The present study estimates the prediction capability of response surface methodology (RSM) and artificial neural network (ANN) models for biodiesel synthesis from sesame (Sesamum indicum L.) oil under ultrasonication (20 kHz and 1.2 kW) using barium hydroxide as a basic heterogeneous catalyst. RSM based on a five level, four factor central composite design, was employed to obtain the best possible combination of catalyst concentration, methanol to oil molar ratio, temperature and reaction time for maximum FAME content. Experimental data were evaluated by applying RSM integrating with desirability function approach. The importance of each independent variable on the response was investigated by using sensitivity analysis. The optimum conditions were found to be catalyst concentration (1.79 wt%), methanol to oil molar ratio (6.69:1), temperature (31.92°C), and reaction time (40.30 min). For these conditions, experimental FAME content of 98.6% was obtained, which was in reasonable agreement with predicted one. The sensitivity analysis confirmed that catalyst concentration was the main factors affecting the FAME content with the relative importance of 36.93%. The lower values of correlation coefficient (R(2)=0.781), root mean square error (RMSE=4.81), standard error of prediction (SEP=6.03) and relative percent deviation (RPD=4.92) for ANN compared to those R(2) (0.596), RMSE (6.79), SEP (8.54) and RPD (6.48) for RSM proved better prediction capability of ANN in predicting the FAME content.

Pyridine carboxylic acids and their derivatives are attracting considerable attention for their presence in many natural products. 2-Pyridinecarboxylic acid, also known as picolinic acid is widely used in the pharmaceutical industries. Compared to chemical methods, enzymatic oxidation of 3-hydroxyanthranillic acid is an advantageous alternative for the production of picolinic acid. Reactive extraction is a promising method to recover carboxylic acid but suffers from toxicity problems of the diluent and extractant employed, therefore there is a need for a nontoxic extractant and diluent or a combination of less toxic extractants in a nontoxic diluent that can recover acid efficiently. The present paper focuses on the reactive extraction of picolinic acid using tri-n-butyl phosphate (TBP) in sunflower oil and castor oil. Results were presented in terms of distribution coefficients (0.0066 to 0.664 for sunflower oil and 0.0099 to 0.94 for castor oil), loading ratio (<0.5), degree of extraction (0.65 to 42.9% for sunflower oil and 0.9 to 74.6% for castor oil), and equilibrium complexation constants. Relative basicity, mass action law, and Langmuir models were used to represent the reactive extraction equilibrium for picolinic acidÀTBPÀdiluent. Model results are close to experimental results.

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