TITLE:
Response Surface Methodology and Decision Tree Used in Oilseed Selection for Enhancing Biofuel Properties and Production in Cameroon
AUTHORS:
Nsah-Ko Tchoumboue, Azemo F. Esther, Kapseu César
KEYWORDS:
Jatropha curcas Oil, Prediction Efficiency, Iodine Index, Acid Index, Peroxide Index
JOURNAL NAME:
Journal of Sustainable Bioenergy Systems,
Vol.16 No.1,
March
30,
2026
ABSTRACT: Oilseeds properties need to be improved for better biofuel production. In developing countries, oilseed plants remain the best and most affordable biomass used for industrial biofuel production. Indeed, industrial development of biofuels requires predictive modeling of the physicochemical properties of substrates and bio-oils produced during extraction. The main objective of this study was to predict physicochemical properties from three Jatropha curcas sp. seed samples. The jatropha seeds underwent determination of their lipid, cellulose, and dry matter content. The obtained bio-oils were characterized by their acidity, peroxide, and iodine values. Response surface methodology and a decision tree were used to predict the chemical properties of the bio-oils from the jatropha seeds samples. The results showed that kernel jatropha seeds had the lowest iodine and acidity values. There was no significant difference in iodine values between the jatropha seed samples. Using the response surface methodology, the optimal values for lipid, cellulose, and dry matter content were respectively 37.69%, 15.67%, and 96.65%, giving optimal bio-oil properties. For the Decision Tree, the physicochemical properties of the bio-oil from the three seed samples were predicted with a correlation coefficient of R2 of 0.50, 0.9 and 0.4 corresponding to whole seed, kernel and crushed seed respectively. The model’s robustness for Acid value, peroxide index and Iodine index shows a precision accuracy of 91%, 95% and 95% respectively. Predicting the physicochemical properties of oilseeds will be a major contribution to reducing operational costs and improving the efficiency of biofuel production mostly for developing countries.