constant temperature and catalyst loading. 
It showed that the yield of biodiesel increases as the metha-
nol-to-oil ratio increases. Increasing the methanol-to-oil ratio 
beyond the optimum value results in excess methanol which 
decreases the yield of biodiesel. The maximum yield of 
biodiesel (94%) was obtained at a methanol-to-oil ratio of 6: 
1. Therefore, this ratio was taken as an optimum value of the 
methanol-to-oil ratio. Decreasing the methanol-to-oil ratio 

below the optimum value (3:1), decreased the conversion 
efficiency of the transesterification reaction and resulted in 
lower biodiesel yield.

Effect of reaction temperature

Figure (3) shows the effect of reaction temperature on the 
yield of biodiesel at a constant methanol-to-oil ratio and 
catalyst loading. The yield of biodiesel highly increased as 

temperature increased from 45°C to 55°C.  Maximum yield 
was obtained at 58°C and the yield started to decrease slight-
ly from 58°C to 65°C due to the vaporization of methanol 
resulting in soap formation. The boiling point of methanol is 
64.7°C. Increasing reaction temperature above this point 
leads to methanol loss by evaporation and decreases the 
conversion efficiency of the reaction. At 45°C, the yield is 
about 75°C.

Effect of catalyst loading

Figure (4) shows the effect of catalyst loading on the yield of 
biodiesel at a constant methanol-to-oil ratio and temperature.  
As the amount of catalyst increased from 0.5% to 1.0%, the 
yield of biodiesel increased from 89% to 94% and the yield 
starts to decrease slightly as the amount of catalyst increased 
from 1.0% to 1.5% due to the formation of soap and emul-
sion. At a lower amount of catalyst (0.5%), the yield of 
biodiesel decreased due to the incomplete conversion of 
triglycerides of oil to fatty acid methyl ester.

Optimization of transesterification process parameters using 
the Response Surface Method (RSM)

The Response Surface Method determined the optimum 
value of process variables that maximize the yield of the 
product and minimize production cost

Table VIII showed that Response Surface Method found 15 
solutions and selected the optimum values to minimize the 
economic cost of Temperature, Methanol, and Catalyst 
required for the reaction and to maximize the yield of 
biodiesel. The optimum yield of biodiesel (83.772%) was 
observed at a temperature of 51.537 and catalyst load of 
0.500 wt.%.

Conclusions

Biodiesel is a promising biofuel that is synthesized by the 
transesterification of vegetable oils and animal fats. In this 
study, biodiesel was synthesized from moringa stenopetala 
seed oil using an alkali catalyst. The effect of methanol to 
oil ratio, reaction temperature, and catalyst weight on the 
yield and quality of biodiesel have been studied. Biodiesel 
produced was characterized according to international fuel 
testing standards methods. The optimization of process 
parameters was carried out using Response Surface 
Method (RSM).

The experimental result showed that the highest yield of 
biodiesel was 94% and this result was obtained at an 
optimum value of temperature 55°C, methanol to oil ratio of 
6:1, and catalyst load of 1.0%. Increasing methanol to oil 
ratio, temperature, and catalyst load up to the optimum point 
increased the yield of biodiesel. However, further increase of 
the parameters above the optimum point decreased the yield 
of biodiesel. The temperature has the highest significant 
effect while the catalyst load has a lower effect. 

Besides to characterization of different basic fuel properties 
of it, biodiesel can be blended with petrol-diesel at different 
percentages and applied in compression ignition engine to 
evaluate the effect of using a blend of biodiesel using differ-

ent parameters such as engine power, brake thermal efficien-
cy, specific fuel consumption, exhaust gas temperature, and 
greenhouse gas temperature and gas emission. However, the 
performance analysis of the blend of biodiesel with petrol 
diesel in a compression ignition engine was not done due to a 
lack of laboratory setup and equipment required to measure 
these parameters. This study did not compare biodiesel with 
diesel fuels used in diesel engines. Moreover, it did not 
characterize the blend of biodiesel with petroleum fuels and 
did not compare biodiesel produced from other feedstocks 
other than moringa stenopetala. Thus, further research should 
be done on these areas. 

