Outlier analysis of the modified Gompertz model used in fitting the growth of sludge microbes on PEG 600

Polyethylene glycols (PEGs) are employed in numerous sectors. PEGs are nephrotoxic and their biodegradation by microbes could be a potential tool for bioremediation. Numerous bacterial growth studies neglect primary modelling even though modelling exercises can reveal important parameters. Previously, we have utilized several growth models to model the growth of sludge microbes on PEG 600. We discovered that the modified Gompertz model via nonlinear regression utilizing the least square method was the best model to describe the growth curve. However, the use of statistical tests to choose the best model relies heavily on the residuals of the curve to be statistically robust. More often than not, the residuals must be tested for the presence of outliers (at 95 or 99% of confidence). In this work, the Grubb’s test to detect the presence of outlier in the growth model was carried out. The test detected an outlier. This datum point will be removed in all future statistical tests such as normality, runs test, tests for homoscedasticity and presence of autocorrelation. In addition, remodeling of the data using the modified Gompertz model will be carried out.