Test of randomness of residuals for the modified Gompertz model used in the fitting the growth of sludge microbes on PEG 600

Abstract

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. Nonlinear regression using the least square method normally uses the assumption that data points do not depend on each other or the value of a data point is not dependent on the value of preceding or proceeding data points or do not exhibit autocorrelation. In this work, the Durbin–Watson statistic for the presence of autocorrelation in the growth model was carried out.