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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