Generally, it can be concluded that moringa stenopetala is a 
promising alternative feedstock for biodiesel production for 
the reasons: it does not affect food security, has a good oil 
content, and can be harvested throughout the year.  The 
biodiesel produced meets the standard fuel quality and 
international standard specifications. 

Acknowledgment

The authors are thankful to Addis Ababa institute of Technol-
ogy, Addis Ababa University, Ethiopian Environment and 
Forest Research Institute, College of Natural and Computa-
tional Science, Addis Ababa University, and Ethiopian 
Geological Survey for their technical support.

References

Agarwal AK and Das LM (2001), Biodiesel development and 
characterization for use as a fuel in compression in 
ignition engines, J Eng Gas Turbines Power. 123(2): 
440-447. DOI: 10.1115/1.1364522

Atabani AE, Silitonga AS,  Ong HC, Mahila TM, Masjuki 
HH,  Irfan A and Fayaz H (2013), Non-edible 
vegetable oils: evaluation of oil extraction, fatty acid 
compositions, biodiesel production, characteristics, 
engine performance and emissions production, Ren. 
Sus. Energy Rev. 18: 211-245. DOI: 10.1016/ 
j.rser.2012.10.013

Atabani AE, Mahlia TM, Ifran A, Masjuki HH, Chong WT 
and Keat TL (2013), Investigation of physical and 
chemical properties of potential edible and non-edible 
feedstocks for biodiesel production, a comparative 
analysis, Ren. Sus. Energy Rev. 21: 749-55. DOI: 
10.1016/j.rser.2013.01.027

Ayerza HR (2012), Seed and oil yields of moringa oleifera 
variety periyakalum-1 introduced for oil production in 
four ecosystems of South America, Ind. Crops Prod. 
36: 70-73. DOI: 10.1016/j.indcrop.2011.08.008

Azad A, Rasul M, Khan K, Subhash CS and Rubayat I 
(2015), Prospect of Moringa Seed oil is a 
sustainable biodiesel fuel in Australia, Procedia 
Engineering. 105: 601-606, DOI: 10.1016/j.proeng. 
2015.05.037

Choi C and Reitz R (1999), A numerical analysis of emission 
characteristics of biodiesel blended fuels, J Eng Gas 
Turbines Power 121(1): 31-37. DOI: 10.1115/1. 
2816309 

Demirbas A (2005), Potential applications of renewable 
energy sources, biomasscombustion problems in boiler 
power systems, and combustion-related 
environmentalissues, Progress in Energy and 
combustion sci. 31: 171-192. DOI: 10.1016/j.pecs. 
2005.02.002 

Demshemino SI, Donnel PS, Muhamma FY, Niwadike and 
Okoro LN (2013), Comparative analysis of biodiesel 
and petroleum diesel, International journal of 
education and research 1(8): 2-5.

Eman NA and Cadence IT (2013), Characterization of 
Biodiesel produced from palm oilvia base-catalyzed 
transesterification, Procedia Engineering. 53: 7-12. 
DOI: 10.1016/j.proeng.2013.02.002  

Gemeda T and Desta N (2020), Pre-extension demonstration 
of Moringa preparation and utilization methods in east 
Shoa zones of Oromia, Ethiopia, Journal of 
Biomaterials. 4(1): 17-22. DOI: 10.11648/j.jb. 
20200401.12 

Gemechu YS (2021), Production and Characterization of 
Biodiesel from Moringa Stenopetala Seed Oil via 
Catalytic Transesterification Process, Thesis work at 
Addis Ababa University Institute of Technology, Addis 
Ababa, Ethiopia.

Hamza TA and Azmach NN (2017), The miraculous Moringa 
trees: from a nutritionaland medicinal point of view in 
tropical regions, Journal of medicinal plants studies 5 
(4): 151-162.

