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

Authors

  • Mohd Izuan Effendi Halmi Department of Chemical Engineering and Process, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia.
  • Mohd Shukri Shukor Snoc International Sdn Bhd, Lot 343, Jalan 7/16 Kawasan Perindustrian Nilai 7, Inland Port, 71800, Negeri Sembilan, Malaysia.
  • Noor Azlina Masdor Biotechnology Research Centre, MARDI, P. O. Box 12301, 50774 Kuala Lumpur, Malaysia
  • Nor Aripin Shamaan Faculty of Medicine and Health Sciences, Universiti Sains Islam Malaysia, 13th Floor, Menara B, Persiaran MPAJ, Jalan Pandan Utama, Pandan Indah, 55100 Kuala Lumpur, Malaysia
  • Mohd Yunus Shukor Department of Biochemistry, Faculty of Biotechnology and Biomolecular Sciences, University Putra Malaysia, UPM 43400 Serdang, Selangor, Malaysia

DOI:

https://doi.org/10.54987/jemat.v3i1.241

Keywords:

Polyethylene Glycol, modified Gompertz, sludge microbes, ordinary least squares method, Grubbs test

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. 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.

Author Biography

  • Mohd Izuan Effendi Halmi, Department of Chemical Engineering and Process, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia.

    Department of Biochemistry

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Published

27.07.2015

Issue

Vol. 3 No. 1 (2015)

Section

Articles

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How to Cite

Outlier analysis of the modified Gompertz model used in fitting the growth of sludge microbes on PEG 600. (2015). Journal of Environmental Microbiology and Toxicology, 3(1), 12-14. https://doi.org/10.54987/jemat.v3i1.241