| Summary: | Disposal of untreated water effluent from local tie and dye industries without prior treatment pose a great danger to the environment. Hence this study investigated the use of Moringa oleifera seed for decolouration of water effluent from local tie and dye industry. The modeling of decolouration process was carried out using Artificial Neural Network (ANN) as well as Response Surface Methodology (RSM). Four parameters (agitation time, agitation speed, pH and Moringa oleifera seed (MOSE) dose) were varied using Box Behnken Design and optimization of the process parameter was carried out using the better model. Result showed ANN coefficient of determination (R2) and root mean squared error (RMSE) were 0.999999 and 2.42526e-2 while the RSM values were 0.86 and 2.34, respectively. The results revealed ANN model performed better and has a better predictive capability than RSM. The ANN model predicted 65% decolouration efficiency with optimal condition of 3.5 h of agitation time, agitation speed of 147 rpm, pH of 8 and MOSE dose of 20 g. The predicted optimal condition was verified in replicate in the laboratory and the result obtained was in the range of the predicted values. The study revealed the efficacy of Moringa oleifera seed as a natural decolourant for water effluent from tie and dye industry.
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