Jayed MH, Masjuki HH, Kalam MA, Mahlia TM, Husnawan 
M and Liaquat AM (2011), Prospects of dedicated 
biodiesel engine vehicles in Malaysia and Indonesia, 
Ren. Sus. Ener. Rev. 15: 220-235. DOI: 
10.1016/j.rser.2010.09.002 

Kafuku G and Mbarawa M (2010), Alkaline-catalyzed 
biodiesel production from moringa oleifera oil with 
optimized production parameters, Applied Energy. 
87 (8): 2561-2565. DOI:10.1016/j. apenergy. 
2010.02.026 

Marchetti JM and Yadessa GK (2012), A review of oil 
extraction from plant seeds for biodiesel production, 
IMS Energy. 5(4): 316-340. DOI: 10.3934/energy. 
2017.2.316 

Mahmudul H, Hagos R, Mamat A, Abdul A and Ishak RA 
(2017), Production, characterization and performance 
of Biodiesel as an alternative fuel in diesel engines, 
Renewable and Sustainable Energy Reviews 72(c): 
497-509. DOI: 10.1016/j.rser.2017.01.001 

Piyush N, Subramanian KA and Dastidar MG (2013), 
Production and characterization of Biodieselfrom 
algae, Fuel processing technology. 120: 79-88. DOI: 
10.1016/j.fuproc.2013.12.003 

Raj S and Bhandari M (2017), Comparison of methods of 
production of biodiesel from Jatropha curcas, Journal 
of Biofuel. 8(2): 58-80.

Rao PV (2011), Experimental investigations on the 
influence of properties of jatropha biodiesel on 
performance, combustion, and emission 
characteristics of DI–CI engines, World Acad. Sci. 
Eng. Technol. 5(3): 855-868.

Sreepada H and Vijayalaxmi H (2013), An overview of 
moringa production in Ethiopia, International Journal 
of Science and Research 4(4): 2319-7064. DOI: 
10.36106/ijsr

Seema R and Meena B (2017), Comparison of methods of 
biodiesel productionfrom Jatropha Curcas, Journal of 
Biofuels. 8(2): 58-80.

Shage and Ali 43

its advantages is it is considered a great natural cosmetic 
emollient and has high oxidative stability (Ayerza, 2012).

Moringa plant is a high-value tree of the Moringaceae family. 
It consists of 13 species highly distributed in Africa and Asia 
(Hamza and Azmach, 2017). Moringa is particularly suitable 
for dry regions since it can be grown using rainwater without 
expensive irrigation techniques.  Moringa has been given less 
attention and ignored tree by communities to utilize it in 
different ways (Gemeda and Desta, 2020). Flowering begins 
within the first six months. Moringa stenopetala seed is an 
available and underutilized resource. Ethiopia has a comfort-
able environment for mooring stenopetala plantations. Many 
parts of the country particularly southern parts such as Gamo 
Goffa, Sidama Wolayitta, Konso, and Darashe have planted 
moringa in their garden and farmland (Sreepada and Vijay-
alaxmi, 2013). Thus, this study investigated that moringa 
stenopetala seed oil is a potential industrial feedstock for 
biodiesel production as an alternative energy source.

Materials and methods

The sample of Moringa seed was collected from the Gamo 
Goffa Zone, Arba Minch area of Ethiopia. The seed sample 

was dried and milled to reduce the particle size. Then, 80 g of 
sample was measured and put into the soxhlet apparatus 
thimble. Then, it was placed in a 500 mL capacity soxhlet 
chamber. 400 mL solvent (Hexane) was used for the 
extraction at different temperatures for 3 hrs. to 5 hrs. The 
extraction was conducted at 70°C, 75°C, and 80°C by 
varying extraction time to get the maximum possible oil 
yield.  The soxhlet extraction method was selected since it 
results in high oil yield, is quick, the solvent can be reused, 
and is low cost (Sreepada and Vijayalaxmi, 2013). The 
unwanted substances were removed by evaporation and 
degumming. Evaporation was used to separate hexane from 



The most common production technology of biodiesel is the 
transesterification process. Transesterification is a chemical 
reaction between one mole of triglyceride with three moles of 
alcohol to produce fatty acid methyl ester and glycerol in the 
presence of a catalyst or without a catalyst. Most transesteri-
fication reactions use ethanol or methanol alcohol. Many 
studies show that methanol is more practically used as 
alcohol than ethanol. Methanol is preferable due to its low 
cost and its physical and chemical advantages. Another 
advantage of using methanol is the ease of separation of 
glycerin which can be achieved by simple decantation 
(Marchetti and Yadessa, 2012).

