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

Main Article Content

Mohd Izuan Effendi Halmi Mohd Shukri Shukor Noor Azlina Masdor Nor Aripin Shamaan Mohd Yunus Shukor


Polyethylene glycols (PEGs), are nephrotoxic, and are employed in numerous industrial sectors. Their biodegradation by microbes could be a potential tool for bioremediation. A lot of bacterial growth reports overlook primary modelling despite the fact that modelling exercises can expose important parameters. Earlier, we have employed several growth models to model the growth of sludge microbes on PEG 600. We found out that the modified Gompertz model via nonlinear regression utilizing the least square method was the most effective model to describe the growth curve. Nonlinear regression using the least square method generally utilizes 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 to check for the presence of autocorrelation in the growth model was carried out.

Article Details

How to Cite
HALMI, Mohd Izuan Effendi et al. Test for the presence of autocorrelation in the modified Gompertz model used in the fitting the growth of sludge microbes on PEG 600. Journal of Environmental Microbiology and Toxicology, [S.l.], v. 3, n. 1, p. 6-8, july 2015. ISSN 2289-5906. Available at: <http://journal.hibiscuspublisher.com/index.php/JEMAT/article/view/238>. Date accessed: 21 sep. 2018.
Polyethylene Glycol; modified Gompertz; sludge microbes; ordinary least squares method; autocorrelation


[1] Herold DA, Rodeheaver GT, Bellamy WT, Fitton LA, Bruns DE, Edlich RF. Toxicity of topical polyethylene glycol. Toxicol Appl Pharmacol. 1982;65(2):329–335.
[2] Watanabe M, Kawai F. Study on biodegradation process of polyethylene glycol with exponential growth of microbial population. 2010;145-157.
[3] Payne WJ, Williams JP, Mayberry WR. Primary alcohol sulfatase in a Pseudomonas species. Appl Microbiol. 1965;13(5):698–701.
[4] Halmi MIE, Shukor MS, Johari WLW, Shukor MY. Evaluation of several mathematical models for fitting the growth of the algae Dunaliella tertiolecta. Asian J Plant Biol. 2014;2(1):1–6.
[5] Zwietering MH, Jongenburger I, Rombouts FM, Van’t Riet K. Modeling of the bacterial growth curve. Appl Environ Microbiol. 1990;56(6):1875–81.
[6] Ahmad SA, Ahamad KNEK, Johari WLW, Halmi MIE, Shukor MY, Yusof MT. Kinetics of diesel degradation by an acrylamide-degrading bacterium. Rendiconti Lincei. 2014;25(4):505–12.
[7] Mcdonald JH, Dunn KW. Statistical tests for measures of colocalization in biological microscopy. J Microsc. 2013;252(3):295–302.
[8] Draper NR, Smith H. Applied Regression Analysis. Wiley, New York; 1981.
[9] Rohatgi, A. WebPlotDigitizer. http://arohatgi.info/WebPlotDigitizer/app/ Accessed June 2 2014.;
[10] Huang Y-L, Li Q-B, Deng X, Lu Y-H, Liao X-K, Hong M-Y, et al. Aerobic and anaerobic biodegradation of polyethylene glycols using sludge microbes. Process Biochem. 2005;40(1):207–11.
[11] Huitema BE, McKean JW, Zhao J. The runs test for autocorrelated errors: unacceptable properties. J Educ Behav Stat. 1996;21(4):390–404.
[12] Motulsky HJ, Ransnas LA. Fitting curves to data using nonlinear regression: a practical and nonmathematical review. FASEB J Off Publ Fed Am Soc Exp Biol. 1987;1(5):365–374.