Abstract
TOXICITY OF BINARY AND TERNARY METAL MIXTURES ON DEHYDROGENASE ACTIVITY OF Pseudomonas fluorescens: AN ASSESSMENT USING RESPONSE SURFACE METHODOLOGY

Ndukwe C.U.*, Nweke C.O., Mike-Anosike E.E. and Nwokorie R. C.

ABSTRACT

Toxicity of cadmium, cobalt, lead and nickel as individual chemicals and their binary, ternary mixtures effect on Pseudomonas fluorescens was determined using response surface methodology. The mixture ratios were designed using central composite response surface design and implemented using minitab statistical software. The toxicity assay showed Cadmium was the most toxic while lead was the least toxic where increase in dehydrogenase enzyme inhibition was observed with corresponding increase in concentration of these metals. The concentration of the individual metals in the mixture was designed not to exceed EC45, EC30, EC25 or EC20 for binary and ternary mixtures respectively. The dose response relationships obtained were fitted into a logistic dose-response model to determine the median inhibitory concentration (EC50). The EC50 values deduced are cadmium 0.023 ± 0.003, lead 0.135 ± 0.007, cobalt 0.099 ± 0.006 and nickel 0.080 ± 0.006. The concentration of the metals alone with their calculated percentage inhibition was used to derive the residual plots, contour plots and surface plots for the binary and ternary mixtures respectively. The surface plots generated were seen to be curved which is as a result of the quadratic nature of the models having the highest values of inhibition (%) found at the top right corner of the plot while the lowest values were seen at the bottom left corner of the surface plot. The contour plots showed different shapes which indicated different interactions between the variables where an elliptical contour plot indicated the interactions between the variables were significant while a circular contour plot meant otherwise. The contour plots showed contour lines which connected points having the same response values during the course of the analysis. Residual plots generated showed data points closer to the regression line without outliners thus statistically inferring a good fit for the linear model. Coefficients of determinations derived during course of this work were relatively good with the lead-nickel binary mixture observed to have the highest coefficient of determination (R2 ) of 99.47% and adjusted determination coefficient (R2 Adj) value of 99.39% which means that the calculated model was able to explain 99.47% of the results. The adjusted determination coefficient (R2 Adj) of the lead-nickel binary model was 0.9939, which indicated only 0.61% of the total variations were not explained by the model.

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