Predicting the impact of food processing industry on water quality of its environment using 24 full factorial design
Modelling, Measurement and Control C
Dept of Agricultural Engineering, Federal University of Technology, PMB 65, Minna, Niger State, Nigeria
A 24 full factorial design was used to predict the impact of a food processing industry on the water quality of its environment. The factorial, main, and interaction effects of four water pollutants, namely, total dissolved solids, sulphide of lead, total nitrates, and total undissolved solids on biological oxygen demand (BOD) were obtained statistically. From sensitive analysis, it was concluded that all the main effects and interactions in the model have significant impacts on the level of BOD of the surface water. The statistical analysis of the experimental data showed that the predictive model is adequate for obtaining optimum conditions. Validation of the model gave a correlation coefficient of 0.999749 between the measured and predicted values. It was recommended that any processing activity by the industry that could lead to the discharge of the pollutants into water bodies at values more than the maximum permissible limits must be discouraged.
Biological oxygen demand; Correlation coefficient; Environment; Experimental data; Factorial design; Food processing industry; Full factorial design; Interaction effect; Main effect; Optimum conditions; Predictive models; Processing activity; Sensitive analysis; Significant impacts; Statistical analysis; Total dissolved solids; Undissolved solids; Water pollutants; Waterbodies; Biochemical oxygen demand; Design; Dissolution; Dissolved oxygen; Forecasting; Industry; Surface waters; Waste treatment; Water pollution; Water quality; Food processing