@Article{crph65,
AUTHOR = {Chisa, Owhor Sampson and Nguseer, Orafa Patience and Adidauki, Samaila Yohanna and Ethan, Doyo},
TITLE = {Optimization and Prediction of Biodiesel Yield from Moringa Seed Oil and Characterization},
JOURNAL = {Current Research in Public Health},
VOLUME = {1},
YEAR = {2021},
NUMBER = {1},
PAGES = {1-14},
URL = {/10.31586/jbls-1-1-110.31586/jbls/1/1/1},
ISSN = {2831-5162},
DOI = {10.31586/jbls.2021.010101},
ABSTRACT = {In this study, oil was extracted from Moringa seed using mechanical and solvent methods. To transesterify the oil into biodiesel, factorial design of experiment of 24 was used to obtain different combination factors at different level of reaction temperature, catalyst amount, reaction time and alcohol to oil ratio, giving rise to 48 experimental runs. The oil sample was transesterified in 48 experimental runs, in each case the biodiesel yield was recorded in percentage. The biodiesel was then characterized according to ASTM test protocol. Factorial design model was developed using Design Expert 7.0, the model generated R of 0.987 and Mean Square Error (MSE) of 5.0453 and was used to predict and optimize biodiesel yield. Artificial Neural Network (ANN) model from MATLAB R2016a was developed using 4 input variables and 30 runs, the remaining 18 runs were tested with the ANN model to predict and compare the biodiesel yield with the experimental biodiesel yield, the model generated R value of 0.99687 and MSE of 3.50804. It was found that solvent method yielded more oil than mechanical method, the biodiesel has good thermo-physical property, optimum biodiesel yield of 91.45 % was obtained at 5:1 alcohol/ oil molar ratio, 18.89 wt% catalyst amounts, 45 minutes reaction time and at 45 reaction temperature. The experimental validation yielded 88.33 % biodiesel. The ANN model adequately predicted the remaining 18 runs with R2 value of 0.99649 and MSE of 4.914243. Both models proved adequate enough to predict biodiesel yield but ANN model proved more adequate.},
}

%0 Journal Article
%A Chisa, Owhor Sampson
%A Nguseer, Orafa Patience
%A Adidauki, Samaila Yohanna
%A Ethan, Doyo
%D 2021
%J Current Research in Public Health

%@ 2831-5162
%V 1
%N 1
%P 1-14

%T Optimization and Prediction of Biodiesel Yield from Moringa Seed Oil and Characterization
%M doi:10.31586/jbls.2021.010101
%U /10.31586/jbls-1-1-110.31586/jbls/1/1/1

TY  - JOUR
AU  - Chisa, Owhor Sampson
AU  - Nguseer, Orafa Patience
AU  - Adidauki, Samaila Yohanna
AU  - Ethan, Doyo
TI  - Optimization and Prediction of Biodiesel Yield from Moringa Seed Oil and Characterization
T2  - Current Research in Public Health
PY  - 2021
VL  - 1
IS  - 1
SN  - 2831-5162
SP  - 1
EP  - 14
UR  - /10.31586/jbls-1-1-110.31586/jbls/1/1/1
AB  - In this study, oil was extracted from Moringa seed using mechanical and solvent methods. To transesterify the oil into biodiesel, factorial design of experiment of 24 was used to obtain different combination factors at different level of reaction temperature, catalyst amount, reaction time and alcohol to oil ratio, giving rise to 48 experimental runs. The oil sample was transesterified in 48 experimental runs, in each case the biodiesel yield was recorded in percentage. The biodiesel was then characterized according to ASTM test protocol. Factorial design model was developed using Design Expert 7.0, the model generated R of 0.987 and Mean Square Error (MSE) of 5.0453 and was used to predict and optimize biodiesel yield. Artificial Neural Network (ANN) model from MATLAB R2016a was developed using 4 input variables and 30 runs, the remaining 18 runs were tested with the ANN model to predict and compare the biodiesel yield with the experimental biodiesel yield, the model generated R value of 0.99687 and MSE of 3.50804. It was found that solvent method yielded more oil than mechanical method, the biodiesel has good thermo-physical property, optimum biodiesel yield of 91.45 % was obtained at 5:1 alcohol/ oil molar ratio, 18.89 wt% catalyst amounts, 45 minutes reaction time and at 45 reaction temperature. The experimental validation yielded 88.33 % biodiesel. The ANN model adequately predicted the remaining 18 runs with R2 value of 0.99649 and MSE of 4.914243. Both models proved adequate enough to predict biodiesel yield but ANN model proved more adequate.
DO  - Optimization and Prediction of Biodiesel Yield from Moringa Seed Oil and Characterization
TI  - 10.31586/jbls.2021.010101
ER  -