Various catalysts can be used in the process. However, it was 
confirmed that the transesterification reaction was completed 
very fast when alkali catalysts are used. After the transesterifi-
cation reaction is completed, glycerol, catalyst, alcohol, and 
soap are separated from biodiesel. The factors affecting 
biodiesel yield and fuel quality are alcohol-to-oil ratios, 
temperature, catalyst loading, and reaction time (Raj and Bhan-
dari, 2017). Biodiesel is formed when triglyceride reacts with 
alcohol leaving glycerol as a byproduct as shown in Figure 1.

There are more than 300 vegetable oils identified as potential 
feedstocks for biodiesel production globally. The availability, 
characteristics, and variety of feedstocks make them promis-
ing ingredients for the sustainable production of biodiesel 
(Piyush et al. 2013). Researchers have proposed Moringa 
seed oil as an alternative potential feedstock to produce 
biodiesel. However, there is a research gap that promotes this 
feedstock for industrial processing. Moringa seed has an 
average of 35%-45% oil content with high oleic content of 
greater than 73% based on the type of the tree. Moringa oil 
has many various industrial and homemade benefits. One of 

oil by rotary evaporation at 80°C. Gum and wax were 
removed by a degumming method. Then, biodiesel was 
synthesized by transesterification reaction using a homoge-
nous catalyst (methanol) at different process parameters.

Experimental design

The experimental design used for this study was a Box 
Behnken design standard using design expert 11.0 software. 
The experimental design was done using three variables and 
tree levels for a response surface method. 17 experimental 
runswere selected by design expert 11.0 software using the 
Box Behnken design standard method, with five central 
points per block. The main factors that affect biodiesel 
production by transesterification reaction are reaction time, 
reaction temperature, and alcohol-to-oil ratio (Seema and 
Meena, 2017). As indicated in Table I, the overall production 
of biodiesel was carried out at optimum parameters of 
catalyst load of 0.5 to 1.5 wt.%, reaction temperature of 45 to 
65°C, and methanol to oil ratio of 3 to 9.  

The other parameters, reaction time and mixing intensity 
were kept constant at 1 hour and 500 rpm for all experimental 
runs. A combination of three factors and three levels of 
experimental runs was conducted. There are 17 experimental 
runs determined byBox Behnken’s design arrangement as 
shown in Table II.

Production and purification of the product

The method used to produce biodiesel was a one-steptranses-
terification reaction. Methanol was the alcohol selected for 
the transesterification reaction due to its availability, low 
cost, popularity, and ease of separation (Demirbas, 2005). 
The catalyst selected for this study was the base catalyst 
(KOH) since biodiesel can be produced at low temperatures 
and pressure reactions. Moreover, it is a homogeneous base 
catalyst that results in high conversion, minimum side 
reactions, short reaction time, and high yield (Marchetti and 

Yadessa, 2012). Though it has many advantages, the disad-
vantage of the catalyst used is it cannot be reused.

When the reaction is completed, biodiesel and glycerol were 
separated by a separatory funnel after it settles for 24 hours. 
Then, biodiesel was washed with hot distilled water to 
remove soap, remaining methanol, and wax.

Optimization of the process parameters using the Response 
Surface Method (RSM).

Optimization aims to determine the optimum value of the 
factors that affect the transesterification process to produce 
the maximum possible biodiesel yield at a minimum produc-
tion cost. This is done by minimizing the methanol to oil 
ratio, reaction temperature, and amount of catalyst used as 
indicated in Table III.

Characterization of biodiesel

Characterization of fuel is determining the physical and 
chemical properties (Atabani et al. 2013). The physical and 
chemical properties of biodiesel were determined according 
to the American Society for Testing Materials (ASTM D 
6751) and European standard (EN 14214) methods (Demir-
bas, 2005). Table IV showed the physical and chemical 
properties of biodiesel and the standard methods used to 
determine them.

Statistical analysis of experimental results

Data analysis of the experiment was done by design expert 
11.0 software using Box Behnken design standard. The 
significance of experimental variables was obtained from 
analysis of variance (ANOVA). 

Results and discussions

Yield

The maximum oil yield obtained at optimum conditions of 
temperature 80°C and extraction time 5 hours was 39.86 %. 
This result agreed with the average oil content of Moringa 
stenopetala seed oil which is 35% - 45% (Ayerza, 2012), and 
this result also agreed with the previous reportof 38% which 
was reported by Azad et al. (2015) and by Gemechu (2021).

The maximum yield of biodiesel was 94% and it was 
obtained at optimum process parameters of methanol to oil 
ratio 6:1, temperature 55°C, and catalyst loading 1.0%.  The 
yield of biodiesel obtained agrees with the previous report of 

Azad et al. (2015) which was 91%. The yield increased as 
transesterification parameters increased until the optimum 
value and decreased beyond the optimum value. At the lower 
value of parameters, the yield decreased due to the incom-
plete conversion of reactants to the product. Table V showed 
the yield response of all experimental runs.

Characterization of biodiesel

Physical and chemical properties of biodiesel were evaluated 
using standard methods and the results were compared with 
ASTM and EN standard methods and previous reports.

Density

The value of the density of biodiesel was 874 kg/m3. This 
result is within the standard range of density (860 – 900 
kg/m3) (Demirbas, 2005) and agrees with the previous report 
by Kafuku and Mbarawa (2010) which was 900 kg/m3. 
Higher density increases thesize of fuel droplets and causes 
higher emission of particulate matter and NOx emission ina 
diesel engine while the lower density of fuel expands the 
efficiency of atomization (Choi and Reitz, 1999).

Kinematic viscosity

The experimental result showed that the value of kinematic 
viscosity was 4.8 mm2/s. This result is within the range of the 
ASTM standard value of biodiesel which is 1.6-6 (Eman and 
Cadence, 2013; Demirbas, 2005). Highly viscous fuel is 
difficult to pump and operate in internal combustion engines 
while lower kinematic viscosity of fuels increases wear 
leakage due to insufficient lubrication (Rao, 2011).

Acid value

The value of an acid value obtained was 0.4 mm KOH/g.  
This result agrees with the previous report (Kafuku and 
Mbarawa, 2010), with a value of 1.2 mmKOH/g. Higher 
acid-value fuels need further acid treatment costs and it also 
lowers the quality of the fuels. In this study, the lower acid 
value of biodiesel indicates that it has higher fuel quality.

Calorific value

The experimental result showed that the value of biodiesel 
was 10287 Cal/ g or 43 MJ/kJ. This result agrees with the 
previous report of Mahamudul et al. (2017) which was 39 

MJ/kg, and the previous report of Agarwal and Das (2001) 
which was 43.2 kJ/kg. The result obtained is above the 
standard ASTM value which is 42-42.5 MJ/kg. This result 
indicates the higher fuel quality of biodiesel. The calorific 
value obtained is similar to that of conventional diesel fuels. 
This is the novel result of this study.

Flash point

The flash point obtained from the experimental result was 
184°C. This result agrees with the standard ASTM value of 
biodiesel flash point which is greater than 130°C. From this 
study, the higher flash point of biodiesel indicates that it is 
safer to handle, store and transport the fuel (Jayed et al. 
2011).

Cetane number

The value of the cetane number observed was 53. This result 
agrees with the standard ASTM value of the cetane number 
of biodiesel which is greater than 47 (Demirbas, 2005). Fuels 
with higher cetane number benefit the engine performance 
since the engine starts rapidly and run smoothly without 
causing much noise.

Cloud and Pour point

The experimental result showed that the cloud and pour 
points of biodiesel were 10°C and 1°C respectively. This 
result agrees with the previous report of Kafuku and Mbara-
wa (2010) which was 10°C and 3°C respectively. Cloud and 
pour point of fuel indicates the fuel performance at low ambi-
ent temperature (Agarwal and Das, 2001). Table VI showed 
the result of all main physicochemical properties of biodiesel 
synthesized.

Statistical analysis of experimental results 

Analysis of variance (ANOVA) for the quadratic model

Analysis of variance determines the significance of the 
experimental results using coded variables as indicated in 
Table VII. 

The Model F-value of 380.98 implies the model is signifi-
cant. There is only a 0.01% chance that an F-value this large 
could occur due to noise.

P-values less than 0.0500 indicate model terms are signifi-
cant. In this case, A, B, C, A², B², C² are significant model 
terms. Values greater than 0.1000 indicate the model terms 
are not significant. If there are many insignificant model 
terms (not counting those required to support hierarchy), 
model reduction may improve your model.

The Lack of Fit F-value of 5.69 implies there is a 6.31% 
chance that a Lack of Fit F-value this large could occur due to 
noise. Lack of fit is bad -- we want the model to fit. This 
relatively low probability (<10%) is troubling.

The coefficient estimate represents the expected change in 
response per unit change in factor value when all remaining 
factors are held constant. The intercept in an orthogonal 
design is the overall average response of all the runs. The 
coefficients are adjustments around that average based on the 

factor settings. When the factors are orthogonal the VIFs are 
1; VIFs greater than 1 indicate multi-collinearity, and the 
higher the VIF the more severe the correlation of factors. As 
a rough rule, VIFs less than 10 are tolerable.

The effect of process parameters on the yield of biodiesel

Effect of methanol to oil ratio

Figure. (2) Shows the effect of methanol to oil ratio on 
biodiesel yield at constant temperature and catalyst loading. 
It showed that the yield of biodiesel increases as the metha-
nol-to-oil ratio increases. Increasing the methanol-to-oil ratio 
beyond the optimum value results in excess methanol which 
decreases the yield of biodiesel. The maximum yield of 
biodiesel (94%) was obtained at a methanol-to-oil ratio of 6: 
1. Therefore, this ratio was taken as an optimum value of the 
methanol-to-oil ratio. Decreasing the methanol-to-oil ratio 

below the optimum value (3:1), decreased the conversion 
efficiency of the transesterification reaction and resulted in 
lower biodiesel yield.

Effect of reaction temperature

Figure (3) shows the effect of reaction temperature on the 
yield of biodiesel at a constant methanol-to-oil ratio and 
catalyst loading. The yield of biodiesel highly increased as 

temperature increased from 45°C to 55°C.  Maximum yield 
was obtained at 58°C and the yield started to decrease slight-
ly from 58°C to 65°C due to the vaporization of methanol 
resulting in soap formation. The boiling point of methanol is 
64.7°C. Increasing reaction temperature above this point 
leads to methanol loss by evaporation and decreases the 
conversion efficiency of the reaction. At 45°C, the yield is 
about 75°C.

Effect of catalyst loading

Figure (4) shows the effect of catalyst loading on the yield of 
biodiesel at a constant methanol-to-oil ratio and temperature.  
As the amount of catalyst increased from 0.5% to 1.0%, the 
yield of biodiesel increased from 89% to 94% and the yield 
starts to decrease slightly as the amount of catalyst increased 
from 1.0% to 1.5% due to the formation of soap and emul-
sion. At a lower amount of catalyst (0.5%), the yield of 
biodiesel decreased due to the incomplete conversion of 
triglycerides of oil to fatty acid methyl ester.

Optimization of transesterification process parameters using 
the Response Surface Method (RSM)

The Response Surface Method determined the optimum 
value of process variables that maximize the yield of the 
product and minimize production cost

Table VIII showed that Response Surface Method found 15 
solutions and selected the optimum values to minimize the 
economic cost of Temperature, Methanol, and Catalyst 
required for the reaction and to maximize the yield of 
biodiesel. The optimum yield of biodiesel (83.772%) was 
observed at a temperature of 51.537 and catalyst load of 
0.500 wt.%.

Conclusions

Biodiesel is a promising biofuel that is synthesized by the 
transesterification of vegetable oils and animal fats. In this 
study, biodiesel was synthesized from moringa stenopetala 
seed oil using an alkali catalyst. The effect of methanol to 
oil ratio, reaction temperature, and catalyst weight on the 
yield and quality of biodiesel have been studied. Biodiesel 
produced was characterized according to international fuel 
testing standards methods. The optimization of process 
parameters was carried out using Response Surface 
Method (RSM).

The experimental result showed that the highest yield of 
biodiesel was 94% and this result was obtained at an 
optimum value of temperature 55°C, methanol to oil ratio of 
6:1, and catalyst load of 1.0%. Increasing methanol to oil 
ratio, temperature, and catalyst load up to the optimum point 
increased the yield of biodiesel. However, further increase of 
the parameters above the optimum point decreased the yield 
of biodiesel. The temperature has the highest significant 
effect while the catalyst load has a lower effect. 

Besides to characterization of different basic fuel properties 
of it, biodiesel can be blended with petrol-diesel at different 
percentages and applied in compression ignition engine to 
evaluate the effect of using a blend of biodiesel using differ-

ent parameters such as engine power, brake thermal efficien-
cy, specific fuel consumption, exhaust gas temperature, and 
greenhouse gas temperature and gas emission. However, the 
performance analysis of the blend of biodiesel with petrol 
diesel in a compression ignition engine was not done due to a 
lack of laboratory setup and equipment required to measure 
these parameters. This study did not compare biodiesel with 
diesel fuels used in diesel engines. Moreover, it did not 
characterize the blend of biodiesel with petroleum fuels and 
did not compare biodiesel produced from other feedstocks 
other than moringa stenopetala. Thus, further research should 
be done on these areas. 

Generally, it can be concluded that moringa stenopetala is a 
promising alternative feedstock for biodiesel production for 
the reasons: it does not affect food security, has a good oil 
content, and can be harvested throughout the year.  The 
biodiesel produced meets the standard fuel quality and 
international standard specifications. 

Acknowledgment

The authors are thankful to Addis Ababa institute of Technol-
ogy, Addis Ababa University, Ethiopian Environment and 
Forest Research Institute, College of Natural and Computa-
tional Science, Addis Ababa University, and Ethiopian 
Geological Survey for their technical support.

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Biodiesel from moringa stenopetala seed oil 58(1) 202344

its advantages is it is considered a great natural cosmetic 
emollient and has high oxidative stability (Ayerza, 2012).

Moringa plant is a high-value tree of the Moringaceae family. 
It consists of 13 species highly distributed in Africa and Asia 
(Hamza and Azmach, 2017). Moringa is particularly suitable 
for dry regions since it can be grown using rainwater without 
expensive irrigation techniques.  Moringa has been given less 
attention and ignored tree by communities to utilize it in 
different ways (Gemeda and Desta, 2020). Flowering begins 
within the first six months. Moringa stenopetala seed is an 
available and underutilized resource. Ethiopia has a comfort-
able environment for mooring stenopetala plantations. Many 
parts of the country particularly southern parts such as Gamo 
Goffa, Sidama Wolayitta, Konso, and Darashe have planted 
moringa in their garden and farmland (Sreepada and Vijay-
alaxmi, 2013). Thus, this study investigated that moringa 
stenopetala seed oil is a potential industrial feedstock for 
biodiesel production as an alternative energy source.

Materials and methods

The sample of Moringa seed was collected from the Gamo 
Goffa Zone, Arba Minch area of Ethiopia. The seed sample 

was dried and milled to reduce the particle size. Then, 80 g of 
sample was measured and put into the soxhlet apparatus 
thimble. Then, it was placed in a 500 mL capacity soxhlet 
chamber. 400 mL solvent (Hexane) was used for the 
extraction at different temperatures for 3 hrs. to 5 hrs. The 
extraction was conducted at 70°C, 75°C, and 80°C by 
varying extraction time to get the maximum possible oil 
yield.  The soxhlet extraction method was selected since it 
results in high oil yield, is quick, the solvent can be reused, 
and is low cost (Sreepada and Vijayalaxmi, 2013). The 
unwanted substances were removed by evaporation and 
degumming. Evaporation was used to separate hexane from